Real-time weighing method, system and equipment of harvester, medium and harvester

Abstract

The invention relates to a real-time weighing method, system and device of a harvester, a medium and the harvester, the harvester is provided with a weighing sensor and an attitude sensor, and the method comprises the following steps: when the harvester is in a working state, obtaining an original weight value collected by the weighing sensor and a current attitude parameter collected by the attitude sensor; and dynamically compensating the original weight value according to the current attitude parameter to obtain a target weight value. By means of the method, if the harvester is in the working state, dynamic compensation is conducted on the original weight value according to the original weight value of the weighing sensor and the current attitude parameters collected by the attitude sensor, and errors caused by vehicle shaking and slope crossing can be eliminated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of agricultural machinery processing, in particular, the present application relates to a real-time weighing method, system, device, medium and harvester of a harvester. BACKGROUND

[0002] In the process of continuous development of modern agriculture, agricultural production is moving towards intelligent, automated and precise direction. In recent years, agricultural machinery is widely used in plowing, planting, management and harvesting, and its role is becoming more and more significant. However, how to obtain grain yield data in real time during the operation of the harvester, so as to provide reliable data support for variable seeding, fertilization, pesticide spraying and field management, has become an important research topic in the field of precision agriculture.

[0003] At present, the real-time yield measurement of the harvester mainly has three ways: impulse type (based on impact force measurement), volumetric type (based on volume calculation) and weighing type (based on direct measurement of weighing sensor). The principle of impulse type yield measurement is based on the impact force generated by crops passing through the conveying device on the sensor. However, in the domestic harvester operation scene, when facing low feeding amount working conditions (such as small plots, sparse crops), the impact force signal is easy to be disturbed, resulting in large measurement error. The volumetric type yield measurement is to measure the height of the grain in the grain bin by using the capacitive sensor, and then calculate the yield combined with the preset density. However, if the grain is not uniformly stacked in the grain bin, or the types of grain are different, the volume calculation will deviate, thereby affecting the yield measurement accuracy.

[0004] In contrast, the weighing type yield measurement is to arrange weighing sensors around the grain bin to directly obtain the weight of the grain in the grain bin. This method not only has high real-time and stability, but also is not affected by the type of harvester, the shape and type of grain, and is the current ideal yield measurement scheme. However, the tracked harvester faces complex working conditions in the actual working process, such as vehicle shaking left and right, slope in farmland, mechanical vibration, etc. The traditional weighing type yield measurement only relies on the weighing sensor, which cannot effectively solve the influence of these factors, and there is a large measurement error. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a real-time weighing method, system, device, medium and harvester of a harvester, which aims to solve at least one of the above technical problems.

[0006] In the first aspect, the technical solution of the present application to solve the above technical problem is as follows: a real-time weighing method of a harvester, wherein the harvester is provided with a weighing sensor and an attitude sensor, and the method comprises: When the harvester is in a working state, the original weight value collected by the weighing sensor and the current attitude parameter collected by the attitude sensor are obtained; The original weight value is dynamically compensated according to the current posture parameters to obtain the target weight value.

[0007] The beneficial effect of the present invention is that when the harvester is in working state, the original weight value is dynamically compensated according to the original weight value of the weighing sensor combined with the current posture parameters collected by the posture sensor, which can eliminate the errors caused by vehicle shaking and overhill.

[0008] On the basis of the above technical solution, the present invention can also be improved as follows.

[0009] Furthermore, the above-mentioned current posture parameters include the current roll angle and the current pitch angle. The original weight value is dynamically compensated according to the current posture parameters to obtain the target weight value, including: Determining a first weight error corresponding to the current pitch angle based on the current pitch angle and a first corresponding relationship, where the first corresponding relationship describes a corresponding relationship between different pitch angles and different first weight errors; Determining a second weight error corresponding to the current roll angle based on the current roll angle and a second corresponding relationship, where the second corresponding relationship describes a corresponding relationship between different roll angles and different second weight errors; Based on a first weight error corresponding to the current pitch angle and a second weight error corresponding to the current roll angle, the original weight value is dynamically compensated to obtain a target weight value.

