Patent Description:
Known cranes include a boom operably connected to a lower works. For example, a mobile crane may include a telescoping boom connected to a mobile carrier, a crawler crane may include a lattice boom connected to a crawler carrier, and a tower crane may include a boom, commonly referred to as a jib, connected to a tower (also referred to as mast). The known cranes also include one or more hoists configured to wind and unwind a rope suspended from the boom. The rope typically extends around one or more sheaves in a desired reeving. A lifting appliance, such as a hook block, is secured to a free end of the rope. The hook block is configured to engage an object to be lifted by the crane.

The known cranes can perform various movements. For example, a boom may be configured for slewing movement (i.e., swing-left and swing-right), lifting movement (i.e., boom-tip up and boom-tip down), jibbing movement (boom-entirety up and boom-entirety down) and telescoping movement (i.e., tele-sections in and tele-sections out), or combinations thereof. The lifting appliance is configured for vertical movement relative to the boom in response to winding and unwinding of the one or more ropes connected to the hoists. In some cranes, such as a tower crane, the lifting appliance is configured for movement along the boom, for example, by way of a trolley movable along the tower crane boom (sometimes referred to as a jib).

It is desirable to monitor a status of the crane, including conditions of various crane components. Currently, a condition of the crane component may be monitored by processing information received from a plurality of sensors, including proximity sensors, load cells, RFID sensors and the like. Conditions which may be monitored include slew angle, lift angle of the boom (including a luffing jib of a tower crane), boom length, unwound rope length, distance between the lifting appliance and a free end of the boom (boom tip) or tower crane trolley.

Other known systems use optical object recognition techniques to determine and monitor a condition of various crane components. For example, <CIT>, <CIT>, <CIT>, <CIT>and <CIT> disclose various systems in which objects may detected in captured images, and a condition or status of a crane component may be determined based on an analysis of the detected object. For example, in <CIT>, a detected object may be a crane carrier or superstructure, and a slew angle or lift angle of the boom may be determined based on an analysis of the detected object.

However, in the systems above, a number and type of crane statuses which may be determined may be limited by physical limitations, e.g., visibility from either end of a boom or from a remotely installed base crane or tower crane base structure.

Another known crane having a sensor unit for detecting a deformation of a jib system transversely to a load plane is disclosed in <CIT> ("US'<NUM>"). However, the sensor unit in US '<NUM> detects movement of the jib system to a predetermined position to activate an adjustment unit for influencing deformation of the jib system. That is, the sensor unit in US '<NUM> does not measure deformations of the jib system through a range of deformations. <CIT> discloses a crane comprising a boom and a system for determining a crane status, specifically a vertical deflection of the crane boom. Said system includes a sensor assembly in the form of a laser displacement meter positioned to have a line of sight along a portion of the length of the boom. The laser displacement meter is configured to detect light transmission and output sensor information. For this purpose, there is a light emitter on the boom which emits a laser beam along a boom axis and a light receiver also positioned on the boom. The light receiver comprises photoreceptors having a plurality of light-receiving portions disposed perpendicularly to a horizontal bending axis of the boom. These photoreceptors are configured to detect the laser beam as it moves vertically with respect to the receiver due to the vertical deflection of the boom. The sensor information then output includes information regarding the detection of the laser beam by a light receiving portion. There is also an arithmetic unit configured to receive the sensor information and determine the crane status based on the sensor information. The arithmetic unit determines the position of the laser beam on the receiver based on the sensor information, wherein the determined crane status includes vertical boom deflection. <CIT> discloses a factory test bed for crane booms, having a light source and an array of light sensors.

Accordingly, it desirable to provide a system for determining a variety of crane statuses based on reference points related to physical measurement taken along a length of an elongated crane component, such as a boom or tower.

The present invention relates to a crane including a system for determining a crane status as set out in appended claim <NUM>.

In one embodiment, the transmitter may emit a plurality of laser beams substantially in a vertical or horizontal plane, as desired. In one embodiment, the transmitter may further include a diffraction device, such as one or more prisms, configured to diffract the laser beam into one or more beams in a vertical or horizontal plane, as desired. In one embodiment, the transmitter may be rotatably mounted on the boom for movement through a range of angles in a vertical plane or horizontal plane, as desired. In one embodiment, an angular position of the transmitter may be varied by a motor. Further, in one embodiment, a position of the diffraction device may be adjusted, for example, by a motor. In one embodiment, the diffraction device may be rotated and/or linearly moved.

In one embodiment, the sensor assembly may be positioned on a lateral side of the boom, an underside of the boom, a top side of the boom. In one embodiment, the system for determining the crane status may be operably connected to one or more crane components, and operation of the one or more crane components may be controlled based on the determined crane status.

<FIG> is a perspective view of a crane <NUM> having a system <NUM> for determining a crane status, according to an embodiment. The crane <NUM> includes lower works <NUM> and upper works <NUM> mounted on the lower works <NUM>. The upper works <NUM> includes a rotating bed (not shown) mounted to the lower works <NUM> and a boom <NUM> mounted to the rotating bed so that the boom <NUM> may rotate with the rotating bed relative to the lower works. An operator's cab <NUM> may also be mounted on the rotating bed.

<FIG> is a block diagram showing an example of the system <NUM> for determining a crane status. The system <NUM> may include a computer <NUM> and one or more sensor assemblies <NUM>. <NUM>, <NUM> operably connected to the computer <NUM>. The computer <NUM> may be mounted, for example, in the operator's cab <NUM>, as shown schematically in <FIG>, but is not limited thereto. For example, the computer <NUM> may comprise a plurality of components operably and/or communicatively connected one another distributed at different locations on the crane <NUM>, positioned remote from the crane <NUM>, or combinations thereof. The computer <NUM> includes a memory configured to store program instructions and a processor, such as a microprocessor, configured to execute the program instructions to control operations of the computer <NUM>. The memory may be a single unit or may include a plurality of units operably connected, for example, to the processor. Similarly, the computer <NUM> may include multiple computers operably connected to one another.

The system <NUM> may further include, for example, a communication device <NUM> configured to allow communications between the various components of the system <NUM> and/or external components, for example, over a communication network. The system <NUM> may also include a visual display device <NUM>. An input/output (I/O) device <NUM> may also be provided, with which an operator may input information to the system <NUM> and/or the system <NUM> may output information. In one embodiment, the I/O device <NUM> may be integrated with the visual display device <NUM>, for example, as a touch screen display. Various components of the system <NUM>, not limited to those described above, may be operably connected to one another on a bus <NUM>.

The one or more sensor assemblies <NUM>, <NUM>, <NUM> are operably connected to the computer <NUM> such that information detected by the one or more sensor assemblies <NUM>, <NUM>, <NUM> may be received by the computer <NUM> and processed by the processor according to the stored program instructions. In one embodiment, the one or more sensor assemblies <NUM>, <NUM>, <NUM> are positioned to have a line sight along at least a portion of the boom <NUM>.

