Method, device and system for determining loss of harvester and storage medium
By determining the screening threshold based on the harvester model, selecting target data from vehicle operation data, monitoring the real-time loss rate, and adjusting operating parameters, the problem of accurately quantifying harvester losses is solved, enabling accurate determination of loss trends and reduction of losses without considering crop quality and yield.
Patent Information
- Application Number
- CN202511474383.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-15
- Publication Date
- 2026-02-27
AI Technical Summary
Existing technologies make it difficult to accurately determine the losses of harvesters during operation, especially the losses caused by entrainment and cleaning, without considering crop quality and yield.
By determining the screening threshold based on the type of harvester, target data is selected from pre-stored operating data of similar vehicles, real-time loss rate is monitored, and compared with the best operating condition information to adjust operating parameters to determine the loss trend.
It enables accurate determination of harvester loss trends without considering crop quality and yield, and reduces grain loss by automatically adjusting operating parameters.
Smart Images
Figure CN121569657A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of harvester control, and particularly relates to a method, device and system for determining loss of a harvester and a storage medium. BACKGROUND
[0002] In the process of performing harvesting work by the harvester, there are mainly two reasons for causing grain loss. The first reason is that the grains are not completely separated from the straws and are discharged together with the straws, which is called entrainment loss. The second reason is that the grains are blown out by the fan during cleaning, which is called cleaning loss.
[0003] At present, when determining the loss of the harvester, the quality of the crops and the yield of the harvesting need to be considered. However, the quality of the crops and the yield of the harvesting are usually difficult to accurately calculate.
[0004] Therefore, how to determine the loss of the harvester in the process of work without considering the quality of the crops and the yield is a technical problem to be solved by the person skilled in the art. SUMMARY
[0005] The embodiment of the present application aims to provide a method, device, system and storage medium for determining loss of a harvester.
[0006] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a method for determining loss of a harvester, comprising: determining a screening threshold for each working condition parameter of the harvester according to a current model of the harvester, wherein the working condition parameter at least includes working time, vehicle speed, entrainment loss rate and cleaning loss rate; selecting target data corresponding to each working condition parameter from a plurality of running data of the same type of vehicles pre-stored based on the screening threshold; monitoring real-time entrainment loss rate and real-time cleaning loss rate of the harvester in the process of work; comparing a plurality of real-time entrainment loss rates and a plurality of real-time cleaning loss rates in a preset period with optimal working condition information to determine a loss trend of the harvester, wherein the optimal working condition information is determined according to the target data corresponding to each working condition parameter; adjusting working parameters of the harvester according to the loss trend.
[0007] In the embodiment of the present application, the selecting the target data corresponding to each working condition parameter from the pre-stored vehicle operation data of the same type based on the screening threshold comprises: traversing the vehicle historical operation data of the same type; selecting the data with the working time greater than or equal to the working time threshold in the vehicle historical operation data as the target data corresponding to the working time; selecting the data with the vehicle speed greater than or equal to the vehicle speed threshold in the vehicle historical operation data as the target data corresponding to the vehicle speed; selecting the data with the entrainment loss rate less than or equal to the entrainment loss rate threshold in the vehicle historical operation data as the target data corresponding to the entrainment loss rate; and selecting the data with the cleaning loss rate less than or equal to the cleaning loss rate threshold in the vehicle historical operation data as the target data corresponding to the cleaning loss rate.
[0008] In the embodiment of the present application, the method further comprises: before the step of comparing the plurality of real-time entrainment loss rates and the plurality of real-time cleaning loss rates in the preset period with the optimal working condition information to determine the loss trend of the harvester, determining a first average value of the entrainment loss rate and a second average value of the cleaning loss rate in the optimal working condition information; determining a third average value of the plurality of real-time entrainment loss rates and a fourth average value of the plurality of real-time cleaning loss rates in the preset period; determining the entrainment loss trend based on a first difference value between the first average value and the third average value, and determining the cleaning loss trend based on a second difference value between the second average value and the fourth average value.
