Belt conveyor detecting and monitoring system based on rail-mounted inspection robot

Abstract

A belt conveyor detection and monitoring system based on a rail-mounted inspection robot is composed of a rail-mounted inspection robot body, a rail platform, a power supply platform, a communication platform, a positioning module and a background monitoring platform, the mounting position of the rail-mounted inspection robot body covers a raw material area belt conveyor conveying area, and the rail-mounted inspection robot body is used for inspecting an indoor surrounding belt conveyor; equipment faults in the inspection process are identified, and normal operation of the equipment is ensured; the rail platform is supported by the rail fixing support and used for carrying the rail hanging inspection robot body; the power supply platform adopts a power supply mode of combining a battery and a distributed contact charging system to meet the power supply requirement of the hanging rail inspection robot body; the network communication platform is used for communicating the on-rail inspection robot with a background; the positioning module adopts a track navigation method, carries out distance measurement through a coded disc, and realizes accurate fixed-point stop of the track-hanging inspection robot body; and the background monitoring platform is used for analyzing and storing all inspection data in the application environment.

Description

Technical Field

[0001] The invention relates to a belt conveyor detection and monitoring system based on a rail-hanging inspection robot, and belongs to the field of conveyor belt conveyor detection. Background Art

[0002] Conveyor belts are key equipment for conveying raw materials. Due to the physical characteristics of the conveyed materials, it is easy for the conveyor belts to get stuck, deviate, tear, pile up, or even break, which seriously affects the operating efficiency and production safety of related systems. Real-time monitoring of material conveyor belts to prevent transmission failures is a necessary means to increase production efficiency and reduce production costs.

[0003] For a long time, the inspection of material conveyor belt conveyors has mainly relied on manual regular inspections and on-site guarding. On the one hand, manual inspections are easily affected by personal experience and subjective consciousness, and are restricted by monitoring methods, data recording, and data analysis. Usually, a lot of manpower is spent but effective data results cannot be obtained, and the data obtained is difficult to form a system and has little reference value. In particular, as the equipment is used for a longer time, the equipment failure rate is higher, and more and more manpower is needed for inspection and maintenance, which greatly increases the cost of electricity production. On the other hand, the transmission corridor environment is harsh, with a large amount of dust and toxic and harmful gases, which may endanger the personal safety of operation and maintenance personnel.

[0004] Rail-mounted inspection robots are increasingly used in narrow passages such as bridges and tracks or in dangerous and complex environments due to their compact appearance, powerful functions, and easy deployment. They reduce tedious and complex manual labor and improve operation and maintenance efficiency and inspection frequency. Summary of the invention

[0005] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and provide a belt conveyor detection and monitoring system based on a rail-hanging inspection robot, to realize the data collection, autonomous charging and other functions of the intelligent robot, to ensure that the robot can achieve barrier-free communication at any position, and to realize real-time detection and monitoring of information such as the belt condition and material condition of the belt conveyor.

[0006] The technical solution of the present invention is: a belt conveyor detection and monitoring system based on a rail-hanging inspection robot, comprising: a rail-hanging inspection robot body, a track platform, a power supply platform, a network communication platform, a positioning module, and a background monitoring platform;

[0007] The installation position of the rail inspection robot covers the conveyor belt area of ​​the raw material area. It is used to inspect the indoor surrounding belt conveyor, identify equipment failures during the inspection process, and ensure the normal operation of the equipment.

[0008] The track platform is supported by a track fixing bracket and is used to carry the track inspection robot body;

[0009] The power supply platform uses a combination of batteries and distributed contact charging systems to meet the power supply needs of the rail inspection robot.

[0010] Network communication platform, used for communication between the rail inspection robot and the backend;

[0011] The positioning module uses the track navigation method to measure distance through the encoder to achieve precise positioning and stopping of the rail inspection robot.

[0012] The background monitoring platform is used to analyze and store all inspection data within this application environment.

[0013] When the rail-hanging inspection robot body inspects the indoor surrounding belt conveyor, it obtains video data in real time through the visible light high-definition camera carried by the rail-hanging inspection robot body, and uses a deep neural network to autonomously learn from the data to obtain accurate results, thereby realizing object detection, that is, obtaining the position of materials in the image, and understanding the operation status of the belt conveyor in real time to ensure the normal operation of the equipment.

[0014] The inspection path is generally U-shaped, and the inspection area covers the conveyor belt.

[0015] The rail inspection robot body also has high-definition video, infrared temperature measurement, temperature and humidity recognition, meter recognition, and particulate matter content monitoring functions.

