Mining transportation equipment safety monitoring system based on Internet of Things

Abstract

The invention discloses a mining transportation equipment safety monitoring system based on the Internet of Things, and relates to the technical field of equipment monitoring. The method comprises the steps of constructing a physical model of the mining transportation equipment, setting a monitoring point to obtain monitoring data, constructing a simulation model of the mining transportation equipment in combination with the physical model, obtaining tension differences under different simulation data sets in the simulation model, dynamically adjusting the mining transportation equipment and obtaining different dynamic tension values. The method comprises the following steps: constructing a tension adjustment model of the mining transportation equipment, dynamically adjusting the mining transportation equipment by using the tension adjustment model, setting an evaluation period to obtain the total number of times of adjustment of the mining transportation equipment, judging whether abnormal adjustment equipment exists or not, and generating corresponding optimization information; the tension in the advancing direction of the mine car can be kept stable all the time, then the stable running speed and transportation capacity are kept, and safety accidents such as rollover and out-of-control caused by uneven tension are avoided.

Description

Technical Field

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

[0002] Safety monitoring of mining transportation equipment is a system that integrates advanced technologies such as the Internet of Things, sensor technology, data analysis and intelligent algorithms. It aims to improve the safety and efficiency of mining transportation equipment. With the continuous development of existing technologies and the expansion of application scenarios, the system will play an increasingly important role in mine safety supervision. In the prior art, due to the particularity of the mining environment, there are many unavoidable influencing factors on the operation of mining transportation equipment, which makes it impossible to keep the pulling force on the forward direction of the mine car constant, thereby affecting the driving speed and transportation capacity of the mine car, and even causing safety accidents such as rollover and loss of control. How to maintain a stable pulling force on the forward direction of the mine car and timely discover potential influencing factors is a technical problem that needs to be solved at present. In view of the shortcomings of the prior art, the present invention provides a mining transportation equipment safety monitoring system based on the Internet of Things. Summary of the invention

[0003] The purpose of the present invention is to provide a mining transportation equipment safety monitoring system based on the Internet of Things.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A mining transportation equipment safety monitoring system based on the Internet of Things, comprising the following modules: The data acquisition module is used to obtain the equipment information and track information of the mining transportation equipment, and build the corresponding physical model, set monitoring points on the mining transportation equipment to obtain monitoring data, and build the corresponding simulation model in combination with the physical model; A data analysis module is used to obtain the tension difference under different simulation data sets in the simulation model, dynamically adjust the mining transportation equipment according to the tension difference, and obtain different dynamic tension values, and build a tension adjustment model for the mining transportation equipment according to different simulation data sets and their dynamic tension values; The data evaluation module is used to dynamically adjust the mining transportation equipment using the tension adjustment model, set the evaluation cycle to obtain the total number of adjustments of the mining transportation equipment, and determine whether there are abnormal adjustment equipment, and generate corresponding optimization information based on the monitoring data of the abnormal adjustment equipment.

[0005] Furthermore, the process of obtaining the equipment information and track information of the mining transportation equipment and constructing the corresponding physical model includes: The mining transport equipment refers to a mine car with a steel wire rope, which is pulled up and down along the transport track by the steel wire rope, and includes the following components, namely a power device, a brake device, a transmission device, a drum device, a base and a mine car; The equipment information refers to the specification parameters of the component structure contained in the mining transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mining transportation equipment follows. Digital twin technology is used to construct physical models of the two based on the obtained equipment information and track information.

[0006] Furthermore, the process of setting monitoring points on the mining transportation equipment to obtain monitoring data and building a corresponding simulation model in combination with the physical model includes: The connection point between the mine car and the wire rope during transportation is used as a monitoring point, and a tension monitoring unit and an inclination monitoring unit are set at the monitoring point. A load monitoring unit is set inside the mine car, and corresponding monitoring data, including tension data, inclination data, and load data, are obtained; On the basis of the physical model, the transportation process of the mining transportation equipment on the transportation track is simulated by using simulation software to obtain a corresponding simulation model, wherein the simulation model is used to simulate the transportation process of the mining transportation equipment and obtain the stress condition of the wire rope.

