Cotton harvesting machine with automatically variable drum and spindle speed

A sensor input is detected on a cotton harvester. A performance characteristic value is identified based upon the detected sensor input. A speed control system controls cotton harvester drum speed and spindle speed, automatically, and separately from the ground speed of the cotton harvester, to improve the performance characteristic value, in a closed-loop fashion.

FIELD OF THE DESCRIPTION

The present description relates to a cotton harvester. More specifically, the present description relates to automatically varying drum and spindle speed on a cotton harvester, separately from ground speed.

BACKGROUND

Some current cotton harvesters have a set of row units on the front end of the harvesters. The row units act to funnel cotton plants, planted in rows, into the individual row units. Each row unit has two columns of spindles, one mounted on either side of the row, as it passes through the row unit. Each set of spindles is driven so that the spindles on one side of the row unit rotate in interdigitated fashion relative to the spindles on the opposite side of the row unit. The spindles are supported for rotation in this way, by a drum. As the drums rotate the spindles, the spindles separate the cotton flowers from the cotton plants. Each of the spindles is elongate along a longitudinal axis. The spindles also rotate about the longitudinal axis. Rotation of the spindles draws the cotton bolls into elongate fibers.

A rotatable doffer rotates in a counter rotating manner, relative to the spindles, to wipe the cotton material from the spindles. The cotton material is then transferred (such as using a vacuum tube or other conveying mechanism) into a containment area. The cotton is transferred from the containment area into a module forming area. Once a module is formed, a door opens at the rearward end of the cotton harvester, so that the module can be ejected, onto the field.

In many current cotton harvesters, the speed of the drum rotation, and the speed of the spindle rotation, is directly and mechanically linked to the forward ground speed of the cotton harvester. This can present a variety of different types of problems. Therefore, a mechanism has been developed so that the drum speed and spindle speed can be varied separately relative to the ground speed of the cotton harvester. One example of this is set out in U.S. Pat. No. 5,325,656.

SUMMARY

A sensor input is detected on a cotton harvester. A performance characteristic value is identified based upon the detected sensor input. A speed control system controls cotton harvester drum speed and spindle speed, automatically, and separately from the ground speed of the cotton harvester, to improve the performance characteristic value, in a closed-loop fashion.

DETAILED DESCRIPTION

As discussed above, some current systems provide for a variable ratio of drum speed and spindle speed relative to the forward ground speed of the cotton harvester. However, even though the drum and spindle speed may vary separately from the ground speed of the cotton harvester, choosing a drum speed and spindle speed that achieve desired harvesting performance can be very difficult. This is because it can be difficult for an operator to observe how the harvesting performance changes, with changes in the spindle and drum speeds. Similarly, even if this can be observed, the field and crop conditions can change relatively quickly. Therefore, it can be difficult to select a drum speed and spindle speed that maintains harvesting performance at a desired level. It can also be distracting for the operator, and it can be error prone. As just some examples, a cotton harvesting operation can have varying degrees of crop loss, at different drum and spindle speeds, due to weather conditions, cotton variety, cotton maturity, yield (number of bolls per plant), crop conditions (such as moisture), field conditions, among other things.

Therefore, the present description proceeds with respect to a system that provides automatic, closed loop drum and spindle speed control. A harvesting performance characteristic value is generated based on one or more sensor inputs. That value is provided to a dynamic machine learning speed control system which generates drum speed control signals and spindle speed control signals. Those speed control signals are used to control drum and spindle speed and are also fed back to the dynamic machine learning speed control system, along with a current value of the performance characteristic, so that the drum and spindle speed signals can be varied to improve the performance characteristic value.

