System and method for monitoring running state of soil conditioner spreading machine
Through the operating status monitoring system of the soil conditioner spreader, abnormal evaluation values are generated using the spreading quantity and uniformity parameter information, and early warning analysis is carried out in combination with historical data, which solves the problem of inaccurate early warning and inaccurate monitoring in the existing technology, and realizes the More accurate operating status monitoring and efficiency guarantee.
Patent Information
- Application Number
- CN202411616532.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-13
- Publication Date
- 2024-12-31
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The operating status monitoring of existing soil conditioner spreaders depends on abnormal spreading conditions, and cannot be warned in advance, and due to accidental factors, the monitoring results are not accurate enough.
A soil conditioner spreader operating status monitoring system was designed, including a dispensing monitoring module, an analysis and calculation center and a real-time alarm module. By obtaining dispensing quantity and dispensing uniformity parameter information, an abnormal evaluation value is generated, and potential abnormalities are combined with historical data. Risk warning analysis, real-time alarm and warning reminder.
It improves the accuracy of monitoring, can detect potential problems early, reduces the occurrence of abnormal operation of the spreader, and ensures operating efficiency.
Smart Images
Figure CN119229625A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of spreader operation monitoring, and in particular relates to a soil conditioner spreader operation status monitoring system and method. Background Art
[0002] Soil conditioner spreader is a kind of mechanical equipment specially used to spread soil conditioner evenly on farmland. Soil conditioner can help improve soil structure, increase soil fertility, promote crop growth, etc.
[0003] In order to ensure the normal operation of soil conditioner spreaders, the operating status of soil conditioner spreaders is generally monitored. Currently, whether the operating status is normal is mostly determined by judging the conditioning and spreading conditions of the soil conditioner spreader during operation. Firstly, due to the influence of accidental factors, it is not accurate to determine that the operating status of the soil conditioner spreader is abnormal only based on the abnormal spreading conditions at a certain moment. In addition, only when the spreading conditions are more obviously abnormal can it be determined that the operating status of the spreader is abnormal, and at this time the spreading abnormality has already occurred, so it is impossible to warn of the abnormal situation in advance. Summary of the invention
[0004] The object of the present invention is to provide a soil conditioner spreader operating status monitoring system and method to solve the problems faced in the above-mentioned background technology.
[0005] The purpose of the present invention can be achieved through the following technical solutions: A soil conditioner spreader operating status monitoring system, the monitoring system comprising: A spreading monitoring module, which is used to obtain parameter information such as spreading amount and spreading uniformity of the spreader during spreading operation; An analysis and calculation center, the analysis and calculation center is used to perform analysis and calculation according to the acquired parameter information, thereby generating an abnormal evaluation value, and analyzing whether the operating state of the spreader is abnormal according to the abnormal evaluation value; A real-time alarm module, when the spreader is in an abnormal state, the real-time alarm module generates a corresponding alarm instruction to give an alarm reminder; The early warning analysis module performs early warning analysis on potential abnormal risks of the spreader's operating status in combination with historical data when the spreader's operating status is normal, thereby issuing corresponding early warnings.
[0006] Furthermore, the method by which the analysis and calculation center analyzes whether the operating state of the spreader is abnormal according to the abnormal evaluation value is as follows: In a monitoring period ∆T, n data are collected to obtain the spreading amount S and spreading uniformity E, and a spreading amount change curve over time is drawn up based on the changes in spreading amount and spreading uniformity. And the spreading uniformity curve over time ; By formula Abnormal evaluation value ; The abnormal assessment value obtained The abnormal assessment threshold set in the system To compare: when When the spreader is in abnormal operation state, in, as well as is the preset scale factor, is the start time of the monitoring period, is the end time of the monitoring period, The time-varying curve of the standard spreading amount set for the system. is the coefficient of variation of spreading amount, is the coefficient of variation of spreading uniformity.
[0007] Furthermore, the coefficient of variation of the spreading amount is And the coefficient of variation of spreading uniformity The method to obtain it is: By formula Get the coefficient of variation of the spreading amount , through the formula Get the coefficient of variation of spreading uniformity ; in, is the spreading amount collected for the i-th time during the monitoring period, is the spreading uniformity collected for the i-th time during the monitoring period, and .
