A method for monitoring and controlling the state of coal conveying protection device based on image linkage

Abstract

The present invention discloses a method for monitoring and controlling the state of a coal conveyor protection device based on image linkage, which relates to the field of coal conveyor belt equipment protection technology protection. The method includes establishing a relationship between the belt conveyor protection device and a PLC based on the signals of each belt conveyor protection device in the fuel coal conveying system; accurately analyzing the belt conveyor protection device based on the signals of image recognition during actual operation, combined with the logical judgment of the belt conveyor protection device; measuring and monitoring the belt conveyor protection device; collecting a large amount of operating data, performing relationship analysis, establishing an accurate digital twin coal conveying system, simulating fault conditions, and optimizing the model for online monitoring; and constructing a digital twin system of the coal conveying system through information fusion, monitoring the system status in real time, and performing comprehensive judgment from all aspects. The present invention can achieve accurate measurement and monitoring of the belt conveyor protection device, so that the belt conveyor protection device system has an autonomous monitoring function when working, and has an unmanned effect.

Description

Technical Field

[0001] The present invention relates to the field of coal conveyor belt equipment protection technology, and in particular to a coal conveyor protection device state monitoring and control method based on image linkage. Background Art

[0002] Currently, the switch on the protective device for the coal conveyor belt conveyor in the coal conveying system can only send an alarm signal to the program control system to shut down the machine, but it cannot accurately report the specific pull-cord switch that caused the alarm. This results in low inspection efficiency for operators and low work efficiency for maintenance personnel, affecting the company's production efficiency. Therefore, designing a method and system for monitoring and controlling the status of the coal conveyor protective device based on image linkage is of great significance to the company's safe and economic development. Summary of the Invention

[0003] In view of the fact that the switch of the protective device of the coal conveyor belt conveyor in the above-mentioned coal conveying system can only send an alarm signal to the program control to shut down the machine, but cannot accurately report which pull rope switch has the problem in the alarm, the present invention is proposed.

[0004] Therefore, the problem to be solved by the present invention is how to provide a method for achieving accurate measurement and monitoring of the belt conveyor protection device, getting rid of the inefficient mode of traditional manual inspection, and enabling the belt conveyor protection device system to have autonomous monitoring function and unmanned operation during operation.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In the first aspect, an embodiment of the present invention provides a method for monitoring and controlling the status of a coal conveying protection device based on image linkage, which includes obtaining parameter information and establishing a relationship between the belt conveyor protection device and the PLC according to the signals of each belt conveyor protection device in the fuel coal conveying system; accurately analyzing the belt conveyor protection device according to the image recognition signal in the actual working process and combining the logical judgment of the belt conveyor protection device; measuring and monitoring the belt conveyor protection device in combination with the sensor and image recognition information; utilizing the big data platform to collect a large amount of operating data, perform relationship analysis, establish an accurate digital twin coal conveying system, simulate fault conditions, and perform online monitoring model optimization; through information fusion, construct a digital twin system of the coal conveying system, monitor the system status in real time, and perform comprehensive judgment from all aspects.

[0007] As a preferred solution of the coal conveying protection device status monitoring and control method based on image linkage described in the present invention, wherein: the parameter information includes the emergency stop switch status St, vibration V and coal conveying cable tray smoke sensor F; the establishment of the relationship between the belt conveyor protection device and the PLC includes reading the signal tag addresses and protection logic parameters P1~Pn in the PLC and establishing a mapping relationship between the parameters and the PLC tags: St->Tag1; V->Tag2; F->Tag3; according to the protection logic, the logical relationship between the parameters and the tags is determined.

[0008] As a preferred solution of the state monitoring and control method of the coal conveying protection device based on image linkage described in the present invention, the protection logic is as follows: check the emergency stop switch state St, if St=0, the state is normal, check the vibration sensor reading V, if V<=Vmax, the vibration is normal, check the smoke sensor state F of the coal conveying cable tray, if F=0, there is no smoke alarm, and the protection judgment ends; if F=1, the smoke alarm protection is triggered and the protection state processing is entered; if V>Vmax, the excessive vibration protection is triggered and the protection state processing is entered; if St=1, the emergency stop protection is triggered and the protection state processing is entered; the protection state processing includes: issuing a protection alarm, stopping the belt operation, checking all protection conditions, determining the specific protection type and displaying the protection event, and waiting for processing.

