Patent Description:
Elevator systems may include multiple cars operating in multiple hoistways. Each hoistway may be associated with multiple gates operating on multiple floors of a building. In general, the vast array of elevator components may make maintenance activity and component monitoring time consuming and cumbersome. <CIT> discloses a method for monitoring the condition of the door of an elevator and determining its need for maintenance. <CIT> discloses an elevator installation in which vibrations are detected by a sensor and evaluated by comparison with a threshold value. <CIT> discloses a temporal frequency analyzing unit which obtains data which is used to check a deteriorated portion of a device. <CIT> discloses a method of elevator sensor system calibration.

According to a first aspect, there is provided an elevator system as claimed in claim <NUM>.

In some embodiments, the faults include at least one of a debris issue, roller degradation, door lock, and belt tension.

In some embodiments, the sensor is at least one of a vibration sensor, a microphone, a velocity sensor, a position sensor, a current sensor, an accelerometer, and a pressure sensor.

The foregoing features and elements may be combined in various combinations without exclusivity, unless expressly indicated otherwise, in accordance with the appended claims. However, it should be understood that the following description and drawings are intended to be exemplary in nature and non-limiting.

Various features will become apparent to those skilled in the art from the following detailed description of the disclosed non-limiting examples.

Referring to <FIG>, an exemplary embodiment of an elevator system <NUM> is illustrated. The elevator system <NUM> may include an elevator car <NUM> adapted to move within a hoistway <NUM> having boundaries defined by a structure or building <NUM>, and between a multitude of floors or landings <NUM> of the building <NUM>. The elevator system <NUM> may further include a control configuration <NUM> and a multitude of operating and/or moving components that may require maintenance and/or repair, and may be generally monitored and/or controlled by the control configuration <NUM>. The components may include a plurality of call panels (four illustrated as <NUM>, <NUM>, <NUM>, <NUM>), at least one gate or landing door (i.e., two illustrated as <NUM>, <NUM>), at least one car door (i.e. two illustrated as <NUM>, <NUM>), and other components. The elevator car <NUM> is propelled by a component (i.e., propulsion system, not shown) that may be controlled by the control configuration <NUM> of the elevator system <NUM>. Examples of a propulsion system may include self-propelled or ropeless (e.g., magnetic linear propulsion), roped, hydraulic, and other propulsion systems. It is further contemplated and understood that the hoistway <NUM> may extend, and thus the car <NUM> may travel, in a vertical direction, a horizontal direction, and/or a combination of both.

The landing doors <NUM>, <NUM> may be located at opposite sides of the hoistway <NUM>. In one example, the doors <NUM>, <NUM> may be located on some floors <NUM> and only one of the doors <NUM>, <NUM> may be located on other floors <NUM>. The car doors <NUM>, <NUM> may be respectively located on opposite sides of the elevator car <NUM>. Car door <NUM> may be associated with landing door <NUM>, and car door <NUM> may be associated with landing door <NUM>. When a passenger enters and exits the elevator car <NUM> at a specific floor <NUM>, door pairs <NUM>, <NUM>, or door pair <NUM>, <NUM> must be open. Before the elevator car <NUM> begins to travel, all doors <NUM>, <NUM>, <NUM>, <NUM> must be closed. The control configuration <NUM> may monitor and control all of these events. It is contemplated and understood that a single elevator car <NUM> may be associated with a single set of doors, three sets of doors, or more.

The landing doors <NUM>, <NUM> may be located at each landing <NUM>, which barriers the otherwise exposed hoistway <NUM> for the protection of waiting passengers yet to board the elevator car <NUM>. The doors <NUM>, <NUM> of the elevator car <NUM> protect the passengers within the elevator car <NUM> while the car is moving within the hoistway <NUM>. The monitoring and actuation of all doors <NUM>, <NUM>, <NUM>, <NUM> may be controlled by the control configuration <NUM> via, for example, electrical signals (see arrows <NUM>) received from a plurality of sensors <NUM> (e.g., motion and/or position sensors) with at least one sensor <NUM> positioned at each door <NUM>, <NUM>, <NUM>, <NUM>. The sensors <NUM> may be motion and/or position sensors, and may further be an integral part of door actuator assemblies <NUM> (see <FIG>) that at least facilitate door opening and closing functions.

