Mine inspection system and inspection method

Abstract

The invention discloses a mine inspection system which comprises an inspection track fixedly arranged between two belt conveyors and an inspection robot running on the inspection track and comprising a driving module, a liftable mechanical arm and an inspection module. The inspection robot is used for inspecting equipment on the belt conveyor in a lifting mode and transmitting inspection data to the main control platform so that the main control platform can obtain an inspection result based on the inspection data, and the state monitoring device is used for monitoring operation state information of the belt conveyor and transmitting the operation state information to the main control platform. The main control platform is used for analyzing the running state information to obtain a belt conveyor state analysis result, and the main control platform is further used for controlling the inspection robot to conduct inspection task work. The method has the beneficial effect of improving the mine inspection efficiency.

Description

Technical Field

[0001] This invention relates to the field of mine inspection, and in particular to a mine inspection system, feedback method, and vehicle. Background Technology

[0002] In the field of mine inspection, traditional manual inspection has long been the mainstream method. However, with the continuous expansion of mining scale and the increasing complexity of the working environment, many drawbacks of this inspection method have gradually become apparent. Manual inspection is not only inefficient and has limited coverage, but it is also easily affected by subjective factors such as personnel experience and physical condition, leading to frequent problems such as missed or false inspections. In addition, mines are often accompanied by high-risk working environments such as gas explosions, collapses, and water inrushes. Manual inspection personnel are exposed to dangerous areas for a long time and face high risks to their lives. Coupled with long inspection times, high labor costs, and serious economic losses caused by equipment failures, traditional methods can no longer support the urgent needs of the mining industry for efficient, safe, and intelligent inspection.

[0003] With the rapid development of sensor technology, intelligent algorithms, and communication equipment, unmanned inspection technology has emerged as a key direction for the intelligent development of mines. Currently, many mining companies have attempted to introduce automated equipment such as drones to conduct high-frequency, high-coverage inspections to improve overall efficiency and safety. However, in practical applications, drones operating in complex mining environments are susceptible to signal interference, have limited endurance, and exhibit poor operational stability in adverse weather conditions. Therefore, there is an urgent need for a mine inspection system that can ensure inspection efficiency while comprehensively considering its stability. Summary of the Invention

[0004] The main objective of this invention is to provide a mine inspection system and method, aiming to solve the technical problem of insufficient inspection efficiency in related technologies.

[0005] To achieve the above objectives, the present invention provides a mine inspection system, which includes: The inspection track is fixedly installed between the two belt conveyors; The inspection robot runs on an inspection track and includes a drive module, a liftable robotic arm, and an inspection module. The inspection robot is used to inspect the equipment on the belt conveyor in a liftable manner and transmits the inspection data to the main control platform so that the main control platform can obtain the inspection results based on the inspection data. The status monitoring device is used to monitor the operating status information of the belt conveyor and transmit the operating status information to the main control platform so that the main control platform can analyze the operating status information and obtain the belt conveyor status analysis results. The main control platform is also used to control the inspection robot to perform inspection tasks.

[0006] In one embodiment, the condition monitoring device includes a belt tear detection module, which includes a line laser detection unit and an image collection unit; The belt tear detection module is used to transmit belt images to the main control platform, enabling the main control platform to identify the tear status of the belt conveyor; among which, The line laser detection unit is used to confirm whether the belt has been distorted based on the line laser characteristics on the belt surface; When distortion occurs on the belt surface, the image acquisition unit is used to collect the belt image scanned by the laser detection unit and transmit it to the main control platform.

[0007] In one embodiment, the condition monitoring device further includes a temperature and vibration monitoring module, which is used to detect the surface temperature data and vibration data of the belt conveyor assembly and transmit the surface temperature data and vibration data to the main control platform.

[0008] In one embodiment, the status monitoring device further includes a material flow monitoring module, which monitors the material flow data at the discharge port of the belt conveyor and transmits the material flow data to the main control platform.

[0009] In one embodiment, the inspection module further includes an image acquisition module, a thermal imaging acquisition module, an audio acquisition module, a smoke detection module, a temperature and humidity monitoring module, and a gas detection module.