[0016] During the inspection process, an inspection route is set up between the two belt conveyors to inspect the temperature equipment of the inner rollers of the two belt conveyors.

[0017] The rail inspection robot body adopts a vision-based fault diagnosis method to identify equipment faults during the inspection process, including: firstly, multi-spectral image acquisition, pixel-level image fusion of the acquired images, and then multi-threaded image processing to extract image features after fusion, and obtain diagnostic results through the image feature status, so as to realize the classification and identification of conveyor belt tearing, deviation and stacking faults.

[0018] The track platform is made of high-strength aluminum alloy, has a splicing function, and can be designed with curvature and slope according to the on-site terrain.

[0019] The power supply platform also has an emergency manual charging function. In an emergency, the manual charger can be used to perform emergency charging on the rail inspection robot body.

[0020] The network communication platform system adopts wireless communication. All control signals, video data, audio data, field sensor collection data and alarm information of the rail inspection robot are transmitted through the wireless network. The remote monitoring background conducts two-way data interaction with the local monitoring background through the IEC61850 protocol and WebService through a private network. It can also communicate based on TCP or UDP protocol using Socket.

[0021] The network communication platform communicates between the rail-hanging inspection robot and the background. The specific process is: the industrial computer and video device on the rail-hanging inspection robot are connected to the wireless hub via Ethernet, and several wireless routers are arranged indoors to form a wireless local area network. The monitoring background is also connected to the wireless local area network via the wireless hub. The devices in the entire mobile monitoring system can access each other, and the network bandwidth can effectively achieve load balancing.

[0022] The specific positioning method of the positioning module is as follows: code plates are set up in sections on the track, the mileage is calibrated regularly, and the mileage is read through the code disk; when the rail-hanging inspection robot body detects the starting point, the inspection path is selected according to the distance information of the stop point to ensure that the inspection vehicle is in a low-speed stop state when it reaches the precise stop point. At this time, when the inspection vehicle detects the stop point, it stops immediately and accurately; while passing the code plate detection, the distance is integrated through the code disk inside the rail-hanging inspection robot body, and accurate positioning and navigation are achieved through external detection and internal distance recursion; at the same time, photoelectric sensors and odometers are used to identify and upload the ID of the code plates passed by during the movement of the rail-hanging inspection robot body to achieve the positioning function, and the movement direction data of the robot is output at the same time.

[0023] It also includes a rail-mounted fire-fighting robot; the rail-mounted fire-fighting robot adopts an independent chassis drive and is equipped with an ultra-fine dry powder fire extinguishing device. When a fire occurs, it can achieve rapid and efficient fire extinguishing; the rail-mounted fire-fighting robot is deployed separately and does not go out under normal circumstances. When the sensor equipment equipped with the rail-mounted inspection robot body senses the fire source, the rail-mounted inspection robot body sends an alarm signal, on-site video and environmental information to the background monitoring platform, and sends instructions to the rail-mounted fire-fighting robot at the same time. When the rail-mounted fire-fighting robot arrives at the designated location, the fire-fighting equipment is triggered by the background monitoring platform or the rail-mounted fire-fighting robot itself to extinguish the fire source by locally flooding the fire with ultra-fine dry powder.

[0024] The backend monitoring platform includes: a real-time monitoring module, an inspection plan designation module, a remote control module, a data report generation module and a history query module;

[0025] The real-time monitoring module is used to monitor the current position of the rail inspection robot, the inspection route, the equipment information to be inspected, the real-time high-definition infrared video during the inspection, and the real-time inspection results during the inspection when the rail inspection robot is in the inspection state;

[0026] Inspection plan designation module, used to edit inspection tasks, formulate inspection plans and issue routine inspection tasks, and also includes task scheduling and task editing;

[0027] The remote control module can remotely control the rail inspection robot to any permitted place according to the needs, conduct manual inspections on the designated equipment, and capture high-definition infrared images and videos of the designated equipment;

[0028] The data report generation module is used to display the results of historical inspection data statistical analysis in a variety of forms including lists, bar charts, calendars, and equipment maps;

[0029] The historical query module is used to query inspection tasks and equipment. In the inspection task query, all completed inspection task information is displayed, and the detailed inspection status of all equipment in this task can be viewed. In the equipment query, all inspection information of a specific equipment can be queried, including equipment selection, basic equipment information, equipment detailed information, defects, historical curves, and historical data.

[0030] The advantages of the present invention compared with the prior art are:

[0031] (1) The rail-mounted inspection robot can perform various inspection modes, including scheduled inspection, fixed-point inspection, temporary inspection for designated tasks, and remote control inspection. It also uses the optimal path planning algorithm to make the inspection more efficient.