FIG. 1is a side pictorial view of a cotton harvester100.FIG. 1shows that harvester100includes a front end102, an operator's compartment104, a set of ground engaging elements (such as wheels)106, a conveyor mechanism108, a cotton containment area110and a module forming area112. An engine (or other power source) drives movement of harvester100in the forward direction indicted by arrow114. As harvester100moves in that direction, the front end (which includes a set of row units116extending in the forward direction) engage rows of crop (cotton) and funnel them into the front end portion102where the cotton bolls are separated from the cotton plants. The cotton is then lifted by conveyor mechanism108(which can be a tube that moves the cotton upwardly under vacuum pressure, or positive air pressure, or it can be another conveyance mechanism). The cotton118is then placed in containment area110where it builds to a desired level. It is then moved rearwardly toward the module forming portion112where it is formed into a module120. Once the module120reaches a desired size, it can be removed from the module forming portion112through a rearward portion122of harvester100.

FIG. 2is another pictorial illustration of the harvester100shown inFIG. 1, except it that is taken from a forward portion of harvester100so that the row units116can be seen more clearly. When the cotton is funneled into harvester100through row units116, the cotton plants encounter the rotatable spindles. The spindles are elongate projections that are rotatably driven by a set of drums. A column of spindles is disposed on either side of the cotton row and the spindles rotate relative to one another in interdigitated fashion to draw the cotton into harvester100. The spindles also rotate about their elongate axes. Thus, the spindles remove the cotton bolls from the cotton plants. The rotation of the spindles about their elongate axes serve to draw the cotton material into elongate fibers.

FIG. 3is a block diagram showing one example of a portion of cotton harvester100.FIG. 3shows that one or more sensors130can be disposed on harvester100and generate sensor signals indicative of sensed variables. For instance, a sensor130may be a mass flow sensor that senses the mass flow of cotton through a particular row unit, or through harvester100. The sensors can be a wide variety of other sensors as well, and some of those are described below with respect toFIG. 4.

The sensor signal is provided to a spindle and drum speed control system132which generates a drum speed signal134and a spindle speed signal136. Those signals are provided to variable drum drive system138and variable spindle drive system140, respectively. The variable drive systems138and140provide outputs that drive rotation of the drums142and spindles144on one or more row units116. The variable drum and spindle drive systems can be variable speed motors, gear boxes with automatically shiftable gears that are driven by a transmission from the harvester engine, or other drive systems.

In one example, there may be different variable drum drive systems138and variable spindle drive systems140for the different row units116on harvester100. Thus, the drums on the different row units can be driven at different speeds, as can the spindles. In that way, the performance of each individual row unit can be optimized or otherwise improved separately from the other row units. In another example, there is one variable drum drive system138and one variable spindle drive system140. Thus, system138drives the drums142on all row units116at the same rate, and system140drives rotation of all spindles144on all row units116at the same rate as well.

Cotton harvester100will, of course, have a wide variety of other cotton harvester functionality as well. This is indicated by block148in the block diagram ofFIG. 3.

FIG. 3also shows that, in one example, spindle and drum speed control system132can include one or more processors150, performance characteristic value identifier system152, data store154, dynamic (on-the-fly) machine learning speed control system156, and it can include other items158.

Performance characteristics value identifier system152receives the sensor signals from sensors130and identifies a performance characteristic value that speed control system132uses for automatically controlling the drum speed and spindle speed. That value is fed into dynamic (on-the-fly) machine learning speed control system156which determines, based upon the current speed control signals and the performance characteristic value, whether the speed signals should be changed (so that the drum speed is increased or decreased, and/or so that the spindle speed is increased or decreased). If so, system156generates one or more new speed control signals134and136and provides them to the variable drive systems138and140, respectively. It thus changes the speed of one or more drums142and/or spindles144. System156then also receives a new performance characteristic value from system152and determines whether the change in speed improved the performance of cotton harvester100(as measured by the performance characteristic value).

As just one example, assume the performance characteristic being monitored is mass flow rate of cotton through the row units (which can be measured in kilograms per second or kilograms per meter of row traveled by machine100). Then, dynamic machine learning speed control system156receives the mass flow value from system152, along with the current speed control signals134and136. It determines whether to change one of more of the speed control signals in an attempt to improve the mass flow value. It can do this based on a machine learned control algorithm that has values, or relationships, that have been learned during the operation of harvester100in the current field (or in neighboring fields). If speed control system156does change one or more of the speed signals134and136, then it determines whether the performance characteristic value improved or got worse, or stayed the same. It uses that result to perform additional learning and to thus modify the machine learned control algorithm, and also to generate the speed control signals134and146.