Referring again to <FIG> and <FIG>, in one embodiment, a sensor assembly <NUM> may include a transmitter <NUM> and a receiver <NUM>. In one embodiment, the transmitter <NUM> is configured to emit electromagnetic radiation. For example, the transmitter <NUM> may include a laser configured to emit at least one laser beam <NUM>.

The receiver <NUM> may be configured to detect the laser beam <NUM> incident on a surface thereof. In one embodiment, the receiver <NUM> may be formed generally as a plate and include an array of photosensors <NUM>, such as photodiodes, light dependent resistors, and the like. In one embodiment, a position of individual photosensors <NUM> may be known and stored, for example, in the memory. <FIG> is a plan view showing an arrangement of the photosensors <NUM> according to an embodiment.

In one embodiment, the transmitter <NUM> and the receiver <NUM> may be spaced apart along a length direction 'L' of the boom <NUM>. In one embodiment, the transmitter <NUM> and the receiver <NUM> may be positioned on a lateral side surface of the boom <NUM>. In one embodiment, the boom <NUM> may be a telescoping boom, but is not limited thereto. In one embodiment, the transmitter <NUM> may be positioned at or near a boom tip <NUM> and the receiver <NUM> may be positioned on a different telescoping section of the boom <NUM>.

The system <NUM> is configured to determine at least one crane status based on sensor information received from the sensor assembly <NUM>. The determined crane status may be, for example, side boom deflection (also referred to as horizontal boom deflection) and/or, in some embodiments, vertical boom deflection. In one embodiment, the system <NUM> may determine whether such a crane status is present, and/or a measurement or estimate of the extent of the crane status.

For example, in one embodiment, with the boom <NUM> in an undeflected condition (both side and vertically), the laser beam <NUM> may be incident on a surface of the receiver <NUM> at an initial position and detected by a photosensor <NUM>. As the boom <NUM> deflects either horizontally or vertically, the position of the laser beam <NUM> on the receiver <NUM> changes. For example, the laser beam <NUM> may move horizontally (i.e., in a transverse, or width direction of the boom) as the boom <NUM> deflects horizontally. Similarly, the laser beam <NUM> may move vertically (i.e., in a height direction of the boom) as the boom <NUM> deflects vertically. In some embodiments, if the boom deflects either horizontally or vertically beyond a threshold extent, the laser beam <NUM> moves to a position where it is offset from, i.e., not incident upon, the receiver <NUM>. To this end, in one embodiment, the receiver <NUM> may be dimensioned to correspond to such threshold deflections.

Accordingly, in one embodiment, the sensor information may indicate whether the laser beam <NUM> is incident upon the receiver, and optionally, which photosensor <NUM> detected the laser beam <NUM>. With a position of the photosensors <NUM> stored in the memory, the system <NUM> may determine a position of the laser beam <NUM> on the receiver <NUM>. The system <NUM> may determine whether side boom deflection is occurring based on a change in position of the laser beam <NUM> on the receiver <NUM>. In one embodiment, a scale factor may be known, for example, through calibration, and stored in the memory. The system <NUM> may then calculate the extent of the side deflection based on the detected change in position of the laser beam <NUM> on the receiver <NUM> and the scale factor.

In one embodiment, as noted above, the laser beam <NUM> moves to a position offset from the receiver <NUM> if side deflection of the boom <NUM> exceeds a threshold amount. Thus, the laser beam <NUM> is not detected on the surface of the receiver <NUM> in such a condition. In one embodiment, the sensor assembly <NUM> may provide sensor information indicating that the laser beam <NUM> is not detected. In another embodiment, the sensor assembly <NUM> may not provide sensor information, and the system <NUM> may determine that side boom deflection exceeds the threshold extent in response to not receiving sensor information, for example, over a predetermined length of time.

In another embodiment, the sensor assembly <NUM> may be configured, such that the laser beam <NUM>, with the boom <NUM> in an undeflected condition, is not incident upon the receiver <NUM>, but becomes incident upon the receiver <NUM> in response to boom deflection beyond a threshold extent.

Referring to <FIG>, in one embodiment, multiple laser beams <NUM> may be incident upon the receiver <NUM> and may be detected by one or more photosensors <NUM>. The different laser beams <NUM> may be emitted from transmitters <NUM> positioned at different lengths along the boom <NUM>, for example.

<FIG> illustrates an example of a boom <NUM> in a vertically deflected condition, according to an embodiment. In some embodiments, such vertical deflection of the boom <NUM> may cause the laser beam <NUM> to become vertically offset from the receiver <NUM>, and thus, not be detected by a photodetector <NUM>.

<FIG> shows an example of the crane <NUM> having the system <NUM> for determining a crane status in which the sensor assembly <NUM> includes another embodiment of a transmitter <NUM>. The transmitter <NUM> is configured to emit a plurality of laser beams <NUM> extending substantially in a vertical plane in the direction of the laser beams <NUM>. <FIG> is an enlarged view of the receiver <NUM> toward which the plurality of laser beams <NUM> are generally directed. As shown in <FIG>, by way of transmitter <NUM>, at least one laser beam <NUM> will remain incident upon the receiver <NUM> through a range of vertical boom deflections, when side deflection is within a predetermined threshold, and is detectable by a photosensor <NUM>. The laser beams <NUM> will become horizontally offset from the receiver <NUM> when horizontal deflection of the boom <NUM> exceeds the predetermined range, and thus, the laser beams <NUM> will not be detected by a photosensor <NUM>.

<FIG> shows an example of the crane <NUM> having the system <NUM> for determining a crane status in which the sensor assembly <NUM> includes another embodiment of a transmitter <NUM>. According to one embodiment, the transmitter <NUM> may include a diffraction device (not shown), such as one or more prisms or diffraction grating, configured to diffract a laser beam <NUM> along a line extending substantially in a vertical plane or horizontal plane, as desired, toward the receiver <NUM>. That is, a laser beam <NUM> may be diffracted by the diffraction device to extend in a direction to be incident upon the receiver <NUM>. For example, the laser beam <NUM> may be diffracted substantially in the vertical plane to become incident upon the receiver <NUM> when horizontal deflection is within a predetermined range. In such an embodiment, horizontal deflection may be measured. In one embodiment, the laser beam <NUM> may be diffracted substantially in a horizontal plane to be incident upon the receiver <NUM> when vertical deflection is within a predetermined range. In such an embodiment, vertical deflection may be measured. In one embodiment, the diffraction device may split the laser beam <NUM> into multiple laser beams in a known manner, the laser beams extending substantially in the vertical plane or the horizontal plane, as desired.

