Airborne real-time yield measuring instrument and method for rice combine harvester based on multi-source sensing

Abstract

The invention provides a rice combine harvester onboard real-time yield measuring instrument and method based on multi-source sensing, and relates to the field of harvesters. The rice combine harvester onboard real-time yield measuring instrument comprises a data acquisition module used for acquiring data of a granary of a rice combine harvester; the positioning module is arranged outside a granary of the rice combine harvester and used for collecting position data of the harvester, and the position data comprises real-time longitude and latitude, current time and vehicle running speed; the communication module is used for transmitting the data processed and analyzed by the microcontroller to a cloud server; the display module is used for displaying a result acquired and processed by the microcontroller in real time; the storage module is used for locally storing data acquired by the data acquisition module, position data of the positioning module and data processed by the microcontroller; the microcontroller is used for processing data acquired by the positioning module and the data acquisition module and transmitting the data to the communication module, the storage module and the display module. The method is high in calculation precision, convenient to install and maintain and low in price.

Description

Technical Field

[0001] The present invention relates to the field of harvesters, and in particular to an on-board real-time yield monitor and method for a rice combine harvester based on multi-source sensing. Background Art

[0002] Digital agriculture is the future development direction of agriculture. In the development of digital agriculture, the accuracy of small-scale plot portraits determines the accuracy of prescription map generation, and yield is the key data of plot portraits. Therefore, how to obtain accurate plot yield data is of great significance. In current yield measurement methods, the scale of satellite remote sensing methods is too large, which is not conducive to the generation of plot-level prescription maps in precision agriculture, and there are problems such as low resolution and low accuracy; UAV remote sensing is affected by weather such as wind and rain, and the window period is short, and there are problems such as missed measurement, under-measurement, and position drift. To improve the accuracy of rice plot-level yield measurement and achieve real-time yield measurement (calculated based on the longitude, latitude, and harvesting weight during the harvesting process of the harvester), on-board yield monitors for harvesters have become an inevitable choice for small-scale yield measurement. However, existing on-board rice yield measurement methods mostly calculate based on the weight of the grain bin and the inlet flow rate. Due to influencing factors such as large dust and mechanical vibration during the harvesting process, these methods still require major modifications to the harvester, not only are the installations complex, but also the yield measurement accuracy is not high and the reliability is low.

[0003] Considering the correlation between the real-time change of the weight in the grain bin during the rice harvesting process and the height of the grain in the bin and the pressure felt at the bottom of the bin, the present invention proposes an on-board yield monitor for a rice combine harvester based on multi-source sensing, that is, according to the actual shape of the on-board grain bin, using local pressure-sensitive and distance measurement elements to convert the real-time change of the weight of the grain in the bin into changes in local pressure and height in the bin, and providing them to the yield meter for data acquisition, processing, storage, and transmission, and assisting with a moisture content detection sensor to correct the calculated data. At the same time, combining the harvesting and unloading states collected by a near-infrared diffuse reflection sensor and an ultrasonic sensor, and integrating real-time positioning system data, so as to achieve real-time measurement of high-precision plot-level yield. In addition, because suitable pressure and height sensor devices can be easily installed inside the grain bin without major modifications to the rice harvester, the present invention only needs simple installation and wiring, has a simpler structure, and is convenient for disassembly. Summary of the Invention

[0004] The purpose of the present invention is to provide an on-board real-time yield monitor and method for a rice combine harvester based on multi-source sensing, which has high calculation accuracy, is convenient for installation and maintenance, and is inexpensive.

[0005] To achieve the above purpose, the present invention provides an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing, including

[0006] The data acquisition module is used to collect data of the grain bin of the rice combine harvester;

[0007] The positioning module is set outside the grain bin of the rice combine harvester and is used to collect the position data of the harvester. The position data includes real-time longitude and latitude, current time, and vehicle driving speed;

[0008] The communication module is used to transmit the data processed and analyzed by the microcontroller to the cloud server;

[0009] The display module displays the results of real-time acquisition and processing by the microcontroller;

[0010] The storage module is for local storage and is used to store the data collected by the data acquisition module, the position data of the positioning module, and the data processed by the microcontroller;

[0011] The microcontroller is used to process the data collected by the positioning module and the data acquisition module, and transmit it to the communication module, the storage module, and the display module.