In another example, performance characteristic value identifier system152may identify the values of a plurality of different performance characteristics. The machine learning control algorithm used by dynamic machine learning speed control system156may be used to optimize (or improve) harvester operation as measured by those plurality of characteristics. This type of multi-input feed back control can be used to improve the overall operation of cotton harvester100, by controlling the speed of drums142and144, on-the-fly, to optimize (or improve) the multiple performance characteristics.

FIGS. 4A and 4B(collectively referred to herein asFIG. 4) show a block diagram showing one example of cotton harvester100, with some items that are similar to those shown inFIG. 3(and they are similarly numbered). However,FIG. 4shows a number of items in more detail.

FIG. 4shows that, in one example, sensors130can be control inputs or sensors that sense the value of control inputs, as indicated by block162. For instance, a ground speed sensor can sense the value of the ground speed control input, or it can sense the actual ground speed of harvester100and provide a sensor signal indicative of that. This is just one example of a control signal that can be sensed.

Sensors130can include a mass flow sensor164. The mass flow sensor may be an optical sensor or another sensor that senses the mass flow of cotton through each individual row units, or through the conveyor, or another portion of harvester100.

Sensors130can include a moisture sensor166. The moisture sensor may generate a sensor value based upon the dimensions of the cotton module120generated by harvester100, and based on its weight. The moisture sensor166can generate a sensor signal in other ways as well.

Sensors130can include module weight/mass sensor168. Sensor168can be a sensor that is disposed on harvester100to sense the weight of a module, as it is being transported by harvester100, as it is exiting harvester100, etc.

The sensors130can include a loss sensor170that senses crop loss. In one example, loss sensor170may be an optical sensor (such as a camera or other image sensor) that senses an amount of crop still on the plants, after harvester100has passed. It can generate a loss signal indicative of an estimated crop loss value.

Sensors130can include a wide variety of other sensors as well. This is indicated by block172.

The sensor signals are received by performance characteristic value identifier system152. It can include signal conditioning logic174, signal aggregation/processing logic176, value identifier logic178, and a wide variety of other items180. Signal conditioning logic174can provide signal conditioning, such as amplification, normalization, linearization, filtering, etc. Signal aggregation/processing logic176can aggregate or otherwise process signals so that various derived performance characteristic values can be obtained. For instance, it may be that signal values are aggregated and averaged over time, or processed relative to other values in order to obtain the desired performance characteristic. Based on the conditioned and possibly aggregated or otherwise processed sensor signals, value identifier logic178generates the value for the one or more performance characteristics being used to control drum and spindle speed. System152then outputs the one more performance characteristic values182to dynamic machine learning speed control system156.

Data store154can store a machine learned model or machine learning algorithm that can be used as the control (or improvement) algorithm it can reside elsewhere as well.

System156can include improvement algorithm execution logic184, learning logic186, drum speed signal generator188, spindle speed signal generator190, and it can include other items192. Improvement algorithm execution logic184executes the optimization or improvement algorithm that can be used to determine whether a speed change is needed for either drums142or spindles144. Learning logic186can perform continuous machine learning to improve the control algorithm. Drum speed signal generator188generates the drum speed signal134that is applied to the variable drum drive system138. Spindle speed signal generator190generates the spindle speed signal136that is applied to the variable spindle drive system140. Speed signals134and136are also fed back to system156, so that they are used in a closed loop fashion.

FIGS. 5A and 5B(collectively referred to herein asFIG. 5) describe a flow diagram illustrating the operation of cotton harvester100in controlling spindle and drum speed separately from harvester ground speed. It is first assumed that cotton harvester100has drum and spindle drive systems that are controllable separately from one another and from the ground speed of harvester100. This is indicated by block200in the flow diagram ofFIG. 5. Dynamic on-the-fly machine learning speed control system156sets an initial drum speed and spindle speed. In doing so, it generates drum and spindle speed signals134and136and provides them to drives138and140so the drums and spindles are rotating at the desired speed. Setting an initial drum speed and spindle speed is indicated by block202in the flow diagram ofFIG. 5.