[0009] As a preferred embodiment of the method for monitoring and controlling the state of a coal conveyor protection device based on image linkage according to the present invention, the method for measuring and monitoring the belt conveyor protection device by combining sensor and image recognition information includes the following steps: obtaining sensor data X(t) and image recognition result Y(t); filtering the sensor data;

[0010] X'(t)=f(X(t))

[0011] Where f is the filter function; if X'(t) or Y(t) is missing or abnormal, an alarm is issued and data is retrieved; feature extraction is performed:

[0012] X1=g1(X'(t))

[0013] Y1=g2(Y(t))

[0014] Among them, g1 and g2 are feature extraction functions respectively; data fusion is performed:

[0015] Z(t)=h(X1,Y1)

[0016] If Z(t) meets the fault characteristics, it is determined that the belt conveyor has a corresponding fault.

[0017] As a preferred solution of the state monitoring and control method of the coal conveying protection device based on image linkage described in the present invention, the fault characteristics are as follows: check the tape tearing feature f1 in Z(t), if f1=0, the tape is not torn, check the smoke alarm feature f2 in Z(t), if f2=0, there is no smoke alarm, check the tape offset feature in Z(t), if f3<threshold, the tape is running normally, check the moisture alarm feature f4 in Z(t), if f4=0, the moisture is normal, and the judgment ends; if f4=1, there is In the case of moisture alarm, the fault type is comprehensively judged; if f1=1, the tape is torn, and the fault type is comprehensively judged; if f2=1, there is a smoke alarm, and the fault type is comprehensively judged; if f3≥threshold, the tape is severely offset, and the fault type is comprehensively judged; the comprehensive judgment of fault type includes: if only f1=1, it is judged as a tape tearing fault; if only f2=1, it is judged as a smoke alarm fault; if only f3≥threshold, it is judged as a tape offset fault; if f1=1 and f2=1, it is judged as a smoke alarm compound fault caused by tape tearing.

[0018] As a preferred solution of the state monitoring and control method of the coal conveying protection device based on image linkage of the present invention, the establishment of an accurate digital twin coal conveying system and the simulation of fault conditions include the following steps: collecting n sources of sample data; extracting features from each source data to obtain a feature set F = {f1, f2, ... f k}; Build a simulation model M, input the feature set F, and output the state y; Use the trained model to simulate and obtain the simulated state y'; Compare the simulated state y' with the actual state y; If |y'-y|>threshold e, enter the model tuning loop, return to building the simulation model, and rebuild the model M; If |y'-y|≤threshold e, then obtain the optimized digital twin system model; The setting process of the threshold e is as follows: Collect a large amount of operating data and state label data set D under normal working conditions of equipment; Assume that the state label y conforms to the normal distribution N(μ,σ2); Calculate the mean μ and standard deviation σ of the state label in the data set D; Determine the significance level α; According to the normal distribution table, obtain the corresponding critical value zα. The calculation process of the threshold e is as follows:

[0019] Threshold e = zα × σ

[0020] After collecting more data, recalculate μ and σ to obtain new thresholds; repeat the above process to dynamically optimize the thresholds.

[0021] As a preferred solution of the state monitoring and control method of the coal conveying protection device based on image linkage described in the present invention, the digital twin system of the coal conveying system is constructed to monitor the system state in real time and make a comprehensive judgment from all aspects, including the following steps: integrating multi-source heterogeneous data R; using a deep learning algorithm to extract a data feature set; using an advanced ground reinforcement learning algorithm to construct a high-precision digital twin simulation system O; simulating various data situations, outputting state features y1', and comparing y1' with the actual state y 1， Perform an assessment; if |y1'-y1|<=threshold 1, the status is normal; if threshold 1<|y1'-y1|<=threshold 2, the status is slightly abnormal and a prompt is given; if threshold 2<|y1'-y1|<=threshold 3, the status is moderately abnormal and a diagnosis and prediction is performed; if |y1'-y1|>threshold 3, the status is seriously abnormal and the machine is shut down for inspection.

