An intelligent control system based on grain processing

Abstract

The present invention relates to the technical field of grain processing, and in particular to an intelligent control system based on grain processing, comprising a control terminal, a monitoring layer, an analysis layer and an evaluation layer; the control terminal is the main control end of the system, and is used to issue an execution command; the operating state parameters of grain processing equipment and the state parameters of a processing target are collected through the monitoring layer, and whether the operating state of the equipment is normal is determined based on the operating state parameters of the grain processing equipment, and the state parameters of the processing target of the grain processing equipment are stored. The present invention monitors and analyzes the operating state of the grain processing equipment, analyzes the functional soundness of the grain processing equipment, ensures that the grain processing equipment has the grain processing capacity, and collects and analyzes the state parameters of the processed grain, ensures that the processing target grain processed by the grain processing meets the processing conditions, ensures that the process of grain processing by the grain processing equipment is more stable, reliable and safe, and brings guarantee to the grain quality output by the grain processing equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of grain processing, and in particular to an intelligent control system based on grain processing. Background Art

[0002] The grain processing industry is also called the grain milling industry, which refers to the production activities of shelling and grinding rice, wheat, corn, millet, sorghum and other grains into finished grains;

[0003] The invention patent with application number 201910837482.9 discloses a grain processing management system based on intelligent control, which is characterized by comprising a main control center, a grain processing system and a grain storage system, wherein the grain processing system and the grain storage system interact with the main control center through wired or wireless communication, the grain processing system comprises a first sub-control center, a grain processing production line, a lifting and unloading device, a dust removal device and a manual controller, and the grain storage system comprises a second sub-control center, a grain silo and a data acquisition device;

[0004] The main control center communicates and interacts with the first sub-control center and the second sub-control center through wired or wireless communication. The lifting and unloading device is arranged between the equipment of the grain processing production line to control the stable transportation of grain in the grain processing production line. The dust removal device is arranged at the grain processing production line equipment and the lifting and unloading device to perform air suction and dust removal. The manual and automatic controller is connected to the lifting and unloading device and the equipment of the grain processing production line to control the operation of the lifting and unloading device and the equipment of the grain processing production line;

[0005] The data collection equipment includes a temperature collector for collecting grain temperature and granary temperature, a humidity sensor for reflecting grain moisture, a relative humidity sensor for collecting relative humidity of granary air, a gas sensor for detecting corrupt gas, and a weighing device for weighing the granary;

[0006] The application aims to solve the problem that "as grain production increases, the requirements for grain processing and storage are also increasing. The old grain production lines and granary management can no longer fully meet the needs of grain processing management due to their low level of intelligent control and low efficiency."

[0007] However, during the grain processing process, it is affected by many factors such as the grain storage status and the operating status of the grain processing equipment. To a certain extent, the grain storage status will also affect the operating status of the grain processing equipment. The intelligence of current grain processing equipment is mostly concentrated on the degree of intelligent control of each process in the processing process, and does not give much consideration to the risk control of the storage status of the processing target grain and the operating status of the grain processing equipment, which leads to the reduction of the quality of grain processed by the grain processing equipment. Summary of the invention

[0008] In view of the above-mentioned shortcomings of the prior art, the present invention provides an intelligent control system based on grain processing, which solves the technical problems raised in the above-mentioned background technology.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0010] An intelligent control system based on grain processing, comprising: a control terminal, a monitoring layer, an analysis layer and an evaluation layer;

[0011] The control terminal is the main control terminal of the system and is used to issue execution commands;

[0012] The operating status parameters of the grain processing equipment and the status parameters of the processing targets are collected through the monitoring layer. Based on the operating status parameters of the grain processing equipment, it is determined whether the equipment operating status is normal. The status parameters of the grain processing equipment processing targets are stored for real-time reading by the analysis layer. After traversing and reading the processing target status parameters, the analysis layer analyzes the processing suitability and processing quality of the processing target based on the processing target status parameters. The evaluation layer further obtains the processing suitability and processing quality of the processing target analyzed in the analysis layer, and evaluates the grain processing risk in combination with the processing suitability and processing quality of the processing target.

[0013] The analysis layer includes a receiving module, an analyzing module and an identifying module. The receiving module is used to receive the processing target state parameters stored in the monitoring layer. The analyzing module is used to obtain the processing target state parameters received by the receiving module and analyze the processing suitability of the processing target based on the processing target state parameters. The identifying module is used to obtain the processing target state parameters received by the receiving module and identify the processing quality of the processing target based on the processing target state parameters.

[0014] The analysis logic of the processing suitability of the processing target in the analysis module is expressed as:

[0015]

[0016] Where k is the processing suitability of the processing target; u is the set of several groups of sub-images into which the image data of the processing target is divided before processing; sim(v,v+1) is the similarity between the vth group of sub-images and the v+1th group of sub-images; n is the total number of times the processing target is picked up; M i is the processing target weight picked up and put into the silo of the grain processing equipment for the i-th time; M i+1 The target weight of the grains to be picked up and put into the silo of the grain processing equipment for the i+1th time;

[0017] Among them, the larger the processing suitability k of the processing target is, the more suitable the processing target is for processing, and vice versa, the less suitable the processing target is for processing. The similarity of the two groups of sub-images is determined based on the distribution of image color features. The segmentation of the image data before processing the processing target is manually set by the system end user, and the size and shape of the sub-images obtained by segmentation are equal, and the number of sub-images obtained by segmentation is 2. 2 , 3 2 , ..., (x-1) 2 or x 2 Group.