[0010] Furthermore, the harvester is also provided with a header height sensor, a grain elevator speed sensor, and a waste return device speed sensor, and the method further comprises: The harvester is also provided with a header height sensor, a grain elevator speed sensor and a debris return device speed sensor.

[0011] Furthermore, if the target weight value includes weight values ​​at multiple time points, the method further includes: A median outlier detection algorithm is used to perform denoising processing on the target weight value or the final target weight value to obtain a processed target weight value or a processed final target weight value.

[0012] Furthermore, the method further comprises: A sliding window filtering algorithm is used to smooth the processed target weight value or the processed final target weight value to obtain a true weight value.

[0013] Furthermore, the harvester is also provided with a speed sensor, and the method further comprises: Get the current vehicle speed collected by the vehicle speed sensor; Based on the current vehicle speed and current operating parameters, determine whether the harvester is in working condition.

[0014] In a second aspect, the present application provides a real-time weighing system of a harvester to solve the above technical problems, comprising a data acquisition device and a data processing device, the data acquisition device comprising a weighing sensor and a posture sensor; the weighing sensor configured to acquire an original weight value when the harvester is in a working state; the posture sensor configured to acquire a current posture parameter when the harvester is in the working state; the data processing device configured to dynamically compensate the original weight value according to the current posture parameter to obtain a target weight value.

[0015] In a third aspect, the present application provides an electronic device to solve the above technical problems, the electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the real-time weighing method of the harvester.

[0016] In a fourth aspect, the present application provides a computer readable storage medium to solve the above technical problems, the computer readable storage medium storing a computer program, the computer program being executable on a processor to implement the real-time weighing method of the harvester.

[0017] In a fifth aspect, the present application provides a harvester to solve the above technical problems, the harvester comprising a real-time weighing device of a harvester as described in the second aspect.

[0018] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced.

[0020] Figure 1 a flowchart of a real-time weighing method of a harvester provided by an embodiment of the present application; Figure 2 a flowchart of another real-time weighing method of a harvester provided by an embodiment of the present application; Figure 3 a schematic diagram of the overall structure of a real-time weighing system of a harvester provided by an embodiment of the present application; Figure 4 a detailed structural schematic diagram of a real-time weighing system of a harvester provided by an embodiment of the present application; Figure 5 a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0021] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0022] The following describes in detail the technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems using specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following embodiments of the present invention are described in conjunction with the accompanying drawings.

[0023] The solution provided by the embodiment of the present invention can be applied to any application scenario where real-time weighing of harvesters is required. The embodiment of the present invention provides a possible implementation method, such as Figure 1 As shown in FIG, a flowchart of a real-time weighing method for a harvester is provided. The scheme can be executed by a data processing device on the harvester. For the convenience of description, the method provided by the embodiment of the present invention will be described below using the data processing device on the harvester as an example of the execution body. Figure 1 As shown in the flowchart, the harvester is provided with a weighing sensor and a posture sensor, and the method may include the following steps: S10, when the harvester is in a working state, obtaining an original weight value collected by a weighing sensor and a current posture parameter collected by a posture sensor; S20, dynamically compensating the original weight value according to the current posture parameter to obtain a target weight value.

[0024] Through the method of the present invention, when the harvester is in working state, the original weight value is dynamically compensated according to the original weight value of the weighing sensor in combination with the current posture parameters collected by the posture sensor, which can eliminate errors caused by vehicle shaking and overhill.

[0025] The scheme of the present invention is further described below in conjunction with the following specific embodiments. The present invention aims to address the influence of dynamic interference factors such as left and right swaying of the vehicle, changes in the posture of the farmland slope, and mechanical vibration on the weighing results of the crawler grain harvester during harvesting operations. A real-time weighing method, system, equipment, medium and harvester for granaries are proposed to solve the problem of high error rate in real-time weighing of crawler grain harvesters under different working conditions.