[0010] In one embodiment, the mine inspection system further includes a charging device, which is located at the start and end positions of the inspection robot and is used to charge the inspection robot.

[0011] Furthermore, to achieve the above objectives, this application also provides a mine inspection method for the main control platform of the aforementioned mine inspection system, the method comprising: The system acquires the operating status information of the belt conveyor from the condition monitoring device, performs data analysis and processing on the operating status information, and obtains the condition analysis results of the belt conveyor. The inspection data is obtained from the inspection robot, and the inspection data is analyzed and processed to obtain the inspection results. Output status analysis results and inspection results.

[0012] In addition, to achieve the above objectives, the methods also include: Obtain the battery status of the inspection robot; If the inspection robot is in a low battery state, control the inspection robot to move to the charging device to charge. If the charging device cannot charge the robot, control the inspection robot to switch to another charging device.

[0013] In one embodiment, obtaining the operating status information of the belt conveyor from the status monitoring device, and performing data analysis and processing on the operating status information to obtain the status analysis result of the belt conveyor includes the following steps: Line laser detection is performed on the belt using a line laser detection unit to identify line laser features in the belt. Based on the characteristics of line laser, the distortion state of the belt is determined; If the belt is distorted, an image of the belt is acquired through the image collection unit; Perform belt image recognition on the belt image to obtain the image recognition result; Based on line laser characteristics and image recognition results, it is determined whether the belt is torn, and the condition analysis results of the belt conveyor are obtained.

[0014] In one embodiment, the step of performing line laser detection on a belt image and identifying line laser features in the belt image includes: Based on the laser transmission speed and laser return time, the actual height of each point on the belt cross section is determined, and the belt deformation is determined based on the difference between the actual height and the reference height of each point on the belt cross section. The belt is checked for missing laser detection lines. If all laser detection lines are missing, the belt is broken. If a belt breakage is detected, the degree of belt breakage is determined based on the extent of the absence of all detected laser detection lines and the belt transport time. The surface roughness of the belt is determined based on the lateral width of the line laser beam projected onto the belt. Based on belt deformation, belt breakage degree, and belt surface roughness, the characteristics of the line laser are determined.

[0015] The mine inspection system and method provided in this application, by setting inspection tracks between belt conveyors and combining them with inspection robots with lifting capabilities and multi-source status monitoring devices, realizes automated, intelligent, and high-frequency inspection of the operating status of mine equipment. This significantly improves inspection efficiency and coverage, reduces interference from subjective human factors, and reduces the exposure time of inspection personnel in hazardous environments. At the same time, the system supports multi-dimensional data acquisition and analysis, such as fault image recognition, temperature and vibration monitoring, and material flow detection. Combined with intelligent charging strategies, it enhances the stability and continuous operation capability of the system, effectively meeting the urgent need for efficient and safe inspection operations in complex mining scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the mine inspection system of the present invention.

[0018] Figure 2 This is a flowchart illustrating the mine inspection method of the present invention.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a mine inspection system according to an embodiment of the present invention. The mine inspection system includes: a mine inspection system, characterized in that the mine inspection system includes: The inspection track is fixedly installed between the two belt conveyors.

[0022] The inspection robot, which operates on an inspection track, includes a drive module, a liftable robotic arm, and an inspection module. The inspection robot is used for the liftable inspection of equipment on a conveyor belt and transmits the inspection data to the main control platform, enabling the platform to obtain inspection results based on the data.

[0023] The status monitoring device is used to monitor the operating status information of the belt conveyor and transmit the operating status information to the main control platform so that the main control platform can analyze the operating status information and obtain the belt conveyor status analysis results.

[0024] The main control platform is also used to control the inspection robot to perform inspection tasks.

[0025] Specifically, the mine inspection system mainly consists of inspection tracks, inspection robots, condition monitoring devices, and a main control platform.

[0026] Understandably, the inspection robot operates on the inspection track, is controlled by the main control platform, and performs inspection tasks (such as inspecting equipment running on the belt conveyor). The status monitoring device can monitor the status data of the equipment running on the mine (such as the operating status of the belt conveyor) in addition to the inspection tasks. The main control platform can analyze and display the data analysis results in real time.

