A non-contact monitoring system and control method for regenerated rice pile height and a harvester

Abstract

The present invention provides a non-contact monitoring system and control method for the height of regenerated rice piles, and a harvester, comprising a controller, a hydraulic cylinder controller, a body inclination sensor, a laser sensor, and a displacement sensor; the body inclination sensor collects harvester body inclination angle information, the laser sensor collects the straight-line distance of the cutting platform from the ground, the displacement sensor collects the extension information of the cutting platform height adjustment cylinder, the controller processes the harvester body inclination angle information, the straight-line distance of the cutting platform from the ground, and the extension information of the cutting platform height adjustment cylinder, and controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice piles. The present invention improves measurement accuracy and reduces interference from external factors, and can automatically adjust the height of the cutting platform without manual intervention, thereby controlling the height of the regenerated rice stubble, saving labor costs.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic control of regenerated rice stubble height, and in particular relates to a non-contact monitoring system and control method for regenerated rice stubble height, and a harvester. Background Art

[0002] Ratoon rice is a double-harvest rice crop. This refers to the cultivation and management measures implemented after the first rice harvest to promote the germination and tillering of dormant axillary buds on the stumps, ultimately leading to heading, flowering, and fruiting. To ensure the yield of the second season of ratoon rice, manual harvesting is often used during the first season to effectively increase the multiple cropping index. However, with my country's rapid economic and social development and the migration of young and middle-aged rural labor to cities, the use of rice combine harvesters has replaced manual harvesting as the primary method for harvesting ratoon rice in the first season. However, domestic rice combine harvesters generally lack automatic height control for the cutting table. Manual adjustment of the cutting table to ensure a stable stump height is not only labor-intensive but also leads to unstable stump height, potentially affecting the overall yield of ratoon rice. This can damage the axillary buds on the stumps, stunt their development, and hinder their growth, resulting in yield losses in the second season of ratoon rice and hindering the expansion of ratoon rice cultivation in my country. Furthermore, the stump height of common ratoon rice varieties in my country varies by variety and region, ranging from 250mm to 400mm. Therefore, different harvester heights are required for different regions and varieties of ratoon rice. Currently, adjustment of the harvester height during harvesting on rice-wheat combine harvesters relies primarily on the operator manipulating a hydraulic control valve in real time based on field conditions. This requires high operator experience and technical skills due to the complex and changing operating environment and conditions. Therefore, designing an automatic detection and adjustment method for ratoon rice stubble height to protect the dominant dormant buds of ratoon rice and promote increased yield and income during the ratoon season remains an important issue in the research and use of ratoon rice combine harvesters.

[0003] Most foreign harvesters use a header profiling mechanism to automatically adjust the height of their harvester headers. For example, the contact-type header height profiling mechanism on the John Deere JD-1075H combine harvester uses a profiling plate installed below the header to oscillate with the ground, acquiring information on ground height changes. Yang Yinhui designed a header height control system based on ultrasonic sensors. This system uses multiple ultrasonic sensors installed at the bottom of the header to detect height and an electro-hydraulic proportional valve for control. Liao Yong et al. used infrared sensors to measure crop height, displacement sensors installed on the lifting cylinder to indirectly measure header height, and an electromagnetic reversing valve to control header elevation. However, these studies still face several challenges. The profiling plate method is significantly affected by terrain variations; the ultrasonic sensor is susceptible to interference from crops; and the electro-hydraulic proportional valve is relatively expensive. Measuring header height using cylinder displacement is not well adapted to ground undulations. Controlling header elevation using an electromagnetic reversing valve is prone to overshoot, and frequent switching of the solenoid valve can damage the valve core. In addition, the regenerated rice piles are the stem residues left after the rice is harvested, mainly including the rice stems, leaf sheaths, leaves, etc. In the practice of mechanized harvesting of the first season of regenerated rice, it is found that due to the high height and many leaves of the regenerated rice piles left after the first season of harvesting, it will cause certain interference to the sensor detection height, resulting in part of the received height data being the distance from the sensor installation position to the rice stems and leaves. Therefore, the received data needs to be processed to meet the needs of height monitoring.

