Crop transportation and storage intelligent control system

Abstract

The invention discloses an intelligent control system for crop transportation and storage, and belongs to the technical field of transportation and storage control. Data analysis is carried out on the grain weight supervision processing sequences of the processing combinations corresponding to different target crops from the grain weight dimension to obtain corresponding grain weight supervision states. Respectively performing data analysis on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the processing combination corresponding to the target crops with different grain quality dimensions to obtain a corresponding grain quality supervision state; performing overall-dimension overall supervision state digital processing and analysis on different target crops by using early-stage different-dimension local supervision analysis data, and adaptively performing targeted supervision rectification on different links of the different target crops according to an analysis result; the technical problems of poor local supervision effect and poor self-adaptive dynamic control effect of different dimensions of crop transportation and storage in the existing scheme can be solved.

Description

Technical Field

[0001] The invention relates to the technical field of transportation and storage control, and in particular to an intelligent control system for transportation and storage of crops. Background Art

[0002] The transportation and storage of crops are important components of agricultural production and supply chain management, involving the entire process of ensuring the safe and efficient transfer of crops from the fields to the hands of consumers. These two aspects are crucial to maintaining the quality of agricultural products, reducing losses and ensuring food safety.

[0003] Existing grain crop transportation and storage solutions face multiple challenges, and there are also some areas that need improvement. When implementing existing grain crop transportation and storage solutions, most of them still rely on Internet of Things technology to monitor the entire process of grain crop transportation and storage, as well as to conduct data statistics and storage. They are unable to implement local and overall regulatory assessments of different dimensions for abnormalities in the grain crop transportation and storage process, and are unable to adaptively and dynamically control the grain crop transportation and storage process based on different assessment results, resulting in poor local regulatory effects in different dimensions of crop transportation and storage and poor adaptive dynamic control effects. Summary of the invention

[0004] The object of the present invention is to provide an intelligent control system for crop transportation and storage, which is used to solve the technical problems of poor local supervision in different dimensions of crop transportation and storage and poor adaptive dynamic control in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent control system for crop transportation and storage, comprising:

[0007] The crop transportation and storage supervision and processing module is used to monitor and collect data on the transportation and storage links of different target crops, and to perform digital processing and monitoring status analysis on the data monitored and collected in different links in different dimensions, so as to obtain the first supervision and processing data and the second supervision and processing data of different dimensions corresponding to different target crops and upload them to the transportation and storage control platform in real time;

[0008] Among them, according to the first grain monitoring weight and the second grain monitoring weight obtained by monitoring the transportation link and the storage link of the target crop, the grain weight supervision status of the transportation link and the storage link corresponding to different target crops is digitally processed and combined respectively to obtain the first supervision processing data corresponding to the different target crops;

[0009] Also, monitoring and obtaining internal temperature distribution diagrams of grain piles corresponding to the transportation link and storage link of different target crops, and digitally processing and combining the monitoring temperature values ​​corresponding to different monitoring points in the internal temperature distribution diagrams of different links to obtain the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding links;

[0010] Perform data analysis on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence to obtain a normal quality supervision label or an abnormal quality supervision label corresponding to the grain quality dimension of the target crop;

[0011] The first grain quality supervision processing sequence and the second grain quality supervision processing sequence corresponding to the target crop are analyzed and the obtained normal quality supervision label or abnormal quality supervision label are obtained to obtain the second supervision processing data corresponding to the target crop;

[0012] The crop transportation and storage supervision and control module is used to integrate and calculate the local abnormal supervision data obtained from different dimensions of the transportation and storage links corresponding to different target crops, and to analyze the overall supervision status in the overall dimension, and to adaptively implement targeted optimization control on the transportation and storage links corresponding to the target crops based on the overall supervision status analysis results in the overall dimension.