[0027] The inspection track, serving as the motion carrier for the inspection robot, is the most important component of the track inspection robot system. The track is made of high-strength aluminum alloy profiles, with anodized and anti-salt spray treatment on the surface, providing high corrosion resistance and strong wear resistance. It is designed according to the spatial conditions of the project's transport area to adapt to conditions such as uphill, downhill, and turning.

[0028] Meanwhile, RFID tag information is also preset at fixed positions on the track to enable the inspection robot to be located. For example, the inspection robot includes a drive motor and an RFID reader. The drive motor includes a position encoder to achieve coarse positioning. Then, the RFID reader reads the RFID tag on the track to correct the error of the position encoder and achieve precise positioning of the inspection robot.

[0029] Understandably, dividing the mine inspection system into fixed-point monitoring (condition monitoring devices) and mobile inspection monitoring (inspection robots) can achieve comprehensive monitoring of the entire mining process. In addition, compared with using drones for mobile inspection, using tracked robots for inspection has the characteristics of strong stability and high inspection efficiency.

[0030] Furthermore, the inspection module also includes an image acquisition module, a thermal imaging acquisition module, an audio acquisition module, a smoke detection module, a temperature and humidity monitoring module, and a gas detection module.

[0031] The mine inspection system also includes a charging device, which is set at the start and end positions of the inspection robot to charge the robot.

[0032] For example, the track-mounted inspection robot is a core component of the entire mine inspection system, undertaking the main functions of inspection and on-site handling within the conveyor area. The main components of the inspection robot include: a vehicle body, a drive motor, a liftable robotic arm, a control box, obstacle avoidance sensors, a 360° all-angle camera (image acquisition module), an infrared thermal imaging lens (thermal imaging acquisition module), LED lighting fixtures, a smoke detector (smoke detection module), a temperature / humidity probe (temperature and humidity monitoring module), a four-in-one (CO, O2, CH4, SH2) gas sensor (gas detection module), and a microphone. The robot can utilize its liftable robotic arm (lifting range of 750mm) to broaden the inspection perspective, covering both equipment above and below the conveyor belt.

[0033] Multiple charging devices are installed at the start and end positions of the inspection track. After completing its inspection task, the inspection robot identifies and charges the charging device based on the RFID tag attached to it. If the current charging device cannot charge, it switches to another charging device. For example, the charging device can be a wireless charging station, using inductive coupling or magnetic resonance to wirelessly transmit power to the track-mounted inspection robot. Before the intelligent inspection robot confirms accurate positioning and connects to the charging device, the charging device is in a disabled state. After complete docking, the intelligent inspection robot transmits a signal, and the charging station connects and begins charging.

[0034] The main control platform is an intelligent inspection and control platform used for real-time management and control of robots performing online inspection tasks. Simultaneously, the inspection robot and other fixed-point intelligent monitoring devices can upload monitoring data and analysis results to the intelligent inspection and control platform via a self-organizing network communication device, enabling real-time monitoring and management of on-site equipment.

[0035] For example, the intelligent inspection and control platform is a one-stop monitoring and management platform for various types of IoT devices. It supports the integration of IoT devices such as inspection robots, fixed-point cameras, thermal imagers, and sensors, forming a comprehensive intelligent inspection and management platform centered on inspection robots. It provides various image and video algorithm models, enabling multi-target identification and analysis of people, equipment, and the environment. The platform is based on a B / S architecture web data browsing mode and operating platform, deployed on a central control room server. It supports multiple standard industrial protocol sets such as MODBUS, CAN, MQTT, HTTP, RTSP, and GB28181, enabling data interaction and linkage between external systems and the intelligent inspection and control platform.

[0036] Understandably, the self-organizing network communication device enables real-time communication and control between the on-site conveyor area and the back-end server. Wireless access points (APs) are deployed along the conveyor belt on-site, and track robots, charging piles, and intelligent camera groups connect to the local area network via wireless signals to transmit real-time images and control commands.