[0018] Furthermore, the monitoring layer includes a collection module, a determination module and a storage module, the collection module is used to collect the operating state parameters of the food processing equipment and the state parameters of the processing target, the determination module is used to receive the operating state parameters of the food processing equipment collected by the collection module, and determine whether the operating state of the food processing equipment is normal based on the operating state parameters of the food processing equipment, and the storage module is used to receive the processing target state parameters collected by the collection module and store the processing target state parameters;

[0019] Among them, the acquisition module is integrated with a sensor module and a camera, and the sensor module is integrated with a temperature sensor, a vibration sensor, a current and voltage sensor, a speed sensor, and a weight sensor. During the operation stage of the acquisition module, the food processing equipment is controlled to run idle, and the operating status parameters of the food processing equipment are collected based on the temperature sensor, vibration sensor, current and voltage sensor, and speed sensor in the sensor module of the acquisition module. After the judgment module determines that the operating status of the equipment is normal based on the operating status parameters of the food processing equipment, the camera and weight sensor further collect image data and weight data of the processing target, and transmit them to the storage module.

[0020] Furthermore, an idle time threshold is set in the collection module. During the operation phase of the collection module, after the grain processing equipment is controlled to run idle, the operation status parameters of the grain processing equipment are collected at a specified time stamp within the idle time threshold;

[0021] Among them, the idle time threshold is not greater than 1min. Each time the system starts running, during the operation phase of the collection module, two groups of timestamps are randomly selected within the idle time threshold as the timestamps for collecting the operating status parameters of the grain processing equipment, and the selected timestamps are subject to the following conditions: the two consecutively selected groups of timestamps are inconsistent, the two selected groups of timestamps are inconsistent with the two groups of timestamps selected during the last system operation, and at least one group of timestamps is inconsistent, and the interval between two consecutive system starts is less than one hour, then the monitoring layer will not perform the collection of the operating status parameters of the grain processing equipment and the determination of whether the operating status is normal.

[0022] Furthermore, after the acquisition module acquires the operating status parameters of the grain processing equipment based on the selected timestamp, the grain processing equipment is controlled to end the idling operation. The determination module stores the threshold of the safe operating status parameters of the grain processing equipment. The determination logic of whether the operating status of the grain processing equipment is normal in the determination module is expressed as follows:

[0023]

[0024] Where: f1, f2 are the judgment values; m min(t,T) is the difference between the collected temperature and the minimum difference between the values ​​contained in the threshold of the safe operation status parameter of the grain processing equipment; m min(p,P) The difference between the collected vibration frequency and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation status of the grain processing equipment; m min(u / i,U / I) The difference between the collected voltage-current ratio and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation state of the grain processing equipment; m min(s,S) is the difference between the acquisition speed and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation status of the grain processing equipment; χ is the correction factor; The difference between the first set of collected temperatures and the second set of collected temperatures collected based on the collection timestamp and the maximum difference value included in the parameter threshold of the safe operation status of the grain processing equipment; The difference between the first group of collected vibration frequencies, the second group of vibration frequencies collected based on the collection timestamp, and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment; The difference between the maximum difference between the first group of collected voltage-current ratios and the second group of collected voltage-current ratios based on the collection timestamp and the values ​​included in the threshold value of the parameter of the safe operation state of the grain processing equipment; The difference between the first group of collected rotation speeds and the second group of rotation speeds collected based on the collection timestamp and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment;

[0025] Among them, t in formula (1) is any group of t1 and t2 in formula (2), p in formula (1) is any group of p1 and p2 in formula (2), u in formula (1) is any group of u1 and u2 in formula (2), i in formula (1) is any group of i1 and i2 in formula (2), s in formula (1) is any group of s1 and s2 in formula (2), t1, t2, p1, p2, u1, u2, i1, i2, s1, s2 all participate in the calculation of formula (1) to determine whether the operating status of the grain processing equipment is normal.

[0026] Furthermore, the correction factor χ takes a value of 1 or -1. When the collected temperature, collected vibration frequency, collected voltage-current ratio and collected speed are not within the parameter threshold of the safe operation state of the grain processing equipment, the correction factor χ takes a value of -1. Otherwise, the correction factor χ takes a value of 1. The judgment value f1≤0 means that the operation state of the grain processing equipment is abnormal. Otherwise, the operation state of the grain processing equipment is normal. The judgment value f2∈[0.95, 1.05] means that the operation state of the grain processing equipment is normal. Otherwise, the operation state of the grain processing equipment is abnormal.