[0012] Preferably, the data acquisition module includes

[0013] Pressure sensors are evenly distributed at the bottom of the grain bin and are used to detect the pressure borne by the plane where they are located;

[0014] Millimeter wave radar sensors are set at the top inside the grain bin and are used to detect the change in the height inside the grain bin;

[0015] Near-infrared diffuse reflection sensors are set on one side of the unloading belt of the rice combine harvester and are used to detect whether the belt is rotating, so as to determine whether it is in the unloading state;

[0016] Moisture content sensors are set at the entrance of the grain bin and are used to detect the moisture content of the harvested rice;

[0017] Ultrasonic sensors are set on the side of the cutting table of the rice combine harvester and are used to detect the height of the cutting table, so as to determine the harvesting state.

[0018] Preferably, an analysis unit is set on the microcontroller. The analysis unit analyzes the data collected by the data acquisition module and the positioning module, and stores the analysis results in the storage unit for local storage of the data.

[0019] A method for an on-board real-time yield monitor of a rice combine harvester based on multi-source sensing includes the following steps:

[0020] Use the positioning module to obtain positioning information, and the data acquisition module to collect the state data of the cutting table and the grain discharging belt of the rice combine harvester. The microcontroller judges the harvesting and grain discharging states according to the collected positioning information and the data of the rice combine harvester. When the current state is non-harvesting or non-grain discharging, this step is continued to be repeated;

[0021] When in the current harvesting state, the data acquisition module continues to collect data of the grain bin of the rice combine harvester. The data collection interval is 1 second each time, and the data of the grain bin of the rice combine harvester is preprocessed;

[0022] Store the preprocessed data in the storage unit, judge the height data of the preprocessed grain bin, and calculate the harvesting data;

[0023] Also store the calculated data in the storage unit.

[0024] Preferably, the grain bin is divided into upper and lower parts. Taking the height H1 as the boundary, judge the height data of the preprocessed grain bin:

[0025] When the height is less than or equal to H1, call the weight calculation model 1, otherwise call the weight calculation model 2.

[0026] Preferably, calculate the harvesting data, including calculating the real-time harvesting yield, real-time harvesting mu number, and real-time harvesting mu yield:

[0027] Respectively calculate the arithmetic mean of the preprocessed pressure and height data to obtain the comprehensive pressure and comprehensive height. The grain weight is proportional to the comprehensive pressure and comprehensive height;

[0028] Calculation of the real-time harvesting mu number: The calculation of the real-time harvesting yield is the difference between the real-time weights calculated in the previous 1 second and the next 1 second. The calculation of the real-time harvesting mu number is based on the longitude and latitude and speed data collected in the previous 1 second and the next 1 second, and according to the actual width of the harvester, calculate the real-time harvesting mu number;

[0029] Calculation of the real-time harvesting mu yield: Obtained by dividing the real-time harvesting yield by the real-time harvesting mu number.

[0030] Therefore, the present invention adopts the above-mentioned on-board real-time yield measuring instrument and method for rice combine harvester based on multi-source sensing, and the technical effects are as follows:

[0031] (1) The metering accuracy is high. Since the basic data for calculating the yield comes from the real-time bottom pressure of the on-board grain bin and the change of grain height, and the above data has a model relationship with the grain bin weight. At the same time, considering information such as the moisture content of the harvested rice, harvesting state, unloading state, longitude and latitude and speed of the harvester, and combining the actual time delay during the harvesting of the rice harvester, it can better calculate data such as the real-time yield and mu yield of the corresponding plot, and the accuracy is higher;

[0032] (2) It is convenient for installation and maintenance. Since the sensor is small, there is no need to disassemble and substantially modify the grain bin, which is convenient for installation, wiring and unloading. And the power supply comes from the on-board battery of the harvester, and all devices consider the waterproof performance, so the maintenance is convenient;

[0033] (3) The technologies of sensor chips, storage chips, display chips, microcontrollers, etc. are mature, the prices are low, and the system cost is not high. Description of the Drawings

[0034] Figure 1 It is a schematic diagram of an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to the present invention;

[0035] Figure 2 It is a flowchart of a method of an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to the present invention;

[0036] Figure 3 It is a top view of the grain bin and a simplified diagram of three-dimensional structure information; Figure 3 (a) is a top view of the grain bin; Figure 3 (b) is a simplified diagram of three-dimensional structure information of the grain bin;

[0037] Figure 4 It is a pressure data diagram after removing the baseline;

[0038] Figure 5 Harvester movement trajectory diagram. Detailed Embodiment

[0039] The technical solution of the present invention will be further described below with reference to the drawings and embodiments.