[0007] Furthermore, the process of obtaining the tension difference under different simulation data sets in the simulation model includes: Obtain the traction distance of the mine car during transportation, where the traction distance refers to the length of the wire rope between the monitoring point and the drum device, and take the component force received in the moving direction of the mine car as the actual pulling force, and preset the theoretical pulling force for it; The pulling force data, inclination data, load data and actual pulling force at different pulling distances are respectively taken as a simulation data set, and each simulation data set is simulated in the simulation model, and the pulling force at the reel device is adjusted so that the actual pulling force is equal to the preset theoretical pulling force; The change of the traction force at the reel device when the actual tension is adjusted to the theoretical tension is taken as the tension difference under the corresponding simulation data set, and the tension difference includes positive and negative values.

[0008] Furthermore, the process of dynamically adjusting the mining transportation equipment according to the tension difference and obtaining different dynamic tension values ​​includes: Construct a visual graph of the traction distance of the mine car during transportation, wherein the ordinate of the visual graph of the traction distance is different traction distances, and the abscissa is the corresponding time. According to the simulation data sets at different traction distances, the corresponding pulling force difference is obtained using the simulation model; Based on the currently provided traction force, the traction force of the winding device is dynamically adjusted using the obtained traction force difference, and the sum of the currently provided traction force and the traction force difference is continuously used as the dynamic traction force value at the corresponding moment; The dynamic adjustment refers to continuously adjusting the traction force at the reel device to the dynamic tension value at the corresponding moment, and constructing a dynamic tension visual graph according to the dynamic tension value.

[0009] Furthermore, the process of constructing a tension adjustment model for mining transportation equipment according to different simulation data sets and their dynamic tension values ​​includes: Generate a tension adjustment set according to different simulation training sets and their corresponding dynamic tension values, and divide the obtained tension adjustment set into a training set and a test set; Constructing a convolutional neural network, taking different simulation training sets in the training set as input data of the convolutional neural network, taking the corresponding dynamic tension values ​​in the training set as output data of the convolutional neural network, and training the convolutional neural network to obtain an initial convolutional neural network; The test set is used to verify the model of the initial convolutional neural network, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding tension adjustment model.

[0010] Furthermore, the process of dynamically adjusting the mining transportation equipment by using the tension adjustment model, setting an evaluation cycle to obtain the total number of adjustments of the mining transportation equipment, and determining whether there is abnormal adjustment equipment includes: The real-time traction distance, pulling force data, inclination data, load data, and actual pulling force of the mine car are used as an adjustment data set, and the adjustment data set is input into the pulling force adjustment model to output the corresponding dynamic pulling force value, and the traction force at the corresponding winding device is continuously adjusted to the obtained dynamic pulling force value; Setting an evaluation cycle, obtaining the total number of adjustments of the same mining transport equipment in different evaluation cycles, wherein the total number of adjustments refers to the total number of dynamic adjustments of the mining transport equipment in the corresponding evaluation cycle; According to the order of evaluation cycles, they are numbered as i, i=1, 2, ..., n, n is the number of evaluation cycles, and the total number of adjustments in different evaluation cycles is recorded as S i , obtain the evaluation coefficient P of mining transportation equipment in different evaluation cycles i ;

[0011] Set the evaluation threshold for For mining transportation equipment, when its evaluation coefficient is greater than the evaluation threshold, the mining transportation equipment in the evaluation period will be marked as abnormal adjustment equipment. In other cases, no processing will be done.