An operator controls cotton harvester100to begin performing initial harvesting operation. Harvester100can harvest for a certain amount of time, for a certain amount of distance, it can harvest a certain amount of cotton, etc. Performing an initial harvesting operation is indicated by block204.

Performance characteristic value identifier system152then senses the inputs from sensors130. This is indicated by block206. As mentioned above, the sensors can be a ground speed sensor162, other control inputs208, a mass flow sensor164, a crop moisture sensor166, a module weight/mass sensor168, a loss sensor170, any of a wide variety of other sensors from which yield can be obtained, as indicated by block210, or other direct sensor inputs or derived metrics, as indicated by block212. Performance characteristic value identifier system152then identifies the value of a desired performance characteristic. This is indicated by block214in the flow diagram ofFIG. 5. It can be a direct sensor input as indicated by block216, or it can be a derived value based on an aggregated or otherwise processed signal (aggregated or processed by logic176) and identified by identifier logic178. Identifying a derived value is indicated by block218in the flow ofFIG. 5.

It is then assumed that improvement algorithm execution logic184executes an improvement algorithm based upon the initial speed signals134and146and based upon the performance characteristic value182. This is indicated by block220in the flow diagram ofFIG. 5. It can be based on a machine learning algorithm that was stored in data store154, as indicated by block222, or it can be based on another algorithm as indicated by block224.

Again, harvester100performs a harvesting operation. This is indicated by block226. It can harvest for a desired distance, a desired time, it can harvest a desired amount of cotton, etc.

Performance characteristic value identifier system152then continues to detect the sensor inputs from one or more of sensors130. This is indicated by block228. System152also identifies a new value of the performance characteristic that is being used to control the drum and spindle speeds. Identifying the new value of the performance characteristics is indicated by block230in the flow diagram ofFIG. 5.

Learning logic186can perform machine learning to update the machine learned algorithm executed by logic184. It can do this based upon the new inputs (e.g., the new performance characteristic value182and the adjusted speed signals134and136). Performing machine learning based upon the new values is indicated by block232in the flow diagram ofFIG. 5.

As long as the operation is not complete, as indicated by block234, then improvement algorithm execution logic184can determine whether either or both of the speed signals134and136need to be changed, based upon the optimization (or improvement) algorithm. If so, it indicates the direction and magnitude of change to drum speed signal generator188and/or spindle speed signal generator190. Generator188generates the drum speed signal134at the new level. It is provided to drum drive system138to change the speed of rotation of drum142. Similarly, when the spindle speed is to be changed, spindle speed signal generator190generates spindle speed signal136based upon the magnitude and direction of change provided by improvement algorithm execution logic184. That signal is provided to variable spindle drive system140which changes the speed of rotation of spindles144. Thus, at block236in the flow diagram ofFIG. 5, if any speed is to be changed based upon the output of improvement algorithm execution logic184, then processing reverts to block220where the drum and/or spindle speed is modified. However, if logic184generates an output indicating that neither the drum nor spindle speed need to be changed, then processing reverts to block226where harvester100again continues to perform the harvesting operating.

It can thus be seen that the present system performs closed loop control of the drum and spindle speed to optimize one or more different performance characteristics. It can also improve harvester operation in other ways. For instance, it may be that the current spindle speed is maintaining the performance characteristic at a desired level, but it may be able to be decreased without the performance characteristic value changing in a significant way (such as by a threshold amount). In that case, system156generates an output to reduce the spindle speed, while still maintaining the performance characteristic value at a desired level. This reduces the wear on the spindle, the spindle drive train, the variable speed drive system140, etc. The same can be done with respect to drum142. Thus, dynamic machine learning speed control system156can optimize or improve machine performance as measured by a number of different metrics (such as yield or efficiency, mass flow rate, as well as machine wear, etc.) at the same time.