[0022] Secondly, in order to further solve the problem that the switch of the coal conveyor belt conveyor protection device in the coal conveying system can only send an alarm signal to the program control to shut down, but cannot accurately report which specific pull rope switch has an alarm, the embodiment provides a coal conveyor protection device status monitoring and control system based on image linkage, which includes: a PLC communication module for establishing communication and data transmission between the belt conveyor protection device and the PLC; an image recognition module for processing and analyzing real-time images, and performing fault analysis in combination with the logical judgment of the belt conveyor protection device; a sensor and monitoring module for obtaining real-time data of the belt conveyor protection device for measurement and monitoring; a big data acquisition and analysis module for collecting a large amount of operating data and performing relationship analysis, establishing a digital twin system to simulate fault conditions and perform model optimization for online monitoring; an information fusion and comprehensive judgment module for integrating and analyzing the information of each module, constructing a digital twin system for the coal conveying system, monitoring the system status in real time, and performing multi-faceted comprehensive judgment.

[0023] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the method for monitoring and controlling the status of a coal conveying protection device based on image linkage as described in the first aspect of the present invention is implemented.

[0024] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, wherein: when the computer program is executed by a processor, any step of the method for monitoring and controlling the status of a coal conveying protection device based on image linkage as described in the first aspect of the present invention is implemented.

[0025] The beneficial effects of the present invention are as follows: the present invention can accurately analyze and monitor the belt conveyor protection device, can timely discover potential faults and abnormal conditions, thereby improving the safety of the system; combined with sensors and image recognition information, the belt conveyor protection device is measured and monitored, and the operating parameters and status can be obtained in real time, and the operation of the system can be effectively monitored, thereby improving the working efficiency of the system; fault conditions can be simulated and the online monitoring model can be optimized to achieve the optimization of the reliability and efficiency of the system; the present invention can achieve accurate measurement and monitoring of the belt conveyor protection device, get rid of the inefficient mode of traditional manual inspection, and enable the belt conveyor protection device system to have autonomous monitoring functions when working, and unmanned. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0027] Figure 1 This is a scene diagram of the coal conveying protection device status monitoring and control method based on image linkage in Example 1.

[0028] Figure 2 This is a flowchart of the protection logic in Example 1. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0030] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0031] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0032] Example 1

[0033] Reference Figure 1 and Figure 2, which is the first embodiment of the present invention, provides an office file cabinet with strong confidentiality, comprising the following steps:

[0034] S1: According to the signals of each protection device of the belt conveyor in the fuel coal conveying system, the parameter information is obtained and the relationship between the belt conveyor protection device and the PLC is established.

[0035] Specifically, the sensor signals of the belt conveyor protection device are read, including analog and digital signals such as the emergency stop switch, liquid level switch, and temperature sensor; key parameters are extracted, such as parameter information including the emergency stop switch status St, vibration V, and coal cable tray smoke sensor F; the relationship between the belt conveyor protection device and the PLC is established, including reading the signal tag addresses and protection logic parameters P1~Pn in the PLC and establishing a mapping relationship between the parameters and the PLC tags: St->Tag1; V->Tag2; F->Tag3; according to the protection logic, the logical relationship between the parameters and the tags is determined.

[0036] Preferably, the protection logic is as follows: check the emergency stop switch status St, if St=0, the status is normal, check the vibration sensor reading V, if V<=Vmax, the vibration is normal, check the coal transportation cable bridge smoke sensor status F, if F=0, there is no smoke alarm, and the protection judgment ends; if F=1, the smoke alarm protection is triggered and the protection state processing is entered; if V>Vmax, the excessive vibration protection is triggered and the protection state processing is entered; if St=1, the emergency stop protection is triggered and the protection state processing is entered; the protection state processing includes: issuing a protection alarm, stopping the belt operation, checking all protection conditions, determining the specific protection type and displaying the protection event, and waiting for processing.