[0009] In the embodiment of the present application, the monitoring the real-time entrainment loss rate and the real-time cleaning loss rate of the harvester in the working process comprises: detecting whether the entrainment loss sensor and the cleaning loss sensor in the harvester are in a normal working state, and detecting whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal; in the case that the entrainment loss sensor is detected to be in the normal working state and the real-time entrainment loss rate is abnormal, replacing the real-time entrainment loss rate with a first average value; and in the case that the cleaning loss sensor is detected to be in the normal working state and the real-time cleaning loss rate is abnormal, replacing the real-time cleaning loss rate with a second average value.
[0010] In the embodiment of the present application, the detecting whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal comprises: in the case that the real-time entrainment loss rate collected by the entrainment loss sensor is detected to be greater than a first preset multiple threshold of the first average value, determining that the real-time entrainment loss rate is abnormal; and in the case that the real-time cleaning loss rate collected by the cleaning loss sensor is detected to be greater than a second preset multiple threshold of the second average value, determining that the real-time cleaning loss rate is abnormal.
[0011] In the embodiment of the present application, the entrainment loss trend is determined based on a first difference between the first average value and the third average value, and the cleaning loss trend is determined based on a second difference between the second average value and the fourth average value, including: calculating a first absolute value of the first difference between the first average value and the third average value; determining a first ratio between the first absolute value and the third average value, and taking the product of the first ratio and a preset coefficient as the entrainment loss trend; calculating a second absolute value of the second difference between the second average value and the fourth average value; determining a second ratio between the second absolute value and the fourth average value, and taking the product of the second ratio and the preset coefficient as the cleaning loss trend; wherein the preset coefficient is preset based on the vehicle type of the harvester.
[0012] In the embodiment of the present application, the step of adjusting the operation parameters of the harvester according to the loss trend includes: automatically adjusting the drum rotating speed, the concave clearance and the vehicle speed based on the entrainment loss trend, and automatically adjusting the upper and lower sieve opening and the fan rotating speed based on the cleaning loss trend.
[0013] The second aspect of the present application provides a device for determining the loss of a harvester, including: a memory configured to store instructions; a processor configured to call the instructions from the memory and capable of implementing the above method for determining the loss of a harvester when executing the instructions.
[0014] The third aspect of the present application provides a system for determining the loss of a harvester, including the above device for determining the loss of a harvester.
[0015] The fourth aspect of the present application provides a machine readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, cause the processor to be configured to perform the above method for determining the loss of a harvester.
[0016] In the embodiment of the present application, the screening threshold values for each working condition parameter of the harvester are determined according to the vehicle type of the current harvester, and the working condition parameters at least include the operation time, the vehicle speed, the entrainment loss rate and the cleaning loss rate, so that accurate screening threshold values can be obtained according to the vehicle type; then the target data corresponding to each working condition parameter is selected from the pre-stored running data of multiple same types of vehicles based on the screening threshold values, so that the target data corresponding to the vehicle type can be obtained according to the screening threshold values; then the real-time entrainment loss rate and the real-time cleaning loss rate of the harvester in the operation process are monitored, so that the loss condition of the harvester in actual operation can be obtained; then the multiple real-time entrainment loss rates and the multiple real-time cleaning loss rates within a preset period are compared with the best operation working condition information to determine the loss trend of the harvester, and the best operation working condition information is determined according to the target data corresponding to each working condition parameter; finally, the operation parameters of the harvester are adjusted according to the loss trend.
[0017] In the embodiment of the present application, the target data under the ideal working condition of the vehicle type can be obtained based on the vehicle type and the screening threshold value, and then the real-time loss rate can be compared with the loss rate in the target data to determine the loss trend of the harvester. Thus, the present application achieves the purpose of determining the loss of the harvester during operation without considering the crop quality and yield.
[0018] Other features and advantages of the embodiments of the present application will be described in detail in the following specific implementation part. BRIEF DESCRIPTION OF DRAWINGS
[0019] The accompanying drawings are used to provide further understanding of the embodiments of the present application and constitute a part of the specification, and are used to explain the embodiments of the present application together with the following specific implementation, but do not constitute a limitation on the embodiments of the present application. In the drawings: Figure 1 The structure schematic diagram of the working vehicle according to the embodiments of the present application is schematically shown; Figure 2 The sensor connection schematic diagram of the method for determining the loss of the harvester according to the embodiments of the present application is schematically shown; Figure 3 The system structure block diagram of the method for determining the loss of the harvester according to the embodiments of the present application is schematically shown; Figure 4 The internal structure diagram of the computer device according to the embodiments of the present application is schematically shown. DETAILED DESCRIPTION
[0020] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiments of the present application, and is not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.