[0004] Therefore, there is an urgent need for a low-cost and practical technical means that can improve measurement accuracy and reduce interference from external factors. Summary of the Invention

[0005] In response to the above technical problems, the present invention provides a non-contact monitoring system and control method for the height of regenerated rice stubble, as well as a harvester, which improves measurement accuracy and reduces interference from external factors. The height of the harvesting platform can be automatically adjusted without human intervention, thereby controlling the height of the regenerated rice stubble and saving labor costs.

[0006] The present invention achieves the above technical objectives through the following technical means.

[0007] A non-contact monitoring system for the height of regenerated rice piles, comprising a controller, a hydraulic cylinder controller, a vehicle body inclination sensor, a laser sensor, and a displacement sensor;

[0008] The body inclination sensor is arranged on the harvester body and on the same side as the harvesting platform, and is used to collect the harvester body inclination angle information and transmit it to the controller;

[0009] The laser sensor is arranged on one side of the cutting platform and is used to collect the straight-line distance between the cutting platform and the ground and transmit it to the controller;

[0010] The displacement sensor is provided on one side of the header height adjustment cylinder and is used to collect information on the extension of the header height adjustment cylinder and transmit it to the controller;

[0011] The controller is respectively connected to the hydraulic cylinder controller, the vehicle body inclination sensor, the laser sensor and the displacement sensor; the controller processes the harvester body inclination angle information, the straight-line distance of the cutting platform from the ground and the extension amount of the cutting platform height adjustment cylinder, and controls the extension amount of the cutting platform height adjustment cylinder through the hydraulic cylinder controller to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0012] In the above scheme, the controller filters the data collected by the laser sensor and the displacement sensor through a combination of multi-stage threshold filtering and Kalman filtering; the controller performs real-time data correction on the filtered data and the data collected by the vehicle body inclination sensor to obtain data corrected based on multi-source sensors; the controller fuses the corrected data through a historical data adaptive weighting method, inputs the data into a support vector machine, and predicts the predicted height value of the cutting platform through the height prediction model of the support vector machine; the controller adjusts the height of the cutting platform by controlling the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller according to the obtained predicted height value of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0013] A control method according to the non-contact monitoring system for regenerated rice stubble height comprises the following steps:

[0014] Step S1, sensor data collection: the body inclination sensor collects the harvester body inclination angle information and transmits it to the controller, the laser sensor collects the straight-line distance of the cutting platform from the ground and transmits it to the controller, and the displacement sensor collects the extension information of the cutting platform height adjustment cylinder and transmits it to the controller;

[0015] Step S2, data filtering processing: the controller performs filtering processing on the data collected by the laser sensor and displacement sensor in step S1 by combining multi-stage threshold filtering and Kalman filtering;

[0016] Step S3, data correction: the controller performs real-time data correction on the data obtained after filtering in step S2 and the data collected by the vehicle body tilt sensor to obtain data corrected based on the multi-source sensor;

[0017] Step S4, data fusion: The controller fuses the corrected data obtained in step S3 by using a historical data adaptive weighting method, inputs the data into a support vector machine, and obtains a predicted height value of the header by using a height prediction model of the support vector machine;

[0018] Step S5, cutting platform height control: the controller controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller according to the predicted height value of the cutting platform obtained in step S4 to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0019] In the above scheme, in the step S1 sensor data collection, when the change in the harvester body inclination angle collected by the body inclination sensor is less than 0.75°, the data is invalid; when the change in the harvester body inclination angle is ≥0.75°, the data is valid, and the inclination data is sent to the controller after the data collection is completed.

[0020] In the above solution, the data filtering process in step S2 specifically includes the following steps:

[0021] Step S2.1, fitting the function between the extension of the header height adjustment cylinder output by the displacement sensor and the header height;

[0022] Step S2.2: First, a multi-stage threshold filter is used to adjust the maximum and minimum extension values ​​of the header height adjustment cylinder based on the displacement sensor in the previous stage. Thresholds are set to process the height data measured by the laser sensor, limiting the height measured by the laser sensor to within the set threshold range.

[0023] Step S2.3: Use the Kalman filter method to perform Kalman filter processing on the height data after the multi-segment threshold filtering.