[0013] Preferably, target crops for different transportation and storage are numbered and marked as i, i={1, 2, 3, ..., N}; N is a positive integer;

[0014] Obtain the initial weight LZi of grain before the transportation of different target crops, as well as the first grain monitoring weight LJi1 and the second grain monitoring weight LJi2 corresponding to the transportation and storage stages of different target crops;

[0015] When processing and analyzing the grain weight supervision status of the transportation link and the storage link corresponding to different target crops according to the first grain monitoring weight and the second grain monitoring weight obtained by monitoring, the first grain monitoring weight and the second grain monitoring weight corresponding to the different target crops are input into the grain weight monitoring identification function for data analysis, and the grain weight supervision identification ZJik corresponding to the transportation link and the storage link is output;

[0016] The food weight supervision marks corresponding to the transportation and storage stages all contain values ​​of 0 or 1;

[0017] A grain weight supervision mark with a value of 0 indicates that the grain weight monitoring status of the corresponding link is normal;

[0018] A grain weight supervision mark with a value of 1 indicates that the grain weight monitoring status of the corresponding link is abnormal;

[0019] The grain weight supervision identifications obtained from the transportation and storage stages of the target crops are sorted and combined to obtain a grain weight supervision processing sequence.

[0020] Preferably, the expression of the grain weight monitoring identification function is: ; In the formula, k=1, 2, representing different links; LJik is LJi1, LJi2; Wik is Wi1, Wi2, which are the standard error of transportation weight and standard error of storage weight corresponding to the transportation link and storage link of different target crops respectively.

[0021] Preferably, when data analysis is performed on the grain weight supervision processing sequence to determine the local supervision status of the grain weight dimension corresponding to the target crop;

[0022] Conduct traversal analysis on grain weight supervision processing sequence;

[0023] If the values ​​of the elements in the grain weight supervision processing sequence are all 0, a normal weight supervision label is generated and the target crop is associated with a normal grain weight supervision status label;

[0024] If there is an element with a value of 1 in the grain weight supervision processing sequence, a weight supervision abnormality label is generated and the target crop is associated with a mark indicating that the grain weight supervision status is abnormal.

[0025] Preferably, the internal temperature distribution diagrams of grain stacks corresponding to the transportation link and the storage link of different target crops are monitored and obtained, and the monitoring temperature values ​​corresponding to different monitoring points in the internal temperature distribution diagrams of different links are obtained; the monitoring temperature values ​​of the monitoring points corresponding to different links are sorted and combined respectively to obtain the monitoring temperature sequence [wjk] of the corresponding link; wherein j is the different monitoring points in the internal temperature distribution diagram, j={1, 2, 3, ..., m}; m is a positive integer; [wj1] and [wj2] are the monitoring temperature sequences corresponding to the grain stacks in the transportation link and the storage link, respectively;

[0026] When performing data analysis on the grain quality supervision status corresponding to different target crops according to the monitoring temperature sequence of grain stacking in the transportation link and storage link, all element values ​​of the monitoring temperature sequence of grain stacking in the transportation link and storage link corresponding to different target crops are sequentially analyzed through the grain quality monitoring identification function, and the grain quality supervision identification ZBjk corresponding to different elements in the monitoring temperature sequence is output;

[0027] Grain quality control labels contain values ​​of 0 or 1;

[0028] A grain quality supervision mark with a value of 0 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is normal;

[0029] A grain quality supervision mark with a value of 1 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is abnormal;

[0030] Different grain quality supervision identifications obtained by processing the monitoring temperature sequence of grain stacks in the transportation and storage links of the target crops are sorted and combined respectively to obtain the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding links.

[0031] Preferably, the expression of the food quality monitoring identification function is: ; In the formula, Ujk is Uj1 and Uj2, which are the monitoring temperature standard ranges corresponding to different monitoring points of grain stacking in the transportation link and storage link of the target crops.