[0021] It should be noted that the execution subject of the method for determining the loss of the harvester in the present application is a computer device, which can be a computer, a processor or the like, and the device can be built-in in the harvester or connected to the harvester in a wired or wireless manner as a separate device, which is not limited in the present application. In each embodiment of the method for determining the loss of the harvester in the present application, the execution subject is omitted.
[0022] Please refer to Figure 1 , Figure 1 The flowchart of the method for determining the loss of the harvester according to the embodiments of the present application is schematically shown. As Figure 1As shown, in the embodiment of the present application, a method for determining the loss of a harvester is provided, and the method comprises the following steps: In step 201, the screening threshold for each working condition parameter of the harvester is determined according to the current model of the harvester, and the working condition parameters at least include the working time, the vehicle speed, the entrainment loss rate and the cleaning loss rate.
[0023] It can be understood that the above-mentioned entrainment loss rate refers to the loss of grains obtained at the classification cylinder, and the cleaning loss rate refers to the loss of grains obtained at the cleaning screen. Specifically, a loss sensor is installed at the end of the separation cylinder in the harvester, which is called an entrainment loss sensor. Of course, under the premise that there are multiple separation cylinders in the harvester, a loss sensor can be installed at each separation cylinder. A loss sensor can also be installed at the tail end of the cleaning screen of the harvester, which can be called a cleaning loss sensor.
[0024] In the embodiment of the present application, before determining the loss of the harvester, the model of the current harvester needs to be obtained, and then in the preset corresponding relationship between the screening threshold and the model, the screening threshold for determining the loss of the current harvester is determined based on the model, so as to improve the correctness of the loss based on the accurate screening threshold.
[0025] In step 202, the target data corresponding to each working condition parameter is selected from the pre-stored multiple same type vehicle running data based on the screening threshold.
[0026] It can be understood that before determining the loss of the harvester, the vehicle running data of each model during field operation will be collected by the on-board 4G terminal. Then, the collected vehicle running data will be uploaded to the cloud platform. When it is necessary to determine the loss of a certain model during operation, the vehicle running data corresponding to the model can be searched from the pre-stored multiple vehicle running data by taking the model as an index. The pre-stored data can be stored in the cloud or stored locally, and the present application does not limit it. Then, for the found data, the target data corresponding to each working condition parameter of the model under ideal conditions can be found from each data by using the screening threshold.
[0027] Specifically, in an embodiment, the step 202 comprises: traversing the historical operation data of the same type of vehicle; selecting the data with the operation time greater than or equal to the operation time threshold value in the historical operation data of the vehicle as the target data corresponding to the operation time; selecting the data with the vehicle speed greater than or equal to the vehicle speed threshold value in the historical operation data of the vehicle as the target data corresponding to the vehicle speed; selecting the data with the entrainment loss rate less than or equal to the entrainment loss rate threshold value in the historical operation data of the vehicle as the target data corresponding to the entrainment loss rate; and selecting the data with the cleaning loss rate less than or equal to the cleaning loss rate threshold value in the historical operation data of the vehicle as the target data corresponding to the cleaning loss rate.
[0028] It can be understood that, in the scenario of only considering the operation time, the target data can be obtained by screening the data through the operation time threshold value; in the scenario of only considering the vehicle speed, the target data can be obtained by screening the data through the vehicle speed threshold value; in the scenario of only considering the entrainment loss rate, the target data can be obtained by screening the data through the entrainment loss rate threshold value; and in the scenario of only considering the cleaning loss rate, the target data can be obtained by screening the data through the cleaning loss rate threshold value.
[0029] Of course, in an embodiment, multiple factors can be considered simultaneously to determine the target data. For example, the operation time, the vehicle speed, the entrainment loss rate and the cleaning loss rate can be considered simultaneously.
[0030] The step 203 comprises: monitoring the real-time entrainment loss rate and the real-time cleaning loss rate of the harvester during the operation.
[0031] In the embodiment, the real-time entrainment loss rate can be obtained by the entrainment loss sensor and the real-time cleaning loss rate can be obtained by the cleaning loss sensor during the operation of the harvester.