Referring to <FIG> and <FIG>, the call panels <NUM>, <NUM>, <NUM>, <NUM> may be configured for two-way communication via electric signals (see arrows <NUM>) with the control configuration <NUM>. In one example, the call panels <NUM>, <NUM> may be landing call panels located adjacent to respective landing doors <NUM>, <NUM> on each floor <NUM>. That is, each landing call panel <NUM>, <NUM> may be mounted to a wall of the building <NUM>. The call panels <NUM>, <NUM> may be car call panels located inside the elevator car <NUM> and, in one example, adjacent to respective car doors <NUM>, <NUM>. Any one or more of the call panels <NUM>, <NUM>, <NUM>, <NUM> may be an interactive touch screen with the images of each call selection <NUM> (i.e., interactive floor or area destination selections) displayed on the screen and configured to visually change when selected. Alternatively, any one or more call panels <NUM>, <NUM>, <NUM>, <NUM> may include mechanical buttons that may be configured to, for example, illuminate when selected. In one alternative embodiment, the elevator system <NUM> may include landing call panels <NUM>, <NUM> that provide a selection of desired car travel direction (e.g., up and down directions represented by arrow) and the car call panels <NUM>, <NUM> may provide, or include, the actual call selection <NUM> relative to a desired floor destination. It is contemplated and understood that many other configurations and locations of the call panels <NUM>, <NUM>, <NUM>, <NUM> may be applicable to the present disclosure. It is contemplated and understood that the call panels <NUM>, <NUM>, <NUM>, <NUM> may include a host of other capabilities and may be programmable and/or may include a processor that may be part of the control configuration <NUM>.

Referring to <FIG>, the door actuator assemblies <NUM> of the elevator system <NUM> may generally include components such as a lower sill <NUM>, a gib <NUM>, a roller <NUM>, a belt <NUM>, an upper track <NUM>, and a door operator <NUM> that may include an electric motor or may be hydraulically actuated. The components of the door actuator assembly <NUM> are generally known by one skilled in the art, thus further explanation of physical arrangements and interactions will not be described herein. Moreover, any desired door actuator assembly <NUM> and components and arrangements thereof may be used. The door operator <NUM> is configured to receive a command signal (see arrow <NUM>) from the control configuration <NUM>, that may be based, at least in-part, on processing of the sensor signal <NUM>.

Referring to <FIG>, which illustrates a non-claimed elevator system comprising a health monitoring system, the control configuration <NUM> includes a local control arrangement <NUM>, and a server <NUM> that is remote and cloud-based. The local control arrangement <NUM> includes at least one controller (i.e., two illustrated as <NUM>, <NUM>). The server <NUM> and the local controllers <NUM>, <NUM> may each generally include respective processors <NUM>, <NUM>, <NUM> and respective electronic storage mediums <NUM>, <NUM>, <NUM> that may be computer writeable and readable. The first local controller <NUM> may be configured to generally monitor and control normal operations and functions of the elevator system via receipt of a multitude of sensory inputs (e.g., signal <NUM>) and a multitude of output commands.

The second local controller <NUM> and the remote server <NUM> may be part of a health monitoring system <NUM> along with, for example, a sensor hub or gateway <NUM>, and the sensor <NUM> and/or any variety of sensors that may be otherwise dedicated to the health monitoring system. The health monitoring system <NUM> may be configured to collect data from one or more sensory inputs, via the gateway <NUM>, and during relevant component operations (e.g., car door <NUM> operations), and process the sensory input data to assess, for example, door health and degradation of various door components. Other sensory inputs may include signals from accelerometer sensors, microphones, image devices, and others. The health monitoring system <NUM> may also be configured to determine door motion through the existing elevator communication system(s) or additional sensor inputs.