[0037] S2: Based on the image recognition of tearing, smoke, deviation and other signals during the actual working process, combined with the logical judgment of the belt conveyor protection device, accurate analysis of the belt conveyor protection device is carried out.

[0038] Specifically, first, the real-time image of the tape conveyor is analyzed through the image recognition algorithm to detect whether the tape is torn, whether there is a smoke alarm, etc., to form the corresponding state quantity; then, these state quantities are mapped to the corresponding PLC internal tag address to trigger the PLC protection judgment logic; finally, the PLC calculates the output result according to the preset protection logic relationship. If the fault condition is met, it is confirmed that the tape conveyor has a protective fault; repeating the above process can monitor the operating status and protection status of the tape conveyor in real time.

[0039] S3: Combine sensors and image recognition information to measure and monitor the belt conveyor protection device, achieving unmanned remote and efficient monitoring.

[0040] Preferably, the method comprises the following steps:

[0041] S3.1: Obtain sensor data X(t) and image recognition results Y(t).

[0042] S3.2: Filter the sensor data:

[0043] X'(t)=f(X(t))

[0044] Where f is the filter function; if X'(t) or Y(t) is missing or abnormal, an alarm is issued and the data is retrieved.

[0045] S3.3: Perform feature extraction:

[0046]

[0047] Among them, g1 and g2 are feature extraction functions respectively.

[0048] S3.4: Perform data fusion:

[0049] Z(t)=h(X1,Y1)

[0050] If Z(t) meets the fault characteristics, it is determined that the tape conveyor has a corresponding fault; the specific judgment process of the fault characteristics is as follows: check the tape tearing feature f1 in Z(t), if f1=0, the tape is not torn, check the smoke alarm feature f2 in Z(t), if f2=0, there is no smoke alarm, check the tape offset feature in Z(t), if f3<threshold, the tape is running normally, check the moisture alarm feature f4 in Z(t), if f4=0, the moisture is normal, and the judgment ends; if f4=1, there is a moisture alarm. Alarm, comprehensively judge the fault type; if f1=1, the tape is torn, and the fault type is comprehensively judged; if f2=1, there is a smoke alarm, and the fault type is comprehensively judged; if f3≥threshold, the tape is seriously offset, and the fault type is comprehensively judged; among them, the comprehensive judgment of fault type includes: if only f1=1, it is judged as a tape tearing fault; if only f2=1, it is judged as a smoke alarm fault; if only f3≥threshold, it is judged as a tape offset fault; if f1=1 and f2=1, it is judged as a combined fault of smoke alarm caused by tape tearing.

[0051] The threshold setting process involves collecting a large amount of Z(t) monitoring data from the belt conveyor under normal operating conditions. Statistically analyze the normal operating data to estimate the mean μ and standard deviation σ of the characteristic parameters. Assuming the characteristic parameters follow a normal distribution N(μ,σ^2), determine a confidence interval. For example, a 95% confidence interval is [μ-2σ, μ+2σ]. If the characteristic parameter falls outside the confidence interval, the condition is considered abnormal. The upper limit of the confidence interval can be used as the threshold. The upper limits of multiple characteristic parameters are combined to form the final composite threshold judgment condition. Repeat this process as more data is collected to continuously optimize the threshold.

[0052] It should be noted that the present invention not only uses images or sensor data alone, but also develops a multi-source heterogeneous information fusion method that effectively integrates the two to further improve the accuracy and reliability of monitoring.

[0053] S4: Utilize the big data platform to collect large amounts of operational data, conduct relationship analysis, establish an accurate digital twin coal transportation system, simulate fault conditions, and optimize the model for online monitoring.

[0054] Specifically, sample data from n sources, including sensor data, camera data, etc., are collected; features are extracted from each source data to obtain a feature set F = {f1, f2, ... f k}; Build a simulation model M, input the feature set F, and output the state y; use the trained model to simulate and obtain the simulated state y'; compare the simulated state y' with the actual state y; if |y'-y|>threshold e, enter the model tuning loop, return to building the simulation model, and rebuild the model M; if |y'-y|≤threshold e, obtain the optimized digital twin system model.

