A safety monitoring system for mine transportation equipment based on the Internet of Things

Abstract

A safety monitoring system for mine transportation equipment based on the Internet of Things, which relates to the technical field of equipment monitoring; constructs a physical model of mine transportation equipment, sets monitoring points to obtain monitoring data, constructs a simulation model of mine transportation equipment in combination with the physical model, obtains the tensile force difference under different simulation data sets in the simulation model, dynamically adjusts the mine transportation equipment and obtains different dynamic tensile force values, constructs a tensile force adjustment model of the mine transportation equipment, uses the tensile force adjustment model to dynamically adjust the mine transportation equipment, sets an evaluation period to obtain the total number of adjustments of the mine transportation equipment, determines whether there is abnormal adjustment equipment and generates corresponding optimization information; can always keep the tensile force in the forward direction of the mine car stable, thereby maintaining a stable driving speed and transportation capacity, and avoiding the occurrence of safety accidents such as rollover and out-of-control caused by uneven tensile force.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment monitoring, and specifically to a safety monitoring system for mine transportation equipment based on the Internet of Things. Background Art

[0002] The safety monitoring of mine transportation equipment is a system integrating advanced technologies such as Internet of Things technology, sensor technology, data analysis and intelligent algorithms, aiming to improve the safety and efficiency of mine transportation equipment. With the continuous development of existing technologies and the expansion of application scenarios, this system will play an increasingly important role in mine safety supervision;

[0003] In the prior art, due to the particularity of the mine environment, there are many inevitable influencing factors for the operation of mine transportation equipment, resulting in the inability to always keep the pulling force in the advancing direction of the mine car constant. As a result, the driving speed and transportation capacity of the mine car are also affected, and even safety accidents such as rollover and out-of-control occur. How to maintain a stable pulling force in the advancing direction of the mine car and timely discover potential influencing factors is a technical problem to be solved currently. In view of the deficiencies of the prior art, the present invention provides a safety monitoring system for mine transportation equipment based on the Internet of Things. Summary of the Invention

[0004] The purpose of the present invention is to provide a safety monitoring system for mine transportation equipment based on the Internet of Things.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A safety monitoring system for mine transportation equipment based on the Internet of Things includes the following modules:

[0006] A data acquisition module, which is used to obtain the equipment information and track information of the mine transportation equipment, construct a corresponding physical model, set monitoring points on the mine transportation equipment to obtain monitoring data, and construct a corresponding simulation model in combination with the physical model;

[0007] A data analysis module, which is used to obtain the pulling force difference under different simulation data sets in the simulation model, dynamically adjust the mine transportation equipment according to the pulling force difference, and obtain different dynamic pulling force values, and construct a pulling force adjustment model of the mine transportation equipment according to different simulation data sets and their dynamic pulling force values;

[0008] A data evaluation module, which is used to dynamically adjust the mine transportation equipment by using the pulling force adjustment model, set an evaluation period to obtain the total number of adjustments of the mine transportation equipment, and judge whether there is an abnormally adjusted equipment, and generate corresponding optimization information according to the monitoring data of the abnormally adjusted equipment.

[0009] Furthermore, the process of obtaining the equipment information and track information of the mine transportation equipment and constructing a corresponding physical model includes:

[0010] The mining transportation equipment mentioned refers to a mine car with a steel wire rope. The mine car is towed by the steel wire rope to move up and down along the transportation track, and includes the following several component structures, namely a power device, a braking device, a transmission device, a drum device, a base and a mine car;

[0011] The equipment information refers to the specification parameters of the component structures included in the mining transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mining transportation equipment moves. The physical models of both are constructed using digital twin technology based on the obtained equipment information and track information.