It will also be noted that multiple cotton harvesters may be operating in one field. In that case, the drive and spindle speeds of the various harvesters can be shared among them and used to learn and adjust speeds on any given harvester.

It will also be noted that the elements ofFIGS. 2 and 3, or portions of them, can be disposed on a wide variety of different devices. Some of those devices include servers, desktop computers, laptop computers, tablet computers, or other mobile devices, such as palm top computers, cell phones, smart phones, multimedia players, personal digital assistants, etc.

FIG. 6is one embodiment of a computing environment in which elements ofFIG. 1, or parts of it, (for example) can be deployed. With reference toFIG. 6, an exemplary system for implementing some embodiments includes a general-purpose computing device in the form of a computer810. Components of computer810may include, but are not limited to, a processing unit820(which can comprise processor150), a system memory830, and a system bus821that couples various system components including the system memory to the processing unit820. The system bus821may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. Memory and programs described with respect toFIG. 1can be deployed in corresponding portions ofFIG. 6.

The computer810may also include other removable/non-removable volatile/nonvolatile computer storage media. By way of example only,FIG. 6illustrates a hard disk drive841that reads from or writes to non-removable, nonvolatile magnetic media, an optical disk drive855, and nonvolatile optical disk856. The hard disk drive841is typically connected to the system bus821through a non-removable memory interface such as interface840, and optical disk drive855are typically, connected to the system bus821by a removable memory interface, such as interface850.

The computer810is operated in a networked environment using logical connections (such as a local area network—LAN, or wide area network WAN) to one or more remote computers, such as a remote computer880.

When used in a LAN networking environment, the computer810is connected to the LAN871through a network interface or adapter870. When used in a WAN networking environment, the computer810typically includes a modem872or other means for establishing communications over the WAN873, such as the Internet. In a networked environment, program modules may be stored in a remote memory storage device.FIG. 6illustrates, for example, that remote application programs885can reside on remote computer880.

Example 1 is a cotton harvester, comprising:

a frame;

ground engaging elements driven by a power source at a drive speed;

a sensor sensing a sensed variable and generating a sensor signal indicative of the sensed variable;

a variable drum drive system;

a variable spindle drive system;

a drum that is rotatable relative to the frame and that is rotatably driven by the drum drive system;

a first spindle mounted to a spindle support structure, rotation of the drum driving rotation of the spindle support structure, the spindle having a corresponding longitudinal axis and being rotatable about the longitudinal axis, the spindle drive system driving rotation of the spindle about the corresponding longitudinal axis; and

a speed control system that automatically generates a drum speed signal, based on the sensor signal, and that automatically generates a spindle speed signal based on the sensor signal, the variable drum drive system driving rotation of the drum at a speed based on the drum speed signal, and the variable speed spindle drive system driving rotation of the spindle at a speed based on the spindle speed signal.

Example 2 is the cotton harvester of any or all previous examples wherein the speed control system automatically generates the drum speed signal and the spindle speed signal independently of the drive speed.

Example 3 is the cotton harvester of any or all previous examples wherein the speed control system comprises:

a performance characteristic value identifier system configured to receive the sensor signal and identify a performance characteristic value of a performance characteristic based on the sensor signal; and

a dynamic speed control system that automatically varies the drum speed signal and the spindle speed signal based on changes in the performance characteristic value.

Example 4 is the cotton harvester of any or all previous examples wherein a current value of the drum speed signal and a current value of the spindle speed signal are fed back into the dynamic speed control system so the dynamic speed control system varies the drum speed signal and the spindle speed signal based on the performance characteristic value and the current value of the drum speed signal and the current value of the spindle speed signal.

Example 5 is the cotton harvester of any or all previous examples wherein the dynamic speed control system varies the drum speed signal and the spindle speed signal during operation of the cotton harvester in performing a harvesting operation.