[0027] Among them, when all the judgment results based on formula (1) and formula (2) are that the operation status of the grain processing equipment is normal, the operation status of the grain processing equipment is judged to be normal, otherwise, the operation status of the grain processing equipment is judged to be abnormal. The analysis layer operates when the judgment module determines that the operation status of the grain processing equipment is normal, otherwise, the grain processing equipment is controlled to stop operating.

[0028] Furthermore, the processing target state parameters received by the receiving module include: the weight of the processing target before processing, the image data of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing; the analyzing module analyzes the processing suitability stage of the processing target, and uses the weight of the processing target before processing and the image data of the processing target before processing in the processing target state parameters to analyze the processing suitability of the processing target; the identifying module identifies the processing quality stage of the processing target, and uses the weight of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing to identify the processing quality of the processing target;

[0029] When the grain processing equipment puts the processing target into use for the first time, it picks up processing targets of equal volume from the upper, center and lower positions of the processing target pile and puts them into the silo of the grain processing equipment in turn, and piles them flat in the silo. The processing target state parameters are collected by the weight sensor and camera in the collection module;

[0030] Among them, the three groups of positions for picking up processing targets are on the same spatial straight line.

[0031] Furthermore, the recognition logic of the processing quality of the processing target in the recognition module is expressed as:

[0032]

[0033] Where: γ is the processing quality performance value of the processing target; M out is the weight of the processed target output by the food processing equipment; u′ is the set of several groups of sub-images after the processed image data of the processing target is divided; sim(v′, v′+1) is the similarity between the v′th group of sub-images and the v′+1th group of images;

[0034] Among them, when segmenting the image data after processing the processing target, the segmentation logic applied is consistent with the segmentation logic of the image data before processing the processing target, and the similarity sim(v′, v′+1) is determined based on the distribution of image color features. The larger the processing quality performance value γ of the processing target, the better the processing quality of the processing target, and vice versa.

[0035] Furthermore, the evaluation layer includes a setting module, a control module and an evaluation module. The setting module is used to set the start-stop control judgment threshold of the grain processing equipment. The control module is used to receive the processing suitability of the processing target analyzed by the analysis module in the analysis layer, and control the start-stop of the grain processing equipment based on the comparison of the processing suitability of the processing target and the start-stop control judgment threshold of the grain processing equipment. The evaluation module is used to receive the processing quality performance value of the processing target identified by the identification module in the analysis layer, and evaluate the state safety of the current grain processing equipment when executing the processing task based on the processing quality performance value of the processing target.

[0036] Among them, the evaluation module records the processing quality performance values ​​of the processing targets received historically, and uses the three most recently recorded sets of processing quality performance values ​​of the processing targets to evaluate the safety of the current state of the grain processing equipment when performing the processing task. The three most recently recorded sets of processing quality performance values ​​of the processing targets include the processing quality performance values ​​of the processing targets currently received by the evaluation module. The three sets of processing quality performance values ​​of the processing targets are denoted as γ1, γ2, and γ3. γ3 represents the processing quality performance value of the processing targets currently received by the evaluation module. When γ3<γ2<γ1, it indicates that the current operating state of the grain processing equipment is unsafe. Otherwise, it indicates that the current operating state of the grain processing equipment is safe.

[0037] Furthermore, when the processing suitability of the processing target is within the start-stop control judgment threshold of the grain processing equipment, the grain processing equipment starts to process the processing target placed in the silo; otherwise, the grain processing equipment is always in a stopped state, and the control module operates to obtain the control results of the grain processing and the evaluation results in the evaluation module, that is, the grain processing risk assessment results in the evaluation layer.

[0038] Furthermore, the receiving module is interactively connected to the analysis module and the identification module through a local area network, the receiving module is interactively connected to the storage module through a local area network, the storage module is interactively connected to the acquisition module and the determination module through a local area network, the analysis module is interactively connected to the setting module through a local area network, and the setting module is interactively connected to the control module and the evaluation module through the local area network.

[0039] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0040] The present invention provides an intelligent control system based on grain processing. During operation, the system monitors and analyzes the operation status of the grain processing equipment, analyzes the functional soundness of the grain processing equipment, ensures that the grain processing equipment has the grain processing capability, further collects and analyzes the state parameters of the processed grain, ensures that the target grain being processed meets the processing conditions, and further evaluates the analysis of the grain processing equipment in the grain processing process in combination with the comprehensive evaluation of the images before and after processing of the processed grain, so that the system end user can perform more predictive management on the grain processing equipment based on the result data output by the system operation, ensures that the grain processing equipment processes the grain more stably, reliably and safely, and guarantees the quality of the grain produced by the grain processing equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 It is a structural diagram of an intelligent control system based on grain processing;

[0043] Figure 2 This is a schematic diagram of the deployment posture of the collection module and the grain processing equipment in the present invention;

[0044] Figure 3 It is a logical diagram of the segmentation of the processing target image data in the present invention;

[0045] The numbers in the figure represent: 1. Camera; 2. Weight sensor; 3. Food processing equipment; 3-1. Silo. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0047] The present invention will be further described below in conjunction with the embodiments.