[0012] Furthermore, the process of setting monitoring points on the mining transportation equipment to obtain monitoring data and constructing a corresponding simulation model in combination with the physical model includes:

[0013] The connection point between the mine car and the steel wire rope during the transportation process is used as a monitoring point. A tension monitoring unit and an inclination monitoring unit are set at the monitoring point, and a load monitoring unit is set inside the mine car, and the corresponding monitoring data is obtained, including tension data, inclination data, and load data;

[0014] Based on the physical model, a simulation software is used to simulate the transportation process of the mining transportation equipment on the transportation track to obtain the corresponding simulation model. The simulation model is used to simulate the transportation process of the mining transportation equipment and obtain the force condition of the steel wire rope.

[0015] Furthermore, the process of obtaining the tension difference under different simulation data sets in the simulation model includes:

[0016] The towing distance of the mine car during the transportation process is obtained. The towing distance refers to the length of the steel wire rope between the monitoring point and the drum device. The component force in the moving direction of the mine car is used as the actual tension, and a theoretical tension is preset for it;

[0017] The tension data, inclination data, load data, and actual tension at different towing distances are respectively used as a simulation data set. Each simulation data set is simulated in the simulation model, and the traction force at the drum device is adjusted so that the actual tension is equal to the preset theoretical tension;

[0018] The change in the traction force at the drum device when the actual tension is adjusted to the theoretical tension is used as the tension difference under the corresponding simulation data set. The tension difference includes positive and negative values.

[0019] Furthermore, the process of dynamically adjusting the mining transportation equipment according to the tension difference and obtaining different dynamic tension values includes:

[0020] Construct a viewable drawing of the towing distance of a mine car during transportation. The vertical coordinate of the viewable drawing of the towing distance represents different towing distances, and the horizontal coordinate represents the corresponding time. According to the simulation data sets at different towing distances, use a simulation model to obtain the corresponding pulling force difference;

[0021] Based on the currently provided pulling force, use the obtained pulling force difference to dynamically adjust the pulling force of the drum device, and continuously use the sum of the currently provided pulling force and the pulling force difference as the dynamic pulling force value at the corresponding time;

[0022] The dynamic adjustment means continuously adjusting the pulling force at the drum device to the dynamic pulling force value at the corresponding time, and constructing a viewable drawing of the dynamic pulling force according to the dynamic pulling force value.

[0023] Further, the process of constructing a pulling force adjustment model for mining transportation equipment according to different simulation data sets and their dynamic pulling force values includes:

[0024] Generate a pulling force adjustment set according to different simulation training sets and their corresponding dynamic pulling force values, and divide the obtained pulling force adjustment set into a training set and a test set;

[0025] Construct a convolutional neural network. Use different simulation training sets in the training set as the input data of the convolutional neural network, and use the corresponding dynamic pulling force values in the training set as the output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network;

[0026] Use the test set to verify the model of the initial convolutional neural network, and output the initial convolutional neural network with a test error threshold less than or equal to the preset value as the corresponding pulling force adjustment model.

[0027] Further, the process of using the pulling force adjustment model to dynamically adjust mining transportation equipment, setting an evaluation period to obtain the total number of adjustments of the mining transportation equipment, and determining whether there is an abnormally adjusted equipment includes:

[0028] Take the real-time towing distance, pulling force data, inclination angle data, load data, and actual pulling force of the mine car as the adjustment data set, input the adjustment data set into the pulling force adjustment model to output the corresponding dynamic pulling force value, and continuously adjust the pulling force at the corresponding drum device to the obtained dynamic pulling force value;

[0029] Set an evaluation period to obtain the total number of adjustments of the same mining transportation equipment in different evaluation periods. The total number of adjustments refers to the total number of dynamic adjustments of the mining transportation equipment in the corresponding evaluation period;

[0030] Number them as i in the order of the evaluation periods, i = 1, 2,..., n, where n is the number of evaluation periods, and record the total number of adjustments in different evaluation periods as S i, obtain the evaluation coefficient P of the mine transportation equipment in different evaluation cycles i ;

[0031]

[0032] Set an evaluation threshold. For the mine transportation equipment, when its evaluation coefficient is greater than the evaluation threshold, mark the mine transportation equipment in this evaluation cycle as an abnormal adjustment equipment. In other cases, no treatment is performed.