[0012] Furthermore, the process of generating corresponding optimization information according to the monitoring data of the abnormal adjustment equipment includes: Obtain various monitoring data of the abnormal adjustment equipment in its corresponding evaluation period, set corresponding monitoring standards for various monitoring data, including tension standard, inclination standard, and load standard, and compare various monitoring data with their monitoring standards to obtain monitoring data in abnormal state; If the tension data is in an abnormal state, it is determined that the reel device of the abnormal adjustment equipment is abnormal, and device optimization information is generated to prompt relevant personnel to optimize the reel device; If the inclination data is in an abnormal state, it is determined that the transport track of the abnormal adjustment equipment is abnormal, and track optimization information is generated to prompt relevant personnel to optimize the transport track; If the load data is in an abnormal state, it is judged that there is an abnormality in the load of the mine car of the abnormal adjustment equipment, and load optimization information is generated to prompt relevant personnel to optimize the load of the mine car. The optimization information includes device optimization information, track optimization information, and load optimization information.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention constructs a physical model of mining transportation equipment and its transportation track, and then constructs a simulation model of the two, so as to simulate the mining car under different working environments, which is conducive to obtaining the tension difference between the traction force on the mining car and the pulling force in its forward direction, and then dynamically adjusts the mining transportation equipment according to the pulling force difference, so that the pulling force in the forward direction of the mining car is always kept stable, thereby maintaining a stable driving speed and transportation capacity, and avoiding the occurrence of safety accidents such as rollover and loss of control caused by uneven pulling force; By constructing a tension adjustment model, the corresponding dynamic tension value can be directly obtained according to the real-time traction distance, tension data, inclination data, load data, and actual tension of the mine car, thereby realizing dynamic adjustment of the mining transportation equipment. At the same time, the total number of adjustments in different evaluation cycles is recorded and analyzed, which is beneficial to reflect whether there are abnormal conditions in the mining transportation equipment according to the adjustment situation, and to generate corresponding optimization information in time, so as to timely discover and solve the safety problems of the mine car. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0015] like Figure 1 As shown, a mining transportation equipment safety monitoring system based on the Internet of Things includes the following modules: The data acquisition module is used to obtain the equipment information and track information of the mining transportation equipment, and build the corresponding physical model, set monitoring points on the mining transportation equipment to obtain monitoring data, and build the corresponding simulation model in combination with the physical model; A data analysis module is used to obtain the tension difference under different simulation data sets in the simulation model, dynamically adjust the mining transportation equipment according to the tension difference, and obtain different dynamic tension values, and build a tension adjustment model for the mining transportation equipment according to different simulation data sets and their dynamic tension values; The data evaluation module is used to dynamically adjust the mining transportation equipment using the tension adjustment model, set the evaluation cycle to obtain the total number of adjustments of the mining transportation equipment, and determine whether there are abnormal adjustment equipment, and generate corresponding optimization information based on the monitoring data of the abnormal adjustment equipment.

[0016] It should be further explained that, in the specific implementation process, the process of obtaining the equipment information and track information of the mining transportation equipment and building the corresponding physical model includes: In the embodiment of the present invention, the mining transportation equipment refers to a mine car with a steel wire rope, which is pulled by the steel wire rope to move up and down along the transportation track. It has the characteristics of simple structure, convenient operation, large traction force, etc., and is an indispensable equipment in mine rail transportation; The mining transportation equipment includes the following components, namely a power device, a braking device, a transmission device, a winding device, a base and a mining car; Power device: used to provide the power required for the operation of the mine car, including electric motors, internal combustion engines, and hydraulic motors; Braking device: used to control the speed and stop of the mine car, including manual band brake and hydraulic push rod brake; Transmission device: used to transmit power from the power device to the reel device, including coupling, reducer, and spindle device; Reel device: used to wind the steel wire rope around the reel device, and achieve traction or lifting through the rotation of the reel device; Base and mine car: the mine car and its supporting structure, which can ensure the stability and safety of the mine car; The equipment information refers to the specification parameters of the component structure contained in the mining transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mining transportation equipment follows. Digital twin technology is used to construct physical models of the two based on the obtained equipment information and track information.

[0017] It should be further explained that, in the specific implementation process, the process of setting monitoring points on the mining transportation equipment to obtain monitoring data and building a corresponding simulation model in combination with the physical model includes: The connection point between the mine car and the wire rope during transportation is used as a monitoring point, and 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, and the monitoring data includes tension data, inclination data, and load data; The tension monitoring unit is used to monitor the tension of the wire rope at the monitoring point in real time to obtain tension data, and the load monitoring unit is used to monitor the load weight of the mine car in real time to obtain load data; The inclination monitoring unit is used to monitor the difference between the traction angle of the 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 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 equal to the difference obtained by subtracting the moving angle from the traction angle at the same time; On the basis of the physical model, the drum device is taken as the fixed end and the monitoring point as the free end, and the transportation process of the mining transportation equipment on the transportation track is simulated by using simulation software to obtain the corresponding simulation model. The simulation model can simulate the transportation process of the mining transportation equipment and obtain the stress condition of the wire rope.