Example 6 is the cotton harvester of any or all previous examples wherein the dynamic speed control system comprises:

improvement algorithm execution logic configured to execute an improvement algorithm to identify a new value for the drum speed signal based on the current value of the drum speed signal and the performance characteristic value, and to identify a new value for the spindle speed signal based on the current value of the spindle speed signal and the performance characteristic value.

Example 7 is the cotton harvester of any or all previous examples wherein the dynamic speed control system comprises:

a drum speed signal generator configured to generate the drum speed signal based on the new value for the drum speed signal; and

a spindle speed signal generator configured to generate the spindle speed signal based on the new value for the drum speed signal.

Example 8 is the cotton harvester of any or all previous examples wherein the sensor comprises:

a mass flow sensor that senses a mass flow of cotton through a portion of the cotton harvester and generates the sensor signal as a mass flow signal indicative of the sensed mass flow.

Example 9 is the cotton harvester of any or all previous examples wherein the sensor comprises:

a loss sensor that senses a crop loss variable indicative of crop loss and generates the sensor signal as a loss signal indicative of the sensed crop loss variable.

Example 10 is the cotton harvester of any or all previous examples wherein the sensor comprises:

a moisture sensor that senses crop moisture and generates the sensor signal as a moisture signal indicative of the sensed crop moisture.

Example 11 is the cotton harvester of any or all previous examples and further comprising a module forming mechanism that forms a cotton module, wherein the sensor comprises:

a module weight/mass sensor that senses module weight or mass and generates the sensor signal as a weight/mass signal indicative of the sensed module weight or mass.

Example 12 is a control system on a cotton harvester that travels at a controllable ground speed and that has a rotatable drum that supports spindles, the control system comprising:

a sensor sensing a sensed variable and generating a sensor signal indicative of the sensed variable; and

a speed control system that automatically generates a drum speed signal, based on the sensor signal, and provides the drum speed signal to a variable drum drive system driving rotation of the drum at a speed based on the drum speed signal.

Example 13 is the control system of any or all previous examples wherein the speed control system automatically generates the drum speed signal and the spindle speed signal independently of the ground speed.

Example 14 is the control system of any or all previous examples wherein the speed control system automatically generates a spindle speed signal, based on the sensor signal, and provides the spindle speed signal to a variable spindle drive system driving rotation of the rotatable spindles at a speed based on the spindle speed signal.

Example 15 is the control system of any or all previous examples wherein the speed control system comprises:

a performance characteristic value identifier system configured to receive the sensor signal and identify a performance characteristic value of a performance characteristic based on the sensor signal; and

a dynamic speed control system that automatically varies the drum speed signal and the spindle speed signal based on changes in the performance characteristic value.

Example 16 is the control system of any or all previous examples wherein a current value of the drum speed signal and a current value of the spindle speed signal are fed back into the dynamic speed control system, the dynamic speed control system varying the drum speed signal and the spindle speed signal based on the performance characteristic value and the current value of the drum speed signal and the current value of the spindle speed signal.

Example 17 is the control system of any or all previous examples wherein the dynamic speed control system varies the drum speed signal and the spindle speed signal during operation of the cotton harvester in performing a harvesting operation.

Example 18 is the control system of any or all previous examples wherein the dynamic speed control system comprises:

improvement algorithm execution logic configured to execute an improvement algorithm to identify a new value for the drum speed signal based on the current value of the drum speed signal and the performance characteristic value, and to identify a new value for the spindle speed signal based on the current value of the spindle speed signal and the performance characteristic value.

Example 19 is a control system on a cotton harvester that travels at a controllable ground speed and that has a rotatable drum that supports rotatable spindles, the control system comprising:

a sensor sensing a sensed variable and generating a sensor signal indicative of the sensed variable; and

a speed control system that automatically generates a spindle speed signal, based on the sensor signal, and provides the spindle speed signal to a variable spindle drive system driving rotation of the rotatable spindles at a speed based on the spindle speed signal.

Example 20 is the control system of any or all previous examples wherein the speed control system that automatically generates a drum speed signal, based on the sensor signal, and provides the drum speed signal to a variable drum drive system driving rotation of the drum at a speed based on the drum speed signal.