[0032] Preferably, when data analysis is performed on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence to determine the local supervision status of the corresponding grain quality dimension of the target crops;

[0033] If the values ​​of the elements in the first grain quality supervision processing sequence and the second grain quality supervision processing sequence are both 0, a normal quality supervision label is generated and the target crop is associated with a normal grain quality supervision status label;

[0034] If there is an element with a value of 1 in the first grain quality supervision processing sequence and / or the second grain quality supervision processing sequence, a quality supervision abnormality label is generated and a mark indicating an abnormal grain quality supervision status is associated with the target crop.

[0035] Preferably, the identities of the target crops are dynamically marked according to the first supervision processing data and the second supervision processing data corresponding to different target crops;

[0036] If there are no weight supervision abnormality labels and quality supervision abnormality labels in the first supervision processing data and the second supervision processing data, an overall normal label is generated and the target crop is marked as a regular target crop;

[0037] Otherwise, an overall abnormal label is generated and the target crop is marked as a special target crop.

[0038] Preferably, the total number of weight supervision anomalies N1 and the total number of quality supervision anomalies N2 corresponding to all special target crops are counted, and the overall supervision formula is used Calculate and obtain the overall abnormality Zy corresponding to all special target crops; where α and β are different weight coefficients, 0<α<β; N is the total number of transportation and storage of all target crops under supervision.

[0039] Preferably, when analyzing the overall abnormality to determine the overall supervision status of the overall dimension, the overall abnormal status formula is used. Calculate and analyze the overall abnormal state identification Zb corresponding to all special target crops; where A is the overall abnormal state standard value; [x] is the rounding function, indicating that the largest integer not exceeding the real number x is called the integer part of x;

[0040] If the overall abnormal status indicator is 0, an overall mild abnormal status is generated and prompted;

[0041] If the overall abnormal status flag is not 0, an overall severe abnormal status will be generated and a prompt will be given. At the same time, the transportation and storage links of subsequent target crops will be controlled to implement comprehensive supervision and rectification.

[0042] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0043] The present invention obtains the grain weight supervision status corresponding to different target crops by performing data analysis on the grain weight supervision processing sequence of the corresponding processing combinations of different target crops from the grain weight dimension. At the same time, it can also provide reliable local grain weight analysis data support for the subsequent overall supervision status analysis of all abnormal target crops corresponding to the overall dimension.

[0044] The present invention obtains the grain quality supervision status corresponding to different target crops by performing data analysis on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding processing combinations of different target crops in the grain quality dimension respectively, and can also provide reliable local grain quality analysis data support for the overall supervision status analysis of the overall dimension corresponding to all subsequent abnormal target crops.

[0045] The present invention utilizes local supervision analysis data of different dimensions in the early stage to dynamically analyze and mark the identities of different target crops, and digitally processes and analyzes the overall supervision status of all special target crops obtained through analysis, and adaptively implements targeted supervision and rectification for different links of different target crops according to the analysis results, thereby improving the local supervision effect and adaptive dynamic control effect in different dimensions of crop transportation and storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described below in conjunction with the accompanying drawings.

[0047] Figure 1 This is a module block diagram of an intelligent control system for crop transportation and storage according to the present invention.

[0048] Figure 2 The present invention is a flowchart of the steps of implementing an intelligent control system for crop transportation and storage.

[0049] Figure 3 A flowchart of the steps for determining the local supervision status of grain weight dimensions corresponding to different target crops in the present invention.

[0050] Figure 4 This is a flowchart of the steps for determining the local supervision status of the food quality dimension corresponding to the target crop in the present invention.

[0051] Figure 5 This is a flowchart of the steps for dynamically marking the identities of different target crops in the present invention. DETAILED DESCRIPTION

[0052] 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.