[0033] Furthermore, the process of generating corresponding optimization information based on the monitoring data of the abnormal adjustment equipment includes:

[0034] Obtain the monitoring data of the abnormal adjustment equipment in its corresponding evaluation cycle, set corresponding monitoring standards for the monitoring data, including tensile strength standards, inclination standards, and load standards, and compare the monitoring data with its monitoring standards to obtain the monitoring data in an abnormal state;

[0035] If the tensile strength data is in an abnormal state, it is determined that there is an abnormality in the drum device of the abnormal adjustment equipment, and device optimization information is generated to prompt relevant personnel to optimize the drum device;

[0036] If the inclination data is in an abnormal state, it is determined that there is an abnormality in the transportation track of the abnormal adjustment equipment, and track optimization information is generated to prompt relevant personnel to optimize the transportation track;

[0037] If the load data is in an abnormal state, it is determined that there is an abnormality in the mine car load of the abnormal adjustment equipment, and load optimization information is generated to prompt relevant personnel to optimize the mine car load. The optimization information includes device optimization information, track optimization information, and load optimization information.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] By constructing a physical model of the mine transportation equipment and its transportation track, and then constructing a simulation model of the two, the present invention can simulate the mine car under different working environments, which is beneficial to obtaining the tensile force difference between the traction force received by the mine car and the tensile force in its advancing direction. Furthermore, the mine transportation equipment is dynamically adjusted according to the tensile force difference, so that the tensile force in the advancing direction of the mine car always remains stable, and thus a stable driving speed and transportation capacity are maintained, avoiding the occurrence of safety accidents such as rollover and out-of-control caused by uneven tensile force;

[0040] By constructing a pulling force adjustment model, it is possible to directly obtain the corresponding dynamic pulling force value based on the real-time pulling distance, pulling force data, inclination data, load data, and actual pulling force of the mine car, thereby realizing the dynamic adjustment of mine transportation equipment. At the same time, the total number of adjustments within different evaluation periods is recorded and analyzed, which is conducive to indirectly reflecting whether there are abnormal conditions in the mine transportation equipment based on the adjustment situation and generating corresponding optimization information in a timely manner, and being able to discover and solve the safety problems of the mine car in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] As Figure 1 shown, a safety monitoring system for mine transportation equipment based on the Internet of Things includes the following modules:

[0043] A data acquisition module, which is used to obtain the equipment information and track information of the mine transportation equipment, construct a corresponding physical model, set monitoring points on the mine transportation equipment to obtain monitoring data, and construct a corresponding simulation model in combination with the physical model;

[0044] A data analysis module, which is used to obtain the pulling force difference under different simulation data sets in the simulation model, dynamically adjust the mine transportation equipment according to the pulling force difference, obtain different dynamic pulling force values, and construct a pulling force adjustment model for the mine transportation equipment according to different simulation data sets and their dynamic pulling force values;

[0045] A data evaluation module, which is used to dynamically adjust the mine transportation equipment by using the pulling force adjustment model, set an evaluation period to obtain the total number of adjustments of the mine transportation equipment, and judge whether there are abnormal adjustment devices, and generate corresponding optimization information according to the monitoring data of the abnormal adjustment devices.