[0048] Embodiment 1:

[0049] An intelligent control system based on grain processing in this embodiment, such as Figure 1 As shown, it includes control terminal, monitoring layer, analysis layer and evaluation layer;

[0050] The control terminal is the main control terminal of the system and is used to issue execution commands;

[0051] The operating status parameters of the grain processing equipment and the status parameters of the processing targets are collected through the monitoring layer. Based on the operating status parameters of the grain processing equipment, it is determined whether the equipment operating status is normal. The status parameters of the grain processing equipment processing targets are stored for real-time reading by the analysis layer. After traversing and reading the processing target status parameters, the analysis layer analyzes the processing suitability and processing quality of the processing target based on the processing target status parameters. The evaluation layer further obtains the processing suitability and processing quality of the processing target analyzed in the analysis layer, and evaluates the grain processing risk in combination with the processing suitability and processing quality of the processing target.

[0052] The monitoring layer includes a collection module, a determination module and a storage module. The collection module is used to collect the operating state parameters of the grain processing equipment and the state parameters of the processing target. The determination module is used to receive the operating state parameters of the grain processing equipment collected by the collection module, and determine whether the operating state of the grain processing equipment is normal based on the operating state parameters of the grain processing equipment. The storage module is used to receive the processing target state parameters collected by the collection module and store the processing target state parameters.

[0053] Among them, the acquisition module is integrated by the sensor module and the camera, and the sensor module is integrated by the temperature sensor, the vibration sensor, the current and voltage sensor, the speed sensor, and the weight sensor. During the operation stage of the acquisition module, the grain processing equipment is controlled to run idle, and the operating state parameters of the grain processing equipment are collected based on the temperature sensor, the vibration sensor, the current and voltage sensor, and the speed sensor in the sensor module of the acquisition module. After the determination module determines that the operating state of the equipment is normal based on the operating state parameters of the grain processing equipment, the camera and the weight sensor further collect the image data and weight data of the processing target, and transmit them to the storage module;

[0054] The analysis layer includes a receiving module, an analyzing module and an identifying module. The receiving module is used to receive the processing target state parameters stored in the monitoring layer. The analyzing module is used to obtain the processing target state parameters received by the receiving module and analyze the processing suitability of the processing target based on the processing target state parameters. The identifying module is used to obtain the processing target state parameters received by the receiving module and identify the processing quality of the processing target based on the processing target state parameters.

[0055] The analysis logic of the processing suitability of the processing target in the analysis module is expressed as:

[0056]

[0057] Where k is the processing suitability of the processing target; u is the set of several groups of sub-images into which the image data of the processing target is divided before processing; sim(v,v+1) is the similarity between the vth group of sub-images and the v+1th group of sub-images; n is the total number of times the processing target is picked up; M i is the processing target weight picked up and put into the silo of the grain processing equipment for the i-th time; M i+1 The target weight of the grains to be picked up and put into the silo of the grain processing equipment for the i+1th time;

[0058] Among them, the larger the processing suitability k of the processing target is, the more suitable the processing target is for processing, and vice versa, the less suitable the processing target is for processing. The similarity of the two groups of sub-images is determined based on the distribution of image color features. The segmentation of the image data before processing the processing target is manually set by the system end user, and the size and shape of the sub-images obtained by segmentation are equal, and the number of sub-images obtained by segmentation is 2. 2 , 3 2 , ..., (x-1) 2 or x 2 Group;

[0059] The recognition logic of the processing quality of the processing target in the recognition module is expressed as:

[0060]

[0061] Where: γ is the processing quality performance value of the processing target; M out is the weight of the processed target output by the food processing equipment; u′ is the set of several groups of sub-images after the processed image data of the processing target is divided; sim(v′, v′+1) is the similarity between the v′th group of sub-images and the v′+1th group of images;

[0062] When segmenting the processed image data of the processing target, the segmentation logic applied is consistent with the segmentation logic of the image data of the processing target before processing. The similarity sim(v′, v′+1) is determined based on the distribution of image color features. The larger the processing quality performance value γ of the processing target, the better the processing quality of the processing target. Conversely, the worse the processing quality of the processing target.

[0063] The evaluation layer includes a setting module, a control module and an evaluation module. The setting module is used to set the start-stop control judgment threshold of the grain processing equipment. The control module is used to receive the processing suitability of the processing target analyzed by the analysis module in the analysis layer, and control the start-stop of the grain processing equipment based on the comparison of the processing suitability of the processing target and the start-stop control judgment threshold of the grain processing equipment. The evaluation module is used to receive the processing quality performance value of the processing target identified by the identification module in the analysis layer, and evaluate the state safety of the current grain processing equipment when performing the processing task based on the processing quality performance value of the processing target;

[0064] Among them, the evaluation module records the processing quality performance values ​​of the processing targets received in the past, and uses the three sets of the latest recorded processing quality performance values ​​of the processing targets to evaluate the safety of the current state of the grain processing equipment when performing the processing task. The three sets of the latest recorded processing quality performance values ​​of the processing targets include the processing quality performance values ​​of the processing targets currently received by the evaluation module. The three sets of processing quality performance values ​​of the processing targets are recorded as γ1, γ2, and γ3. γ3 represents the processing quality performance value of the processing targets currently received by the evaluation module. When γ3<γ2<γ1, it indicates that the current operation state of the grain processing equipment is unsafe. Otherwise, it indicates that the current operation state of the grain processing equipment is safe.