[0026] Specifically, in this embodiment, the harvester (the harvester in this solution may be a crawler grain harvester) is provided with a weighing sensor and a posture sensor. A real-time weighing method for the harvester may include the following steps: S10, when the harvester is in a working state, obtaining an original weight value collected by a weighing sensor and a current posture parameter collected by a posture sensor; Before S10, the harvester is further provided with a header height sensor, a grain elevator speed sensor, a waste return device speed sensor, and a vehicle speed sensor. The method further includes: S01, obtaining current operating parameters collected by the header height sensor, the grain elevator speed sensor, and the miscellaneous return device speed sensor, as well as the current vehicle speed collected by the vehicle speed sensor; S02: Based on the current vehicle speed and current operating parameters, determine whether the harvester is in working condition.

[0027] One possible implementation of S02 is to determine that the harvester is in operation when the current vehicle speed is greater than a vehicle speed threshold, the current operating parameter of the header height sensor is less than a header height threshold, the current operating parameter of the grain elevator speed sensor is greater than a grain elevator speed threshold, and the current operating parameter of the waste return device speed sensor is greater than a waste speed threshold. Only when all these conditions are met is the crawler-type grain harvester considered to be in the harvesting operation, and vibration elimination of the entire vehicle is required.

[0028] Among them, the original weight value and the current posture parameter can be collected in a periodic manner, that is, the original weight value and the current posture parameter are sampled once every set target sampling time interval, and the collection time corresponding to the original weight value and the current posture parameter involved in the processing process is consistent.

[0029] After collecting the original weight value and current posture parameters, the linear interpolation algorithm can be used to synchronize the timestamps of the collected data. Specifically: The sampling time sequence of each sensor is , the corresponding data value is , based on the sampling time series and the corresponding data values, generate a unified time series , in, ,in, is the target sampling time interval, for each uniform time point , No. Data values ​​collected by sensors Calculated by linear interpolation: Among them, the requirements satisfy .

[0030] Optionally, in order to accurately calculate the vertical downward gravity of the granary, in this application, two weighing sensors are arranged at the connection between the belt harvester chassis axle and the bottom of the granary, and two weighing sensors are also set at the connection between the left side of the granary and the axle threshing chamber as auxiliary measurement sensors; the purpose of this arrangement is to separate the granary and the threshing chamber, eliminate the interference between the threshing chamber and the granary, and measure the vertical downward gravity of the granary at the same time. The forces measured by the above four weighing sensors are respectively 、 、 、 .

[0031] Optionally, the above-mentioned posture sensor can be installed in the center of the granary to collect the current posture parameters of the harvester in real time.

[0032] Optionally, the current posture parameters include a current roll angle and a current pitch angle. The roll angle reflects posture changes caused by the harvester's swaying during operation, and the pitch angle reflects posture changes caused by the harvester's traversing a slope during operation. Dynamic compensation of the original weight value can then be performed by executing the following step S20.

[0033] S20, dynamically compensating the original weight value according to the current posture parameter to obtain a target weight value.

[0034] Optionally, one possible implementation of S20 is as follows: S201, determining a first weight error corresponding to the current pitch angle based on the current pitch angle and a first corresponding relationship, where the first corresponding relationship describes a corresponding relationship between different pitch angles and different first weight errors; S202, determining a second weight error corresponding to the current roll angle based on the current roll angle and a second corresponding relationship, where the second corresponding relationship describes a corresponding relationship between different roll angles and different second weight errors; S203 : Dynamically compensate the original weight value based on a first weight error corresponding to the current pitch angle and a second weight error corresponding to the current roll angle to obtain a target weight value.

[0035] Optionally, the first weight error can be Indicates that the second weight error can be It indicates that under the influence of the roll angle and the pitch angle, one possible implementation of the above S203 is: in, is the total weight of grain in the granary, i.e. the target weight value, It is the vertical downward force on the grain in the granary.