[0046] It should be further noted that in the specific implementation process, the process of obtaining the equipment information and track information of the mine transportation equipment and constructing a corresponding physical model includes:

[0047] In the embodiment of the present invention, the mine transportation equipment refers to a mine car with a steel wire rope, which uses the steel wire rope to tow transportation tools such as mine cars to move up and down along the transportation track. It has the characteristics of simple structure, convenient operation, and large traction force, and is an indispensable equipment in mine track transportation;

[0048] The mine transportation equipment includes the following several component structures, namely a power device, a braking device, a transmission device, a drum device, a base, and a mine car, etc.;

[0049] Power device: It is used to provide the power required for the operation of the mine car, including an electric motor, an internal combustion engine, and a hydraulic motor;

[0050] Braking device: used to control the running speed and stop of the mine car, including a manual belt brake and a hydraulic pusher brake;

[0051] Transmission device: used to transmit power from the power device to the drum device, including a coupling, a reducer, and a main shaft device;

[0052] Drum device: used to wind the steel wire rope on the drum device, and realize traction or lifting through the rotation of the drum device;

[0053] Base and mine car: the support structure for the mine car, which can ensure the stability and safety of the mine car;

[0054] The equipment information refers to the specification parameters of the constituent structures included in the mine transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mine transportation equipment travels. The physical models of both are constructed using digital twin technology based on the obtained equipment information and track information.

[0055] It should be further noted that in the specific implementation process, the process of setting monitoring points on the mine transportation equipment to obtain monitoring data and constructing a corresponding simulation model in combination with the physical model includes:

[0056] The connection point between the mine car and the steel wire rope during transportation is used as the monitoring point. A tension monitoring unit and an inclination monitoring unit are respectively set at the monitoring point, and a load monitoring unit is set inside the mine car. The monitoring data includes tension data, inclination data, and load data;

[0057] The tension monitoring unit is used to monitor the tension of the steel wire rope at the monitoring point in real time to obtain tension data, and the load monitoring unit is used to monitor the loading weight of the mine car in real time to obtain load data;

[0058] The inclination monitoring unit is used to monitor the difference between the traction angle of the steel wire rope and the moving angle of the mine car in real time to obtain inclination data. The traction angle is the angle between the steel wire rope and the horizontal plane, the moving angle is the angle between the moving direction of the mine car and the horizontal plane, and the inclination data is the difference obtained by subtracting the moving angle from the traction angle at the same moment;

[0059] Based on the physical model, the drum device is used as the fixed end and the monitoring point is used as the free end. The transportation process of the mine transportation equipment on the transportation track is simulated using simulation software to obtain the corresponding simulation model. The simulation model can simulate the transportation process of the mine transportation equipment and obtain the force condition of the steel wire rope.

[0060] It should be further noted that in the specific implementation process, the process of obtaining the tension difference under different simulation data sets in the simulation model includes:

[0061] Obtain the towing distance of the mine car during transportation. The towing distance refers to the length of the steel wire rope between the monitoring point and the drum device. Take the component force in the moving direction of the mine car as the actual pulling force, and preset a theoretical pulling force for it. The theoretical pulling force is used to reflect the pulling force expected to be achieved in the moving direction of the mine car;

[0062] The pulling force data is consistent with the magnitude of the traction force provided at the drum device, and its direction is also consistent with the traction direction of the steel wire rope. Due to the changes in the towing distance, inclination data, and load data, the actual pulling force will also change accordingly, while the pulling force data is default fixed at this time;

[0063] Take the pulling force data, inclination data, load data, and actual pulling force at different towing distances as a simulation data set respectively. Taking any simulation data set as an example, simulate this simulation data set in the simulation model. Due to the influence of the towing distance, inclination data, and load data, the actual pulling force is not equal to the pulling force data;

[0064] Therefore, the traction force at the drum device can be adjusted so that the actual pulling force is equal to the preset theoretical pulling force. Take the change of the traction force at the drum device when the actual pulling force is adjusted to the theoretical pulling force as the pulling force difference under this simulation data set. The pulling force difference includes positive and negative values.