[0053] like Figure 1 to Figure 2 As shown, the present invention is an intelligent control system for crop transportation and storage, comprising a transportation and storage control platform, and a crop transportation and storage supervision processing module and a crop transportation and storage supervision control module which are communicatively connected to the transportation and storage control platform;

[0054] The crop transportation and storage supervision and processing module is used to monitor and collect data for the transportation and storage links of different target crops, and to perform digital processing and monitoring status analysis on the data monitored and collected in different links in different dimensions, so as to obtain the first supervision and processing data and the second supervision and processing data corresponding to different dimensions of different target crops and upload them to the transportation and storage control platform in real time; it includes:

[0055] The target crops for different transportation and storage are numbered and marked as i, i={1, 2, 3, ..., N}; N is a positive integer, representing the total number of target crops for transportation and storage;

[0056] The crop may specifically be rice; the target crop is a truckload of rice transported by a transport vehicle;

[0057] Obtain the initial weight LZi of grain before the transportation of different target crops, as well as the first grain monitoring weight LJi1 and the second grain monitoring weight LJi2 corresponding to the transportation and storage stages of different target crops;

[0058] It should be noted that there is a loss of grain weight in both the transportation and storage stages of target crops, and the existing regulations stipulate that the maximum single grain loss is generally no more than 0.05%; in the embodiment of the present invention, by statistically analyzing and processing the corresponding grain weight monitoring data before the start of transportation of different target crops and after the transportation and storage stages, reliable data support can be provided for the subsequent analysis of the grain weight supervision status of different target crops at different stages; in addition, the monitoring of the grain weight corresponding to different target crops can be achieved by weighing based on the existing weighbridge;

[0059] When processing and analyzing the grain weight supervision status of the transportation link and the storage link corresponding to different target crops according to the first grain monitoring weight and the second grain monitoring weight obtained by monitoring, the first grain monitoring weight and the second grain monitoring weight corresponding to the different target crops are input into the grain weight monitoring identification function for data analysis, and the grain weight supervision identification ZJik corresponding to the transportation link and the storage link is output;

[0060] Among them, the expression of the grain weight monitoring identification function is: ; In the formula, k=1, 2, representing different links; LJik is LJi1, LJi2; Wik is Wi1, Wi2, which are the standard errors of transportation weight and storage weight corresponding to the transportation link and storage link of different target crops, respectively, which can be determined based on the existing transportation and storage data;

[0061] It should be noted that the grain weight supervision mark is used to calculate and digitally represent the corresponding grain weight supervision status of different target crops after different links;

[0062] The food weight supervision marks corresponding to the transportation and storage stages all contain values ​​of 0 or 1;

[0063] A grain weight supervision mark with a value of 0 indicates that the grain weight monitoring status of the corresponding link is normal;

[0064] A grain weight supervision mark with a value of 1 indicates that the grain weight monitoring status of the corresponding link is abnormal;

[0065] The grain weight supervision marks obtained from the transportation and storage stages of the target crops are sorted and combined to obtain a grain weight supervision processing sequence;

[0066] In the embodiment of the present invention, by processing, calculating and combining the grain weight monitoring data of different links corresponding to different target crops, the grain weight supervision processing sequence corresponding to different target crops is obtained, which realizes the monitoring and processing of grain weight dimension data, and can also provide reliable data support for the subsequent local supervision status analysis of grain weight dimensions corresponding to different target crops;

[0067] like Figure 3 As shown, when data analysis is performed on the grain weight supervision processing sequence to determine the local supervision status of the target crops corresponding to the grain weight dimension;

[0068] Conduct traversal analysis on grain weight supervision processing sequence;

[0069] If the values ​​of the elements in the grain weight supervision processing sequence are all 0, a normal weight supervision label is generated and the target crop is associated with a normal grain weight supervision status label;

[0070] If there is an element with a value of 1 in the grain weight supervision processing sequence, a weight supervision abnormality label is generated and the target crop is associated with a grain weight supervision abnormality label;

[0071] The grain weight supervision processing sequence corresponding to the target crop and the normal weight supervision label or abnormal weight supervision label obtained by analysis are sorted and combined to obtain the first supervision processing data corresponding to the target crop;

[0072] In an embodiment of the present invention, by performing data analysis on the grain weight supervision processing sequence of the corresponding processing combinations of different target crops from the grain weight dimension, the grain weight supervision status corresponding to the different target crops is obtained. At the same time, reliable local grain weight analysis data support can also be provided for the subsequent overall supervision status analysis of all abnormal target crops corresponding to the overall dimension.