[0008] Furthermore, the method for the real-time alarm module to perform an alarm reminder is: When the spreader is in an abnormal state, the abnormal evaluation value will be obtained. Another abnormal assessment threshold set in the system To compare: when When the alarm is triggered, a primary alarm command is generated to remind the operator to check and adjust the operating parameters of the spreader; when When an alarm occurs, a high-level alarm command is generated to stop the spreading operation and repair the spreader.
[0009] Furthermore, the method in which the early warning analysis module performs early warning analysis on the potential abnormal risk of the spreader operation state is: By formula Derive risk warning values; The risk warning value obtained The risk warning threshold preset in the system To compare: when When the spreader is running, it is judged that there is a potential abnormal risk; Otherwise, it is judged that the spreader is operating normally; as well as is the preset scale factor, is the current risk factor, is the historical risk factor.
[0010] Furthermore, the current risk factor The method to obtain it is: When the spreader is in normal operation, a large cycle is set, and the abnormal evaluation values obtained in m monitoring cycles ∆T are obtained in the large cycle, so as to formulate the abnormal evaluation value change curve over time. ; By formula Get the current risk factor ; in, is the start time of the big cycle, is the end time of the big cycle, This is the time-varying curve of the standard abnormality assessment value preset by the system. For a large cycle The maximum value of is the maximum abnormal assessment value within a large cycle, It is the minimum abnormal assessment value within a large period.
[0011] Furthermore, the historical risk factor The method to obtain it is: In the historical database, according to the abnormal evaluation values of the spreader during the two most recent operations, a time curve of abnormal evaluation values during the two operations is drawn up; A rectangular coordinate system is established with time as the x-axis and the abnormal assessment value as the y-axis. The proposed curve is brought into the rectangular coordinate system and compared with the respective preset threshold curves. In the rectangular coordinate system, the area below the proposed curve and above the respective preset threshold curves is recorded as , ; By formula Deriving the historical risk factor ; in, as well as The average abnormal evaluation value of the spreader during the last two operations. A method for monitoring the operating status of a soil conditioner spreader is implemented by the soil conditioner spreader operating status monitoring system.
[0012] Beneficial effects of the present invention: The present invention obtains parameter information such as the spreading amount and spreading uniformity of the spreader during the spreading operation within the monitoring period. In this way, it can be judged whether the operating state of the spreader is abnormal based on the changes in the spreading amount and the spreading uniformity within the monitoring period. The influence of accidental factors on the monitoring results can be eliminated, and the accuracy of monitoring can be ensured.
[0013] When the spreader is in normal operation, the present invention can conduct a comprehensive analysis based on the changes in the currently acquired abnormal assessment value combined with the changes in the spreading amount and spreading uniformity in the historical data to conduct early warning analysis on the potential abnormal risks of the spreader's operation status. In this way, potential problems with the spreader can be discovered early and corresponding processing can be performed, which can reduce the occurrence of operating abnormalities during subsequent spreader operations and effectively ensure the efficiency of the operation.
[0014] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.
[0016] Figure 1 is a system block diagram of the present invention; Figure 2 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION
[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0018] In one embodiment, a soil conditioner spreader operating status monitoring system is disclosed. Figure 1 As shown, the monitoring system mainly includes: The spreading monitoring module is used to obtain parameter information such as the spreading amount and spreading uniformity of the spreader during the spreading operation; The analysis and calculation center is used to perform analysis and calculation based on the acquired parameter information, generate abnormal evaluation values, and analyze whether the operation status of the spreader is abnormal based on the abnormal evaluation values; Real-time alarm module: when the spreader is in abnormal operation, the real-time alarm module generates corresponding alarm instructions to give an alarm; Early warning analysis module: When the spreader is in normal operation, the early warning analysis module combines historical data to conduct early warning analysis on the potential abnormal risks of the spreader's operation status, thereby issuing corresponding early warnings.