[0040] Unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those of ordinary skill in the field to which the present invention belongs.

[0041] Embodiment 1

[0042] As Figure 1 shown, an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing includes

[0043] A data acquisition module is used to acquire data of the rice combine harvester and its grain bin; the data acquisition module includes

[0044] Pressure sensors are evenly distributed at the bottom of the grain bin and are used to detect the pressure borne by the plane where they are located, with a total of 4 pieces;

[0045] Millimeter wave radar sensors are arranged at the top inside the grain bin and are used to detect the change in height inside the grain bin, with a total of 4 pieces;

[0046] Near-infrared diffuse reflection sensors are arranged on one side of the unloading belt of the rice combine harvester and are used to detect whether the belt rotates, so as to determine whether it is in the unloading state;

[0047] Moisture sensors are arranged at the entrance of the grain bin and are used to detect the moisture content of the harvested rice;

[0048] The ultrasonic sensor is installed on the side of the cutter bar of the rice combine harvester and is used to detect the height of the cutter bar so as to determine the harvesting status.

[0049] The positioning module is installed outside the grain bin of the rice combine harvester and is used to collect the position data of the harvester. The position data includes real-time longitude and latitude, current time and vehicle driving speed.

[0050] The communication module is used to send the data processed and analyzed by the microcontroller to the cloud server through the 5G network at a fixed baud rate.

[0051] The display module displays the results of real-time acquisition and processing by the microcontroller, including forms such as text and curves.

[0052] The storage module is for local storage and is used to store the data collected by the data acquisition module, the position data of the positioning module, and the data processed by the microcontroller.

[0053] The microcontroller is used to process the data collected by the positioning module and the data acquisition module and transmit it to the communication module, the storage module, and the display module. An analysis unit is set on the microcontroller. The analysis unit analyzes the data collected by the data acquisition module and the positioning module and stores the analysis results in the storage unit for local storage of the data.

[0054] The power supply circuit provides various power supplies such as 12V, 5V, and 3.3V for the entire yield measuring instrument, which is obtained by stabilizing and stepping down the on-board battery (DC12V) of the harvester through the power supply circuit.

[0055] As Figure 2 shown, a method for an on-board real-time yield measuring instrument of a rice combine harvester based on multi-source sensing includes the following steps:

[0056] Use the positioning module to obtain positioning information, and the data acquisition module to collect the data of the cutter bar and the grain discharging belt state of the rice combine harvester. The microcontroller judges the harvesting and grain discharging states according to the collected positioning information and the data of the grain bin of the rice combine harvester. When the current state is non-harvesting or non-grain discharging, this step is continuously repeated.

[0057] When the current state is the harvesting state, the data acquisition module continues to collect the data of the grain bin of the rice combine harvester (the pressure at 4 points at the bottom of the grain bin, the grain height at 4 points in the grain bin, and the moisture content information of 1 point of paddy). The collection interval time is 1 second each time. The data of the grain bin of the rice combine harvester is preprocessed (threshold judgment, outlier removal, Kalman filtering, baseline removal. Baseline removal is to subtract the base value collected during normal walking without harvesting under the vibration condition after the harvester starts, that is, the inherent value detected by the harvester vibration).

[0058] Store the preprocessed data in the storage unit and judge the height data of the granary after preprocessing. Due to the incomplete regularity of the on-board granary of the harvester, the granary is divided into upper and lower parts, and the weight calculation method for each part is different. Taking the height H1 as the boundary, judge the height data of the granary after preprocessing:

[0059] When the height is less than or equal to H1, call the weight calculation model 1, otherwise call the weight calculation model 2.