[0073] And, monitor and obtain the internal temperature distribution diagrams of grain stacks in the transportation link and storage link corresponding to different target crops, and obtain the monitoring temperature values ​​corresponding to different monitoring points in the internal temperature distribution diagrams of different links; sort and combine the monitoring temperature values ​​of the monitoring points corresponding to different links respectively, and obtain the monitoring temperature sequence [wjk] of the corresponding link; wherein j is the different monitoring points in the internal temperature distribution diagram, j={1, 2, 3, ..., m}; m is a positive integer, representing the total number of all monitoring points in the internal temperature distribution diagram; [wj1] and [wj2] are the monitoring temperature sequences corresponding to the grain stacks in the transportation link and the storage link respectively;

[0074] It should be noted that infrared imaging technology can detect the temperature distribution inside the grain stack, and abnormal hot spots may be signs of mildew or insect pests; the acquisition of the internal temperature distribution map of the grain stack corresponding to the transportation link and storage link of the target crop is achieved through existing conventional technical means, for example, infrared thermal imaging technology is used to detect the temperature distribution of different preset monitoring points inside the grain stack, and the temperature distribution of different preset monitoring points is processed to obtain the corresponding internal temperature distribution map. The specific data processing steps are not repeated here;

[0075] In addition, the positions of all preset monitoring points corresponding to the grain stacks in the transportation and storage stages of the target crops are the same; the setting of different preset monitoring points inside the grain stack can be based on the hot spots or problem areas found in previous monitoring as monitoring points; monitoring points are set at different heights and directions of the grain stack; additional monitoring points are set at the center and bottom of the stack where heat is likely to accumulate, and the setting of other monitoring points can be customized according to the actual application scenario;

[0076] When performing data analysis on the grain quality supervision status corresponding to different target crops according to the monitoring temperature sequence of grain stacking in the transportation link and storage link, all element values ​​of the monitoring temperature sequence of grain stacking in the transportation link and storage link corresponding to different target crops are sequentially analyzed through the grain quality monitoring identification function, and the grain quality supervision identification ZBjk corresponding to different elements in the monitoring temperature sequence is output;

[0077] Among them, the expression of the grain quality monitoring identification function is: ; In the formula, Ujk is Uj1 and Uj2, which are the standard ranges of monitoring temperature corresponding to different monitoring points of grain stacking in the transportation link and storage link of the target crop, respectively. The standard ranges of monitoring temperature corresponding to different monitoring points can be determined based on the actual ambient temperature and the surface temperature of the grain stacking, or based on the monitoring test temperature range corresponding to the same monitoring point in history;

[0078] It should be noted that the grain quality supervision mark is used to calculate and digitally represent the grain quality supervision status of grain stacks corresponding to different target crops at different stages;

[0079] Grain quality control labels contain values ​​of 0 or 1;

[0080] A grain quality supervision mark with a value of 0 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is normal;

[0081] A grain quality supervision mark with a value of 1 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is abnormal;

[0082] The different grain quality supervision marks obtained by processing the monitoring temperature sequence of grain stacks in the transportation link and the storage link of the target crops are sorted and combined respectively to obtain the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding link;

[0083] In the embodiment of the present invention, by processing, calculating and combining the grain quality monitoring data of different links corresponding to different target crops, a first grain quality supervision processing sequence and a second grain quality supervision processing sequence corresponding to different target crops are obtained, which realizes the monitoring and processing of grain quality dimension data and can also provide reliable data support for the subsequent local supervision status analysis of grain quality dimensions corresponding to different target crops;

[0084] like Figure 4 As shown, when data analysis is performed on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence to determine the local supervision status of the grain quality dimension corresponding to the target crops;

[0085] If the values ​​of the elements in the first grain quality supervision processing sequence and the second grain quality supervision processing sequence are both 0, a normal quality supervision label is generated and the target crop is associated with a normal grain quality supervision status label;