[0065] The receiving module is interactively connected to the analysis module and the identification module through the local area network, the receiving module is interactively connected to the storage module through the local area network, the storage module is interactively connected to the acquisition module and the judgment module through the local area network, the analysis module is interactively connected to the setting module through the local area network, and the setting module is interactively connected to the control module and the evaluation module through the local area network.

[0066] In this embodiment, the control terminal controls the operation of the control system, the collection module operates to collect the operation status parameters of the grain processing equipment and the status parameters of the processing target, the determination module synchronously receives the operation status parameters of the grain processing equipment collected by the collection module, and determines whether the operation status of the grain processing equipment is normal based on the operation status parameters of the grain processing equipment, the storage module receives the processing target status parameters collected by the collection module in real time, and stores the processing target status parameters, the receiving module further receives the processing target status parameters stored in the monitoring layer, and then the analysis module obtains the processing target status parameters received by the receiving module, analyzes the processing suitability of the processing target based on the processing target status parameters, and obtains the processing target status parameters received by the receiving module through the identification module, identifies the processing quality of the processing target based on the processing target status parameters, and finally sets the start-stop control determination threshold of the grain processing equipment through the setting module, the control module receives the processing suitability of the processing target analyzed by the analysis module in the analysis layer, and controls the start-stop of the grain processing equipment based on the comparison of the processing suitability of the processing target and the start-stop control determination threshold of the grain processing equipment, the evaluation module operates to receive the processing quality performance value of the processing target identified by the identification module in the analysis layer, and evaluates the state safety of the current grain processing equipment when performing the processing task based on the processing quality performance value of the processing target;

[0067] Through the operation of the system in the above embodiment, the risk control effect is brought about in the process of grain processing equipment for processing grain, ensuring the stable operation of the grain processing equipment and better quality of the processed grain output.

[0068] See also Figure 2 As shown, the figure further shows the deployment positions of the camera 1 and the weight sensor 2 in the acquisition module relative to the grain processing equipment;

[0069] See also Figure 3 As shown, the parameter sources of the logical formula used by the system in the above embodiment are further displayed. The numbered squares in the figure represent a group of sub-images obtained by segmentation, and each group of sub-images with numbers represents the image segmentation result under a certain image segmentation logic.

[0070] Embodiment 2:

[0071] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The intelligent control system based on grain processing in Example 1 is further described in detail:

[0072] An idling time threshold is set in the collection module. During the operation phase of the collection module, after the grain processing equipment is controlled to run idle, the operation status parameters of the grain processing equipment are collected at a specified time stamp within the idling time threshold.

[0073] Among them, the idle time threshold is not greater than 1min. Each time the system starts running, during the operation phase of the collection module, two groups of timestamps are randomly selected within the idle time threshold as the timestamps for collecting the operating status parameters of the grain processing equipment, and the selected timestamps are subject to the following conditions: the two consecutively selected groups of timestamps are inconsistent, the two selected groups of timestamps are inconsistent with the two groups of timestamps selected during the last system operation, and at least one group of timestamps is inconsistent, and the interval between two consecutive system starts is less than one hour, then the monitoring layer will not perform the collection of the operating status parameters of the grain processing equipment and the determination of whether the operating status is normal.

[0074] Through the above settings, the logic of the acquisition module cooperating with the grain processing equipment in the system is further limited, ensuring that the monitoring layer where the acquisition module is located in the system can stably operate and collect data, providing necessary operation data support for the operation of subsequent operation layers in the system.

[0075] like Figure 1 As shown, after the acquisition module acquires the operating status parameters of the grain processing equipment based on the selected timestamp, the grain processing equipment is controlled to end the idling operation. The determination module stores the threshold of the safe operating status parameters of the grain processing equipment. The determination logic of whether the operating status of the grain processing equipment is normal in the determination module is expressed as follows:

[0076]

[0077] Where: f1, f2 are the judgment values; m min(t,T) is the difference between the collected temperature and the minimum difference between the values ​​contained in the threshold of the safe operation status parameter of the grain processing equipment; m min(p,P) The difference between the collected vibration frequency and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation status of the grain processing equipment; mmin(u / i,U / I) The difference between the collected voltage-current ratio and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation state of the grain processing equipment; m min(s,S) is the difference between the acquisition speed and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation status of the grain processing equipment; χ is the correction factor; The difference between the first set of collected temperatures and the second set of collected temperatures collected based on the collection timestamp and the maximum difference value included in the parameter threshold of the safe operation status of the grain processing equipment; The difference between the first group of collected vibration frequencies, the second group of vibration frequencies collected based on the collection timestamp, and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment; The difference between the maximum difference between the first group of collected voltage-current ratios and the second group of collected voltage-current ratios based on the collection timestamp and the values ​​included in the threshold value of the parameter of the safe operation state of the grain processing equipment; The difference between the first group of collected rotation speeds and the second group of rotation speeds collected based on the collection timestamp and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment;