[0060] Calculate the harvesting data, including calculating the real-time harvesting yield, real-time harvesting mu number, and real-time harvesting mu yield:

[0061] Respectively calculate the arithmetic mean of the preprocessed pressure and height data to obtain the comprehensive pressure and comprehensive height. The grain weight is proportional to the comprehensive pressure and comprehensive height;

[0062] Calculation of the mu number of real-time harvesting: The calculation of the real-time harvesting yield is the difference between the real-time weights calculated in the previous second and the next second. The calculation of the real-time harvesting mu number is based on the longitude and latitude and speed data collected in the previous second and the next second, and according to the actual width of the harvester, calculate the real-time harvesting mu number;

[0063] Calculation of the real-time harvesting mu yield: Obtained by dividing the real-time harvesting yield by the real-time harvesting mu number.

[0064] Example 2

[0065] Taking the unmanned rice combine harvester model Ward Ryzen 4LZ-7.0ENQ as an example, first, conduct on-site measurements on the geometric data of the on-board granary of the Ward Ryzen 4LZ-7.0ENQ harvester, and draw a three-dimensional map of the granary according to the measurement data, as Figure 3 shown.

[0066] Relying on the geometric dimension information of this granary, through experimental methods, analyze the relationship between the height of paddy rice in the on-board granary of the harvester and the pressure on the bottom plane of the granary.

[0067] In view of the structural characteristics of the rice combine harvester (model: Ward 4LZ-7.0ENQ), a yield measurement software and hardware test device was developed. During the autumn harvest period from September to October 2024, the project research team went to the Rice Science and Technology Park of Bawu Liu Farm in Heilongjiang Province to install and test the yield measurement device.

[0068] Partial modifications were made to the rice combine harvester, mainly involving the installation of pressure sensors, moisture sensors and their components outside the angle iron above the grain auger in the grain bin, height sensors above the grain bin, diffuse reflection sensors installed near the belt outside the grain auger, ultrasonic sensors installed above the inner side of the cutter bar, positioning sensors arranged above the locomotive, and power taking from the vehicle-mounted battery, etc. Through reasonable wiring, the above-mentioned equipment was successfully installed, realizing the modification of the rice combine harvester. Under the static state of the vehicle, the system functions were tested. The test results showed that the power supply was normal, the data acquisition module, display module and storage module were normal, and the positioning module was working properly.

[0069] The data acquisition effect test was further carried out under the dynamic state of the harvesting vehicle. The lodged rice in the science and technology park was harvested, and the yield measurement system was started synchronously during the harvesting process.

[0070] The field yield measurement test was carried out during the harvesting of the rice combine harvester. The harvester was harvested according to Figure 5 the route map to obtain relevant sensor data. An original data set related to yield measurement was established. During the data acquisition process, since the harvesting was mainly carried out on the lodged rice fields in the early stage, the test process mainly collected the yield-related data during the harvesting process of the lodged rice.

[0071] Data was obtained from multiple rice fields one after another, the data was preliminarily marked, and an experimental data set was established. A total of 7,852 pieces of original experimental data were collected. The data was stored in text format and needed to be converted to excel format for display during the later processing.

[0072] The collected data was preprocessed. Figure 4 The pressure data graph after preprocessing and removing the baseline.

[0073] The preprocessed data was stored in the storage unit, and the height data of the grain bin after preprocessing was judged. Since the on-board grain bin of the harvester was irregular, the upper part was basically a cuboid, and the lower part was approximately trapezoidal but not completely so. The grain bin was divided into upper and lower parts, and the weight calculation methods for each part were different. Taking the height H1 as the boundary, the height data of the grain bin after preprocessing was judged:

[0074] When the height is less than or equal to H1, the weight calculation model 1 is called, otherwise the weight calculation model 2 is called. For this embodiment,

[0075] The weight model 1 is the model of the grain weight and pressure when the height is lower than or equal to H1, and the calculation formula is:

[0076]

[0077] The weight model 2 is the model of the grain weight and pressure when the height is higher than H1, and the calculation formula is:

[0078]

[0079] Among them, m1 is the grain weight of weight model 1, m2 is the grain weight of weight model 2, and m' is the pressure value.

[0080] Through the calculation of real-time weight, harvesting yield, harvested mu number, and harvested mu yield, some yield measurement data of the test area were obtained. Figure 4 Through the partial harvester movement trajectory map drawn by longitude and latitude information, Table 1 shows the mu yield calculation results for 1 minute. It can be seen from Table 1 that the average mu yield after calculation using the data within 60s is 633775 g / mu, that is, 633.775 kg / mu, and the real-time mu yield fluctuates within the range of 1355463.25 g / mu to 220298.16 g / mu. This is not only related to the processing and analysis of the data collected by the sensors, but also related to the distribution of rice in the lodged plots (all the plots collected during the test period were lodged plots).