[0086] If there is an element with a value of 1 in the first grain quality supervision processing sequence and / or the second grain quality supervision processing sequence, a quality supervision abnormality label is generated and a mark of abnormal grain quality supervision status is associated with the target crop;

[0087] The first grain quality supervision processing sequence and the second grain quality supervision processing sequence corresponding to the target crop are analyzed and the obtained normal quality supervision label or abnormal quality supervision label are obtained to obtain the second supervision processing data corresponding to the target crop;

[0088] In an embodiment of the present invention, data analysis is performed separately on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence corresponding to the processing combinations of target crops in different grain quality dimensions, so as to obtain the grain quality supervision status corresponding to different target crops, and at the same time, provide reliable local grain quality analysis data support for the subsequent overall supervision status analysis of all abnormal target crops corresponding to the overall dimension.

[0089] The crop transportation and storage supervision and control module is used to integrate and calculate the local abnormal supervision data obtained from different dimensions of the transportation and storage links of different target crops, and analyze the overall supervision status of the overall dimension, and adaptively implement targeted optimization control on the transportation and storage links of the target crops according to the overall supervision status analysis results of the overall dimension; including:

[0090] like Figure 5 As shown, the identities of the target crops are dynamically marked according to the first supervision processing data and the second supervision processing data corresponding to different target crops;

[0091] If there are no weight supervision abnormality labels and quality supervision abnormality labels in the first supervision processing data and the second supervision processing data, an overall normal label is generated and the target crop is marked as a regular target crop;

[0092] Otherwise, an overall abnormal label is generated and the target crop is marked as a special target crop. The total number of weight supervision abnormalities N1 and quality supervision abnormalities N2 corresponding to all special target crops are counted, and the overall supervision formula is used to calculate the total number of weight supervision abnormalities N1 and quality supervision abnormalities N2. Calculate and obtain the overall abnormality Zy corresponding to all special target crops; where α and β are different weight coefficients, 0<α<β, and the specific value can be determined by the actual design requirement data of the actual application scenario. The specific value is not limited, and the condition requirements corresponding to the weight coefficient can be met; N is the total number of all target crops transported and stored under supervision;

[0093] It should be noted that the overall abnormality degree is used to integrate and calculate all abnormal supervision data corresponding to different special target crops to digitally represent the overall supervision status corresponding to different special target crops from an overall dimension;

[0094] When analyzing the overall abnormality to determine the overall supervision status of the overall dimension, the overall abnormal status formula is used Calculate and obtain the overall abnormal state identification Zb corresponding to all special target crops and analyze it; where A is the overall abnormal state standard value, which can be determined based on the overall design requirement data for transportation and storage of existing crops; [] is the rounding function;

[0095] If the overall abnormal state indicator is 0, an overall mild abnormal state is generated and prompted; no specific control measures are required here;

[0096] If the overall abnormal status flag is not 0, an overall severe abnormal status will be generated and prompted, and the transportation and storage links of subsequent target crops will be controlled to implement comprehensive supervision and rectification;

[0097] Among them, comprehensive supervision and rectification are implemented in the transportation and storage links, including the optimization of supervision measures in different links in terms of grain weight and grain quality, such as adding supervision measures and preventive measures in different aspects.

[0098] In the embodiment of the present invention, the local supervision analysis data of different dimensions in the early stage are used to dynamically analyze and mark the identities of different target crops, and the overall supervision status of all special target crops obtained by the analysis is digitally processed and analyzed in the overall dimension, and targeted supervision rectification is adaptively implemented for different links of different target crops according to the analysis results, thereby improving the local supervision effect and adaptive dynamic control effect of different dimensions of crop transportation and storage.