[0018] It should be further explained that, in the specific implementation process, the process of obtaining the tension difference under different simulation data sets in the simulation model includes: Obtain the traction distance of the mine car during transportation, where the traction distance refers to the length of the 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, which is used to reflect the pulling force expected to be achieved in the moving direction of the mine car; The pulling force data is consistent with the traction force provided by the drum device, and its direction is also consistent with the traction direction of the wire rope. Due to the changes in the traction distance, inclination data, and load data, the actual pulling force will also change accordingly, and the pulling force data is fixed by default at this time; The pulling force data, inclination data, load data and actual pulling force at different pulling distances are respectively taken as a simulation data set. Taking any simulation data set as an example, the simulation data set is simulated in the simulation model. Due to the influence of the pulling distance, inclination data and load data, the actual pulling force is not equal to the pulling force data. Therefore, the traction force at the reel device can be adjusted so that the actual tension is equal to the preset theoretical tension, and the change of the traction force at the reel device when the actual tension is adjusted to the theoretical tension can be used as the tension difference under the simulation data set, and the tension difference includes positive and negative values.

[0019] It should be further explained that, in the specific implementation process, the process of dynamically adjusting the mining transportation equipment according to the tension difference and obtaining different dynamic tension values ​​includes: When the tension difference is a positive value, it means that the reel device under the corresponding simulation data set needs to add a tension difference on the basis of the currently provided traction force in order to make the actual tension equal to the theoretical tension; When the tension difference is a negative value, it means that the reel device under the corresponding simulation data set needs to reduce a tension difference based on the currently provided traction force in order to make the actual tension equal to the theoretical tension; Taking any mine car as an example, a visual graph of the traction distance of the mine car during transportation is constructed, wherein the ordinate of the visual graph of traction distance is different traction distances, and the abscissa is the corresponding time. According to the simulation data sets at different traction distances, the corresponding pulling force difference is obtained using the simulation model; Based on the currently provided traction force, the traction force of the winding device is dynamically adjusted using the obtained traction force difference, and the sum of the currently provided traction force and the traction force difference is continuously used as the dynamic traction force value at the corresponding moment; The dynamic adjustment refers to continuously adjusting the traction force at the reel device to the dynamic tension value at the corresponding moment, and constructing a dynamic tension visual graph based on the dynamic tension value, wherein the ordinate of the dynamic tension visual graph is the dynamic tension value and the abscissa is the corresponding moment.

[0020] It should be further explained that, in the specific implementation process, the process of constructing the tension adjustment model of mining transportation equipment according to different simulation data sets and their dynamic tension values ​​includes: Since it is a complex calculation process to obtain the tension difference under different simulation data sets using a simulation model and then obtain the dynamic tension value, the present invention uses a machine learning algorithm to construct a tension adjustment model and then directly obtain the corresponding dynamic tension value; Generate a tension adjustment set according to different simulation training sets and their corresponding dynamic tension values, and divide the obtained tension adjustment set into a training set and a test set; Constructing a convolutional neural network, taking different simulation training sets in the training set as input data of the convolutional neural network, taking the corresponding dynamic tension values ​​in the training set as output data of the convolutional neural network, and training the convolutional neural network to obtain an initial convolutional neural network; The test set is used to verify the model of the initial convolutional neural network, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding tension adjustment model.