[0032] The step 204 comprises: comparing the multiple real-time entrainment loss rates and the multiple real-time cleaning loss rates in the preset period with the best operation condition information to determine the loss trend of the harvester, the best operation condition information being determined according to the target data corresponding to each operation condition parameter.
[0033] It can be understood that the values of the entrainment loss sensor and the cleaning loss sensor can only represent the situation at a certain moment and cannot measure the harvesting situation of the harvester from the overall perspective. Therefore, the multiple real-time entrainment loss rates and the multiple real-time cleaning loss rates in the preset period are compared with the best operation condition information to determine the loss trend of the harvester. The best operation condition information can be all the target data corresponding to the current vehicle model.
[0034] The step 205 comprises: adjusting the operation parameters of the harvester according to the loss trend.
[0035] In the embodiment, after the loss trend corresponding to the harvester is obtained, the operation parameters of the harvester can be automatically adjusted according to the loss trend to reduce the loss of the grain.
[0036] In the embodiment, the screening threshold of each working condition parameter of the harvester is determined according to the vehicle type of the current harvester, the working condition parameters at least include the operation time, the vehicle speed, the entrainment loss rate and the cleaning loss rate, and the accurate screening threshold can be obtained according to the vehicle type; then the target data corresponding to each working condition parameter is selected from the pre-stored operation data of multiple vehicles of the same type based on the screening threshold, so that the target data corresponding to the vehicle type can be obtained based on the screening threshold; then the real-time entrainment loss rate and the real-time cleaning loss rate of the harvester in the operation process are monitored, and the loss of the actual operation of the harvester can be obtained; then the multiple real-time entrainment loss rates and the multiple real-time cleaning loss rates in the preset period are compared with the best operation working condition information to determine the loss trend of the harvester, and the best operation working condition information is determined according to the target data corresponding to each working condition parameter; finally, the operation parameters of the harvester are adjusted according to the loss trend.
[0037] In the embodiment, the target data under the ideal working condition of the vehicle type can be obtained based on the vehicle type and the screening threshold, and then the real-time loss rate can be compared with the loss rate in the target data to determine the loss trend of the harvester. Thus, the purpose of determining the loss of the harvester in the operation process without considering the quality and yield of the crops is achieved.
[0038] Further, based on the first embodiment of the method for determining the loss of the harvester, the second embodiment of the method for determining the loss of the harvester is proposed.
[0039] In the embodiment, the method further includes: before the step of comparing the multiple real-time entrainment loss rates and the multiple real-time cleaning loss rates in the preset period with the best operation working condition information to determine the loss trend of the harvester, determining the first average value of the entrainment loss rate and the second average value of the cleaning loss rate in the best operation working condition information; determining the third average value of the multiple real-time entrainment loss rates and the fourth average value of the multiple real-time cleaning loss rates in the preset period; determining the entrainment loss trend based on the first difference value between the first average value and the third average value, and determining the cleaning loss trend based on the second difference value between the second average value and the fourth average value.
[0040] It is understandable that the optimal operating condition information contains multiple entrainment loss rates and multiple cleaning loss rates. To facilitate comparison between the optimal operating condition and the real-time operating condition, the average values can be used to represent each loss rate. Specifically, the average entrainment loss rate in the optimal operating condition information can be used as the first average value, and the average cleaning loss rate in the optimal operating condition information can be used as the second average value. Furthermore, the average value of multiple real-time entrainment loss rates within a preset period can be used as the third average value, and the average value of multiple real-time cleaning loss rates within a preset period can be used as the fourth average value. Then, the entrainment loss trend can be determined based on the first difference between the first and third average values, and the cleaning loss trend can be determined based on the second difference between the second and fourth average values.
[0041] It should be noted that, in addition to using the average to represent multiple data points, the mode, median, or other data points can also be used to represent multiple data points, and this application does not impose any restrictions on this.
[0042] Furthermore, in one feasible implementation, determining the entrainment loss trend based on the first difference between the first average and the third average, and determining the cleaning loss trend based on the second difference between the second average and the fourth average, includes: calculating the first absolute value of the first difference between the first average and the third average; determining the first ratio between the first absolute value and the third average, and using the product of the first ratio and a preset coefficient as the entrainment loss trend; calculating the second absolute value of the second difference between the second average and the fourth average; determining the second ratio between the second absolute value and the fourth average, and using the product of the second ratio and a preset coefficient as the cleaning loss trend; wherein the preset coefficient is preset based on the model of the harvester.