[0099] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0100] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0101] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0103] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent control system for crop transportation and storage, characterized in that: include: The crop transportation and storage supervision and processing module is used to monitor and collect data on the transportation and storage links of different target crops, and to perform digital processing and monitoring status analysis on the data monitored and collected in different links in different dimensions, so as to obtain the first supervision and processing data and the second supervision and processing data of different dimensions corresponding to different target crops and upload them to the transportation and storage control platform in real time; Among them, according to the first grain monitoring weight and the second grain monitoring weight obtained by monitoring the transportation link and the storage link of the target crop, the grain weight supervision status of the transportation link and the storage link corresponding to different target crops is digitally processed and combined respectively to obtain the first supervision processing data corresponding to the different target crops; Also, monitoring and obtaining internal temperature distribution diagrams of grain piles corresponding to the transportation link and storage link of different target crops, and digitally processing and combining the monitoring temperature values ​​corresponding to different monitoring points in the internal temperature distribution diagrams of different links to obtain the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding links; Perform data analysis on the first grain quality supervision processing sequence and the second grain quality supervision processing sequence to obtain a normal quality supervision label or an abnormal quality supervision label corresponding to the grain quality dimension of the target crop; The first grain quality supervision processing sequence and the second grain quality supervision processing sequence corresponding to the target crop are analyzed and the obtained normal quality supervision label or abnormal quality supervision label are obtained to obtain the second supervision processing data corresponding to the target crop; The crop transportation and storage supervision and control module is used to integrate and calculate the local abnormal supervision data obtained from different dimensions of the transportation and storage links corresponding to different target crops, and to analyze the overall supervision status in the overall dimension, and to adaptively implement targeted optimization control on the transportation and storage links corresponding to the target crops based on the overall supervision status analysis results in the overall dimension.

2. The intelligent control system for crop transportation and storage according to claim 1 is characterized in that: The target crops for different transportation and storage are numbered and marked as i, i={1, 2, 3, ..., N}; N is a positive integer; Obtain the initial weight LZi of grain before the transportation of different target crops, as well as the first grain monitoring weight LJi1 and the second grain monitoring weight LJi2 corresponding to the transportation and storage stages of different target crops; When processing and analyzing the grain weight supervision status of the transportation link and the storage link corresponding to different target crops according to the first grain monitoring weight and the second grain monitoring weight obtained by monitoring, the first grain monitoring weight and the second grain monitoring weight corresponding to the different target crops are input into the grain weight monitoring identification function for data analysis, and the grain weight supervision identification ZJik corresponding to the transportation link and the storage link is output; The food weight supervision marks corresponding to the transportation and storage stages all contain values ​​of 0 or 1; A grain weight supervision mark with a value of 0 indicates that the grain weight monitoring status of the corresponding link is normal; A grain weight supervision mark with a value of 1 indicates that the grain weight monitoring status of the corresponding link is abnormal; The grain weight supervision identifications obtained from the transportation and storage stages of the target crops are sorted and combined to obtain a grain weight supervision processing sequence.

3. The intelligent control system for crop transportation and storage according to claim 2 is characterized in that: The expression of the grain weight monitoring identification function is: ; In the formula, k=1, 2, representing different links; LJik is LJi1, LJi2; Wik is Wi1 and Wi2, which are the standard error of transportation weight and storage weight of different target crops in the corresponding transportation link and storage link respectively.

4. The intelligent control system for crop transportation and storage according to claim 2 is characterized in that: When data analysis is performed on the grain weight supervision processing sequence to determine the local supervision status of the target crops corresponding to the grain weight dimension; Conduct traversal analysis on grain weight supervision processing sequence; If the values ​​of the elements in the grain weight supervision processing sequence are all 0, a normal weight supervision label is generated and the target crop is associated with a normal grain weight supervision status label; If there is an element with a value of 1 in the grain weight supervision processing sequence, a weight supervision abnormality label is generated and the target crop is associated with a mark indicating that the grain weight supervision status is abnormal.