[0032] (2) The inspection content includes video data, infrared thermal imaging, gas, temperature and humidity data, and is combined with deep learning-based video analysis technology to assist staff in judging on-site conditions.

[0033] (3) The rail-mounted inspection robot has the function of adapting to terrain. It can classify special positioning points and ordinary points through the positioning system, perform intelligent analysis, and adjust the speed according to the actual situation on site.

[0034] (4) Equipped with a rail-mounted firefighting robot, which is driven by the background system and linked with the entire system.

[0035] (5) Adopt an on-site three-dimensional comprehensive intelligent monitoring system, develop a comprehensive intelligent monitoring system based on three-dimensional scenes, and realize full-dimensional intelligent monitoring of indoor navigation, on-site environment, and equipment in terminal devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a system block diagram of the present invention;

[0037] Figure 2 A schematic diagram of a flame identification system is reproduced for the present invention; DETAILED DESCRIPTION

[0038] like Figure 1 As shown, the present invention is a belt conveyor detection and monitoring system based on a rail-hanging inspection robot, comprising: a rail-hanging inspection robot body, a track platform, a power supply platform, a network communication platform, a positioning module, and a background monitoring platform;

[0039] The installation position of the rail inspection robot covers the conveyor belt area of ​​the raw material area. It is used to inspect the indoor surrounding belt conveyor, identify equipment failures during the inspection process, and ensure the normal operation of the equipment.

[0040] The track platform is supported by a track fixing bracket and is used to carry the track inspection robot body;

[0041] The power supply platform uses a combination of batteries and distributed contact charging systems to meet the power supply needs of the rail inspection robot.

[0042] Network communication platform, used for communication between the rail inspection robot and the background;

[0043] The positioning module uses the track navigation method to measure distance through the encoder to achieve precise positioning and stopping of the rail inspection robot.

[0044] The background monitoring platform is used to analyze and store all inspection data within this application environment.

[0045] When the rail-hanging inspection robot body inspects the indoor surrounding belt conveyor, it obtains video data in real time through the visible light high-definition camera carried by the rail-hanging inspection robot body, and uses a deep neural network to autonomously learn from the data to obtain accurate results, thereby realizing object detection, that is, obtaining the position of materials in the image, and understanding the operation status of the belt conveyor in real time to ensure the normal operation of the equipment.

[0046] The inspection path is generally U-shaped, and the inspection area covers the conveyor belt.

[0047] The rail inspection robot body also has high-definition video, infrared temperature measurement, temperature and humidity recognition, meter recognition, and particulate matter content monitoring functions.

[0048] During the inspection process, an inspection route is set up between the two belt conveyors to inspect the temperature equipment of the inner rollers of the two belt conveyors.

[0049] The rail inspection robot body adopts a vision-based fault diagnosis method to identify equipment faults during the inspection process, including: firstly, multi-spectral image acquisition, pixel-level image fusion of the acquired images, and then multi-threaded image processing to extract image features after fusion, and obtain diagnostic results through the image feature status, so as to realize the classification and identification of conveyor belt tearing, deviation and stacking faults.

[0050] The rail inspection robot-assisted flame recognition system uses a flame monitoring algorithm to identify open flames in the monitoring area. The algorithm is based on large-scale flame data recognition training and cooperates with cameras to identify open flames in the monitoring area in real time. If there is a fire hazard, an alarm will be issued immediately. Figure 2 As shown in the figure, the flame recognition system, user feedback system and early warning system are combined. The flame recognition system performs convolutional neural network judgment by segmenting the flame candidate area. The user feedback system optimizes the convolutional neural network through the user feedback database. The final recognition result is fed back as early warning information through the early warning system.

[0051] The track platform is made of high-strength aluminum alloy, has a splicing function, and can be designed with curvature and slope according to the on-site terrain.

[0052] The power supply platform also has an emergency manual charging function. In an emergency, the manual charger can be used to perform emergency charging on the rail inspection robot body.

[0053] The network communication platform system adopts wireless communication. All control signals, video data, audio data, field sensor collection data and alarm information of the rail inspection robot are transmitted through the wireless network. The remote monitoring background conducts two-way data interaction with the local monitoring background through the IEC61850 protocol and WebService through a private network. It can also communicate based on TCP or UDP protocol using Socket.

[0054] The network communication platform communicates between the rail-hanging inspection robot and the background. The specific process is: the industrial computer and video device on the rail-hanging inspection robot are connected to the wireless hub via Ethernet, and several wireless routers are arranged indoors to form a wireless local area network. The monitoring background is also connected to the wireless local area network via the wireless hub. The devices in the entire mobile monitoring system can access each other, and the network bandwidth can effectively achieve load balancing.