In one embodiment, a scanning operation may be performed by adjusting the diffraction device to direct the laser beam <NUM> through a range of angles in the vertical plane and/or horizontal plane as desired. <FIG> is an enlarged view of the receiver <NUM> toward which the plurality of laser beams <NUM> are generally directed. The system <NUM> may determine the horizontal boom deflection based on sensor information indicating whether a laser beam <NUM> is detected by a photodetector <NUM> in the manner detailed above. With diffraction known, either horizontally, vertically, or both, as well as a position of the laser beam <NUM> on the receiver <NUM>, the horizontal deflection, vertical deflection, or both, may be determined. In one embodiment, the diffraction device may split the laser beam <NUM> into multiple beams, for example, due to crane jittering, shivering, oscillation and the like. The diffracted laser beam or beams <NUM> may then be detected along a line of reference points and/or on the array of photosensors <NUM> located on the receiver <NUM>.

In another embodiment, the transmitter <NUM> may be rotatably mounted on the boom <NUM> to perform a scanning operation. For example, the transmitter <NUM> may be rotated by a motor through a range of angles in the vertical plane. Accordingly, the laser beam <NUM> would become incident on receiver <NUM> and detected by a photosensor <NUM> during at least a portion of the scanning operation, when side boom deflection is within the predetermined threshold. In one embodiment, a rated capacity limiter (RCL) of the crane may perform calculations to predict the vertical deflection of the boom <NUM>. The transmitter <NUM> may be rotatably mounted on the boom <NUM> and operably connected to the system <NUM> and/or the RCL. The system <NUM> or RCL may control the motor (not shown) to adjust an angular position of the transmitter based on the predicted vertical boom deflection so that the laser beam <NUM> remains incident upon the receiver <NUM> through a range of vertical boom deflections, when the horizontal deflection is within predetermined limits.

Referring again to <FIG>, in one embodiment, the system <NUM> may include a sensor assembly <NUM> in the form of an image capture device, such as a digital camera, which incorporates an image sensor configured to detect, for example, electromagnetic radiation, such as light. Information from the image sensor may be used for example, by the computer <NUM>, to generate and capture an image within a field of view of the image capture device. Suitable cameras include, but are not limited wide-angle, stereo, telephoto, zoom, video and similar known cameras configured to capture an image in a field of view.

Alternatively, or in addition, the system <NUM> may include a sensor assembly <NUM> formed as a LiDAR assembly. As understood in the art, the LiDAR assembly <NUM> is configured to perform surveying operations and includes a transmitter configured to emit electromagnetic radiation, such as one or more laser beams, for example, as pulsed beams, and a receiver which includes a sensor, such as a photosensor, configured to receive reflected laser beams (i.e., reflections of the one or more laser beams emitted from the transmitter). The LiDAR assembly <NUM> may then provide sensor information indicative of the received reflected laser beams to the computer <NUM>. The computer <NUM> may then generate a three-dimensional image of the captured field of view, i.e., a captured image, of the LiDAR assembly <NUM>. In one embodiment, the computer <NUM> and LiDAR assembly <NUM> may be integrated.

In the embodiments above, the system <NUM> may include any one of the sensor assemblies <NUM>, <NUM>, <NUM>, various combinations of the sensor assemblies (e.g., any two of the assemblies), or all of the sensor assemblies <NUM>, <NUM>, <NUM>. In one embodiment, multiple sensor assemblies of the same type may be provided as well. Accordingly, in some embodiments, multiple and/or different sensor assemblies may provide sensor information to the computer <NUM>.

The system <NUM> is configured to detect one or more objects in the captured image using one or more known, suitable, object detection algorithms which will be appreciated by those having ordinary skill in the art. Such known algorithms may relate to, for example, edge detection, brightness contrast, pixel density, blob detection, motion detection, and the like. The object detection algorithms may be feature-based or incorporate known deep learning techniques. The detected objects may include, for example, a crane component, a load being lifting by the crane, worksite obstacles adjacent to the crane, and a horizon.

The crane components which may be detected, include, but are not limited to, the boom <NUM>, a flexible member <NUM> suspended from the boom <NUM> (<FIG>), sheaves <NUM> (<FIG>) around which the flexible member <NUM> may extend, anti-two block ("ATB") detection components <NUM>, <NUM>, <NUM> (<FIG>), a lifting appliance <NUM> (<FIG>), a tower crane mast (also referred to as a tower) (not shown), a tower crane trolley <NUM> (<FIG>), a trailing boom dolly (not shown), boom attachments <NUM> such as a jib extension (<FIG>), support pendants (not shown), and a marker (not shown) on any of the crane components.

The detected boom <NUM> may be any of a telescoping boom, lattice boom (<NUM> in <FIG>), or tower crane jib (<NUM> in <FIG>). In addition, individual sections of the boom <NUM> may be detected, including telescoping sections or lattice sections. Further, individual cords of a lattice boom or jib section may be detected. The boom tip <NUM> may be detected on the boom <NUM> as well. A stop block (also referred to as a mousetrap) (not shown) may also be detected on the boom <NUM>.

The flexible member <NUM> may be, for example, a rope or cable. Depending on the resolution of the captured image, individual components of the flexible member <NUM> may be detected as well, such as strands and/or wires. The ATB components which may be detected include, for example, an ATB switch <NUM>, an ATB weight <NUM>, an ATB flag (not shown), and an ATB chain <NUM>. The detected lifting appliance <NUM> may be, for example, a hook-block or a headache ball. The marker (not shown) may be, for example, a particular color or coating, shape, or pattern, for example, a QR code, a bar code, or other pattern which may be detected in the captured and recognized by way of analyzing the captured image. It is envisioned that other objects, including other crane components generally positioned along, connected to, or formed integrally with the boom <NUM> or tower crane mast may be detected as well.

In one embodiment, the system <NUM> is configured to analyze the captured image and/or the detected object to determine one or more parameters of the detected object within the captured image. Such a parameter may include, for example, a position of the detected object in the captured image, a change in position of the detected object with respect to time in a series of captured images, a relative position of one or more detected objects including a distance between the detected object and a reference point in the captured image, one or more dimensions of the detected object in the captured image, an orientation, a direction of extension, and/or a size, shape, color or pattern of the detected object in the captured image.

The parameter within the captured image may be determined, for example, by counting pixels within the captured image or by measurements taken when a physical size of the captured image is known. In one embodiment, the reference point may be, for example a center point, a vertical midline, a horizontal midline, a boundary of the captured image, an initial position of the detected object, a predetermined threshold position, another detected object within the captured image, or any other suitable reference point or line. The reference point may be stored in the memory and/or provided in the captured image. The position of the reference point may be known and stored in the memory as well. In one embodiment, the crane status may be determined based on the determined parameters within the captured image.