[0019] Through the above technical scheme, the present application first sets a monitoring cycle, and then obtains parameter information such as the spreading amount and spreading uniformity of the spreader during the spreading operation in real time through the spreading monitoring module, and transmits these parameter information to the analysis and calculation center for analysis and calculation, generates an abnormal evaluation value, and analyzes whether the operating state of the spreader is abnormal based on the abnormal evaluation value. In this way, the spreader can be judged whether the operating state of the spreader is abnormal based on the changes in the spreading amount and the changes in the spreading uniformity within the monitoring period. In this way, the influence of accidental factors on the monitoring results can be eliminated, and the accuracy of monitoring can be ensured; at the same time, when the operating state of the spreader is abnormal When the spreader is in normal operation, the early warning analysis module can also conduct a comprehensive analysis based on the changes in the acquired abnormal evaluation values and the changes in the spreading amount and spreading uniformity in the historical data to conduct early warning analysis on the potential abnormal risks of the spreader's operating status. In this way, potential problems of the spreader can be discovered early and handled accordingly, which can reduce the occurrence of abnormal operations during subsequent spreader operations and effectively ensure the efficiency of the operation.
[0020] As an embodiment of the present invention, the method for the analysis and calculation center to analyze whether the operating state of the spreader is abnormal is: In a monitoring period ∆T, n data are collected to obtain the spreading amount S and spreading uniformity E, and a spreading amount change curve over time is drawn up based on the changes in spreading amount and spreading uniformity. And the spreading uniformity curve over time ; By formula Abnormal evaluation value ; The abnormal assessment value obtained The abnormal assessment threshold set in the system Compare: When When the spreader is in abnormal operation state, in, as well as is the preset scale factor, is the start time of the monitoring period, is the end time of the monitoring period, The time-varying curve of the standard spreading amount set for the system. is the coefficient of variation of spreading amount, is the coefficient of variation of spreading uniformity; The coefficient of variation of the spreading amount And the coefficient of variation of spreading uniformity The method of obtaining is: through the formula Get the coefficient of variation of the spreading amount through the formula Obtain the coefficient of variation of spreading uniformity; in, is the spreading amount collected for the i-th time during the monitoring period, is the spreading uniformity collected for the i-th time during the monitoring period, and .
[0021] Through the above technical scheme, this embodiment provides a specific method for the analysis and calculation center to analyze whether the operating state of the spreader is abnormal. Since the operating state of the spreader is mainly related to the accuracy of the amount of soil conditioner spread and the uniformity of the soil conditioner spread, the spreading amount and the spreading uniformity are obtained. The spreading amount can be obtained by monitoring the weight change of the soil conditioner in real time through the installed weight sensor, and the spreading uniformity can be obtained by analyzing the spectral sensor; and affected by a certain accidental factor, such as a high wind speed at a certain moment, uneven spreading may occur. At this time, judging that the operating state of the spreader is abnormal based on uneven spreading may result in misjudgment; therefore, in order to more accurately judge the operating state of the spreader, this embodiment sets a monitoring period ∆T, which can be artificially determined according to actual conditions. Within a monitoring period ∆T, n collections are performed to obtain the spreading amount S and the spreading uniformity E, and according to the changes in the spreading amount and the spreading uniformity, a spreading amount change curve over time is formulated. And the spreading uniformity curve over time , so that through the formula Abnormal evaluation value ,in is the coefficient of variation of spreading amount, and , is the coefficient of variation of spreading uniformity, and , the operating status of the spreader is judged based on the abnormal evaluation value, the formula It is expressed as the fluctuation of the spreading amount during the monitoring period. The larger its value is, the greater the fluctuation of the spreading amount in each monitoring is, which means that the possibility of abnormal operation of the spreader is greater. The formula It indicates the difference between the spreading amount and the standard spreading amount during the monitoring period. The larger the value, the greater the difference between the spreading amount and the set standard spreading amount, which indicates that the spreader operation is more likely to be abnormal. Similarly, the formula It is expressed as the fluctuation of spreading uniformity during the monitoring period. The larger its value is, the greater the fluctuation of spreading uniformity during each monitoring is, which means that the possibility of abnormal operation of the spreader is greater. The formula It indicates the change of spreading uniformity during the monitoring period. The larger its value is, the worse the spreading uniformity is, which means the possibility of abnormal operation of the spreader is greater. Therefore, from the formula It can be seen that when the abnormal assessment value The larger the value, the greater the possibility that the spreader is abnormal; so the abnormal evaluation value The abnormal assessment threshold set in the system Compare: When In this way, a comprehensive analysis can be performed based on the spreading amount accuracy, spreading amount fluctuation, spreading uniformity, and spreading uniformity fluctuation during the monitoring period to generate an abnormal evaluation value. Based on the abnormal evaluation value, whether the spreading machine operation state is abnormal can be analyzed to eliminate misjudgment caused by accidental factors, thereby making the monitoring results more accurate.