[0078] Among them, t in formula (1) is any one of t1 and t2 in formula (2), p in formula (1) is any one of p1 and p2 in formula (2), u in formula (1) is any one of u1 and u2 in formula (2), i in formula (1) is any one of i1 and i2 in formula (2), s in formula (1) is any one of s1 and s2 in formula (2), t1, t2, p1, p2, u1, u2, i1, i2, s1, s2 all participate in the operation of formula (1) to determine whether the operation status of the grain processing equipment is normal;

[0079] The correction factor χ takes a value of 1 or -1. When the collected temperature, collected vibration frequency, collected voltage-current ratio, and collected speed are not within the parameter threshold of the safe operation state of the grain processing equipment, the correction factor χ takes a value of -1. Otherwise, the correction factor χ takes a value of 1. The judgment value f1≤0 means that the operation state of the grain processing equipment is abnormal. Otherwise, the operation state of the grain processing equipment is normal. The judgment value f2∈[0.95, 1.05] means that the operation state of the grain processing equipment is normal. Otherwise, the operation state of the grain processing equipment is abnormal.

[0080] Among them, when all the judgment results based on formula (1) and formula (2) are that the operation status of the grain processing equipment is normal, the operation status of the grain processing equipment is judged to be normal, otherwise, the operation status of the grain processing equipment is judged to be abnormal. The analysis layer operates when the judgment module determines that the operation status of the grain processing equipment is normal, otherwise, the grain processing equipment is controlled to stop operating.

[0081] In this embodiment, whether the operating status of the grain processing equipment is normal is determined by the above-defined determination logic, so as to provide specified operating conditions for subsequent operating layers in the system based on the determination result.

[0082] Embodiment 3:

[0083] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The intelligent control system based on grain processing in Example 1 is further described in detail:

[0084] The processing target state parameters received by the receiving module include: the weight of the processing target before processing, the image data of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing; the analyzing module analyzes the processing suitability stage of the processing target, and uses the weight of the processing target before processing and the image data of the processing target before processing in the processing target state parameters to analyze the processing suitability of the processing target; the identifying module identifies the processing quality stage of the processing target, and uses the weight of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing to identify the processing quality of the processing target;

[0085] When the grain processing equipment puts the processing target into use for the first time, it picks up processing targets of equal volume from the upper, center and lower positions of the processing target pile and puts them into the silo of the grain processing equipment in turn, and piles them flat in the silo. The processing target state parameters are collected by the weight sensor and camera in the collection module;

[0086] Among them, the three groups of positions for picking up processing targets are on the same spatial straight line.

[0087] Through the above settings, a further source of operating data is provided for the analysis module and identification module of the analysis layer in the system, ensuring that the system analysis layer can stably analyze the processing suitability and processing quality of the processing target.

[0088] like Figure 1 As shown, when the processing suitability of the processing target is within the start-stop control judgment threshold of the grain processing equipment, the grain processing equipment starts to process the processing target placed in the silo. Otherwise, the grain processing equipment is always in a stopped state. The control module runs the control results of the grain processing and the evaluation results in the evaluation module, that is, the grain processing risk assessment results in the evaluation layer.

[0089] Through the above settings, the system further provides control logic for the grain processing equipment based on the system operation results, making the linkage operation process of the system and the grain processing equipment more consistent.

[0090] In summary, during the operation of the system in the above embodiment, the functional integrity of the grain processing equipment is analyzed by monitoring and analyzing the operating status of the grain processing equipment to ensure that the grain processing equipment has the ability to process grain, and further collects and analyzes the state parameters of the processed grain to ensure that the target grain being processed meets the processing conditions. Combined with the comprehensive evaluation of the images before and after processing of the processed grain, the analysis of the grain processing equipment during grain processing is further evaluated, so that system-end users can perform more predictive management of the grain processing equipment based on the result data output by the system operation, to ensure that the process of grain processing by the grain processing equipment is more stable, reliable and safe, thereby ensuring the quality of the grain produced by the grain processing equipment.