The system <NUM> is also configured to analyze the captured image, for example, by analyzing the determined parameters within the captured image, to obtain one or more actual parameters of the detected object and/or in the captured image, an identity of the detected object, and/or a crane status. In one embodiment, the system <NUM> may analyze the captured image by way of an image/parameter compare technique which includes comparing one or more of the parameters of the detected object within the captured image to one or more known corresponding parameters of a known corresponding object in one or more stored images which may be stored in the memory. In one embodiment, actual parameters, a crane status, and/or a crane component identity of the corresponding object in the one or more stored images may be known and stored as additional information with the stored image. The stored images may also represent expected crane statuses, including expected positions or changes in position of known crane components.

For example, in one embodiment, a detected crane component in a captured image may be identified as corresponding to a known crane component, such as, but not limited to, a boom tip, a flexible member, a boom section, and the like, based on the additional information. The identification may be based on, for example, a parameter of the detected object in the captured image, such as size, shape or particular dimension of the detected object. In one embodiment, the system <NUM> is configured to count the number of detected objects, and thus, may count a number of detected objects that have been identified as corresponding to a particular crane component.

In one embodiment, when one or more parameters of the detected object in the captured image are found to match or substantially match one or more corresponding parameters of the corresponding object in a stored image, the additional information associated stored with the stored image may be associated with the detected object in the captured image. The actual parameters may refer to, for example, an actual measurement, dimension, position, distance and the like in the crane work environment. In this manner, actual parameters may be determined.

In one embodiment, the captured image and the one or more objects detected therein maybe compared to one or more stored images by superimposing one over the other, and comparing parameters of a detected object, for example, size, shape, dimensions, to those of a corresponding object in the stored images.

In one embodiment, the system <NUM> may analyze the captured image by using a scale factor technique, which includes applying a scale factor to one or more of the parameters of detected objects in the captured image to calculate an actual parameter. The scale factor may be determined, for example, by a calibration process in which actual parameters for detected objects are known and a ratio between the actual parameters and the parameters in the captured image may be determined. The scale factor may be stored in the memory.

In one embodiment, the actual parameters obtained in the calibration process may be stored in a table in the memory with corresponding parameters from the captured image. In such an embodiment, applying the scale factor includes looking up a parameter of the detected object in the captured image in the table to determine the actual parameter of the detected object. In one embodiment, the actual parameter may be determined by a calculation based on the parameter within the captured image and the scale factor.

In an embodiment of the system <NUM> in which a sensor assembly is a LiDAR assembly <NUM>, the system <NUM> may determine one or more actual parameters of the detected object based on the sensor information received from the LiDAR assembly <NUM>, e.g., sensor information obtained in a LiDAR surveying operation. This may be referred to herein as the LiDAR information technique. For example, based on the time between the transmitter <NUM> emitting a laser beam <NUM> and receipt of the reflected laser beam at the receiver <NUM>, a distance to a detected object from the LiDAR assembly <NUM> may be determined. With this information, as well as other known information, such as an orientation or angle of the emitted laser beam <NUM>, the system <NUM> may carry out various calculations based on trigonometric and/or geometric functions to determine, for example, an actual position of the detected object relative to a reference point (such as the LiDAR assembly <NUM>), an actual distance between the detected object and a reference point or other detected object, and other relevant, suitable measurements.

The system <NUM> is configured to determine the crane status based on the one or more detected objects. In one embodiment, system <NUM> may determine the crane status based on the one or more detected objects and one or more of parameters of the detected objects in the captured image. In one embodiment, the system <NUM> may determine the crane status based on the one or more detected objects, one or more of the parameters of the detected objects in the captured image, and an analysis of the captured image and/or the one or more detected objects in the captured image.

In some embodiments, the crane status and the one or more actual parameters may be one and the same. In some embodiments, the crane status and the one or more parameters of the detected object in the captured image may be one and the same, i.e., the crane status may be a parameter of a detected object in the captured image, for example, the position or distance of a detected object relative to a reference point or other detected obj ect.

According to embodiments herein, the crane status may include, for example: vertical boom deflection; side (or horizontal) boom deflection; boom length; boom section length, number of boom sections, type of boom sections, boom attachment installation condition and position (e.g., stowed, extended, not installed); boom attachment length; boom attachment offset; ATB component status including installation, correct positioning, condition, relative positioning; ATB status of the crane; reeving conditions including number of flexible member lines reeved, optimal reeving configuration, retaining pin installation status, sheave rotation; telescopic pick point; flexible member condition; pendant rope length; correct positioning of crane components; number of falls; number of flexible members; differences in construction from desired or expected construction; trolley position; tower crane mast deflection; tower crane mast twist; boom twist; load sway; trailing boom monitoring; jib rigging mode; and flexible member speed.

<FIG> show various examples of crane statuses which may be determined by the system <NUM>. However, these examples are not exhaustive, and it will be appreciated that other crane conditions not shown in the figures or specifically identified in the following examples may be determined as well, based on the detection of objects in captured images described herein. <FIG> and <FIG> relate to embodiments which do not form part of the present invention.

<FIG> is a representation of a captured image <NUM>, generated, for example, by the computer <NUM> based on sensor information from the sensor assembly <NUM> or the sensor assembly <NUM>. That is, the captured image <NUM> may be an optical image from an image captured device such as a camera, or a LiDAR image from the LiDAR assembly <NUM>. According to an embodiment, the system <NUM> may detect one or more objects in the captured image, such as the boom tip <NUM>. In one embodiment, the system <NUM> may superimpose, or store in the memory, horizontal and vertical reference lines <NUM>, <NUM> at known reference positions.

In one embodiment, the system <NUM> may analyze the captured image and/or the detected objects to determine one or more parameters of the boom tip <NUM> in the captured image <NUM>, such as a vertical position of the boom tip <NUM> and/or a distance of the boom tip <NUM> from a reference point, such as the horizontal midline <NUM>. The system <NUM> may analyze the captured image <NUM>, for example, the parameters in the captured image determined above, using any of the image/parameter compare, scale factor, and/or LiDAR information techniques) described herein. In one embodiment, an actual parameter for a change in vertical position or vertical distance from a known non-deflected vertical position of the boom tip <NUM> may be determined, and thus, the vertical deflection crane status may be determined.

<FIG> is another representation of the captured image <NUM> in which the boom <NUM> is vertically deflected. Vertical deflection of boom tip <NUM> may be determined in the manner described above with respect to <FIG>. In one embodiment, for example, the vertical deflection may be determined as the change in vertical distance of the boom tip <NUM> from the horizontal midline <NUM> from the initial undeflected position (D1 in <FIG>) to the deflected position (D2 in <FIG>).