[0055] The specific positioning method of the positioning module is as follows: code plates are set up in sections on the track, the mileage is calibrated regularly, and the mileage is read through the code disk; when the rail-hanging inspection robot body detects the starting point, the inspection path is selected according to the distance information of the stop point to ensure that the inspection vehicle is in a low-speed stop state when it reaches the precise stop point. At this time, when the inspection vehicle detects the stop point, it stops immediately and accurately; while passing the code plate detection, the distance is integrated through the code disk inside the rail-hanging inspection robot body, and accurate positioning and navigation are achieved through external detection and internal distance recursion; at the same time, photoelectric sensors and odometers are used to identify and upload the ID of the code plates passed by during the movement of the rail-hanging inspection robot body to achieve the positioning function, and the movement direction data of the robot is output at the same time.

[0056] It also includes a rail-mounted fire-fighting robot; the rail-mounted fire-fighting robot adopts an independent chassis drive and is equipped with an ultra-fine dry powder fire extinguishing device. When a fire occurs, it can achieve rapid and efficient fire extinguishing; the rail-mounted fire-fighting robot is deployed separately and does not go out under normal circumstances. When the sensor equipment equipped with the rail-mounted inspection robot body senses the fire source, the rail-mounted inspection robot body sends an alarm signal, on-site video and environmental information to the background monitoring platform, and sends instructions to the rail-mounted fire-fighting robot at the same time. When the rail-mounted fire-fighting robot arrives at the designated location, the fire-fighting equipment is triggered by the background monitoring platform or the rail-mounted fire-fighting robot itself to extinguish the fire source by locally flooding the fire with ultra-fine dry powder.

[0057] The backend monitoring platform includes: a real-time monitoring module, an inspection plan designation module, a remote control module, a data report generation module and a history query module;

[0058] The real-time monitoring module is used to monitor the current position of the rail inspection robot, the inspection route, the equipment information to be inspected, the real-time high-definition infrared video during the inspection, and the real-time inspection results during the inspection when the rail inspection robot is in the inspection state;

[0059] Inspection plan designation module, used to edit inspection tasks, formulate inspection plans and issue routine inspection tasks, and also includes task scheduling and task editing;

[0060] The remote control module can remotely control the rail inspection robot to any permitted place according to the needs, conduct manual inspections on the designated equipment, and capture high-definition infrared images and videos of the designated equipment;

[0061] The data report generation module is used to display the results of historical inspection data statistical analysis in a variety of forms including lists, bar charts, calendars, and equipment maps;

[0062] The historical query module is used to query inspection tasks and equipment. In the inspection task query, all completed inspection task information is displayed, and the detailed inspection status of all equipment in this task can be viewed. In the equipment query, all inspection information of a specific equipment can be queried, including equipment selection, basic equipment information, equipment detailed information, defects, historical curves, and historical data.

[0063] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solution of the present invention by using the technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A belt conveyor detection and monitoring system based on a rail-hanging inspection robot, characterized in that: include: The rail inspection robot body, rail platform, power supply platform, network communication platform, positioning module, and background monitoring platform; The installation position of the rail inspection robot covers the conveyor belt area of ​​the raw material area. It is used to inspect the indoor surrounding belt conveyor, identify equipment failures during the inspection process, and ensure the normal operation of the equipment. The track platform is supported by a track fixing bracket and is used to carry the track inspection robot body; The power supply platform uses a combination of batteries and distributed contact charging systems to meet the power supply needs of the rail inspection robot. Network communication platform, used for communication between the rail inspection robot and the backend; The positioning module uses the track navigation method to measure distance through the encoder to achieve precise positioning and stopping of the rail inspection robot. The background monitoring platform is used to analyze and store all inspection data within this application environment.

2. A belt conveyor detection and monitoring system based on a rail-hanging inspection robot according to claim 1, characterized in that: When the rail-hanging inspection robot body inspects the indoor surrounding belt conveyor, it obtains video data in real time through the visible light high-definition camera carried by the rail-hanging inspection robot body, and uses a deep neural network to autonomously learn from the data to obtain accurate results, thereby realizing object detection, that is, obtaining the position of materials in the image, and understanding the operation status of the belt conveyor in real time to ensure the normal operation of the equipment.

3. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The inspection path is generally U-shaped, and the inspection area covers the conveyor belt.

4. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The rail inspection robot body also has high-definition video, infrared temperature measurement, temperature and humidity recognition, meter recognition, and particulate matter content monitoring functions.

5. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: During the inspection process, an inspection route is set up between the two belt conveyors to inspect the temperature equipment of the inner rollers of the two belt conveyors.

6. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The rail inspection robot body adopts a vision-based fault diagnosis method to identify equipment faults during the inspection process, including: firstly, multi-spectral image acquisition, pixel-level image fusion of the acquired images, and then multi-threaded image processing to extract image features after fusion, and obtain diagnostic results through the image feature status, so as to realize the classification and identification of conveyor belt tearing, deviation and stacking faults.

7. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The track platform is made of high-strength aluminum alloy, has a splicing function, and can be designed with curvature and slope according to the on-site terrain.

8. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The power supply platform also has an emergency manual charging function. In an emergency, the manual charger can be used to perform emergency charging on the rail inspection robot body.

9. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The network communication platform system adopts wireless communication. All control signals, video data, audio data, field sensor collection data and alarm information of the rail inspection robot are transmitted through the wireless network. The remote monitoring background conducts two-way data interaction with the local monitoring background through the IEC61850 protocol and WebService through a private network. It can also communicate based on TCP or UDP protocol using Socket.

10. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The network communication platform communicates between the rail-hanging inspection robot and the background. The specific process is: the industrial computer and video device on the rail-hanging inspection robot are connected to the wireless hub via Ethernet, and several wireless routers are arranged indoors to form a wireless local area network. The monitoring background is also connected to the wireless local area network via the wireless hub. The devices in the entire mobile monitoring system can access each other, and the network bandwidth can effectively achieve load balancing.

11. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The specific positioning method of the positioning module is as follows: code plates are set up in sections on the track, the mileage is calibrated regularly, and the mileage is read through the code disk; when the rail-hanging inspection robot body detects the starting point, the inspection path is selected according to the distance information of the stop point to ensure that the inspection vehicle is in a low-speed stop state when it reaches the precise stop point. At this time, when the inspection vehicle detects the stop point, it stops immediately and accurately; while passing the code plate detection, the distance is integrated through the code disk inside the rail-hanging inspection robot body, and accurate positioning and navigation are achieved through external detection and internal distance recursion; at the same time, photoelectric sensors and odometers are used to identify and upload the ID of the code plates passed by during the movement of the rail-hanging inspection robot body to achieve the positioning function, and the movement direction data of the robot is output at the same time.

12. The belt conveyor detection and monitoring system based on the rail-hanging inspection robot according to claim 1 is characterized in that: The backend monitoring platform includes: a real-time monitoring module, an inspection plan designation module, a remote control module, a data report generation module and a history query module; The real-time monitoring module is used to monitor the current position of the rail inspection robot, the inspection route, the equipment information to be inspected, the real-time high-definition infrared video during the inspection, and the real-time inspection results during the inspection when the rail inspection robot is in the inspection state; Inspection plan designation module, used to edit inspection tasks, formulate inspection plans and issue routine inspection tasks, and also includes task scheduling and task editing; The remote control module can remotely control the rail inspection robot to any permitted place according to the needs, conduct manual inspections on the designated equipment, and capture high-definition infrared images and videos of the designated equipment; The data report generation module is used to display the results of historical inspection data statistical analysis in a variety of forms including lists, bar charts, calendars, and equipment maps; The historical query module is used to query inspection tasks and equipment. In the inspection task query, all completed inspection task information is displayed, and the detailed inspection status of all equipment in this task can be viewed. In the equipment query, all inspection information of a specific equipment can be queried, including equipment selection, basic equipment information, equipment detailed information, defects, historical curves, and historical data.

13. A belt conveyor detection and monitoring system based on a rail-hanging inspection robot according to any one of claims 1 to 12, characterized in that: It also includes a rail-mounted fire-fighting robot; the rail-mounted fire-fighting robot adopts an independent chassis drive and is equipped with an ultra-fine dry powder fire extinguishing device. When a fire occurs, it can achieve rapid and efficient fire extinguishing; the rail-mounted fire-fighting robot is deployed separately and does not go out under normal circumstances. When the sensor equipment equipped with the rail-mounted inspection robot body senses the fire source, the rail-mounted inspection robot body sends an alarm signal, on-site video and environmental information to the background monitoring platform, and sends instructions to the rail-mounted fire-fighting robot at the same time. When the rail-mounted fire-fighting robot arrives at the designated location, the background monitoring platform or the rail-mounted fire-fighting robot itself triggers the fire-fighting equipment to extinguish the fire source by local flooding of dry powder.

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