[0037] Servers and deployment accessories enable on-site deployment of the main control platform, completing the storage of monitoring videos and inspection data.

[0038] The condition monitoring device includes a belt tear detection module, which comprises a line laser detection unit and an image acquisition unit.

[0039] The belt tear detection module is used to transmit belt images to the main control platform, enabling the platform to identify the tear condition of the belt conveyor. The line laser detection unit is used to confirm whether the belt has been distorted based on the line laser characteristics on the belt surface.

[0040] When distortion occurs on the belt surface, the image acquisition unit is used to collect the belt image scanned by the laser detection unit and transmit it to the main control platform.

[0041] The condition monitoring device also includes a temperature and vibration monitoring module, which is used to detect the surface temperature and vibration data of the belt conveyor components and transmit the surface temperature and vibration data to the main control platform.

[0042] The status monitoring device also includes a material flow monitoring module, which is used to monitor the material flow data at the discharge port of the belt conveyor and transmit the material flow data to the main control platform.

[0043] Specifically, the condition monitoring device is a fixed-point monitoring device, which includes various monitoring devices fixed at corresponding positions on the belt conveyor for monitoring the operating status of the belt conveyor.

[0044] For example, the temperature and vibration monitoring device is attached to key equipment such as motors, reducers, and rollers using a special adhesive, and interacts with the main control platform via a wireless local area network. The temperature and vibration monitoring device can effectively collect temperature and vibration (horizontal, vertical, and axial) data of the equipment surface, and display them uniformly on the centralized control platform.

[0045] The belt tear monitoring device mainly consists of a fixed-point high-speed CCD optical camera, a laser emitter, and other accessories. The laser emitter is installed below the belt, and the monitoring device determines whether the belt has a tear by identifying the distortion of the auxiliary laser line.

[0046] Furthermore, it also includes intelligent camera groups, which are deployed at the machine head, tail, material discharge port, and above the belt conveyor to monitor for any abnormal phenomena such as unauthorized intrusion, smoking, failure to wear safety helmets, foreign objects, open flames, and smoke within the area. They also detect whether there are any abnormal phenomena such as material blockage at the material discharge port, belt deviation, or overturning, and locate the fault location to transmit the data information to the back-end monitoring platform, promptly alerting back-end management personnel for handling.

[0047] Furthermore, such as Figure 2 As shown, corresponding to the mine inspection system, this embodiment also provides a mine inspection method, which includes steps S10-S30: Step S10: Obtain the operating status information of the belt conveyor from the status monitoring device, perform data analysis and processing on the operating status information, and obtain the status analysis results of the belt conveyor.

[0048] Step S20: Obtain inspection data from the inspection robot, perform data analysis and processing on the inspection data, and obtain inspection results.

[0049] Step S30: Output the status analysis results and inspection results.

[0050] The method also includes steps T10-T30: Step T10: Obtain the battery status of the inspection robot; Step T20: If the inspection robot is in a low battery state, control the inspection robot to move to the charging device to charge. In step T30, if the charging device cannot charge the robot, control the inspection robot to switch to another charging device.

[0051] Step S10 includes steps S11-S14: Step S11: The belt is subjected to line laser detection by the line laser detection unit to identify the line laser features in the belt.

[0052] Step S12: Determine the distortion state of the belt based on the line laser characteristics.

[0053] Step S13: If the belt is distorted, the belt image is acquired through the image collection unit.

[0054] Step S14: Perform belt image recognition on the belt image to obtain the image recognition result. Step S15: Determine whether the belt is torn based on the line laser features and image recognition results, and obtain the condition analysis results of the belt conveyor.

[0055] Corresponding to the belt tear monitoring module, steps S11-S15 provide a belt tear detection method. For ease of understanding, exemplarily, a line laser beam is projected onto the bottom of the belt, following the belt's arc shape. As the belt moves, the line laser scans the belt. A high-speed camera is positioned at approximately a 45° elevation angle to the bottom of the belt on both sides, capturing images of the bottom of the belt in real time. When the texture of the belt bottom is abnormal (with cracks, tears, or other signs of impending tearing), the abnormal portion will distort when passing through the line laser (indicating that the belt surface is distorted and no longer smooth). At this time, the high-speed camera captures the image of the distorted line laser, which is then transmitted to the backend for image recognition technology (belt image recognition) to perform diagnostic analysis and issue an alarm. The location of the distortion is recorded, attracting the attention of monitoring personnel and prompting them to take appropriate measures.