In some instances, a parameter of the detected object in the captured image <NUM> may not match a parameter of the corresponding object in a stored image. In one embodiment, the system <NUM> may retrieve the additional information for stored images in which the corresponding object has parameter values nearest to those of the detected object, identify the corresponding actual parameters, and interpolate to determine or estimate the actual parameters of the detected object.

<FIG> is a representation of a captured image <NUM> in which the boom <NUM> is horizontally (or side) deflected. In one embodiment, the system <NUM> may detect an object, such as the boom tip <NUM>, and determine one or more parameters of the detected object in the captured image <NUM>, such as a horizontal position or change in position of the boom tip <NUM>, and/or a distance of the boom tip <NUM> from a reference point, such the vertical reference line <NUM>. The system <NUM> may analyze the captured image <NUM> and/or the detected object, such as the boom tip <NUM>, using any of the image/parameter compare, scale factor or LiDAR information techniques described herein to determine the horizontal deflection of the boom <NUM> as the crane status. It is understood that vertical and horizontal boom deflection, as well as other crane statuses described below may be determined from the same captured image <NUM>.

<FIG> is a representation of a captured image <NUM> in which the boom <NUM> is extended, and <FIG> is a representation of a captured image <NUM> in which the boom <NUM> is retracted. In one embodiment, the system <NUM> may detect one or more objects, such as the boom tip <NUM>, in the captured image <NUM>. The system <NUM> may determine one or more parameters of the detected object in the captured image, such as, a height 'h', width 'w' and/or diagonal 'd' of the boom tip <NUM>. In one embodiment, the parameters of the detected object in the captured image <NUM> decrease in value as the boom <NUM> extends and increase in value as the boom <NUM> retracts. The system <NUM> may analyze the captured image <NUM>, and/or the detected object, such as the boom tip <NUM>, using any of the image/parameter compare, scale factor or LiDAR information techniques above to determine the boom length as the crane status. In one embodiment, a boom length may be determined in the manner above for each of the one or more determined parameters. The boom lengths may then be averaged to produce a single boom length value. However, the present disclosure is not limited to such a technique, and the boom length may be determined using only one parameter in some embodiments.

In one embodiment, the system <NUM> may detect one or more boom sections of the boom <NUM> in the captured image, including the ends of the boom section. The system <NUM> then determine a length of the boom section using any one or more the of the techniques described herein.

<FIG> is a representation of a captured image <NUM> in which an ATB condition may be monitored when the boom <NUM> is in an extended position, and <FIG> is a representation of a captured image <NUM> in which the ATB condition may be monitored when the boom <NUM> is in a retracted position. The system <NUM> may detect one or more objects in the captured image <NUM>, such as various ATB components, including, but not limited to an ATB switch <NUM>, an ATB weight <NUM>, ATB flag (not shown) and an ATB chain <NUM>. The system <NUM> may determine one or more parameters of the detected objects, such as the position, position relative to a reference point, size, shape, color, pattern, dimensions, and the like, of the various ATB components <NUM>, <NUM>, <NUM>.

In one embodiment, the system <NUM> may analyze the captured image <NUM> and/or the various components <NUM>, <NUM>, <NUM>, using any of the aforementioned image/parameter compare, scale factor and/or LiDAR information techniques, as appropriate. Accordingly, in one embodiment, the system <NUM> may determine which ATB components are installed by identifying the detected objects, if the ATB are correctly positioned and dimensioned (e.g., correct length), and if the ATB components are in an undesired operating condition (e.g., tangled), as a crane status.

In one embodiment, the system <NUM> may determine an ATB status of crane. For example, the system <NUM> may detect one or more objects in the captured image <NUM>, such as the lifting appliance <NUM> and the boom tip <NUM>. The system <NUM> may determine one or more parameters of the detected objects in the captured image <NUM>, such as a position, distance or change in distance between the detected lifting appliance <NUM> and boom tip <NUM>. In one embodiment, the system <NUM> may determine an ATB condition as the crane status based on the one or more parameters of the detected objects in the captured image <NUM>. Alternatively, or in addition, the system <NUM> may determine an ATB condition as the crane status based on an analysis of the captured image <NUM> and/or the detected objects, using any of the aforementioned image/parameter compare, scale factor or LiDAR information techniques.

<FIG> is a representation of a captured image <NUM> in which a correct reeving is provided, and <FIG> is a representation of a captured image <NUM> in which an incorrect reeving is provided, according to embodiments. The system <NUM> may detect one or more objects in the captured image <NUM>, such as the flexible member <NUM> (including individual lines of the flexible member <NUM>) and one or more sheaves <NUM> at the boom tip <NUM> and/or the lifting appliance <NUM>. The system <NUM> may determine one or more parameters of the detected objects in the captured image <NUM>, such as the positions, relative positions, shapes and/or sizes of the flexible member <NUM> and the sheaves <NUM>.

The system <NUM> may analyze the captured image <NUM> and/or the detected objects, such as the flexible member <NUM> and sheaves <NUM>, using any of the aforementioned image/parameter compare, scale factor, or LiDAR information techniques. From the analysis, the system <NUM> may identify and count individual lines of the flexible member <NUM> and the sheaves <NUM>. Accordingly, the system <NUM> may determine the number of lines <NUM> reeved as the crane status.

The system <NUM> may also determine whether the detected reeving is an optimal reeving. For example, system <NUM> may store images or actual parameters of optimal reeving configurations for a given number of lines of the flexible member <NUM>. With the number of detected lines determined in the manner above, and various parameters in the captured image <NUM> determined in the manner above, including the relative positions of the detected lines <NUM> and the sheaves <NUM>, the system <NUM> may determine whether the detected reeving in the captured image <NUM> corresponds to an optimal reeving stored in the memory. Accordingly, the system <NUM> may determine a crane status as having an optimal or non-optimal reeving. In a similar manner, the system <NUM> may determine whether the lines <NUM> are correctly reeved.

The system <NUM> may also determine whether various components of the reeving, such as retaining pins, are present in the captured image, for example, by identifying the detected objects as corresponding to particular components as detailed above and comparing the detected (and identified) objects to a corresponding list of expected objects stored in the memory. Alternatively, or in addition, a stored image having expected objects identified therein may be compared to the captured image <NUM> to determine if the expected objects are present in the captured image. The system <NUM> may also determine if the detected objects are correctly positioned in a similar manner.

The system <NUM> may determine the crane status to be a status of the sheaves <NUM>, for example, as locked or turning. For example, the system <NUM> may analyze the detected sheaves <NUM> by comparing a current captured image <NUM> to previously captured images <NUM> to determine a change in position of the sheave <NUM> with respect to time. In one embodiment, the sheave <NUM> may have one or more markers (not shown) thereon which may be detected in the captured image <NUM>. The system <NUM> may determine if a position of the marker has changed in a manner indicative of sheave rotation. Alternatively, or in addition, the detected marker may be identified as corresponding to a known marker having additional information associated therewith stored in the memory. The additional information may include rotational position information. Different markers may be included on the sheave <NUM> having additional information that is indicative of different rotational positions of the sheave <NUM>. In a similar manner, the system <NUM> may determine a rotational speed of the sheave <NUM>, and in turn, a speed of the flexible member <NUM> on the sheave <NUM>.