[0036] Optionally, the first correspondence relationship and the second correspondence relationship may be determined based on the following method: For the first weight error caused by the roll angle, different weights of grain (for example, 1~1500kg) are placed in the granary, and the roll angle of the harvester is gradually increased by the left and right tilt control device of the vehicle. From the minimum to the maximum value, the first weight error caused by different roll angles is calculated, and the obtained value is Relationship curve (first correspondence) and coefficients corresponding to each first weight error For the second weight error caused by the pitch angle, similarly, different weights of grain (for example, 1~1500kg) are placed in the granary, and the pitch angle of the harvester is gradually increased through the pitch angle control device. From the minimum to the maximum value, calculate the second weight error caused by different pitch angles, and you can get Relationship curve and coefficients corresponding to each second weight error .

[0037] The above It can also be expressed as: Optionally, the above-mentioned harvester is also provided with a header height sensor, a grain elevator speed sensor and a debris return device speed sensor. In order to eliminate the influence of vibrations generated by the rotation of the header wheel, the grain elevator, the engine, etc. during the harvesting process of the crawler grain harvester on the target weight value, it is necessary to calibrate the mechanical vibration of the harvester and filter the mechanical vibration of the harvester. If it is too small, the mechanical vibration will be converted into grain weight in the target weight value, and if it is too large, part of the grain weight will be lost.

[0038] Specifically, the above method further includes: S30, obtaining current operating parameters collected by the header height sensor, the grain elevator speed sensor, and the miscellaneous return device speed sensor; S40, adjusting the target weight value based on the current operating parameters to obtain a final target weight value.

[0039] One implementation of the above S40 is: Based on the current operating parameters and the preset standard weight value, the target weight value is adjusted to obtain the final target weight value. Specifically, if the target weight value corresponding to the current operating parameters is less than the standard weight value, the standard weight value is determined as the final target weight value.

[0040] The above standard weight values ​​can be determined based on the following methods: Put the machine in a stationary state, ensure that the grain bin is empty, adjust the header height to the normal operating position, and adjust the header reel speed to the normal operating speed. The engine speed reaches the maximum, and the speed of the grain elevator and the waste return device is adjusted to the normal operating level. Perform a 1-minute vibration calibration, that is, collect the weight value obtained within 1 minute; then use the initial sampling sequence to collect the weight values ​​obtained multiple times. Indicates that the initial sampling sequence is sorted from small to large to obtain the intermediate sampling sequence .if If is an odd number, the median is ,like If is an even number, the median is The determined median is taken as the standard weight value.

[0041] In this solution, after eliminating errors caused by vehicle sway, slope crossing, and vibration, in order to improve the accuracy of the measurement results, it is usually necessary to preprocess the raw data (current posture parameters and / or current operating parameters) to eliminate noise and outliers in the data. Furthermore, in this application solution, if the target weight value includes weight values ​​at multiple time points, the method also includes: A median outlier detection algorithm is used to perform denoising processing on the target weight value or the final target weight value to obtain a processed target weight value or a processed final target weight value.

[0042] Among them, the median-based outlier detection algorithm is a commonly used outlier detection method. Its core idea is to identify and exclude outliers through multiple sampling and statistical analysis, thereby improving the stability of measurement results.

[0043] Optionally, one implementation method of the above-mentioned outlier detection algorithm using the median to perform denoising on the target weight value or the final target weight value is: taking the target weight value or the final target weight value as the original data; sorting the original data to obtain , find the median , for each measurement value in the original data, calculate the median of each measurement value The absolute value deviation , ,right Sort from small to large and get the median If the i-th measurement value is identified as an outlier (i.e., its absolute deviation divided by exceeds the threshold), the measured value Replace with Otherwise, keep the measured value The original value of can be expressed as: In the present application, after removing the outliers, a sliding window filtering algorithm may be used to smooth the processed target weight value or the processed final target weight value to obtain the true weight value.

[0044] Weight data after removing outliers , that is, the target weight value after processing or the final target weight after processing, the specific implementation method of using the sliding window filtering algorithm to obtain the actual weight of the grain in the grain bin of the crawler harvester is: define a size of For each window, calculate the mean of all elements in the window. .