[0022] In the above technical solution, the standard spreading amount set by the system changes with time The proportional coefficient can be preset according to the actual situation of the spreader operation area. as well as , the abnormal assessment threshold set in the system , It can be determined based on historical data combined with empirical data, which will not be elaborated here.
[0023] As an implementation mode of the present invention, the method for the real-time alarm module to perform an alarm is: When the spreader is in an abnormal state, the abnormal evaluation value will be obtained. Another abnormal assessment threshold set in the system To compare: when When the alarm is triggered, a primary alarm command is generated to remind the operator to check and adjust the operating parameters of the spreader; when When an alarm occurs, a high-level alarm command is generated to stop the spreading operation and repair the spreader.
[0024] Through the above technical solution, this embodiment provides a method for the real-time alarm module to alarm. First, the alarm is divided into primary alarm instructions and advanced alarm instructions. When the spreader is abnormal, the risk of abnormality is not high, so a primary alarm instruction is generated to remind the operator to check and adjust the operating parameters of the spreader and conduct continuous monitoring; When the spreader is judged to be abnormal, it is judged that the spreader operation status is seriously abnormal. In order to ensure the spreading quality, the spreading operation needs to be stopped. Then, a high-level alarm instruction is generated to stop the spreading operation and repair the spreader. In this way, the corresponding alarm instruction can be generated according to the size of the abnormal evaluation value to remind the operator to handle the spreader accordingly, so as to better manage and maintain the spreader.
[0025] As an embodiment of the present invention, the method in which the early warning analysis module performs early warning analysis on the potential abnormal risk of the spreader operation state is: By formula Derive risk warning values; The risk warning value obtained The risk warning threshold preset in the system To compare: when When the spreader is running, it is judged that there is a potential abnormal risk; Otherwise, it is judged that the spreader is operating normally; in, as well as is the preset scale factor, is the current risk factor, is the historical risk factor; The current risk factor The acquisition method is: when the spreader is in normal operation, set a large cycle, and obtain the abnormal evaluation values obtained in m monitoring cycles ∆T in the large cycle, so as to formulate the abnormal evaluation value change curve over time. ; By formula Get the current risk factor ; in, is the start time of the big cycle, is the end time of the big cycle, This is the time-varying curve of the standard abnormality assessment value preset by the system. For a large cycle The maximum value of is the maximum abnormal assessment value within a large cycle, It is the minimum abnormal assessment value within a large cycle; The historical risk factor The acquisition method is: in the historical database, according to the abnormal evaluation values of the spreader in the last two operations, a time curve of abnormal evaluation values in the two operations is drawn up; A rectangular coordinate system is established with time as the x-axis and the abnormal assessment value as the y-axis. The proposed curve is brought into the rectangular coordinate system and compared with the respective preset threshold curves. In the rectangular coordinate system, the area below the proposed curve and above the respective preset threshold curves is recorded as , ; By formula Deriving the historical risk factor ; in, as well as It is the average abnormal evaluation value of the spreader during the last two operations.