[0065] It should be further noted that in the specific implementation process, the process of dynamically adjusting the mine transportation equipment according to the pulling force difference and obtaining different dynamic pulling force values includes:

[0066] When the pulling force difference is positive, it means that the drum device under the corresponding simulation data set needs to increase a pulling force difference on the basis of the currently provided traction force to make the actual pulling force equal to the theoretical pulling force;

[0067] When the pulling force difference is negative, it means that the drum device under the corresponding simulation data set needs to reduce a pulling force difference on the basis of the currently provided traction force to make the actual pulling force equal to the theoretical pulling force;

[0068] Taking any mine car as an example, construct a viewable towing distance diagram of the mine car during transportation. The ordinate of the towing distance viewable diagram is different towing distances, and the abscissa is the corresponding time. According to the simulation data sets at its different towing distances, use the simulation model to obtain the corresponding pulling force difference;

[0069] On the basis of the currently provided traction force, use the obtained pulling force difference to dynamically adjust the traction force of the drum device, and continuously take the sum of the currently provided traction force and the pulling force difference as the dynamic pulling force value at the corresponding time;

[0070] The dynamic adjustment refers to continuously adjusting the traction force at the reel device to the dynamic tensile force value at the corresponding moment, and constructing a dynamic tensile force visualization diagram based on the dynamic tensile force value. The ordinate of the dynamic tensile force visualization diagram is the dynamic tensile force value, and the abscissa is the corresponding moment.

[0071] It should be further noted that in the specific implementation process, the process of constructing the tensile force adjustment model of the mining transportation equipment according to different simulation data sets and their dynamic tensile force values includes:

[0072] Since obtaining the tensile force difference under different simulation data sets by using the simulation model and then obtaining the dynamic tensile force value is a complex calculation process, the present invention uses a machine learning algorithm to construct the tensile force adjustment model, and then directly obtains the corresponding dynamic tensile force value;

[0073] Generate a tensile force adjustment set according to different simulation training sets and their corresponding dynamic tensile force values, and divide the obtained tensile force adjustment set into a training set and a test set;

[0074] Construct a convolutional neural network, use different simulation training sets in the training set as the input data of the convolutional neural network, and use the corresponding dynamic tensile force values in the training set as the output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network;

[0075] Use the test set to verify the model of the initial convolutional neural network, and output the initial convolutional neural network whose test error threshold is less than or equal to the preset value as the corresponding tensile force adjustment model.

[0076] It should be further noted that in the specific implementation process, using the tensile force adjustment model to perform dynamic adjustment on the mining transportation equipment, setting an evaluation period to obtain the total number of adjustments of the mining transportation equipment, and judging whether there is an abnormally adjusted equipment includes:

[0077] Take the real-time traction distance, tensile force data, inclination angle data, load data, and actual tensile force of the mine car as the adjustment data set, input the adjustment data set into the tensile force adjustment model to output the corresponding dynamic tensile force value, and continuously adjust the traction force at the corresponding reel device to the obtained dynamic tensile force value;

[0078] Set an evaluation period. When the traction force at the reel device undergoes a dynamic adjustment once, it is regarded as one adjustment time, and obtain the total number of adjustments of the same mining transportation equipment within different evaluation periods. The total number of adjustments refers to the total number of dynamic adjustments of the mining transportation equipment within the corresponding evaluation period;

[0079] Number them in the order of the evaluation periods, denoted as i, i = 1, 2,..., n, where n is the number of evaluation periods, and denote the total number of adjustments within different evaluation periods as S i, obtain the evaluation coefficients of the mine transportation equipment in different evaluation cycles, denoted as P i ;

[0080]

[0081] Set an evaluation threshold. For the mine transportation equipment, no operation is performed on it. For the mine transportation equipment, when its evaluation coefficient is less than or equal to the evaluation threshold, no operation is performed on it. When its evaluation coefficient is greater than the evaluation threshold, the mine transportation equipment in this evaluation cycle is marked as an abnormal adjustment equipment.