[0045] As the corresponding window The value at the position, and so on to get the weight data sequence , take the average value of the weight data sequence to get the true value of the grain weight in the granary (true weight value), that is: Optionally, this solution uses pin sensors placed on the left side of the grain bin and threshing chamber to measure the horizontal force on the grain bin components and eliminate the shaking caused by harvester vibration. This solution uses vehicle speed sensors, header height sensors, waste return device speed sensors, and grain elevator speed sensors placed on the harvester to monitor operating status. It uses posture sensors and vibration calibration to eliminate vehicle vibration, side-to-side vehicle sway, and the effects of hill climbing. It also uses outlier detection algorithms and sliding window filtering algorithms to improve the grain weighing accuracy of crawler grain harvesters during operation.

[0046] Optionally, this solution can also use a volumetric yield measurement method to calculate the weight of the grain in the silo, while using a header height sensor to determine operating conditions. This solution uses a weighing sensor to obtain the real-time weight of the grain in the silo, which is a weighing-based yield measurement method. Considering that in actual operation, relying solely on header height cannot determine the operating status of a crawler-type grain harvester, the solution of the present invention also incorporates a vehicle speed sensor, a residual return device speed sensor, and a grain elevator speed sensor. When the data from these sensors reaches a set threshold, it indicates that the crawler-type grain harvester is in working condition. A calibration algorithm is then used to eliminate the impact of vehicle vibration on weight.

[0047] In order to better illustrate and understand the principle of the method provided by the present invention, the solution of the present invention is described below in conjunction with an optional specific embodiment. It should be noted that the specific implementation of each step in this specific embodiment should not be understood as limiting the solution of the present invention. On the basis of the principle of the solution provided by the present invention, other implementations that can be thought of by those skilled in the art should also be considered as within the scope of protection of the present invention.

[0048] See also Figure 2 The real-time weighing method of a harvester provided in this embodiment may include the following steps: (1) The data acquisition device periodically collects data from each sensor and transmits it to the data processing device via the CAN bus. The data processing device synchronizes the data using timestamp synchronization technology.

[0049] (2) The data processing device sets the thresholds of each sensor to determine whether the harvester is in working condition.

[0050] (3) If in working state, the weight error caused by shaking / slope is compensated by combining the weighing sensor and attitude sensor data.

[0051] (4) Use the median calibration method to remove the influence of mechanical vibration.

[0052] (5) Output real-time accurate weight data (true weight value) through outlier detection and sliding window averaging algorithm.

[0053] Through the solution of the present invention, the present invention has the following beneficial effects compared with the prior art: Multi-sensor data is aligned through timestamp synchronization technology, achieving spatiotemporal consistency in multi-source data processing. The vehicle's pitch and roll angles are acquired through attitude sensors, and the measured values ​​(raw weight) of the weighing sensors are dynamically corrected to eliminate errors caused by vehicle sway and slope. A median filter algorithm is used to eliminate high-frequency noise caused by vibrations from components such as the header and engine. An outlier detection algorithm is used to eliminate outliers, and a multi-stage filtering strategy combining a sliding window averaging algorithm solves the weighing accuracy challenges faced by tracked machinery in complex terrain and vibrating environments, making it suitable for similar dynamic weighing scenarios.

[0054] Based on Figure 1 The present invention also provides a real-time weighing system for harvesters based on the same principle as the method shown in Figure 3 and Figure 4 The real-time grain weighing system shown in , the system includes a data acquisition device and a data processing device, the data acquisition device includes a weighing sensor and a posture sensor; A weighing sensor is used to obtain the original weight value when the harvester is in working state; The posture sensor is used to obtain the current posture parameters when the harvester is in working state; The data processing device is used to dynamically compensate the original weight value according to the current posture parameter to obtain the target weight value.