[0081] Table 1 Mu yield measurement results for 1 minute

[0082]

[0083]

[0084] Therefore, the present invention adopts the above-mentioned airborne real-time yield measuring instrument and method for rice combine harvester based on multi-source sensing, which has high calculation accuracy, convenient installation and maintenance, and low price.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An on-board real-time yield monitor for rice combine harvesters based on multi-source sensing, characterized in that, including The data acquisition module is used to collect data of the grain bin of a rice combine harvester; The positioning module is arranged outside the grain bin of the rice combine harvester and is used to collect the position data of the harvester. The position data includes real-time longitude and latitude, current time, and vehicle driving speed; The communication module is used to transmit the data processed and analyzed by the microcontroller to the cloud server; The display module displays the results of real-time acquisition and processing by the microcontroller; The storage module is for local storage and is used to store the data collected by the data acquisition module, the position data of the positioning module, and the data processed by the microcontroller; The microcontroller is used to process the data collected by the positioning module and the data acquisition module and transmit it to the communication module, the storage module, and the display module.

2. The on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to claim 1, wherein, The data acquisition module includes Pressure sensors are evenly distributed at the bottom of the grain bin and are used to detect the pressure borne by the plane where they are located; Millimeter-wave radar sensors are arranged at the top inside the grain bin and are used to detect the change in the height inside the grain bin; Near-infrared diffuse reflection sensors are arranged on one side of the unloading belt of the rice combine harvester and are used to detect whether the belt is rotating, so as to determine whether it is in the unloading state; The moisture content sensor is arranged at the entrance of the grain bin and is used to detect the moisture content of the harvested rice; The ultrasonic sensor is arranged on the side of the cutting table of the rice combine harvester and is used to detect the height of the cutting table, so as to determine the harvesting state.

3. The on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to claim 1, characterized in that, An analysis unit is arranged on the microcontroller. The analysis unit analyzes the data collected by the data acquisition module and the positioning module, and stores the analysis results in the storage unit for local storage of the data.

4. A method for an on-board real-time yield monitor of a rice combine harvester based on multi-source sensing, characterized in that, including the following steps: Use the positioning module to obtain positioning information. The data acquisition module collects data on the state of the cutting table and the unloading belt of the rice combine harvester. The microcontroller judges the harvesting and unloading states according to the collected positioning information and the data of the grain bin of the rice combine harvester. When the current state is non-harvesting or non-unloading, this step is continued to be executed repeatedly; When the current state is the harvesting state, the data acquisition module continues to collect data of the grain bin of the rice combine harvester. The collection interval is 1 second each time, and the data of the grain bin of the rice combine harvester is preprocessed; Store the preprocessed data in the storage unit, judge the height data of the preprocessed grain bin, and calculate the harvesting data; Also store the calculated data in the storage unit.

5. The method of an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to claim 4, characterized in that, The grain bin is divided into upper and lower parts. Taking the height H1 as the boundary, judge the height data of the preprocessed grain bin: When the height is less than or equal to H1, call the weight calculation model 1, otherwise call the weight calculation model 2.

6. The method of an on-board real-time yield monitor for a rice combine harvester based on multi-source sensing according to claim 4, characterized in that, Calculate the harvesting data, including calculating the real-time harvesting yield, real-time harvesting mu number, and real-time harvesting mu yield: Respectively calculate the arithmetic mean of the preprocessed pressure and height data to obtain the comprehensive pressure and comprehensive height. The grain weight is proportional to the comprehensive pressure and comprehensive height; Calculation of the real-time harvesting mu number: The calculation of the real-time harvesting yield is the difference between the real-time weights calculated in the previous second and the next second. The calculation of the real-time harvesting mu number is based on the longitude and latitude and speed data collected in the previous second and the next second, and is calculated according to the actual width of the harvester to obtain the real-time harvesting mu number; Calculation of the real-time harvesting mu yield: Obtained by dividing the real-time harvesting yield by the real-time harvesting mu number.

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