[0091] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent control system based on grain processing, characterized in that: include: Control terminal, monitoring layer, analysis layer and evaluation layer; The control terminal is the main control terminal of the system and is used to issue execution commands; The operating status parameters of the grain processing equipment and the status parameters of the processing targets are collected through the monitoring layer. Based on the operating status parameters of the grain processing equipment, it is determined whether the equipment operating status is normal. The status parameters of the grain processing equipment processing targets are stored for real-time reading by the analysis layer. After traversing and reading the processing target status parameters, the analysis layer analyzes the processing suitability and processing quality of the processing target based on the processing target status parameters. The evaluation layer further obtains the processing suitability and processing quality of the processing target analyzed in the analysis layer, and evaluates the grain processing risk in combination with the processing suitability and processing quality of the processing target. The analysis layer includes a receiving module, an analyzing module and an identifying module. The receiving module is used to receive the processing target state parameters stored in the monitoring layer. The analyzing module is used to obtain the processing target state parameters received by the receiving module and analyze the processing suitability of the processing target based on the processing target state parameters. The identifying module is used to obtain the processing target state parameters received by the receiving module and identify the processing quality of the processing target based on the processing target state parameters. The analysis logic of the processing suitability of the processing target in the analysis module is expressed as: Where k is the processing suitability of the processing target; u is the set of several groups of sub-images into which the image data of the processing target is divided before processing; sim(v,v+1) is the similarity between the vth group of sub-images and the v+1th group of sub-images; n is the total number of times the processing target is picked up; M i is the processing target weight picked up and put into the silo of the grain processing equipment for the i-th time; M i+1 The target weight of the grains to be picked up and put into the silo of the grain processing equipment for the i+1th time; Among them, the larger the processing suitability k of the processing target is, the more suitable the processing target is for processing, and vice versa, the less suitable the processing target is for processing. The similarity of the two groups of sub-images is determined based on the distribution of image color features. The segmentation of the image data before processing the processing target is manually set by the system end user, and the size and shape of the sub-images obtained by segmentation are equal, and the number of sub-images obtained by segmentation is 2. 2 , 3 2 , ..., (x-1) 2 or x 2 Group.

2. According to claim 1, an intelligent control system based on grain processing is characterized in that: The monitoring layer includes a collection module, a determination module and a storage module. The collection module is used to collect the operating state parameters of the food processing equipment and the state parameters of the processing target. The determination module is used to receive the operating state parameters of the food processing equipment collected by the collection module, and determine whether the operating state of the food processing equipment is normal based on the operating state parameters of the food processing equipment. The storage module is used to receive the processing target state parameters collected by the collection module and store the processing target state parameters. Among them, the acquisition module is integrated with a sensor module and a camera, and the sensor module is integrated with a temperature sensor, a vibration sensor, a current and voltage sensor, a speed sensor, and a weight sensor. During the operation stage of the acquisition module, the food processing equipment is controlled to run idle, and the operating status parameters of the food processing equipment are collected based on the temperature sensor, vibration sensor, current and voltage sensor, and speed sensor in the sensor module of the acquisition module. After the judgment module determines that the operating status of the equipment is normal based on the operating status parameters of the food processing equipment, the camera and weight sensor further collect image data and weight data of the processing target, and transmit them to the storage module.

3. According to claim 2, an intelligent control system based on grain processing is characterized in that: The collection module is set with an idle time threshold. During the operation phase of the collection module, after the grain processing equipment is controlled to run idle, the operation status parameters of the grain processing equipment are collected at a specified time stamp within the idle time threshold. Among them, the idle time threshold is not greater than 1min. Each time the system starts running, during the operation phase of the collection module, two groups of timestamps are randomly selected within the idle time threshold as the timestamps for collecting the operating status parameters of the grain processing equipment, and the selected timestamps are subject to the following conditions: the two consecutively selected groups of timestamps are inconsistent, the two selected groups of timestamps are inconsistent with the two groups of timestamps selected during the last system operation, and at least one group of timestamps is inconsistent, and the interval between two consecutive system starts is less than one hour, then the monitoring layer will not perform the collection of the operating status parameters of the grain processing equipment and the determination of whether the operating status is normal.

4. The intelligent control system based on grain processing according to claim 3 is characterized in that: After the acquisition module acquires the operating state parameters of the grain processing equipment based on the selected timestamp, the grain processing equipment is controlled to end the idling operation. The determination module stores the threshold of the safe operating state parameters of the grain processing equipment. The determination logic of whether the operating state of the grain processing equipment is normal in the determination module is expressed as follows: Where: f1, f2 are the judgment values; m min(t,T) It is the difference between the collected temperature and the minimum difference value among the values ​​included in the threshold value of the parameter of the safe operation status of the grain processing equipment; m min(p,P) The difference between the collected vibration frequency and the minimum difference value contained in the threshold value of the parameter of the safe operation state of the grain processing equipment; m min(u / i,U / I) The difference between the collected voltage-current ratio and the minimum difference value among the values ​​included in the threshold value of the parameter of the safe operation state of the grain processing equipment; m min(s,S) is the difference between the acquisition speed and the minimum difference between the values ​​contained in the threshold of the parameter of the safe operation status of the grain processing equipment; χ is the correction factor; The difference between the first set of collected temperatures and the second set of collected temperatures collected based on the collection timestamp and the maximum difference value included in the parameter threshold of the safe operation status of the grain processing equipment; The difference between the first group of collected vibration frequencies, the second group of vibration frequencies collected based on the collection timestamp, and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment; The difference between the maximum difference between the first group of collected voltage-current ratios and the second group of collected voltage-current ratios based on the collection timestamp and the values ​​included in the threshold value of the parameter of the safe operation state of the grain processing equipment; The difference between the first group of collected rotation speeds and the second group of rotation speeds collected based on the collection timestamp and the maximum difference value included in the value of the parameter threshold of the safe operation state of the grain processing equipment; Among them, t in formula (1) is any group of t1 and t2 in formula (2), p in formula (1) is any group of p1 and p2 in formula (2), u in formula (1) is any group of u1 and u2 in formula (2), i in formula (1) is any group of i1 and i2 in formula (2), s in formula (1) is any group of s1 and s2 in formula (2), t1, t2, p1, p2, u1, u2, i1, i2, s1, s2 all participate in the calculation of formula (1) to determine whether the operating status of the grain processing equipment is normal.