[0055] Optionally, the above system also includes a header height sensor, a grain elevator speed sensor and a debris return device speed sensor arranged on the harvester, and a data processing device, which is also used to obtain current operating parameters collected by the header height sensor, the grain elevator speed sensor and the debris return device speed sensor respectively, and adjust the target weight value based on the current operating parameters to obtain the final target weight value.

[0056] Optionally, the above system also includes a vehicle speed sensor and a data processing device arranged on the harvester, and is also used to obtain the current vehicle speed collected by the vehicle speed sensor; based on the current vehicle speed and current operating parameters, it is determined whether the harvester is in a working state.

[0057] In the present application, the data acquisition device transmits the data collected by the above-mentioned sensors to the data processing device. The data processing device accurately determines the working status of the crawler grain harvester by analyzing the sensor data, and compensates for the weight of the grain in combination with the vehicle body inclination information provided by the attitude sensor. At the same time, the system uses a median filtering algorithm to eliminate the impact of vehicle vibration caused by the rotation of the harvesting table reel wheel, the rotation of the grain elevator, the rotation of the engine, etc. during operation. The algorithm is then used to process the raw data to improve the weighing accuracy of the grain weight. This solution effectively solves the problem of low weight measurement accuracy under complex terrain or machine vibration conditions through multi-sensor fusion and algorithm processing.

[0058] Specifically, the processing flow of the system is: (1) The data acquisition device collects the data collected by each sensor and sends the data collected by each sensor to the data processing device through the CAN (Controller Area Network) bus. The data processing device generates a timestamp for each sensor data and accurately synchronizes the CAN bus data sent by the data acquisition device based on the timestamp synchronization mechanism.

[0059] (2) The data processing device determines the working status of the crawler grain harvester based on the collected CAN data (data collected by each sensor received through CAN).

[0060] (3) If the crawler grain harvester is in working condition, the original measurement value (original weight value) of the weighing sensor is dynamically compensated in combination with the pitch angle and roll angle collected by the attitude sensor to eliminate the errors caused by vehicle shaking and overhill conditions, and obtain the target weight value.

[0061] (4) Use the median filter algorithm to reduce the noise of the vibration signal and eliminate the vibration interference caused by the rotation of the cutting table reel, engine and other components. That is, use the median outlier detection algorithm to denoise the target weight value or the final target weight value to obtain the processed target weight value or the processed final target weight value.

[0062] (5) An outlier detection algorithm is used to remove outliers, and then the filtered data is smoothed using a sliding window averaging algorithm to achieve real-time and accurate calculation of the grain weight in the granary.

[0063] Based on Figure 1 Based on the same principle as the method shown in , an embodiment of the present invention further provides a real-time weighing device for a harvester, wherein a weighing sensor and a posture sensor are provided on the harvester. The real-time weighing device for the harvester may include an acquisition module and a processing module, wherein: The acquisition module is used to obtain the original weight value collected by the weighing sensor and the current posture parameters collected by the posture sensor when the harvester is in working state; The processing module is used to dynamically compensate the original weight value according to the current posture parameters to obtain the target weight value.

[0064] The real-time weighing device and system of the harvester in the embodiments of the present invention can both execute the real-time weighing method of the harvester provided by the embodiments of the present invention, and the implementation principles are similar. The actions performed by each module and unit in the real-time weighing device of the harvester in each embodiment of the present invention correspond to the steps in the real-time weighing method of the harvester in each embodiment of the present invention. For the detailed functional description of each module of the real-time weighing device of the harvester, please refer to the description of the corresponding real-time weighing method of the harvester shown in the previous text, which will not be repeated here.

[0065] Among them, the real-time weighing device of the above-mentioned harvester can be a computer program (including program code) running in a computer device, for example, the real-time weighing device of the harvester is an application software; the device can be used to execute the corresponding steps in the method provided in the embodiment of the present invention.

[0066] In some embodiments, the real-time weighing device of the harvester provided by the embodiment of the present invention can be implemented by a combination of software and hardware. As an example, the real-time weighing device of the harvester provided by the embodiment of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the real-time weighing method of the harvester provided by the embodiment of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs) or other electronic components.