[0056] The specific measures are detailed below: Step S12 includes steps A10 to A50: Step A10: Based on the laser transmission speed and laser return time, determine the actual height of each point on the belt cross section, and based on the difference between the actual height and the reference height of each point on the belt cross section, determine the belt deformation.

[0057] Step A20: Detect the degree of missing laser detection lines on the belt. If all laser detection lines are missing, the belt is broken.

[0058] Step A30: If a belt breakage is detected, the degree of belt breakage is determined based on the degree of missing laser detection lines and the belt transport time.

[0059] Step A40: Determine the surface roughness of the belt based on the lateral width of the line laser projection onto the belt.

[0060] Step A50: Determine the line laser characteristics based on belt deformation, belt breakage degree, and belt surface roughness.

[0061] Specifically, for laser detection, the core is laser center extraction. In this embodiment, the height deformation, fracture value, and surface roughness of the belt can be calculated and monitored using the returned laser point.

[0062] For belt deformation, a coordinate axis centered on the laser sensor is first constructed. Based on the laser transmission speed and return time, the actual height of the belt is calculated. Then, within 5 minutes of starting the belt under no-load conditions, the reference height of each point on the belt cross-section is obtained based on the average value. At this time, the deformation is the difference between the actual height and the reference height.

[0063] For belt integrity testing, for a single belt, a linear laser emitter creates three parallel laser detection lines (three lines bisect the belt, perpendicular to both sides). When the laser return from the first line indicates a gap, the second and third lines are monitored for gaps. If all three lines return gaps, a belt break is detected. When a belt break is detected, the span of the gap (i.e., the belt break length) on the third detection line is recorded. The width of the belt break is then calculated by combining the first and last detected gaps with the belt transport time. Both length and width measurements are in millimeters (mm).

[0064] For belt roughness, this embodiment achieves it through spot detection, that is, by confirming the lateral width of the laser stripe, that is, the absolute length of the projection of the returned laser point position and the laser emission point position on the x-axis.

[0065] For the issue of light spot width, Wm = current ideal surface fringe width, θ = surface tilt angle, K = material scattering coefficient, and S = surface roughness. The actual surface fringe width W = Wm / cos(θ) + K*S, where the material scattering system's scattering coefficient is estimated using the Kubelka-Munk model based on transmittance and haze, as shown in the following formula: Where H equals haze, T equals total transmittance, and R equals reflectance at infinite thickness.

[0066] Subsequently, a threshold range can be set, and the degree of belt deformation, the degree of belt breakage, and the surface roughness of the belt can be compared with the threshold to determine the line laser characteristics and judge whether the belt has been distorted.

[0067] For example, a threshold setting is made for laser detection of belt deformation, with the unit being millimeters (mm), and a value of 30-50 is suitable. For fracture detection, the units for both length and width detection are millimeters (mm), with a length value of 20-30 and a width value of 5-10 being suitable. For belt roughness, i.e., calculating the transverse width of the laser stripes, the threshold condition here is that the monitored value cannot exceed 30% of the previous monitored value.

[0068] Furthermore, if the degree of belt deformation, the degree of belt breakage, or the surface roughness of the belt is not within the threshold range, the belt image is then identified.

[0069] For image recognition of belt deformation, camera physical coordinate calibration and reference plane setting are required: After simultaneously starting the line laser and running the unloaded belt for 5 minutes, two values ​​need to be set. Measure the standard width of the belt, and then calculate the pixel value corresponding to the belt width in the camera image. Obtain the millimeter value corresponding to 1 pixel by calculating [actual width (mm) / number of pixels in a single column].