[0024] In the above solution, the data correction in step S3 specifically includes the following steps:

[0025] First, calibrate the vehicle body inclination sensor on a horizontal plane and set it to zero. The data changes on the Z and Y axes of the vehicle body inclination sensor can now reflect the degree of tilt in the front-back and left-right directions, respectively. Set the angle change on the Y axis to α and the change on the Z axis to β. When their values ​​change, the laser sensor will correct them according to the increments. The height data obtained is:

[0026] h z =h·cosα·cosβ

[0027] Where: h z is the height data of the laser sensor after correction, that is, the output value; h is the original height data collected by the laser sensor, that is, the input value.

[0028] In the above solution, in step S4, the corrected data obtained in step S3 are fused by the historical data adaptive weighting method:

[0029] The calculation formula of the height value at a certain moment after weighted average fusion is as follows:

[0030]

[0031]

[0032] Where: is the height value after filtering and weighted averaging at a certain moment, is the altitude value at the current moment after filtering, is the weight of a certain measurement data at the current moment, The mean absolute error of a set of measurement data at the current moment; n is the number of acquired data; The current measurement value of a group of measurement data of the laser sensor; is the set height value, which is calculated based on the detection value of the displacement sensor; i is a certain moment.

[0033] Furthermore, the input values ​​of the height prediction model in step S4 also include features related to height: the average height and height change rate of regenerated rice within a preset number of days;

[0034] The height prediction model is:

[0035] y=w T φ(x)+b

[0036] in

[0037]

[0038] Where x is the input vector, including the feature variables and historical data values, t represents the number of days, and h t is the average height on day t, r t is the rate of change of height between the tth day and the previous day, is the height value after filtering and weighted averaging at a certain moment, w is the weight vector obtained by model training, b is the bias term obtained by model training, φ(x) is the feature mapping function, and the RBF radial basis kernel function is used here, where x m is the support vector, and σ is a hyperparameter related to the samples in the dataset.

[0039] In the above scheme, in step S5, the controller adjusts the predicted height value of the cutting platform through the fuzzy PID controller, and then controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0040] A harvester comprises the non-contact monitoring system for the height of regenerated rice piles and is controlled according to the control method for the non-contact monitoring system for the height of regenerated rice piles.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention uses a laser sensor, an inclination sensor, and a displacement sensor to collect information about the surrounding environment, identifies the straight-line distance of the cutting platform from the ground, the inclination angle of the vehicle body, and the displacement of the oil cylinder. The controller performs filtering processing on the data collected by the laser sensor and the displacement sensor by combining multi-segment threshold filtering and Kalman filtering. The controller performs real-time data correction on the filtered data and the data collected by the vehicle body inclination sensor to obtain data corrected based on multi-source sensors. The controller fuses the corrected data by a historical data adaptive weighting method, inputs the data into a support vector machine, and predicts the predicted height value of the cutting platform through the height prediction model of the support vector machine. The controller controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller according to the obtained predicted height value of the cutting platform to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile. The present invention integrates multi-source sensing to achieve non-contact automatic control of the height of the regenerated rice pile, improves the accuracy and reliability of the data, and automatically adjusts the height of the cutting platform without manual intervention, greatly saving labor costs and experimental accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the assembly of a sensor on a harvester according to one embodiment of the present invention.

[0044] Figure 2 It is a schematic diagram of a method flow chart of one embodiment of the present invention.

[0045] Figure 3 Schematic diagram of the relationship between the installation plane of the tilt sensor and the XYZ axes according to one embodiment of the present invention.

[0046] In the figure: 1. Controller; 2. Hydraulic cylinder control system; 3. Vehicle body tilt sensor; 4. Laser sensor; 5. Displacement sensor. DETAILED DESCRIPTION

[0047] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0048] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "front", "back", "left", "right", "up", "down", "axial", "radial", "vertical", "horizontal", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0049] In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connect," "fixed," etc. should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0050] Figure 1 The figure shows a preferred embodiment of the non-contact control system for the height of regenerated rice piles, which includes a controller 1, a hydraulic cylinder controller 2, a vehicle body inclination sensor 3, a laser sensor 4, and a displacement sensor 5;

[0051] The body inclination sensor 3 is provided on the harvester body and on the same side as the header, and is used to collect the harvester body inclination angle information and transmit it to the controller 1;

[0052] The laser sensor 4 is provided on the side plate of the cutting platform divider, and is used to collect the straight-line distance between the cutting platform and the ground and transmit it to the controller 1;

[0053] The displacement sensor 5 is provided on one side of the header height adjustment cylinder and is used to collect information on the extension of the header height adjustment cylinder and transmit it to the controller 1;

[0054] The controller 1 is respectively connected to the hydraulic cylinder controller 2, the vehicle body inclination sensor 3, the laser sensor 4 and the displacement sensor 5; the controller 1 processes the harvester body inclination angle information, the straight-line distance of the cutting platform from the ground and the extension information of the cutting platform height adjustment cylinder, and adjusts the height of the cutting platform by controlling the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller 2, thereby adjusting the height of the regenerated rice pile.