[0055] Preferably, the threshold e is set as follows: collect a large amount of operating data and a state label data set D under normal working conditions of the equipment; assume that the state label y conforms to the normal distribution N(μ,σ2); calculate the mean μ and standard deviation σ of the state labels in the data set D; determine the significance level α (such as 0.05); obtain the corresponding critical value zα according to the normal distribution table; and calculate the threshold e:

[0056] Threshold e = zα × σ

[0057] After collecting more data, recalculate μ and σ to obtain new thresholds; repeat the above process to dynamically optimize the thresholds.

[0058] S5: Through information fusion, a digital twin system of the coal transportation system is constructed to monitor the system status in real time and make comprehensive judgments from all aspects.

[0059] Preferably, integrate multi-source heterogeneous data R such as sensor data, video images, historical logs, and equipment parameters; use deep learning algorithms to extract data feature sets; use advanced ground reinforcement learning algorithms to build a high-precision digital twin simulation system O; simulate various situations, output state features y1', and compare y1' with the actual state y 1， Perform an assessment; if |y1'-y1|<=threshold 1, the status is normal; if threshold 1<|y1'-y1|<=threshold 2, the status is slightly abnormal and a prompt is given; if threshold 2<|y1'-y1|<=threshold 3, the status is moderately abnormal and a diagnosis and prediction is performed; if |y1'-y1|>threshold 3, the status is seriously abnormal and the machine is shut down for inspection.

[0060] The process for setting thresholds 1, 2, and 3 is as follows: Collect the actual state y1 and the digital twin simulated state y1' of a large number of devices under normal working conditions; calculate their error |y1'-y1|, fit the error to a normal distribution, and estimate the mean μ and standard deviation σ; determine three signature levels, such as 99%, 95%, and 90%; determine the corresponding critical values ​​z1, z2, and z3 based on the normal distribution cumulative probability table; and calculate the three thresholds:

[0061] Threshold 1 = μ + z1 × σ

[0062] Threshold 2 = μ + z2 × σ

[0063] Threshold 3 = μ + z3 × σ

[0064] In the new data, the error is compared with the three thresholds and a graded judgment is made.

[0065] This embodiment also provides a coal conveying protection device status monitoring and control system based on image linkage, including: a PLC communication module, used to establish communication and data transmission between the belt conveyor protection device and the PLC; an image recognition module, used to process and analyze real-time images, and perform fault analysis in combination with the logical judgment of the belt conveyor protection device; a sensor and monitoring module, used to obtain real-time data of the belt conveyor protection device for measurement and monitoring; a big data acquisition and analysis module, used to collect a large amount of operating data and perform relationship analysis, establish a digital twin system to simulate fault conditions and perform model optimization for online monitoring; an information fusion and comprehensive judgment module, used to integrate and analyze the information of each module, construct a digital twin system of the coal conveying system, monitor the system status in real time, and perform comprehensive judgment from all aspects.

[0066] This embodiment also provides a computer device, which is suitable for the coal conveying protection device status monitoring and control method based on image linkage, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the coal conveying protection device status monitoring and control method based on image linkage proposed in the above embodiment.

[0067] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0068] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for monitoring and controlling the state of a coal conveying protection device based on image linkage as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0069] In summary, the present invention can accurately analyze and monitor the belt conveyor protection device, and can timely discover potential faults and abnormal conditions, thereby improving the safety of the system; combining sensors and image recognition information, the belt conveyor protection device is measured and monitored, and the operating parameters and status can be obtained in real time, and the operation of the system can be effectively monitored, thereby improving the working efficiency of the system; fault conditions can be simulated, and the model of online monitoring can be optimized to achieve the optimization of the reliability and efficiency of the system; the present invention achieves accurate measurement and monitoring of the belt conveyor protection device, gets rid of the inefficient mode of traditional manual inspection, and enables the belt conveyor protection device system to have autonomous monitoring functions when working, and has an unmanned effect.

[0070] Example 2

[0071] This is the second embodiment of the present invention. Based on the first embodiment, in order to verify its beneficial effects, experimental simulation data of the present invention are provided.