[0070] Furthermore, the calculation of the actual reference height corresponds to the elevation of the Y-axis, which needs to be combined with sub-pixel offset. The sub-pixel offset is calculated using Gaussian fitting: Δy = 0.5 * (upper point bright spot - lower point bright spot) / (upper point - 2 * current point + lower point), while the actual Y-axis elevation = current coordinate value + sub-pixel offset (where bright spot = the brightest value of each column of pixels).

[0071] For belt deformation issues, an alert is triggered if the current detection height deviates from the reference height by more than 3mm. For longitudinal belt tears, an alert is triggered if the interval between adjacent points multiplied by the pixel scale is greater than 1mm. For transverse tears, an alert is triggered if the interval between adjacent points multiplied by the pixel scale is greater than 2mm.

[0072] The laser detection result is compared with the image value. Taking the transverse tear of the belt as an example, when the laser detection value is 3mm, if the image detection result is within the range of 3*0.67=2mm, the detection result is considered true and the relevant management personnel are notified. If the value is higher or lower than this value, the comparison test is repeated (up to three times, and no test is performed after three inconsistencies), and the relevant technical personnel are notified to adjust and maintain the equipment and algorithm.

[0073] Understandably, the alarm from laser detection is used to initially determine the type of anomaly, and then image detection is used. Based on about twenty frames of image data, the accuracy of laser detection is verified by image algorithms. If the results of the two consecutive detections are consistent, it proves that an anomaly exists, thus improving the reliability of belt detection.

[0074] Furthermore, when performing image anomaly detection and verification, anti-interference processing needs to be added to ensure the accuracy of the results. Since ore materials often generate dust, dust interference needs to be eliminated.

[0075] The specific dust detection method is as follows: P = dust probability, ΔW / W: instantaneous width change rate, I_max / I_avg: ratio of maximum to average intensity, ▽²I: image Laplacian operator (edge ​​sharpness), α, β, γ: weighting coefficients (set to 0.39, 0.24, and 0.37 respectively based on multiple experiments). The formula is: P = α·(ΔW / W) + β·(I_max / I_avg) + γ·▽²I.

[0076] in, ; I refers to the grayscale value. When the dust probability P is greater than 0.7, the cleaning mechanism is triggered, at which point the vacuuming device and spraying device are activated to reduce dust.

[0077] Furthermore, regarding the material flow monitoring module, the material flow monitoring method of this application is exemplified as follows: The material flow monitoring device is installed approximately 3 meters downstream of the conveyor belt's discharge port. Point cloud data collected by a 3D structured light camera is used to fit a curve of the measured cross-section. Combined with the current conveyor belt speed, the current conveyor belt flow rate is calculated. Simultaneously, the flow rate value is transmitted back to the robot control platform. After receiving the data, the control platform displays historical curves and shows real-time changes in the flow rate value. When a change in the flow rate value is detected, and it drops to a certain threshold, the platform issues an alarm, indicating that a blockage or spillage may have occurred at the discharge port, causing a decrease in the downstream material flow rate.

[0078] It's easy to understand that the combination of "fixed monitoring + mobile inspection by tracked robots" enables all-weather, full-coverage, and all-element intelligent monitoring of mine conveyor belts and their surrounding environment: Tracked robots, with RFID-assisted precise positioning, stably and efficiently collect multi-dimensional information such as images, thermal imaging, sound, and gas; fixed-point status monitoring devices capture key data in real time, including temperature-vibration, laser-image composite tearing, and 3D point cloud material flow. All data is uniformly aggregated on a main control platform supporting multiple industrial protocols, and through algorithm cross-validation and dust anti-interference processing, the accuracy of fault detection and the reliability of alarms are significantly improved; wireless charging and self-organizing network communication ensure continuous equipment operation and low maintenance. Overall, this system significantly reduces the risks and missed detection rates of manual inspections, shortens fault response time, extends equipment life, and provides a scalable, integrated solution for digital operation and maintenance in mines.