5. The intelligent control system for crop transportation and storage according to claim 4 is characterized in that: Monitor and obtain the internal temperature distribution diagrams of grain stacks in the transportation link and storage link corresponding to different target crops, and obtain the monitoring temperature values ​​corresponding to different monitoring points in the internal temperature distribution diagrams of different links; sort and combine the monitoring temperature values ​​of the corresponding monitoring points in different links to obtain the monitoring temperature sequence [wjk] of the corresponding link; where j is the different monitoring points in the internal temperature distribution diagram, j={1, 2, 3, ..., m}; m is a positive integer; [wj1] and [wj2] are the monitoring temperature sequences corresponding to the grain stacks in the transportation link and the storage link, respectively; When performing data analysis on the grain quality supervision status corresponding to different target crops according to the monitoring temperature sequence of grain stacking in the transportation link and storage link, all element values ​​of the monitoring temperature sequence of grain stacking in the transportation link and storage link corresponding to different target crops are sequentially analyzed through the grain quality monitoring identification function, and the grain quality supervision identification ZBjk corresponding to different elements in the monitoring temperature sequence is output; Grain quality control labels contain values ​​of 0 or 1; A grain quality supervision mark with a value of 0 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is normal; A grain quality supervision mark with a value of 1 indicates that the monitoring temperature status of the corresponding monitoring point of the grain stack in the transportation link or storage link of the target crop is abnormal; Different grain quality supervision identifications obtained by processing the monitoring temperature sequence of grain stacks in the transportation and storage links of the target crops are sorted and combined respectively to obtain the first grain quality supervision processing sequence and the second grain quality supervision processing sequence of the corresponding links.

6. The intelligent control system for crop transportation and storage according to claim 5 is characterized in that: The expression of the grain quality monitoring identification function is: ; In the formula, Ujk is Uj1 and Uj2, which are the monitoring temperature standard ranges corresponding to different monitoring points of grain stacking in the transportation link and storage link of the target crops.

7. The intelligent control system for crop transportation and storage according to claim 5 is characterized in that: When the data of the first grain quality supervision processing sequence and the second grain quality supervision processing sequence are analyzed to determine the local supervision status of the grain quality dimension corresponding to the target crops; If the values ​​of the elements in the first grain quality supervision processing sequence and the second grain quality supervision processing sequence are both 0, a normal quality supervision label is generated and the target crop is associated with a normal grain quality supervision status label; If there is an element with a value of 1 in the first grain quality supervision processing sequence and / or the second grain quality supervision processing sequence, a quality supervision abnormality label is generated and a mark indicating an abnormal grain quality supervision status is associated with the target crop.

8. The intelligent control system for crop transportation and storage according to claim 7 is characterized in that: Dynamically marking the identities of the target crops according to the first supervision processing data and the second supervision processing data corresponding to the different target crops; If there are no weight supervision abnormality labels and quality supervision abnormality labels in the first supervision processing data and the second supervision processing data, an overall normal label is generated and the target crop is marked as a regular target crop; Otherwise, an overall abnormal label is generated and the target crop is marked as a special target crop.

9. The intelligent control system for crop transportation and storage according to claim 8, characterized in that: Count the total number of weight supervision anomalies N1 and quality supervision anomalies N2 corresponding to all special target crops, and use the overall supervision formula Calculate and obtain the overall abnormality Zy corresponding to all special target crops; where α and β are different weight coefficients, 0<α<β; N is the total number of transportation and storage of all target crops under supervision.

10. The intelligent control system for crop transportation and storage according to claim 9, characterized in that: When analyzing the overall abnormality to determine the overall supervision status of the overall dimension, the overall abnormal status formula is used Calculate and analyze the overall abnormal state identification Zb corresponding to all special target crops; where A is the standard value of the overall abnormal state; [] is the rounding function; If the overall abnormal status indicator is 0, an overall mild abnormal status is generated and prompted; If the overall abnormal status flag is not 0, an overall severe abnormal status will be generated and a prompt will be given. At the same time, the transportation and storage links of subsequent target crops will be controlled to implement comprehensive supervision and rectification.

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