[0072] In a coal conveying system in a power plant, to improve coal transportation efficiency, it is necessary to monitor and control the operating status of the belt conveyor in the coal conveying system. The following example obtains parameter information of the belt conveyor protection device in the PLC:

[0073] Emergency stop switch status St, address Tag1, initial state St = 1; vibration sensor V, address Tag2, initial reading V = 2m / s2; coal cable tray smoke sensor F, address Tag3, initial state F = 0; through the image recognition system, the belt conveyor track offset M = 0.5m is monitored in real time.

[0074] The data from PLC and image recognition are integrated to perform status judgment: St = 1, triggering emergency stop protection; M = 0.5m > threshold 0.2m, the belt is severely deviated; through the digital twin system simulation fault prediction, a track deviation fault is also predicted; a comprehensive judgment is made that the belt conveyor has a track deviation fault, the belt operation is immediately stopped, and the on-site situation is checked, and it is found that the deviation is caused by the breakage at the belt joint.

[0075] In summary, it can be seen that compared with the existing image monitoring system that can only monitor the offset but cannot determine the root cause; this method can accurately determine the fault type and improve maintenance efficiency through multi-source data fusion.

[0076] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring and controlling the state of a coal conveying protection device based on image linkage, characterized in that: include: According to the signals of each protective device of the belt conveyor in the fuel coal conveying system, the parameter information is obtained and the relationship between the belt conveyor protection device and the PLC is established; Based on the image recognition signals during the actual working process and combined with the logical judgment of the belt conveyor protection device, the belt conveyor protection device is accurately analyzed; Combine sensors and image recognition information to measure and monitor the belt conveyor protection device; Leveraging a big data platform, we collect large amounts of operational data, conduct relationship analysis, build an accurate digital twin coal handling system, simulate fault conditions, and optimize models for online monitoring. Through information fusion, a digital twin system of the coal transportation system is constructed to monitor the system status in real time and make comprehensive judgments from all aspects; The parameter information includes the emergency stop switch status St, the vibration sensor reading V and the coal cable bridge smoke sensor F; Establishing the relationship between the belt conveyor protection device and the PLC includes reading the addresses of each signal tag in the PLC, protection logic parameters P1 to Pn, and establishing a mapping relationship between the parameters and the PLC tags: St->Tag1; V->Tag2; F->Tag3; according to the protection logic, determining the logical relationship between the emergency stop switch state St and the signal tag Tag1 in the PLC, the logical relationship between the vibration sensor reading V and the signal tag Tag2 in the PLC, and the logical relationship between the coal transportation cable bridge smoke sensor F and the signal tag Tag3 in the PLC; The protection logic is as follows: Check the emergency stop switch status St. If St=0, the status is normal. Check the vibration sensor reading V. If V≤Vmax, the vibration is normal. Check the coal transmission cable bridge smoke sensor status F. If F=0, there is no smoke alarm and the protection judgment ends. If F=1, the smoke alarm protection is triggered and the protection state is entered. If V>Vmax, the excessive vibration protection is triggered and the protection state is entered. If St=1, the emergency stop protection is triggered and the protection state is entered. The protection status processing includes: issuing a protection alarm, stopping the belt operation, checking all protection conditions, determining the specific protection type and displaying the protection event, waiting for processing; The method of combining the sensor and the image recognition information to measure and monitor the protective device of the belt conveyor includes the following steps: Obtain sensor data X(t) and image recognition results Y(t); Filter the sensor data: X'(t)=f(X(t)) Where, f is the filter function; If X'(t) or Y(t) is missing or abnormal, an alarm will be issued and the data will be retrieved again; Perform feature extraction: X1=g1(X'(t)) Y1=g2(Y(t)) Among them, g1 and g2 are feature extraction functions respectively; Perform data fusion: Z(t)=h(X1,Y1) If Z(t) meets the fault characteristics, it is determined that the belt conveyor has a corresponding fault.