In general, the health monitoring system <NUM> may be configured to process data in two phases. The first phase may extract relevant features from sensory data, and aggregate and compress the signal. The second phase may apply machine learning to determine degradation level of individual components (e.g., door components). The first phase may be done locally (i.e., on site), and the second phase may be done either remotely (i.e., in the cloud), or locally (e.g., on a service technician's smartphone).

The health monitoring system <NUM> may further include a feature generation module <NUM>, a fault detection module <NUM>, a fault classification module <NUM> and a degradation estimation module <NUM>. The modules <NUM>, <NUM>, <NUM>, <NUM> may be software based, and may be part of a computer software product. In one embodiment, the feature generation module <NUM> and the fault detection module <NUM> may be stored locally in the electronic storage medium <NUM> of the local controller <NUM> or local control arrangement <NUM>, and executed by the processor <NUM>. In the same embodiment, the fault classification module <NUM> and the degradation estimation module <NUM> may be stored in the electronic storage medium <NUM> of the server <NUM> and executed by the processor <NUM>.

The feature generation module <NUM> is configured to extract a predesignated feature from a parameter signal (i.e., signal <NUM>) and from at least one sensor <NUM>. In one example, the sensor <NUM> may be adapted to at least assist in controlling and/or monitoring door motion as the parameter and generally detect vibration (i.e., amplitude and frequency) as the feature. That is, the feature generation module <NUM> receives relevant properties of raw signals and applies data reduction techniques producing processed data sent to the fault detection module <NUM>. It is contemplated and understood that the sensor <NUM> may be dedicated to detect vibration (e.g., an accelerometer) for use by the feature generation module <NUM>. Other examples of a sensor <NUM> may include a microphone, a velocity sensor, a position sensor, an accelerometer, a pressure sensor, and a current sensor. The microphone may be applied to detect unusual sounds. The velocity sensor may be applied to detect unexpected high or low velocities, the position sensor may be applied to detect an unusual or unexpected position of a component in a given moment in time. The current sensor may be applied to detect unexpected current levels in, for example, an electric motor of the door operator <NUM>.

The fault detection module <NUM> receives the processed data from the feature generation module <NUM>, analyzes the predesignated feature (e.g., vibration), and extracts feature derivations from the predesignated feature that may be indicative of abnormal operation (e.g., door operation). Such abnormal door operation may be caused by any number of issues including debris in the sill <NUM>, degradation of the rollers <NUM>, tension issues of the belt <NUM>, and others. The processed data associated with the feature derivations may then be sent over a wireless pathway <NUM> to the cloud-based server <NUM> for further processing by the fault classification module <NUM>. In one embodiment, the pathway <NUM> may be wired.

The fault classification module <NUM> receives the feature derivation data from the fault detection module <NUM>, and classifies the feature derivations into multiple faults. For example, the feature derivation data may contain trait frequencies at trait amplitudes each indicative of a particular fault. One vibration trait characteristic may point toward issues with the sill <NUM>, and another toward issues with the track <NUM>, and yet another toward issues with the belt <NUM>. The processed data associated with the classified feature derivations may then be sent to the degradation estimation module <NUM>.

Referring to <FIG> and <FIG>, the degradation estimation module <NUM> may be configured to apply a model <NUM> stored in the storage medium <NUM> of the server <NUM> to the classified feature derivation data to determine where the associated component lies along a degradation model or line. That is, by applying the model <NUM> the expected remaining life of a component (e.g., door component) and/or the severity of the need for maintenance may be determined. The degradation estimation module <NUM> may apply machine learning (i.e., algorithms) and/or may include a temporal regression feature, to enhance accuracy of the model <NUM>.