[0043] In the embodiments of this application, the above method can be used to display the entrainment loss trend and the cleaning loss trend in numerical form, thereby improving the visualization of harvester losses.
[0044] Furthermore, in one feasible implementation, monitoring the real-time entrainment loss rate and real-time cleaning loss rate of the harvester includes: detecting whether the entrainment loss sensor and the cleaning loss sensor in the harvester are in normal working condition, and detecting whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal; if the entrainment loss sensor is detected to be in normal working condition and the real-time entrainment loss rate is abnormal, a first average value is used to replace the real-time entrainment loss rate; if the cleaning loss sensor is detected to be in normal working condition and the real-time cleaning loss rate is abnormal, a second average value is used to replace the real-time cleaning loss rate.
[0045] It can be understood that, under the premise that the entrainment loss sensor and the cleaning loss sensor are in a normal working state, if it is detected that the real-time entrainment loss rate collected by the entrainment loss sensor is abnormal, or it is detected that the real-time cleaning loss rate collected by the cleaning loss sensor is abnormal, it may be that the harvester is shaken due to the uneven ground during the harvesting process, and then the cleaning loss sensor or the entrainment loss sensor fails to measure. To avoid the influence of abnormal data collected by the loss sensor on the accuracy of loss trend calculation, the first average value can be used to replace the abnormal entrainment loss rate, and the second average value can be used to replace the abnormal cleaning loss rate, so as to ensure the accuracy of loss trend calculation.
[0046] In addition, in a possible implementation, detecting whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal includes: determining that the real-time entrainment loss rate is abnormal when it is detected that the real-time entrainment loss rate collected by the entrainment loss sensor is greater than a first preset multiple of the first average value; and determining that the real-time cleaning loss rate is abnormal when it is detected that the real-time cleaning loss rate collected by the cleaning loss sensor is greater than a second preset multiple of the second average value.
[0047] The first preset multiple of the first average value and the second preset multiple of the second average value are preset based on the vehicle type of the harvester.
[0048] Further, in a possible implementation, the step of adjusting the operation parameters of the harvester according to the loss trend includes: automatically adjusting the drum rotation speed, the concave clearance and the vehicle speed based on the entrainment loss trend, and automatically adjusting the upper and lower sieve opening degrees and the fan rotation speed based on the cleaning loss trend.
[0049] In this embodiment, the loss trend is divided into the entrainment loss trend and the cleaning loss trend, which can facilitate adjustment of the operation parameters of the harvester according to the loss in different areas.
[0050] Specifically, in a case where it is determined that the entrainment loss trend is high, the drum rotation speed can be increased to reduce the probability of the grains being discharged while being wrapped by the straws, the concave clearance can be reduced to enhance rubbing and extrusion of the straws, and the vehicle speed can be reduced to allow the drum to have more time to separate the grains. In a case where it is determined that the cleaning loss trend is high, the lower sieve opening degree can be reduced to prevent the grains from leaking out, the upper sieve opening degree can be appropriately increased to avoid blockage of the sieve surface by large impurities, and the fan rotation speed can be increased to blow out the impurities.
[0051] Further, based on the various embodiments of the method for determining the loss of the harvester, an embodiment of the method for determining the loss of the harvester is provided.