5. The intelligent control system based on grain processing according to claim 4 is characterized in that: The correction factor χ takes a value of 1 or -1. When the collected temperature, collected vibration frequency, collected voltage-current ratio and collected speed are not within the parameter threshold of the safe operation state of the grain processing equipment, the correction factor χ takes a value of -1. Otherwise, the correction factor χ takes a value of 1. The judgment value f1≤0 means that the operation state of the grain processing equipment is abnormal. Otherwise, the operation state of the grain processing equipment is normal. The judgment value f2∈[0.95, 1.05] means that the operation state of the grain processing equipment is normal. Otherwise, the operation state of the grain processing equipment is abnormal. Among them, when all the judgment results based on formula (1) and formula (2) are that the operation status of the grain processing equipment is normal, the operation status of the grain processing equipment is judged to be normal, otherwise, the operation status of the grain processing equipment is judged to be abnormal. The analysis layer operates when the judgment module determines that the operation status of the grain processing equipment is normal, otherwise, the grain processing equipment is controlled to stop operating.

6. The intelligent control system based on grain processing according to claim 1 is characterized in that: The processing target state parameters received by the receiving module include: the weight of the processing target before processing, the image data of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing; the analyzing module analyzes the processing suitability stage of the processing target, and uses the weight of the processing target before processing and the image data of the processing target before processing in the processing target state parameters to analyze the processing suitability of the processing target; the identifying module identifies the processing quality stage of the processing target, and uses the weight of the processing target before processing, the image data of the processing target after processing, and the weight of the processing target after processing to identify the processing quality of the processing target; When the grain processing equipment puts the processing target into use for the first time, it picks up processing targets of equal volume from the upper, center and lower positions of the processing target pile and puts them into the silo of the grain processing equipment in turn, and piles them flat in the silo. The processing target state parameters are collected by the weight sensor and camera in the collection module; Among them, the three groups of positions for picking up processing targets are on the same spatial straight line.

7. The intelligent control system based on grain processing according to claim 1 is characterized in that: The recognition logic of the processing quality of the processing target in the recognition module is expressed as: Where: γ is the processing quality performance value of the processing target; M out is the weight of the processed target output by the food processing equipment; u′ is the set of several groups of sub-images after the processed image data of the processing target is divided; sim(v′, v′+1) is the similarity between the v′th group of sub-images and the v′+1th group of images; Among them, when segmenting the image data after processing the processing target, the segmentation logic applied is consistent with the segmentation logic of the image data before processing the processing target, and the similarity sim(v′, v′+1) is determined based on the distribution of image color features. The larger the processing quality performance value γ of the processing target, the better the processing quality of the processing target, and vice versa.

8. The intelligent control system based on grain processing according to claim 1 is characterized in that: The evaluation layer includes a setting module, a control module and an evaluation module. The setting module is used to set the start-stop control judgment threshold of the grain processing equipment. The control module is used to receive the processing suitability of the processing target analyzed by the analysis module in the analysis layer, and control the start-stop of the grain processing equipment based on the comparison of the processing suitability of the processing target and the start-stop control judgment threshold of the grain processing equipment. The evaluation module is used to receive the processing quality performance value of the processing target identified by the identification module in the analysis layer, and evaluate the state safety of the current grain processing equipment when executing the processing task based on the processing quality performance value of the processing target; Among them, the evaluation module records the processing quality performance values ​​of the processing targets received historically, and uses the three most recently recorded sets of processing quality performance values ​​of the processing targets to evaluate the safety of the current state of the grain processing equipment when performing the processing task. The three most recently recorded sets of processing quality performance values ​​of the processing targets include the processing quality performance values ​​of the processing targets currently received by the evaluation module. The three sets of processing quality performance values ​​of the processing targets are denoted as γ1, γ2, and γ3. γ3 represents the processing quality performance value of the processing targets currently received by the evaluation module. When γ3<γ2<γ1, it indicates that the current operating state of the grain processing equipment is unsafe. Otherwise, it indicates that the current operating state of the grain processing equipment is safe.

9. The intelligent control system based on grain processing according to claim 8 is characterized in that: When the processing suitability of the processing target is within the start-stop control judgment threshold of the grain processing equipment, the grain processing equipment starts to process the processing target placed in the silo. Otherwise, the grain processing equipment is always in a stopped state, and the control module operates to obtain the control results of the grain processing and the evaluation results in the evaluation module, that is, the grain processing risk assessment results in the evaluation layer.

10. The intelligent control system based on grain processing according to claim 1, characterized in that: The receiving module is interactively connected to the analysis module and the identification module through the local area network, the receiving module is interactively connected to the storage module through the local area network, the storage module is interactively connected to the acquisition module and the determination module through the local area network, the analysis module is interactively connected to the setting module through the local area network, and the setting module is interactively connected to the control module and the evaluation module through the local area network.

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