Referring to <FIG>, one example of a table <NUM> representing the degradation level of various exemplary components is illustrated. The table <NUM> may generally be produced by the degradation estimation module <NUM> utilizing the model <NUM>, and may be sent to any variety of destinations. In one embodiment, a service technician, building owner, service center, or other interested party may receive the table <NUM>. In the present example, the table <NUM> informs the technician that a right sill has degraded by <NUM>%, a right track has degraded by <NUM>%, a left track has degraded by <NUM>% and requires maintenance, a right roller has not degraded, and a belt has not degraded.

The modules <NUM>, <NUM> may be executed by the local controller <NUM>. The modules <NUM>, <NUM> are loaded into and executed by a smartphone that may be carried by a service technician, and the model <NUM> is stored in a cloud-based server <NUM> and retrieved by the smartphone.

It is contemplated and understood that application of the health monitoring system <NUM> and the vandalism monitoring system <NUM> is not limited to elevator doors, but may include other elevator components such as brakes, drive motors, guide wheels, interior car walls, other structural components, and more. The type of sensor <NUM> may generally be dependent upon the elevator component being monitored.

The control configuration <NUM>, or portions thereof, may be part of, one or more Application Specific Integrated Circuit(s) (ASIC), electronic circuit(s), central processing unit(s) (e.g., microprocessor and associated memory and storage) executing one or more software or firmware programs and routines, combinational logic circuit(s), input/output circuit(s) and devices, appropriate signal conditioning and buffer circuitry, and other components to provide the described functionality.

Software, modules, applications, firmware, programs, instructions, routines, code, algorithms and similar terms mean any controller executable instruction sets including calibrations and look-up tables. The control module has a set of control routines executed to provide the desired functions. Routines are executed, such as by a central processing unit, and are operable to monitor inputs from sensing devices and other networked control modules, and execute control and diagnostic routines to control operation of actuators and other devices.

Benefits and advantages of the present disclosure include a health monitoring system <NUM> that enables automated health monitoring of individual door components for each landing in an elevator system <NUM>. Such monitoring may be used to determine if maintenance is required and on what components. Because the information is available remotely, the information may be used to determine if a site visit is required by a technician or not. Yet further, and locally, the data may provide technicians with information relative to which components require attention and on which landing.

Claim 1:
An elevator system (<NUM>) comprising:
a component (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>) adapted to perform a function;
a sensor (<NUM>) configured to detect an operating parameter associated with the function; and
a control configuration (<NUM>) configured to receive a parameter signal from the sensor (<NUM>); extract a predesignated feature from data associated with the parameter signal, aggregate the predesignated feature, and apply machine learning to determine a degradation level of the function associated with the predesignated feature;
characterized by the elevator system further comprising:
a feature generation module (<NUM>) executed by the control configuration (<NUM>) for extracting the predesignated feature from the parameter signal;
a fault detection module (<NUM>) executed by the control configuration (<NUM>) to analyze the predesignated feature and extract feature derivations from the predesignated feature indicative of abnormal operation;
a fault classification module (<NUM>) executed by the control configuration (<NUM>) to classify the feature derivations into respective fault classes;
a degradation estimation module (<NUM>) executed by the control configuration (<NUM>) to establish a learned degradation model (<NUM>);
further characterized in that the control configuration (<NUM>) includes:
a local controller (<NUM>, <NUM>), and a server (<NUM>), and the local controller (<NUM>, <NUM>) is configured to execute the feature generation module (<NUM>) and the server (<NUM>) is configured to execute the fault classification module (<NUM>) and the degradation estimation module (<NUM>);
wherein the server (<NUM>) is cloud-based; and
wherein the control configuration includes:
a sensor hub (<NUM>) configured to receive the parameter signal;
a mobile device, wherein the mobile device is configured to receive the parameter signal from the local controller (<NUM>, <NUM>), execute the feature generation module (<NUM>), execute the fault detection module (<NUM>), execute the fault classification module (<NUM>), and execute the degradation estimation module (<NUM>); and
a cloud-based server (<NUM>) configured to communicate with the mobile device and store the learned degradation model (<NUM>) for use by the degradation estimation module (<NUM>).