[0021] It should be further explained that, in the specific implementation process, the process of dynamically adjusting the mining transportation equipment using the tension adjustment model, setting the evaluation cycle to obtain the total number of adjustments of the mining transportation equipment, and judging whether there is abnormal adjustment equipment includes: The real-time traction distance, pulling force data, inclination data, load data, and actual pulling force of the mine car are used as an adjustment data set, and the adjustment data set is input into the pulling force adjustment model to output the corresponding dynamic pulling force value, and the traction force at the corresponding winding device is continuously adjusted to the obtained dynamic pulling force value; An evaluation cycle is set. When the traction force at the drum device undergoes a dynamic adjustment, it is regarded as an adjustment number. The total number of adjustments of the same mining transport equipment in different evaluation cycles is obtained. The total number of adjustments refers to the total number of dynamic adjustments of the mining transport equipment in the corresponding evaluation cycle. The evaluation cycles are numbered in the order of their sequence, denoted as i, i=1, 2, ..., n, where n is the number of evaluation cycles, and the total number of adjustments in different evaluation cycles is denoted as S i , obtain the evaluation coefficient of mining transportation equipment in different evaluation cycles, denoted as P i ;

[0022] Set the evaluation threshold for Mining transport equipment, without any operation, For mining 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 mining transportation equipment in the evaluation period is marked as abnormal adjustment equipment.

[0023] It should be further explained that, in the specific implementation process, the process of generating corresponding optimization information according to the monitoring data of the abnormal adjustment equipment includes: Obtain various monitoring data of the abnormal adjustment equipment within its corresponding evaluation period, including tension data, inclination data, and load data, and set corresponding monitoring standards for each monitoring data, including tension standard, inclination standard, and load standard; Compare the acquired monitoring data with the corresponding monitoring standards. If the monitoring data is less than or equal to the monitoring standard, it is marked as a normal state. If the monitoring data is greater than the monitoring standard, it is marked as an abnormal state. If the tension data is in an abnormal state, it is determined that the reel device of the abnormal adjustment equipment is abnormal, and corresponding device optimization information is generated to prompt relevant personnel to optimize the reel device; If the inclination data is in an abnormal state, it is determined that the transport track of the abnormal adjustment equipment is abnormal, and corresponding track optimization information is generated to prompt relevant personnel to optimize the transport track; If the load data is in an abnormal state, it is judged that there is an abnormality in the load of the mine car of the abnormal adjustment equipment, and corresponding load optimization information is generated to prompt relevant personnel to optimize the load of the mine car. The optimization information includes device optimization information, track optimization information, and load optimization information.

[0024] 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 skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A mining transportation equipment safety monitoring system based on the Internet of Things, characterized in that: Includes the following modules: The data acquisition module is used to obtain the equipment information and track information of the mining transportation equipment, and build the corresponding physical model, set monitoring points on the mining transportation equipment to obtain monitoring data, and build the corresponding simulation model in combination with the physical model; A data analysis module is used to obtain the tension difference under different simulation data sets in the simulation model, dynamically adjust the mining transportation equipment according to the tension difference, and obtain different dynamic tension values, and build a tension adjustment model for the mining transportation equipment according to different simulation data sets and their dynamic tension values; The data evaluation module is used to dynamically adjust the mining transportation equipment using the tension adjustment model, set the evaluation cycle to obtain the total number of adjustments of the mining transportation equipment, and determine whether there are abnormal adjustment equipment, and generate corresponding optimization information based on the monitoring data of the abnormal adjustment equipment.

2. According to the Internet of Things-based mining transportation equipment safety monitoring system of claim 1, it is characterized in that: The process of building a physical model of mining haulage equipment includes: The mining transport equipment refers to a mine car with a steel wire rope, which is pulled up and down along the transport track by the steel wire rope, and includes the following components, namely a power device, a brake device, a transmission device, a drum device, a base and a mine car; The equipment information refers to the specification parameters of the component structure contained in the mining transportation equipment, and the track information refers to the specification parameters of the transportation track along which the mining transportation equipment follows. Digital twin technology is used to construct physical models of the two based on the obtained equipment information and track information.

3. The mining transportation equipment safety monitoring system based on the Internet of Things according to claim 2 is characterized in that: The process of obtaining monitoring data and building a simulation model in combination with the physical model includes: The connection point between the mine car and the wire rope during transportation is used as a monitoring point, and a tension monitoring unit and an inclination monitoring unit are set at the monitoring point. A load monitoring unit is set inside the mine car, and corresponding monitoring data, including tension data, inclination data, and load data, are obtained; On the basis of the physical model, the transportation process of the mining transportation equipment on the transportation track is simulated by using simulation software to obtain a corresponding simulation model, wherein the simulation model is used to simulate the transportation process of the mining transportation equipment and obtain the stress condition of the wire rope.