[0067] The modules involved in the embodiments of the present invention may be implemented in software or hardware, wherein the name of a module does not necessarily limit the module itself.

[0068] Based on the same principle as the method shown in the embodiments of the present invention, an electronic device is also provided in the embodiments of the present invention, which may include but is not limited to: a processor and a memory; the memory is used to store computer programs; the processor is used to execute the method shown in any embodiment of the present invention by calling the computer program.

[0069] In an alternative embodiment, an electronic device is provided, such as Figure 5 As shown, Figure 5 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data exchange between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the number of transceivers 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0070] Processor 4001 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the present disclosure. Processor 4001 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, or a combination of a DSP and a microprocessor.

[0071] Bus 4002 may include a path for transmitting information between the above components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0072] The memory 4003 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0073] The memory 4003 is used to store application code (computer program) for executing the solution of the present invention, and is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0074] Among them, the electronic device can also be a terminal device, Figure 5 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0075] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0076] According to another aspect of the present invention, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various implementations described above.

[0077] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0078] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0079] The computer-readable storage medium provided by the embodiments of the present invention may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device.

[0080] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0081] The above description is merely an illustration of preferred embodiments of the present invention and the underlying technical principles. Those skilled in the art should understand that the scope of the present invention is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned concepts. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A real-time weighing method for a harvester, characterized in that: The harvester is provided with a weighing sensor and a posture sensor, and the method comprises: When the harvester is in a working state, obtaining an original weight value collected by the weighing sensor and a current posture parameter collected by the posture sensor; The original weight value is dynamically compensated according to the current posture parameter to obtain a target weight value.

2. The method according to claim 1, characterized in that The current posture parameters include a current roll angle and a current pitch angle, and the dynamically compensating the original weight value according to the current posture parameters to obtain a target weight value includes: determining a first weight error corresponding to the current pitch angle based on the current pitch angle and a first corresponding relationship, where the first corresponding relationship describes a corresponding relationship between different pitch angles and different first weight errors; determining a second weight error corresponding to the current roll angle based on the current roll angle and a second corresponding relationship, wherein the second corresponding relationship describes a corresponding relationship between different roll angles and different second weight errors; Based on a first weight error corresponding to the current pitch angle and a second weight error corresponding to the current roll angle, the original weight value is dynamically compensated to obtain a target weight value.

3. The method according to claim 1, characterized in that The harvester is also provided with a header height sensor, a grain elevator speed sensor, and a waste return device speed sensor, and the method further comprises: Acquiring current operating parameters collected by the header height sensor, the grain elevator speed sensor, and the miscellaneous return device speed sensor respectively; The target weight value is adjusted based on the current operating parameters to obtain a final target weight value.

4. The method according to claim 1 or 3, characterized in that If the target weight value includes weight values ​​at multiple time points, the method further includes: The target weight value or the final target weight value is subjected to denoising processing by adopting a median outlier detection algorithm to obtain a processed target weight value or a processed final target weight value.

5. The method according to claim 4, characterized in that The method further comprises: A sliding window filtering algorithm is used to smooth the processed target weight value or the processed final target weight value to obtain a true weight value.

6. The method according to claim 3, characterized in that The harvester is also provided with a vehicle speed sensor, and the method further comprises: Obtaining the current vehicle speed collected by the vehicle speed sensor; Based on the current vehicle speed and the current operating parameters, it is determined whether the harvester is in a working state.

7. A real-time weighing system for a harvester, characterized in that: It includes a data acquisition device and a data processing device, wherein the data acquisition device includes a weighing sensor and a posture sensor; The weighing sensor is used to obtain an original weight value when the harvester is in a working state; The posture sensor is used to obtain current posture parameters when the harvester is in a working state; The data processing device is used to dynamically compensate the original weight value according to the current posture parameter to obtain a target weight value.

8. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A harvester, characterized in that: A real-time weighing system for a harvester comprising the method according to claim 7.

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