[0055] The controller 1 filters the data collected by the laser sensor 4 and the displacement sensor 5 by combining multi-stage threshold filtering and Kalman filtering; the controller 1 performs real-time data correction on the filtered data and the data collected by the vehicle body inclination sensor 3 to obtain data corrected based on multi-source sensors; the controller 1 fuses the corrected data through a historical data adaptive weighting method, inputs the data into a support vector machine, and predicts the predicted height value of the cutting platform through the height prediction model of the support vector machine; the controller 1 controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller 2 according to the obtained predicted height value of the cutting platform to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0056] Preferably, the controller 1 is a single chip microcomputer.

[0057] like Figure 2 As shown, a control method of the non-contact monitoring system for the height of regenerated rice piles comprises the following steps:

[0058] Step S1, sensor data collection: the body inclination sensor 3 collects the harvester body inclination angle information and transmits it to the controller 1, the laser sensor 4 collects the straight-line distance of the cutting platform from the ground and transmits it to the controller 1, and the displacement sensor 5 collects the extension amount information of the cutting platform height adjustment cylinder and transmits it to the controller 1;

[0059] Step S2, data filtering processing: the controller 1 performs filtering processing on the data collected by the laser sensor 4 and the displacement sensor 5 in step S1 by combining multi-stage threshold filtering and Kalman filtering;

[0060] Step S3, data correction: the controller 1 performs real-time data correction on the data obtained after filtering in step S2 and the data collected by the vehicle body inclination sensor 3 to obtain data corrected based on multi-source sensors;

[0061] Step S4, data fusion: the controller 1 fuses the corrected data obtained in step S3 by using a historical data adaptive weighting method, inputs the data into a support vector machine, and obtains a predicted height value of the header by using a height prediction model of the support vector machine;

[0062] Step S5, cutting platform height control: the controller 1 controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller 2 according to the predicted height value of the cutting platform obtained in step S4 to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0063] The static measurement average value error of the tilt sensor 3 is ±0.01°. The tilt sensor 3 is a sensitive component. Since the harvester experiences slight bumps when driving in the field, in the sensor data collection step S1, when the change in the harvester body tilt angle collected by the body tilt sensor 3 is less than 0.75°, the data is invalid; when the change in the harvester body tilt angle is ≥0.75°, the data is valid. After the data collection is completed, the tilt data is sent to the controller 1.

[0064] The data filtering process in step S2 specifically includes the following steps:

[0065] Step S2.1, fitting the function between the extension of the header height adjustment cylinder and the header height output by the displacement sensor 5 based on the least squares method to obtain a more accurate result. When the cylinder is extended, the change in header height can be obtained based on the function between the extension of the header height adjustment cylinder and the header height, thereby obtaining a more accurate result;

[0066] Furthermore, in a specific embodiment of the present invention, in order to fit the function between the extension of the cutting platform height adjustment cylinder and the cutting platform height output by the displacement sensor 5, the cutting platform is manually raised from the lowest point to the highest point at intervals of 5 cm during calibration, and the cutting platform height and the voltage value of the displacement sensor are recorded during the process to obtain a linear function.