[0052] In the embodiment, the data of each vehicle model in field operation can be collected by the vehicle-mounted 4G terminal, including vehicle speed, roller speed, fan speed, concave gap, upper and lower sieve opening, operation time, entrainment and cleaning loss sensor values and other information. The collected data is uploaded to the cloud platform. Then, according to the operation time, vehicle speed information, entrainment and cleaning loss sensor values, the best operation condition information is screened out through the corresponding threshold. The screening threshold includes operation time≥aH and vehicle speed≥bkm / h, wherein the two parameters a and b have certain differences for different models. In the embodiment, the interval with long operation time and stable vehicle speed is the ideal working condition. Then, based on the screened values, the best operation condition information is established, and the entrainment and cleaning loss sensor values of this part are taken as the reference value K. Then, in the normal operation process of the vehicle, the loss sensor collects the current monitored values in real time, and the data xi of the sensor in the collection period is collected every t seconds (i is the data subscript, corresponding to the ith number), and the collected values are compared with the reference value. If xi>λK, the ith value is assigned as K, which can avoid the signal fluctuation caused by the interference of vehicle body shaking during vehicle operation. Then, the average value A of the statistical value in t seconds can be calculated by sliding average filtering. Then, the current loss trend can be calculated according to the formula S=λ|A-K| / (γA), and the value range is (0~100). The larger the value, the greater the current loss. Wherein, the values of λ and γ are different for different vehicle models, which are determined according to the best operation condition information of each vehicle model in the database.
[0053] It can be understood that as the number of vehicles in use increases, the K value in the database is also gradually updated, and the more the number of vehicles, the more realistic the ability of K value to reflect the best operation condition. Please refer to Figure 2 , Figure 2 for the sensor connection diagram of the present application. In Figure 2 , there are entrainment left sensor, entrainment right sensor and cleaning loss sensor, and the entrainment left sensor, entrainment right sensor and cleaning loss sensor are connected with the display screen. Thus, the pilot can check the current loss trend S through the vehicle-mounted display screen, and then the operation parameters can be adjusted in time. In addition, for the models that can be adjusted by electric control, such as concave gap, fan speed, roller speed and sieve opening, the operation parameters can be automatically adjusted based on the pre-stored best operation condition values according to the current loss trend value.
[0054] In the embodiment, the application collects a large amount of operation data through a 4G terminal, and can establish an optimal operation condition information database in the cloud. In the actual operation process of the vehicle, the operation parameters can be adjusted in time according to the loss trend. Moreover, the application does not need additional yield sensors, specific crop thousand-grain weight information, and the like, and can determine the loss condition of the current operation through the judgment of the loss trend. In addition, the user does not need other operations, and can know the loss condition of the harvesting operation in the cab, thereby improving the operation experience of the user.
[0055] In one embodiment, the application further provides a device for determining loss of a harvester, the device comprising a processor and a memory, wherein the memory is configured to store instructions, and the processor is configured to call the instructions from the memory and implement the method for determining loss of a harvester when executing the instructions.
[0056] Specifically, the processor comprises a core, and the core calls corresponding program units from the memory. The core can be one or more, and the method for determining loss of a harvester is implemented by adjusting core parameters.
[0057] The memory can include non-permanent memory in a computer readable medium, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM), and the memory comprises at least one memory chip.
[0058] Please refer to Figure 3 In one embodiment, the application further provides a system for determining loss of a harvester, wherein the system comprises the device for determining loss of a harvester as above.
[0059] In one embodiment, the above computer device can be a server, and an internal structure diagram thereof can be as shown in Figure 4 The computer device comprises a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected through a system bus. The processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operating system B01 and the computer program B02 in the non-volatile storage medium A04 to run. The database of the computer device is used to store target distances and target images. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. The computer program B02 has implemented a method for determining loss of a harvester when executed by the processor A01.
[0060] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0061] This application provides a storage medium storing a program that, when executed by a processor, implements the above-described method for determining harvester loss.
[0062] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0063] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0065] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1steps of a function specified in one or more blocks.
[0066] It should also be noted that the terms "comprising," "including," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.
[0067] The above embodiments of the present application have been described only for clarity's sake and should not be considered limiting. Various changes and modifications can be made to the application by those skilled in the art. Any such changes or modifications are intended to fall within the scope of the application as defined by the appended claims, which are to be interpreted in the broadest sense and under the doctrine of equivalents.
Claims
1. A method for determining harvester loss, characterized in that, The method includes: The screening thresholds for various operating parameters of the harvester are determined based on the current harvester model. The operating parameters include at least the operating time, vehicle speed, entrainment loss rate, and cleaning loss rate. Based on the filtering threshold, target data corresponding to each operating condition parameter is selected from multiple pre-stored vehicle operation data of the same type. Monitor the real-time carry-over loss rate and real-time cleaning loss rate of the harvester during operation; The loss trend of the harvester is determined by comparing multiple real-time entrainment loss rates and multiple real-time cleaning loss rates within a preset period with the optimal operating condition information. The optimal operating condition information is determined based on the target data corresponding to each operating condition parameter. Adjust the operating parameters of the harvester according to the loss trend.