[0079] The above are merely optional embodiments of the present invention and do not limit the patent scope of the present invention. All equivalent structural transformations made using the contents of the present invention specification and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A mine inspection system, characterized in that, The mine inspection system includes: The inspection track is fixedly installed between the two belt conveyors; An inspection robot, operating on the inspection track, includes a drive module, a liftable robotic arm, and an inspection module. The inspection robot is used to inspect equipment on the conveyor belt in a liftable manner and transmits the inspection data to the main control platform, so that the main control platform can obtain the inspection results based on the inspection data. A status monitoring device is used to monitor the operating status information of the belt conveyor and transmit the operating status information to the main control platform, so that the main control platform can analyze the operating status information and obtain the belt conveyor status analysis results. The main control platform is also used to control the inspection robot to perform inspection tasks.

2. The mine inspection system as described in claim 1, characterized in that, The condition monitoring device includes a belt tear detection module, which includes a line laser detection unit and an image collection unit. The belt tear detection module is used to transmit belt images to the main control platform, enabling the main control platform to identify the tear status of the belt conveyor; wherein... The line laser detection unit is used to confirm whether the belt has been distorted based on the line laser characteristics on the belt surface; When distortion occurs on the surface of the belt, the image collection unit is used to collect the belt image scanned by the laser detection unit and transmit it to the main control platform.

3. The mine inspection system as described in claim 2, characterized in that, The condition monitoring device also includes a temperature and vibration monitoring module, which is used to detect the surface temperature data and vibration data of the belt conveyor assembly, and transmit the surface temperature data and vibration data to the main control platform.

4. The mine inspection system as described in claim 3, characterized in that, The status monitoring device also includes a material flow monitoring module, which is used to monitor the material flow data at the discharge port of the belt conveyor and transmit the material flow data to the main control platform.

5. The mine inspection system as described in claim 1, characterized in that, The inspection module also includes an image acquisition module, a thermal imaging acquisition module, an audio acquisition module, a smoke detection module, a temperature and humidity monitoring module, and a gas detection module.

6. The mine inspection system as described in claim 1, characterized in that, The mine inspection system also includes a charging device, which is located at the start and end positions of the inspection robot and is used to charge the inspection robot.

7. A mine inspection method, characterized in that, The method, used as a main control platform for the mine inspection system as described in any one of claims 1-6, comprises: The system acquires the operating status information of the belt conveyor from the condition monitoring device, performs data analysis and processing on the operating status information, and obtains the condition analysis result of the belt conveyor. The inspection data is obtained from the inspection robot, and the inspection data is analyzed and processed to obtain the inspection results. Output the status analysis results and inspection results.

8. The method as described in claim 7, characterized in that, The method further includes: Obtain the battery status of the inspection robot; If the inspection robot is in a low battery state, control the inspection robot to move to the charging device to charge; If the charging device cannot charge the robot, the inspection robot is controlled to switch to another charging device.

9. The method as described in claim 7, characterized in that, The steps of acquiring the operating status information of the belt conveyor from the status monitoring device, performing data analysis and processing on the operating status information, and obtaining the status analysis result of the belt conveyor include: The belt is subjected to line laser detection by a line laser detection unit to identify the line laser features in the belt. Based on the line laser characteristics, the distortion state of the belt is determined; If the belt is distorted, an image of the belt is acquired through the image collection unit; Perform belt image recognition on the belt image to obtain the image recognition result; Based on the line laser characteristics and image recognition results, it is determined whether the belt is torn, and the state analysis results of the belt conveyor are obtained.

10. The method as described in claim 9, characterized in that, The step of performing line laser detection on the belt image and identifying line laser features in the belt image includes: Based on the laser transmission speed and laser return time, the actual height of each point on the belt cross section is determined, and the belt deformation is determined based on the difference between the actual height and the reference height of each point on the belt cross section. The degree of missing laser detection lines on the belt is detected. If all laser detection lines are missing, the belt is broken. If a break in the belt is detected, the degree of belt breakage is determined based on the extent of the absence of all detected laser detection lines and the belt transport time. The surface roughness of the belt is determined based on the lateral width of the line laser beam projected onto the belt. The line laser characteristics are determined based on the belt deformation, belt breakage degree, and belt surface roughness.

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