<FIG> is a representation of a captured image <NUM> in which an end of the boom <NUM> is positioned, according to an embodiment. In one embodiment, the system <NUM> may detect one or more objects, such as the boom tip <NUM> and the boom attachment <NUM>. The system <NUM> may determine one or more parameters of the detected objects in the captured image <NUM>, such as a position, relative position, shape, size, dimensions and the like of the boom tip <NUM> and/or the boom attachment <NUM>. The system <NUM> may analyze the captured image <NUM> and/or the detected objects in the captured image <NUM> using any of the image/parameter compare, scale factor or LiDAR information techniques above. From the analysis, the system <NUM> may identify the detected objects as corresponding to particular crane components. Accordingly, the system <NUM> may determine whether the boom attachment <NUM> is detected in the captured image <NUM>. Thus, the system <NUM> may determine whether the boom attachment <NUM> is installed as a crane status. In addition, the system <NUM> may determine whether the boom attachment <NUM>, if installed, is in its stowed position alongside the boom <NUM> (as shown in <FIG>), or extended position at the boom tip <NUM>, based on the analysis of the captured image <NUM>. Further still, the system <NUM> may determine a length and/or offset of the boom attachment <NUM> based on the analysis.

The system <NUM> may determine other crane statuses from the captured images <NUM> shown in <FIG> as well. For example, as detailed above, the system <NUM> may detect the flexible member <NUM> in the captured image <NUM>. In one embodiment, the system <NUM> may also detect individual strands or wires of the flexible member <NUM>. The system <NUM> may determine one or more parameters of the detected flexible member <NUM> and/or wires or strands, such as the position, relative position, shape and/or size, in the captured image. The system <NUM> may analyze the captured image <NUM> and/or the detected objects using any of the techniques above, and determine, based on the analysis, a type of flexible member and a condition (such as a wear and/or damage condition) of the flexible member <NUM>.

In one embodiment, the system <NUM> may determine the pick point and hoist used. For example, the system <NUM> may detect the boom tip <NUM>, an auxiliary boom (not shown) and the flexible member <NUM> in the captured image <NUM>. The system <NUM> could also detect one or more sheaves <NUM>. The system <NUM> may determine one or more parameters of the detected objects, such as the position, relative position, size, shape and the like, of the detected objects. The system <NUM> may analyze the captured image <NUM> and/or the detected objects to determine whether the flexible member <NUM> is moving. Such an analysis may include a comparison to previous captured images to determine if a position of the flexible member <NUM> has changed with respect to time. In one embodiment, the flexible member <NUM> includes markers which may be detected in the captured image <NUM>, and a position of the detected markers may be used to determine if the flexible member is moving. The system <NUM> may then determine whether the moving flexible member extends from the main boom (boom tip <NUM>) or the auxiliary boom, based on the relative positions of each. In addition, with movement of the flexible member <NUM> detected, the system <NUM> may determine which hoist is driving the movement by identifying the hoist in operation during movement of the flexible member <NUM>, based on external sensor or control system information.

In the embodiments above, the crane status may be determined by the system <NUM> for a boom <NUM> implemented as any of a telescoping boom, lattice boom or tower crane jib. In addition, the system <NUM> may determine a crane status, including those above, based on the detection of objects which may be specific to certain types of booms, such as a lattice boom or tower crane jib.

<FIG> is a representation of a captured image in which the boom <NUM> is a lattice boom <NUM>, for example, of the type typically installed on a crawler or derrick crane. <FIG> are other representations of captured images <NUM> in which the boom <NUM> is lattice boom <NUM>, according embodiments. Referring to <FIG>, the system <NUM> may detect one or more objects in the captured image <NUM>, such as, the lattice boom <NUM>, a lattice boom section <NUM>, a lattice cord <NUM>, the lattice boom tip <NUM> and the like. The boom tip <NUM> of the lattice boom <NUM> may be substantially held against vertical deflection by pendant ropes (not shown). However, the lattice boom <NUM> may still deflect vertically at an intermediate portion along its length. The system <NUM> may determine such vertical deflection of the lattice boom <NUM> by analyzing the captured image <NUM> and/or the detected objects according to any of the image/parameter compare, scale factor and/or LiDAR information techniques detailed above.

In one embodiment, the system <NUM> may determine vectors for one or more detected lattice cords <NUM>. The vectors generally correspond to an orientation or direction in which the lattice cords <NUM> extend. The system <NUM> may analyze the vector according to any of the image/parameter compare, scale factor and/or LiDAR information techniques described here, to determine vertical deflection of the lattice boom <NUM>. In one embodiment, the system <NUM> may determine vertical deflection of the lattice boom <NUM> based on an analysis of the vectors. For example, the system <NUM> may determine that the lattice boom <NUM> is substantially undeflected if the vectors are substantially parallel with one another. Conversely, the system <NUM> may determine that the lattice boom <NUM> is vertically deflected if one or more vectors are angled relative to one another. The system <NUM> may also measure the vertical deflection based on the angle between the vectors.

In one embodiment, the system <NUM> may determine side deflection of the lattice boom <NUM> in a manner similar to that described above with respect to vertical deflection of the lattice boom <NUM>. Alternatively, or in addition, the system <NUM> may determine side deflection of the lattice boom <NUM> based on support pendants detected in a captured image <NUM>. For example, although not shown in the drawings, the sensor assembly <NUM> and/or <NUM> may be positioned on the crane <NUM> such that support pendants are captured within the field of view. The system <NUM> may detect one or more support pendants in the captured image and determine one or more parameters of the detected support pendants, such as position, change in position, relative position, shape, size and the like, in the captured image. The system <NUM> may analyze the captured image and/or the detected support pendants according to any of the techniques above. Accordingly, the system <NUM> may detect whether tension has decreased in a support pendant based on a change in shape or position, for example. A decrease in tension in the support pendant is associated with side deflection of the lattice boom <NUM>. Thus, the system <NUM> may determine the crane status of lattice boom side deflection in this manner.

The system <NUM> may also be configured to determine various other crane statuses related to lattice booms <NUM> as well, based on an analysis according to any of the image/parameter compare, scale factor and/or LiDAR information techniques above. For example, the system <NUM> may determine a length of a detected pendant rope, whether an additional lifting flexible member is installed, whether other crane components and/or attachments are installed, proper crane construction, a number of falls and proper crane component positioning.