2. The method for determining harvester loss according to claim 1, characterized in that, The step of selecting target data corresponding to each operating condition parameter from multiple pre-stored vehicle operation data of the same type based on the filtering threshold includes: Iterate through the historical operating data of multiple vehicles of the same type; Select the data in the vehicle's historical operation data whose operation time is greater than or equal to the operation time threshold as the target data corresponding to the operation time; Select the data in the vehicle's historical operating data whose speed is greater than or equal to the vehicle speed threshold as the target data corresponding to the vehicle speed; The data in the vehicle's historical operation data with a carry-in loss rate less than or equal to the carry-in loss rate threshold are selected as the target data corresponding to the carry-in loss rate; The data in the vehicle's historical operating data with a cleaning loss rate less than or equal to the cleaning loss rate threshold are selected as the target data corresponding to the cleaning loss rate.
3. The method for determining harvester loss according to claim 1, characterized in that, The method further includes: before the step of comparing multiple real-time entrainment loss rates and multiple real-time cleaning loss rates within a preset period with optimal operating condition information to determine the loss trend of the harvester, determining a first average value of the entrainment loss rate and a second average value of the cleaning loss rate in the optimal operating condition information; Determine the third average of multiple real-time entrainment loss rates and the fourth average of multiple real-time cleaning loss rates within a preset period; The entrainment loss trend is determined based on the first difference between the first average value and the third average value, and the cleaning loss trend is determined based on the second difference between the second average value and the fourth average value.
4. The method for determining harvester loss according to claim 3, characterized in that, Monitoring the real-time entrainment loss rate and real-time cleaning loss rate of the harvester during operation includes: The system detects whether the entrainment loss sensor and the cleaning loss sensor in the harvester are in normal working condition, and detects whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal. If the entrainment loss sensor is detected to be in normal working condition and the real-time entrainment loss rate is abnormal, the first average value is used to replace the real-time entrainment loss rate. If the cleaning loss sensor is detected to be in normal working condition and the real-time cleaning loss rate is abnormal, the second average value is used to replace the real-time cleaning loss rate.
5. The method for determining harvester loss according to claim 4, characterized in that, The step of detecting whether the real-time entrainment loss rate collected by the entrainment loss sensor and the real-time cleaning loss rate collected by the cleaning loss sensor are abnormal includes: When the real-time entrainment loss rate collected by the entrainment loss sensor is detected to be greater than a first preset multiple threshold of the first average value, the real-time entrainment loss rate is determined to be abnormal. When the real-time cleaning loss rate collected by the cleaning loss sensor is detected to be greater than the second preset multiple threshold of the second average value, the real-time cleaning loss rate is determined to be abnormal.
6. The method for determining harvester loss according to claim 3, characterized in that, The step of determining the entrainment loss trend based on the first difference between the first average and the third average, and determining the cleaning loss trend based on the second difference between the second average and the fourth average, includes: Calculate the first absolute value of the first difference between the first average value and the third average value; Determine a first ratio between the first absolute value and the third average value, and use the product of the first ratio and a preset coefficient as the entrainment loss trend; Calculate the second absolute value of the second difference between the second average and the fourth average; Determine a second ratio between the second absolute value and the fourth average value, and use the product of the second ratio and the preset coefficient as the cleaning loss trend; The preset coefficient is preset based on the model of the harvester.
7. The method for determining harvester loss according to claim 3, characterized in that, The step of adjusting the operating parameters of the harvester according to the loss trend includes: The roller speed, gravure screen gap, and machine speed are automatically adjusted based on the entrainment loss trend, and the upper and lower screen openings and fan speed are automatically adjusted based on the cleaning loss trend.
8. A device for determining harvester losses, characterized in that, include: The memory is configured to store instructions; A processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for determining harvester loss according to any one of claims 1 to 7.
9. A system for determining harvester losses, characterized in that, Includes the apparatus for determining harvester loss as described in claim 8.
10. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, the instruction causes the processor to be configured to perform the method for determining harvester loss according to any one of claims 1 to 7.