[0082] It should be further noted that in the specific implementation process, the process of generating corresponding optimization information based on the monitoring data of the abnormal adjustment equipment includes:

[0083] Obtain the monitoring data of the abnormal adjustment equipment in its corresponding evaluation cycle, including tensile force data, inclination angle data, and load data, and set corresponding monitoring standards for each monitoring data, including tensile force standard, inclination angle standard, and load standard;

[0084] Compare the obtained monitoring data with their corresponding monitoring standards. If the monitoring data is less than or equal to the monitoring standard, mark it as the normal state. If the monitoring data is greater than the monitoring standard, mark it as the abnormal state;

[0085] If the tensile force data is in the abnormal state, it is determined that there is an abnormality in the drum device of the abnormal adjustment equipment, and the corresponding device optimization information is generated to prompt relevant personnel to optimize the drum device;

[0086] If the inclination angle data is in the abnormal state, it is determined that there is an abnormality in the transportation track of the abnormal adjustment equipment, and the corresponding track optimization information is generated to prompt relevant personnel to optimize the transportation track;

[0087] If the load data is in the abnormal state, it is determined that there is an abnormality in the mine load of the abnormal adjustment equipment, and the corresponding load optimization information is generated to prompt relevant personnel to optimize the mine load. The optimization information includes device optimization information, track optimization information, and load optimization information.

[0088] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A safety monitoring system for mining transportation equipment based on the Internet of Things, characterized in that, It includes the following modules: A data acquisition module, which is used to obtain the device information of the mine transportation equipment and its track information, construct a corresponding physical model, set monitoring points on the mine transportation equipment to obtain monitoring data, and construct a corresponding simulation model in combination with the physical model; A data analysis module, which is used to obtain the pulling force difference under different simulation data sets in the simulation model, dynamically adjust the mine transportation equipment according to the pulling force difference, obtain different dynamic pulling force values, and construct a pulling force adjustment model for the mine transportation equipment according to different simulation data sets and their dynamic pulling force values; A data evaluation module, which is used to dynamically adjust the mine transportation equipment by using the pulling force adjustment model, set an evaluation period to obtain the total number of adjustments of the mine transportation equipment, and determine whether there is an abnormally adjusted device, and generate corresponding optimization information according to the monitoring data of the abnormally adjusted device; The process of dynamically adjusting the mine transportation equipment and obtaining the dynamic pulling force value includes: Construct a visible view of the traction distance of the mine car during transportation. The ordinate of the visible view of the traction distance is different traction distances, and the abscissa is the corresponding moment. According to the simulation data sets at different traction distances, use the simulation model to obtain the corresponding pulling force difference; On the basis of the currently provided traction force, dynamically adjust the traction force of the drum device by using the obtained pulling force difference, and continuously use the sum of the currently provided traction force and the pulling force difference as the dynamic pulling force value at the corresponding moment; The dynamic adjustment means continuously adjusting the traction force at the drum device to the dynamic pulling force value at the corresponding moment, and constructing a visible view of the dynamic pulling force according to the dynamic pulling force value.

2. The safety monitoring system for mining transportation equipment based on the Internet of Things according to claim 1, wherein, The process of constructing the physical model of the mine transportation equipment includes: The mine transportation equipment refers to a mine car with a steel wire rope. The mine car is towed up and down along the transportation track by the steel wire rope, and includes the following several component structures, namely a power device, a braking device, a transmission device, a drum device, a base and a mine car; The device information refers to the specification parameters of the component structures included in the mine transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mine transportation equipment travels. Use digital twin technology to construct the physical models of the two according to the obtained device information and track information.

3. The safety monitoring system for mine transportation equipment based on the Internet of Things according to claim 2, wherein, The process of obtaining monitoring data and constructing a simulation model in combination with the physical model includes: Take the connection point between the mine car and the steel wire rope during transportation as the monitoring point, set a pulling force monitoring unit and an inclination monitoring unit at the monitoring point, and set a load monitoring unit inside the mine car, and obtain the corresponding monitoring data, including pulling force data, inclination data, and load data; On the basis of the physical model, use simulation software to simulate the transportation process of the mine transportation equipment on the transportation track to obtain a corresponding simulation model. The simulation model is used to simulate the transportation process of the mine transportation equipment and obtain the force condition of the steel wire rope.