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

5. The mining transportation equipment safety monitoring system based on the Internet of Things according to claim 4 is characterized in that: The process of dynamically adjusting mining transport equipment and obtaining dynamic tension values ​​includes: Construct a visual graph of the traction distance of the mine car during transportation, wherein the ordinate of the visual graph of the traction distance is different traction distances, and the abscissa is the corresponding time. According to the simulation data sets at different traction distances, the corresponding pulling force difference is obtained using the simulation model; Based on the currently provided traction force, the traction force of the winding device is dynamically adjusted using the obtained traction force difference, and the sum of the currently provided traction force and the traction force difference is continuously used as the dynamic traction force value at the corresponding moment; The dynamic adjustment refers to continuously adjusting the traction force at the reel device to the dynamic tension value at the corresponding moment, and constructing a dynamic tension visual graph according to the dynamic tension value.

6. The mining transportation equipment safety monitoring system based on the Internet of Things according to claim 5 is characterized in that: The process of building a tension regulation model for mining transport equipment includes: Generate a tension adjustment set according to different simulation training sets and their corresponding dynamic tension values, and divide the obtained tension adjustment set into a training set and a test set; Constructing a convolutional neural network, taking different simulation training sets in the training set as input data of the convolutional neural network, taking the corresponding dynamic tension values ​​in the training set as output data of the convolutional neural network, and training the convolutional neural network to obtain an initial convolutional neural network; The test set is used to verify the model of the initial convolutional neural network, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding tension adjustment model.

7. The mining transportation equipment safety monitoring system based on the Internet of Things according to claim 6 is characterized in that: The process of obtaining the total number of adjustments and determining whether there are abnormally adjusted devices includes: The real-time traction distance, pulling force data, inclination data, load data, and actual pulling force of the mine car are used as an adjustment data set, and the adjustment data set is input into the pulling force adjustment model to output the corresponding dynamic pulling force value, and the traction force at the corresponding winding device is continuously adjusted to the obtained dynamic pulling force value; Setting an evaluation cycle, obtaining the total number of adjustments of the same mining transport equipment in different evaluation cycles, wherein the total number of adjustments refers to the total number of dynamic adjustments of the mining transport equipment in the corresponding evaluation cycle; According to the order of evaluation cycles, they are numbered as i, i=1, 2, ..., n, n is the number of evaluation cycles, and the total number of adjustments in different evaluation cycles is recorded as S i , obtain the evaluation coefficient P of mining transportation equipment in different evaluation cycles i ; Set the evaluation threshold for For mining transportation equipment, when its evaluation coefficient is greater than the evaluation threshold, the mining transportation equipment in the evaluation period will be marked as abnormal adjustment equipment. In other cases, no processing will be done.

8. The mining transportation equipment safety monitoring system based on the Internet of Things according to claim 7 is characterized in that: The process of generating optimization information based on monitoring data of abnormally regulated equipment includes: Obtain various monitoring data of the abnormal adjustment equipment within its corresponding evaluation period, set corresponding monitoring standards for various monitoring data, including tension standard, inclination standard, and load standard, and compare various monitoring data with their monitoring standards to obtain monitoring data in abnormal state; If the tension data is in an abnormal state, it is determined that the reel device of the abnormal adjustment equipment is abnormal, and device optimization information is generated to prompt relevant personnel to optimize the reel device; If the inclination data is in an abnormal state, it is determined that the transport track of the abnormal adjustment equipment is abnormal, and track optimization information is generated to prompt relevant personnel to optimize the transport track; If the load data is in an abnormal state, it is judged that there is an abnormality in the load of the mine car of the abnormal adjustment equipment, and load optimization information is generated to prompt relevant personnel to optimize the load of the mine car. The optimization information includes device optimization information, track optimization information, and load optimization information.

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