[0067] Step S2.2: First, use multi-stage threshold filtering to adjust the maximum and minimum extension values ​​of the oil cylinder based on the height of the header measured by the displacement sensor 5, set thresholds to process the height data measured by the laser sensor 4, and limit the height measured by the laser sensor 4 to the set threshold range;

[0068] Furthermore, based on the previous test results and the observation and analysis of the height of the pile and the height of the blades from the ground, multiple thresholds are set using multi-threshold filtering to divide the obtained height data into three data areas, which can effectively avoid the interference of field leaves on the detection data. Based on the maximum and minimum values ​​of the extension of the header height adjustment cylinder measured by the displacement sensor 5, thresholds are set to process the height data measured by the laser sensor 4 respectively, and the height measured by the laser sensor 4 is limited to the set threshold range; in particular, the upper and lower thresholds will change with the maximum and minimum values ​​of the extension of the header height adjustment cylinder measured by the displacement sensor 5. The upper and lower thresholds will change with the regional division as follows:

[0069]

[0070] Where h i is the data measured by the laser sensor, H1 is the minimum value measured by the displacement sensor, and H2 is the maximum value measured by the displacement sensor.

[0071] Step S2.3: Use the Kalman filter method to perform Kalman filter processing on the height data after the multi-segment threshold filtering, and input the filtered data as sample data to the controller 1.

[0072] The present invention first adopts multi-stage threshold filtering combined with Kalman filtering to effectively eliminate outliers and noise, especially when the altitude data is subject to external interference.

[0073] The data correction step S3 specifically includes the following steps:

[0074] First, calibrate the vehicle body tilt sensor 3 on the horizontal plane and set it to zero. Figure 3 As shown, the data changes of the Z-axis and Y-axis of the vehicle body inclination sensor 3 can respectively reflect the degree of inclination of the vehicle body in the front-back and left-right directions. Assuming the angle change of the Y-axis is α and the change of the Z-axis is β, when their values ​​change, the laser sensor 4 will be corrected according to the increment, and the height data obtained is:

[0075] h z =h·cosα·cosβ

[0076] Where: h z is the height data of the laser sensor 4 after correction, that is, the output value, in cm; h is the original height data collected by the laser sensor 4, that is, the input value, in mm.

[0077] The data fusion of step S4 includes the following steps:

[0078] Data fusion of laser sensor 4 based on historical data: By calculating the average absolute error between the measurement data of laser sensor 4 and the true value of header height in the period before the measurement, and controlling the number of acquired data, combined with the current height value, the height value at a certain moment after weighted average fusion is obtained;

[0079] The calculation formula of the height value at a certain moment after weighted average fusion is as follows:

[0080]

[0081] Where: is the height value after filtering and weighted averaging at a certain moment, is the altitude value at the current moment after filtering, is the weight of a certain measurement data at the current moment, The mean absolute error of a set of measurement data at the current moment; n is the number of acquired data, which is 20; The current measurement value of a certain set of measurement data of the laser sensor 4; is the set height value, which is calculated based on the detection value of the displacement sensor 5; i is a certain moment.

[0082] The support vector machine in step S4 uses support vector regression (SVR) to predict height, specifically the following steps:

[0083] 1. Data collection: Collect altitude data, which is the altitude value and related features after filtering and weighted averaging at a certain moment;

[0084] 2. Data preprocessing: processing missing values, outliers (such as extreme values), and feature standardization or normalization of the collected data;

[0085] 3. Divide the data set: Divide the preprocessed data into a training set and a test set. Specifically, 80% is the training set and 20% is the test set.

[0086] 4. Model training: Use the support vector regression (SVR) algorithm to train the height prediction model based on the training set;

[0087] 5. Model prediction: Use the trained height prediction model to make predictions on the test set;

[0088] 6. Evaluate the model: by using mean square error (MSE), coefficient of determination (R 2 ) and other methods to evaluate the model performance.

[0089] The height-related features include the average height and height change rate of regenerated rice within a preset number of days.

[0090] The height prediction model in step S4 is:

[0091] y=w T φ(x)+b

[0092] in

[0093]

[0094] Where x is the input vector, including the feature variables and historical data values, t represents the number of days, and h t is the average height on day t, r t is the rate of change of height between the tth day and the previous day, is the height value after filtering and weighted averaging at a certain moment, w is the weight vector obtained by model training, b is the bias term obtained by model training, φ(x) is the feature mapping function, and the RBF radial basis kernel function is used here, where x m is the support vector, and σ is a hyperparameter related to the samples in the dataset.

[0095] The adaptive weighted historical data method of the present invention fuses the corrected data obtained in step S3, and predicts the predicted height value of the header through the height prediction model of the support vector machine. The combination of the adaptive weighted historical data method and the support vector machine helps to achieve efficient, flexible and accurate prediction in the process of height data processing.