<FIG> is a representation of a captured image <NUM> in which the boom <NUM> is a tower crane jib <NUM>, according embodiments. In one embodiment, a tower crane jib may be a substantially horizontally extending jib along which a trolley is moveable for displacing the flexible member, lifting appliance and load in a horizontal direction. The tower crane jib may also refer to a luffing jib which is displaceable through a range of angles in a vertical plane (i.e., a lifting angle). In one embodiment, the sensor assembly may be positioned to have a line of sight along the length of an underside of the jib <NUM>. The system <NUM> may detect one or more objects in the captured image <NUM>, such as the jib <NUM>, a trolley <NUM> movable along the jib <NUM> and a jib tip <NUM>. The system <NUM> may determine one or more parameters of the detected objects, such as a size, position, change in position and/or one or more dimensions of the detected trolley <NUM>. The system <NUM> may analyze the captured image <NUM> and/or the one or more detected objects, such as the trolley <NUM>, according to any of the techniques described herein. Accordingly, the system <NUM> may determine a position of the trolley <NUM> as the crane status.

The system <NUM> may determine vertical deflection of the tower crane jib <NUM> in the same manner as vertical deflection is determined in the embodiments above. Alternatively, or in addition, the system <NUM> may detect a horizon (not shown) in the captured image <NUM>, and determine, for example, a position, change in position, and/or distance from a reference point, such as the jib tip <NUM>, in the captured image <NUM>. The captured image <NUM> and/or the detected horizon (and optionally the jib tip <NUM>) may be analyzed according to any of the techniques above. The system <NUM> may determine the vertical deflection of the jib <NUM> as the crane status based on the analysis.

The system <NUM> may also determine an ATB status of the tower crane in substantially the manner as described in the embodiments above. However, it is understood that in a tower crane environment, the system <NUM> may detect the trolley <NUM> or sheaves on the trolley <NUM> in the captured image, rather than a boom tip <NUM> or sheaves at the boom tip <NUM>.

In one embodiment, the sensor assembly <NUM>, <NUM> may be positioned on the tower crane to have a line of sight along a length the lower works, implemented in the tower crane as a vertically extending mast (not shown). As understood in the art, the tower crane jib <NUM> is supported on, and extends from the mast. The system <NUM> may determine tower mast deflection of a tower crane. In one embodiment, the system <NUM> may detect one or more objects, such as the mast or a mast end in the captured image, and determine one or more parameters of the detected object, such as the position, change in position, distance from a reference point, size, shape, orientation and the like, in the captured image. The system <NUM> may analyze the captured image and/or the detected object, such as the mast end, according to any of the techniques above. In this manner, the system <NUM> may determine a mast deflection, the mast height and/or mast twist as the crane status. In one embodiment, the twist may refer to a displacement, for example, a rotational displacement about a longitudinal axis, of the mast. Using similar techniques, a twist of a boom, including a telescoping boom, lattice boom, and/or tower crane boom, i.e., a tower crane jib, may be determined as well.

Alternatively, or in addition, the system <NUM> may detect the horizon in the captured image <NUM> and determine one or more parameters of the horizon in the captured image, such as a position, change in position and/or distance from a reference point. The system <NUM> may analyze the captured image and/or the detected object, such as the horizon, according to any of the techniques above, and may determine mast deflection as the crane status based on the analysis.

Further, in some embodiments, the system <NUM> may determine both forward/backward deflection and side-to-side deflection. In one embodiment, the upper works <NUM> of the tower crane, including the jib <NUM>, may slew <NUM> degrees in order to detect the horizon. Images obtained in the <NUM> degree slew operation may be stored and referenced as the basis for determining a future crane status, for example using the image/parameter compare technique. A difference in level (i.e., position) of the horizon in a captured image and the stored images may be sorted out by comparing an expected position of the horizon to the position of the horizon in the captured image. The sensor assembly <NUM>, <NUM> should be mounted level with regards to the crane.

If the system <NUM> determines that the position of the detected horizon in the captured image does not match the position of the horizon as setup and calibrated, the system <NUM> may determine that there was some amount of deflection during the <NUM> degree slew operation. This difference in position may then be compensated for, and a true horizon level may be set and stored. Subsequently, the system <NUM> may determine an absolute deflection of the tower. The <NUM> degree slew operation, while not limited to a particular environment, may be suitable for determining a position of the horizon when surrounding buildings are in the field of view of the sensor assembly which may block a line of sight to the horizon at some slew angles. It will be appreciated that various deflections of the tower crane may result from a lifting operation or environmental causes, such as wind or sun.

Referring generally to the crane <NUM>, including a crane <NUM> having the boom <NUM> implemented as any of a telescoping boom, lattice boom or tower crane jib, the system <NUM> may further determine a height of the lifting appliance <NUM>, a horizontal position of lifting appliance <NUM>, and a swaying condition of the lifting appliance <NUM>. For example, the system <NUM> may detect one or more objects, such as the lifting appliance <NUM> and the boom tip <NUM> in a captured image <NUM>. The system <NUM> may determine one or more parameters of the detected objects, such as a position, change in position and/or distance from a reference point, including a distance between the lifting appliance <NUM> and boom tip <NUM>, in the captured image <NUM>. The captured image <NUM> and/or the detected objects may be analyzed according to any of the techniques above.

Accordingly, with a boom tip height known through conventional crane monitoring methods, a height of the lifting appliance <NUM> may be determined, for example, based on the distance between the detected lifting appliance <NUM> and the boom tip <NUM>. In one embodiment, a determined vertical deflection of boom <NUM>, described above, may be used to adjust the conventionally determined boom tip height. In addition, the horizontal position the lifting appliance <NUM> may be determined, for example, based on the horizontal distance between the detected lifting appliance and vertical reference line <NUM>. The vertical reference line <NUM>, in one embodiment, represents a horizontal position of the boom <NUM>.

Further, the system <NUM> may determine a swaying condition based on the horizontal position of the lifting appliance <NUM> and/or a change in the horizontal position of the lifting appliance. In one embodiment, the system <NUM> may be operably connected to one or more crane components, and in response determining a sway condition, control the one or more crane components to take corrective movements until the sway condition is no longer detected, or substantially prevent crane movements which may produce a sway condition.

The system <NUM> may be configured to determine a trailing boom status, for example, during transport of the crane <NUM>. For instance, the system <NUM> may detect one or more objects, such as the boom <NUM>, boom tip <NUM> and/or trailing boom dolly (not shown), if present. The system <NUM> may analyze the captured image and/or the detected objects and determine if trailing boom dolly is present in the captured image based on parameters and techniques described above. For example, the system <NUM> may identify a detected object in the captured image <NUM> as corresponding to a trailing boom dolly based on a size or shape of the detected object. In one embodiment, the system <NUM> may analyze the captured image <NUM> by searching for objects within the captured having parameters which correspond to known parameters of a trailing boom dolly stored in the memory.