2. The method for monitoring and controlling the state of a coal conveying protection device based on image linkage according to claim 1, characterized in that: The fault characteristics are as follows: Check the tape tear feature f1 in Z(t). If f1=0, the tape is not torn. Check the smoke alarm feature f2 in Z(t). If f2=0, there is no smoke alarm. Check the tape offset feature f3 in Z(t). If f3<threshold, the tape is running normally. Check the moisture alarm feature f4 in Z(t). If f4=0, the moisture is normal and the judgment ends. If f4=1, there is a moisture alarm and the fault type is comprehensively judged. If f1=1, the tape is torn and the fault type is comprehensively judged. If f2=1, there is a smoke alarm and the fault type is comprehensively judged. If f3 ≥ threshold, the tape is severely deflected and the fault type is determined comprehensively; The comprehensive judgment of the fault type includes: if only f1=1, it is judged to be a tape tearing fault; If only f2=1, it is judged as a smoke alarm fault; if only f3≥threshold, it is judged as a tape offset fault; if f1=1 and f2=1, it is judged as a smoke alarm compound fault caused by tape tearing.

3. The method for monitoring and controlling the state of a coal conveying protection device based on image linkage according to claim 2, characterized in that: The establishment of an accurate digital twin coal handling system and simulation of fault conditions includes the following steps: Collect sample data from n sources; Extract features from each sample data and obtain feature set F = {f1,f2,...f k }; Construct a simulation model M, input feature set F, and output state y; Use the trained model to simulate and obtain the simulated state y'; Compare the simulated state y' with the actual state y; if |y'-y|>threshold e, enter the model tuning loop, return to building the simulation model, and rebuild model M; if |y'-y|≤threshold e, obtain the optimized digital twin system model; The process of setting the threshold e is as follows: collect a large amount of operating data and state label data set D of the equipment under normal working conditions; assume that the state label y conforms to the normal distribution N(μ,σ 2 ); calculate the mean μ and standard deviation σ of the state labels in the dataset D; determine the significance level α; and obtain the corresponding critical value zα according to the normal distribution table. The calculation process of the threshold e is as follows: Threshold e = zα × σ After collecting more data, recalculate μ and σ to obtain new thresholds; Repeat the process to dynamically optimize the threshold.

4. The method for monitoring and controlling the state of a coal conveying protection device based on image linkage according to claim 3, characterized in that: The construction of a digital twin system for the coal transportation system, real-time monitoring of the system status, and comprehensive judgment from all aspects includes the following steps: Integrate multi-source heterogeneous data R; Use deep learning algorithms to extract data feature sets; Use reinforcement learning algorithms that have been put into practical use to build a high-precision digital twin simulation system O; Simulate various data conditions, output state characteristics y1', and compare y1' with the actual state y 1， Conduct assessments; If |y1'-y1|≤threshold 1, the status is normal; if threshold 1<|y1'-y1|≤threshold 2, the status is slightly abnormal and a prompt is given; if threshold 2<|y1'-y1|≤threshold 3, the status is moderately abnormal and a diagnosis and prediction is performed; if |y1'-y1|>threshold 3, the status is seriously abnormal and the system is shut down for inspection.

5. A coal conveyor protection device state monitoring and control system based on image linkage, based on the coal conveyor protection device state monitoring and control method based on image linkage according to any one of claims 1 to 4, characterized in that: include: PLC communication module, used to establish communication and data transmission between the belt conveyor protection device and PLC; Image recognition module, used to process and analyze real-time images and perform fault analysis in combination with the logical judgment of the belt conveyor protection device; Sensor and monitoring modules are used to obtain real-time data of the belt conveyor protection device for measurement and monitoring; Big data acquisition and analysis module, used to collect large amounts of operating data and conduct relationship analysis, establish a digital twin system to simulate fault conditions and perform model optimization for online monitoring; The information fusion and comprehensive judgment module is used to integrate and analyze the information of each module, build a digital twin system of the coal transportation system, monitor the system status in real time, and make comprehensive judgments from all aspects.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for monitoring and controlling the state of a coal conveying protection device based on image linkage according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for monitoring and controlling the state of a coal conveying protection device based on image linkage according to any one of claims 1 to 4 are implemented.

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