[0026] Through the above technical solution, this embodiment provides a method for the early warning analysis module to perform early warning analysis on the potential abnormal risks of the spreader operation state, and conducts a comprehensive analysis in combination with the historical operation data and the current operation data. First, the current risk coefficient is obtained. When the spreader operation state is normal, a large cycle is set. The large cycle time is determined manually according to the actual situation, and the abnormal assessment values obtained in m monitoring cycles ∆T are obtained in the large cycle, so as to formulate a curve of abnormal assessment value change over time. , and by the formula Get the current risk factor ; Since the set abnormality assessment threshold is a fixed value, only when it exceeds the threshold can the spreader operation status be judged to be abnormal. However, if the obtained abnormality assessment value does not exceed the set threshold, but its value continues to increase, or is always near the threshold, it means that the spreader may have a greater risk of abnormal operation. Therefore, the formula It represents the cumulative change between the abnormal evaluation value generated in a large cycle and the standard abnormal evaluation value. The larger the value, the greater the risk of abnormal operation of the spreader. The formula Indicates that within a large cycle The maximum value of is, when its value is larger, it means that the abnormal evaluation value changes more in the large cycle, and the formula It indicates the difference between the maximum abnormal assessment value and the minimum assessment value in the large cycle. The larger the value, the greater the change span of the abnormal assessment value in the large cycle. Therefore, the formula The larger the value, the greater the risk of potential abnormal operation of the spreader. However, the current operation data alone is not accurate enough. Therefore, in the historical database, two operations are planned based on the abnormal evaluation values of the spreader during the last two operations (the two operations are recorded as as well as ,and The abnormal evaluation value of the most recent operation) is plotted over time, and a rectangular coordinate system is established with time as the x-axis and the abnormal evaluation value as the y-axis. The proposed curve is brought into the rectangular coordinate system and compared with the respective preset threshold curves. In the rectangular coordinate system, the area below the proposed curve and above the respective preset threshold curves is recorded as , , through the formula Deriving the historical risk factor ,in as well as is the average abnormal evaluation value of the spreader during the last two operations; from the formula, it can be seen that when as well as The larger the value, the larger the abnormal evaluation value generated when the spreader is operating twice, indicating that the risk of potential abnormal operation of the spreader is greater; therefore, the historical risk coefficient is obtained. Then, through the formula The risk warning value is obtained. The risk warning threshold preset in the system Compare: When If the abnormality is detected, it is judged that there is a potential abnormal risk in the operation of the spreader; otherwise, it is judged that the operation of the spreader is normal. In this way, a comprehensive analysis can be performed based on the changes in the abnormal evaluation value obtained and the changes in the spreading amount and spreading uniformity in the historical data to conduct an early warning analysis of the potential abnormal risks in the operation of the spreader. In this way, the potential abnormal operation of the spreader can be discovered early and handled accordingly, which can reduce the occurrence of abnormal operation during subsequent spreader operations and effectively ensure the efficiency of the operation.
[0027] In the above technical solution, the preset proportionality coefficient as well as , risk warning thresholds preset in the system It can be determined based on historical data and empirical data, so I will not go into details here.
[0028] In addition, the calculation formulas and parameters involved in the calculations in the present invention are all dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.
[0029] In one embodiment, a method for monitoring the operating status of a soil conditioner spreader is disclosed. The monitoring method is performed by the above-mentioned soil conditioner spreader operating status monitoring system. Figure 2 As shown, the monitoring method mainly includes the following steps: Step 1: Real-time acquisition of parameter information such as spreading amount and spreading uniformity of the spreader during spreading operation; Step 2: Analyze and calculate the acquired parameter information to generate an abnormal evaluation value, thereby judging whether the operating state of the spreader is abnormal according to the abnormal evaluation value; Step 3: When the spreader is in an abnormal operating state, a corresponding alarm instruction is generated to give an alarm reminder; Step 4: When there is no abnormality in the operation status of the spreader, a comprehensive analysis is performed based on the currently generated abnormal assessment value and the abnormal assessment value in the historical database to conduct an early warning analysis of the potential abnormal risk of the spreader operation status and issue a corresponding early warning.
[0030] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.