In one embodiment, the system <NUM> may determine relative positions of the boom <NUM> and the trailing boom dolly in the captured image and based on an analysis of the captured image <NUM> and/or detected objects, determine if the boom <NUM> and trailing boom dolly are properly positioned for transport. In one embodiment, a captured image, images or video in which the trailing boom condition is captured may be presented on the display device <NUM> so that an operator may monitor the trailing boom.

The system <NUM> may also determine a jib-rigging mode of the crane <NUM>. For example, the system <NUM> may detect a stop block (also referred to as a mousetrap, not shown) on the boom <NUM> in a captured image <NUM>, and determine one or more parameters of the detected stop block, such as a position, change in position, relative position, size or shape in the captured image. The system <NUM> may analyze the captured image <NUM> and/or the detected the stop block and determine, for example, the position of the stop block along the boom <NUM>. A relationship between the position of the stop block and the jib-rigging mode may be known and stored in the memory. Accordingly, the system <NUM> may determine the jib-rigging mode.

As discussed above, one of the objects which may be detected by the system <NUM> in a captured image is a marker (not shown) that is disposed on or attached to a crane component. In one embodiment, the system <NUM> may analyze the marker according to any of the image/parameter compare, scale factor and/or LiDAR information techniques above. For example, the system <NUM> may compare the detected marker to one or more stored markers in the memory, and retrieve additional information associated with the stored marker when the stored marker is found to match the detected marker. The additional information may include, for example, an identity of a particular crane component, component specifications and the like. Thus, in one embodiment, a crane component in a captured image may be identified as a particular crane component based on the analysis of a marker detected on the crane component in the captured image.

In the embodiments above, the captured image <NUM> may be stored in the memory and the object detection, parameter determination, analysis and determining steps described above may be carried out by the system <NUM> in the memory. However, in some embodiments, the system <NUM> may include, or be operably connected to a display device <NUM> on which the captured image may be displayed.

In one embodiment, the system <NUM> may detect one or more boom sections in a captured image and count the number of detected boom sections. In one embodiment, the system <NUM> may identify the detected boom sections as corresponding to known boom sections, and further, may identify the type of boom section. The system <NUM> may perform these operations using any of techniques described herein, as appropriate.

In some embodiments, the determined crane status may be output to a crane control system, including, for example, a rated capacity limiter (RCL). For instance, actual parameters determined by the system <NUM> may be provided to the crane control system, including the RCL, and crane movements or functions may be controlled (including limiting movements) based, at least in part, on the actual parameters. That is, the crane control system may be operably connected to one or more of the crane components and may control operation of the crane components based on the crane status. For example, one or more crane components may be controlled to prevent movements which would further or maintain an undesired crane status. Additionally, the crane components may be controlled to move out of an undesired crane status. Further, the crane components may be controlled to prevent movement into an undesired crane status. In one embodiment, the crane control system may output the crane status for example, on the display device <NUM>, or any other visual, audio and/or tactile indicator. In one embodiment, an alert or alarm may be output based on the determined crane status. In one embodiment, the crane control system and the system <NUM> may be integrated as a single system.

<FIG> is a block diagram showing a method S800 of determining a crane status, according an embodiment. The method includes, generally, at S810, capturing an image along a length of an elongated crane component, such as a boom or mast. At S820, the method includes detecting one or more objects in the captured image. At S830, the method includes analyzing the captured image and/or the one or more detected object to determine one or more parameters within the captured image. In one embodiment, as shown at S910, the method may include determining a crane status based on the one or more determined parameters within the captured image. In one embodiment, the method includes, at S840, analyzing the captured image and/or one or more detected objects within the captured image, for example, based on the determined parameters within the captured image. In one embodiment, the method, at S920, determines the crane status based on the analysis of the parameters in the captured image. In one embodiment, at S850, the method includes determining one or more of: actual parameters corresponding to parameters determined in the captured image and/or of the detected object or an identity of the detected object and at S930, determining the crane status based on the analysis of the determined parameters, for example, based on the actual parameter or the identity of the detected object. In one embodiment, an additional crane status maybe determined based on a previously determined crane status. The method S800 may be performed by the system <NUM>, for example, in response to executing, with the processor, the program instructions stored in the memory.

In some embodiments, the system <NUM> may include one of the sensor assemblies <NUM>, <NUM>, <NUM> described above and determine a crane status based in part, on information from the sensor assembly. The system <NUM> may additionally include another one or more of the sensor assemblies <NUM>, <NUM> to supplement, back up or verify any of the other sensor assemblies <NUM>, <NUM>, <NUM>, or any known sensor assembly readily apparent to those having skill in the art, to determine the crane status.

In the embodiments above, various features from one embodiment may be implemented in, used together with, or replace other features in different embodiments as suitable. For example, various parameters or objects detected in one embodiment may be determined or detected in other embodiments even if not expressly described as such. In addition, in some embodiments, some of the steps described above may be combined or optionally omitted. For example, a step of determining one or more parameters in a captured image may be combined with a step of analyzing the captured image.

Claim 1:
A crane (<NUM>) comprising:
a lower works (<NUM>) having one or more ground engaging elements;
an upper works (<NUM>) connected to the lower works (<NUM>), the upper works (<NUM>) having a boom (<NUM>); characterized by
a system (<NUM>) for determining a crane status, the system (<NUM>) comprising:
a sensor assembly (<NUM>) positioned to have a line of sight along at least a portion of a length of the boom (<NUM>), the sensor assembly (<NUM>) configured to detect light transmission and output sensor information, wherein the sensor assembly (<NUM>) comprises a transmitter (<NUM>) positioned on the boom (<NUM>) and configured to emit a laser beam (<NUM>) and a receiver (<NUM>) positioned on the boom (<NUM>) and having an array of photosensors (<NUM>) configured to detect the laser beam (<NUM>), such that the laser beam (<NUM>) moves with respect to the receiver (<NUM>) vertically as the boom (<NUM>) deflects vertically, and the laser beam (<NUM>) moves with respect to the receiver (<NUM>) horizontally as the boom (<NUM>) deflects horizontally, and wherein the sensor information includes information regarding detection of the laser beam (<NUM>) by a photosensor (<NUM>) of the array of photosensors (<NUM>) and information regarding the photosensor (<NUM>) detecting the laser beam (<NUM>); and
a computer (<NUM>) configured to receive the sensor information and determine the crane status based on the sensor information, wherein the computer (<NUM>) determines a position of the laser beam (<NUM>) on the receiver (<NUM>) based on the sensor information, wherein
the determined crane status includes: vertical boom deflection and side boom deflection.