[0096] In step S5, the controller 1 adjusts the predicted height value of the cutting platform through the fuzzy PID controller, and then controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller 2 to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0097] In step S5, the controller 1 adjusts the predicted height value of the header through the fuzzy PID controller, specifically:

[0098] First, define the input and output quantities. Input: Height error (e): The displacement sensor 5 uses the measured data after the function calculation of the height value c as the actual value and the external input predicted value r as the target value to obtain the height error e (e = cr) and the height error change rate ec (ec = de / dt). Output: Proportional coefficient K P , integral coefficient K I , differential coefficient K D : PID control signal corresponding to the adjustment function.

[0099] Then, we define the fuzzy set: the fuzzy subsets of the input and output variables are quantized into 7 levels, and their fuzzy word set is represented as [NBNM NS ZO PS PM PB]. The basic domain is {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}.

[0100] Next, fuzzy rules are designed: according to the input combination, the control signal output in each case is determined. The specific fuzzy rule table is as follows (cited from Liu Weijian, Luo Xiwen, Zeng Shan, et al. Performance test and analysis of adaptive profiling harvesting platform for regenerated rice based on fuzzy PID control [J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(10): 1-9.):

[0101] Table 1 Fuzzy rules table

[0102]

[0103] Finally, defuzzification: convert the fuzzy output into the proportional coefficient K of the PID controller parameters P , integral coefficient K I , differential coefficient K D As the output of the fuzzy PID controller.

[0104] Furthermore, the controller 1 performs PID processing on the data based on the result obtained by the fuzzy PID controller, and inputs the processed data into the hydraulic cylinder controller 2 to control the extension of the cutting platform height adjustment cylinder to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

[0105] The fuzzy PID algorithm of the fuzzy PID controller of the present invention is used for regulation and control, which can improve the overall performance and adaptability of the system.

[0106] A harvester comprises the non-contact monitoring system for the height of regenerated rice piles and is controlled according to the control method for the non-contact monitoring system for the height of regenerated rice piles.

[0107] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0108] The series of detailed descriptions listed above are only specific descriptions of feasible embodiments of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent embodiments or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A control method for a non-contact monitoring system for the height of regenerated rice stubble, characterized in that: The invention comprises a non-contact monitoring system for the height of regenerated rice piles; the non-contact monitoring system for the height of regenerated rice piles comprises a controller (1), a hydraulic cylinder controller (2), a vehicle body inclination sensor (3), a laser sensor (4) and a displacement sensor (5); The body inclination sensor (3) is arranged on the harvester body and on the same side as the harvesting platform, and is used to collect the harvester body inclination angle information and transmit it to the controller (1); The laser sensor (4) is arranged on one side of the cutting platform and is used to collect the straight-line distance between the cutting platform and the ground and transmit it to the controller (1); The displacement sensor (5) is arranged on one side of the header height adjustment oil cylinder and is used to collect information on the extension of the header height adjustment oil cylinder and transmit it to the controller (1); The controller (1) is respectively connected to a hydraulic cylinder controller (2), a vehicle body inclination sensor (3), a laser sensor (4), and a displacement sensor (5); the controller (1) processes information on the harvester vehicle body inclination angle, the straight-line distance of the cutting platform from the ground, and the extension amount of the cutting platform height adjustment cylinder, and controls the extension amount of the cutting platform height adjustment cylinder through the hydraulic cylinder controller (2) to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile; The method comprises the following steps: Step S1, sensor data collection: the body inclination sensor (3) collects the harvester body inclination angle information and transmits it to the controller (1); the laser sensor (4) collects the straight-line distance of the cutting platform from the ground and transmits it to the controller (1); the displacement sensor (5) collects the extension amount information of the cutting platform height adjustment cylinder and transmits it to the controller (1); Step S2, data filtering processing: the controller (1) performs filtering processing on the data collected by the laser sensor (4) and the displacement sensor (5) in step S1 by combining multi-stage threshold filtering and Kalman filtering; Step S3, data correction: the controller (1) performs real-time data correction on the data obtained after filtering in step S2 and the data collected by the vehicle body tilt sensor (3), to obtain data corrected based on the multi-source sensor; Step S4, data fusion: the controller (1) fuses the corrected data obtained in step S3 by using a historical data adaptive weighting method, inputs the data into a support vector machine, and obtains a predicted height value of the header by using a height prediction model of the support vector machine; Step S5, cutting platform height control: the controller (1) controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller (2) according to the predicted height value of the cutting platform obtained in step S4 to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

2. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 1, characterized in that: The controller (1) performs filtering processing on data collected by the laser sensor (4) and the displacement sensor (5) by combining multi-segment threshold filtering and Kalman filtering; the controller (1) performs real-time data correction on the filtered data and the data collected by the vehicle body tilt sensor (3) to obtain data corrected based on the multi-source sensor; the controller (1) fuses the corrected data by using a historical data adaptive weighting method, inputs the data into a support vector machine, and obtains a predicted height value of the cutting platform by using a height prediction model of the support vector machine; the controller (1) controls the extension of the cutting platform height adjustment cylinder through a hydraulic cylinder controller (2) according to the obtained predicted height value of the cutting platform to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

3. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 1, characterized in that: In the sensor data collection step S1, when the change in the harvester body inclination angle collected by the body inclination sensor (3) is less than 0.75°, the data is invalid; when the change in the harvester body inclination angle is greater than or equal to 0.75°, the data is valid, and after the data collection is completed, the inclination angle data is sent to the controller (1).

4. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 1, characterized in that: The data filtering process in step S2 specifically includes the following steps: Step S2.1, fitting the function between the extension of the header height adjustment cylinder output by the displacement sensor (5) and the header height; Step S2.2, first adopting multi-stage threshold filtering, based on the maximum and minimum values ​​of the extension of the cutting platform adjustment cylinder measured by the displacement sensor (5), setting thresholds to process the height data measured by the laser sensor (4) respectively, and limiting the height measured by the laser sensor (4) to within the set threshold range; Step S2.3: Use the Kalman filter method to perform Kalman filter processing on the height data after the multi-segment threshold filtering.

5. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 1, characterized in that: The data correction step S3 specifically includes the following steps: First, the vehicle body tilt sensor (3) is calibrated on a horizontal plane and set to zero. At this time, the data changes of the Z axis and Y axis of the vehicle body tilt sensor (3) can respectively reflect the degree of tilt of the vehicle body in the front and rear and left and right directions. The angle change of the Y axis is set to α and the change of the Z axis is set to β. When the values ​​change, the laser sensor (4) will be corrected according to the increment, and the height data obtained is: h z =h·cosα·cosβ Where: h z is the height data of the laser sensor (4) after correction, that is, the output value; and h is the original height data collected by the laser sensor (4), that is, the input value.

6. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 1, characterized in that: In step S4, the corrected data obtained in step S3 are fused using the historical data adaptive weighting method: The calculation formula of the height value at a certain moment after weighted average fusion is as follows: Where: is the height value after filtering and weighted averaging at a certain moment, is the altitude value at the current moment after filtering, is the weight of a certain measurement data at the current moment, The mean absolute error of a set of measurement data at the current moment; n is the number of acquired data; is the current measurement value of a certain set of measurement data of the laser sensor (4); is the set height value, which is calculated based on the detection value of the displacement sensor (5); i is a certain moment.

7. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 6, characterized in that: The input values ​​of the height prediction model in step S4 also include features related to height: the average height and height change rate of regenerated rice within a preset number of days; The height prediction model is: in Where x is the input vector, including the feature variables and historical data values, t represents the number of days, and h t is the average height on day t, r t is the rate of change of height between the tth day and the previous day, is the height value after filtering and weighted averaging at a certain moment, w is the weight vector obtained by model training, b is the bias term obtained by model training, φ(x) is the feature mapping function, and the RBF radial basis kernel function is used here, where x m is the support vector, and σ is a hyperparameter related to the samples in the dataset.

8. The control method of the non-contact monitoring system for the height of regenerated rice stubble according to claim 6, characterized in that: In step S5, the controller (1) adjusts the predicted height value of the cutting platform through the fuzzy PID controller, and then controls the extension of the cutting platform height adjustment cylinder through the hydraulic cylinder controller (2) to adjust the height of the cutting platform, thereby adjusting the height of the regenerated rice pile.

9. A harvester, characterized in that: The method comprises controlling the non-contact monitoring system for the height of regenerated rice piles according to any one of claims 1 to 8.

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