Claims
1. A soil conditioner spreader operation status monitoring system, characterized in that: The monitoring system comprises: A spreading monitoring module, which is used to obtain parameter information such as spreading amount and spreading uniformity of the spreader during spreading operation; An analysis and calculation center, the analysis and calculation center is used to perform analysis and calculation according to the acquired parameter information, thereby generating an abnormal evaluation value, and analyzing whether the operating state of the spreader is abnormal according to the abnormal evaluation value; A real-time alarm module, when the spreader is in an abnormal state, the real-time alarm module generates a corresponding alarm instruction to give an alarm reminder; The early warning analysis module performs early warning analysis on potential abnormal risks of the spreader's operating status in combination with historical data when the spreader's operating status is normal, thereby issuing corresponding early warnings.
2. A soil conditioner spreader operation status monitoring system according to claim 1, characterized in that: The method by which the analysis and calculation center analyzes whether the operation state of the spreader is abnormal according to the abnormal evaluation value is as follows: In a monitoring period ∆T, n data are collected to obtain the spreading amount S and spreading uniformity E, and a spreading amount change curve over time is drawn up based on the changes in spreading amount and spreading uniformity. And the spreading uniformity curve over time ; By formula Abnormal evaluation value ; The abnormal assessment value obtained The abnormal assessment threshold set in the system To compare: when When the spreader is in abnormal operation state, in, as well as is the preset scale factor, is the start time of the monitoring period, is the end time of the monitoring period, The time-varying curve of the standard spreading amount set for the system. is the coefficient of variation of spreading amount, is the coefficient of variation of spreading uniformity.
3. A soil conditioner spreader operation status monitoring system according to claim 2, characterized in that: The coefficient of variation of the spreading amount And the coefficient of variation of spreading uniformity The method to obtain it is: By formula Get the coefficient of variation of the spreading amount , through the formula Get the coefficient of variation of spreading uniformity ; in, is the spreading amount collected for the i-th time during the monitoring period, is the spreading uniformity collected for the i-th time during the monitoring period, and .
4. A soil conditioner spreader operation status monitoring system according to claim 3, characterized in that: The method for the real-time alarm module to perform an alarm reminder is: When the spreader is in an abnormal state, the abnormal evaluation value will be obtained. Another abnormal assessment threshold set in the system To compare: when When the alarm is triggered, a primary alarm command is generated to remind the operator to check and adjust the operating parameters of the spreader; when When an alarm occurs, a high-level alarm command is generated to stop the spreading operation and repair the spreader.
5. The soil conditioner spreader operation status monitoring system according to claim 2, characterized in that: The method for the early warning analysis module to perform early warning analysis on the potential abnormal risk of the spreader operation state is: By formula Derive risk warning values; The risk warning value obtained The risk warning threshold preset in the system To compare: when When the spreader is running, it is judged that there is a potential abnormal risk; Otherwise, it is judged that the spreader is operating normally; in, as well as is the preset scale factor, is the current risk factor, is the historical risk factor.
6. A soil conditioner spreader operation status monitoring system according to claim 5, characterized in that: The current risk factor The method to obtain it is: When the spreader is in normal operation, a large cycle is set, and the abnormal evaluation values obtained in m monitoring cycles ∆T are obtained in the large cycle, so as to formulate the abnormal evaluation value change curve over time. ; By formula Get the current risk factor ; in, is the start time of the big cycle, is the end time of the big cycle, This is the time-varying curve of the standard abnormality assessment value preset by the system. For a large cycle The maximum value of is the maximum abnormal assessment value within a large cycle, It is the minimum abnormal assessment value within a large period.
7. The soil conditioner spreader operation status monitoring system according to claim 5, characterized in that: The historical risk factor The method to obtain it is: In the historical database, according to the abnormal evaluation values of the spreader during the two most recent operations, a time curve of abnormal evaluation values during the two operations is drawn up; A rectangular coordinate system is established with time as the x-axis and the abnormal assessment value as the y-axis. The proposed curve is brought into the rectangular coordinate system and compared with the respective preset threshold curves. In the rectangular coordinate system, the area below the proposed curve and above the respective preset threshold curves is recorded as , ; By formula Deriving the historical risk factor ; in, as well as It is the average abnormal evaluation value of the spreader during the last two operations.
8. A method for monitoring the operating status of a soil conditioner spreader, characterized in that: The monitoring method is performed by the soil conditioner spreader operation status monitoring system described in any one of claims 1 to 7.