4. The safety monitoring system for mine transportation equipment based on the Internet of Things according to claim 3, wherein The process of obtaining the pulling force difference under different simulation data sets in the simulation model includes: Obtain the traction distance of the mine car during transportation. The traction distance refers to the length of the steel wire rope between the monitoring point and the drum device. Take the component force received in the moving direction of the mine car as the actual pulling force, and preset a theoretical pulling force for it; Take the tensile force data, inclination angle data, load data, and actual tensile force at different traction distances as a simulation data set respectively, simulate each simulation data set in the simulation model, and adjust the traction force at the drum device so that the actual tensile force is equal to the preset theoretical tensile force; Take the change in the traction force at the drum device when the actual tensile force is adjusted to the theoretical tensile force as the tensile force difference under the corresponding simulation data set, and the tensile force difference includes positive and negative values.

5. The safety monitoring system for mine transportation equipment based on the Internet of Things according to claim 4, characterized in that, The process of constructing the tensile force adjustment model of the mine transportation equipment includes: Generate a tensile force adjustment set according to different simulation training sets and their corresponding dynamic tensile force values, and divide the obtained tensile force adjustment set into a training set and a test set; Construct a convolutional neural network, take different simulation training sets in the training set as the input data of the convolutional neural network, and take the corresponding dynamic tensile force values in the training set as the output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network; Use the test set to verify the model of the initial convolutional neural network, and output the initial convolutional neural network with a test error threshold less than or equal to the preset value as the corresponding tensile force adjustment model.

6. The safety monitoring system for mine transportation equipment based on the Internet of Things according to claim 5, characterized in that, The process of obtaining the total number of adjustments and judging whether there is an abnormal adjustment device includes: Take the real-time traction distance, tensile force data, inclination angle data, load data, and actual tensile force of the mine car as the adjustment data set, input the adjustment data set into the tensile force adjustment model to output the corresponding dynamic tensile force value, and continuously adjust the traction force at the corresponding drum device to the obtained dynamic tensile force value; Set an evaluation period, and obtain the total number of adjustments of the same mine transportation equipment in different evaluation periods. The total number of adjustments refers to the total number of dynamic adjustments of the mine transportation equipment in the corresponding evaluation period; Number them as i in the order of the evaluation periods, where i = 1, 2, ……, n, and n is the number of evaluation periods. Denote the total number of adjustments in different evaluation periods as S i , and obtain the evaluation coefficient P of the mining transportation equipment in different evaluation periods i ; Set an evaluation threshold. For mining transportation equipment, when its evaluation coefficient is greater than the evaluation threshold, mark the mining transportation equipment in this evaluation period as abnormal adjustment equipment. In all other cases, no treatment is performed.

7. The safety monitoring system for mining transportation equipment based on the Internet of Things according to claim 6, wherein, The process of generating optimization information according to the monitoring data of the abnormal adjustment device includes: Obtain the monitoring data of the abnormal adjustment device in its corresponding evaluation period, set corresponding monitoring standards for each monitoring data, including tensile force standard, inclination angle standard, and load standard, and compare each monitoring data with its monitoring standard to obtain the monitoring data in an abnormal state; If the tensile force data is in an abnormal state, it is judged that there is an abnormality in the drum device of the abnormal adjustment device, and device optimization information is generated to prompt relevant personnel to optimize the drum device; If the inclination angle data is in an abnormal state, it is judged that there is an abnormality in the transportation track of the abnormal adjustment device, and track optimization information is generated to prompt relevant personnel to optimize the transportation track; If the load data is in an abnormal state, it is judged that there is an abnormality in the mine car load of the abnormal adjustment device, and load optimization information is generated to prompt relevant personnel to optimize the mine car load. The optimization information includes device optimization information, track optimization information, and load optimization information.

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