Application case of coal conveyor belt tear monitoring in a thermal power generation enterprise-KEENVIEW

Application case of coal conveyor belt tear monitoring in a thermal power generation enterprise

A thermal power generation enterprise is prone to power outages due to tearing of coal conveying belts. By using equipment that integrates image recognition and stress-strain monitoring technology, it solves the problem of interference in complex working conditions, realizes real-time accurate monitoring, timely detects tearing hazards, and ensures stable operation of power generation. Follow-up plans to expand the scope of application and optimize the system

Overview

Application case of coal conveyor belt tear monitoring in thermal power generation enterprises

The application of tear detection of coal conveyor belts in thermal power plants is to use relevant detection systems or devices to monitor the coal conveyor belts in real time through various advanced technologies such as machine vision intelligent algorithms, laser technology, stereo vision technology, edge analysis technology, etc., to detect the tear of the belts in a timely manner and carry out grading alarms, automatic regulation, etc., to ensure the safe and efficient operation of the belts, reduce economic losses and safety risks, and help intelligent control of power plants. The company provides a belt tear online detection system for a thermal power plant in a certain place to solve the problem of coal conveyor belt tear prevention and dust removal under high concentration of dust.

Challenge

The coal conveying system has problems such as large production area, complex on-site conditions, difficult investigation, and fast fault diffusion speed. It is difficult to identify the characteristics of belt tear faults, and it is necessary to accurately and timely determine whether the belt is torn from a large amount of image data. When the coal conveying belt of a power plant transports coal, large dust is generated, which interferes with manual detection of belt tear faults, and cannot achieve fast and accurate judgment. Traditional detection methods are difficult to meet the needs. Manual inspection has limitations such as low efficiency, insufficient coverage, and difficulty in finding hidden dangers in time.

Solution

Based on machine vision intelligent algorithms and laser technology, a customized "conveyor belt longitudinal tear online detection system" is developed, and it is specially equipped with a scraping dust removal device for effective dust removal. The system has its own scraping dust removal, high-precision detection, real-time comprehensive tear detection, tear grade distinction, multi-level alarm, data storage playback and other highlights.
Through the industrial high-speed camera and laser beam on the bottom surface of the belt full section scanning to achieve 24-hour all-weather belt tear detection, can set the alarm value independently, when greater than the set value, automatically achieve sound and light alarm, the software automatically recognizes the belt tear, display the tear image, automatically generate a test report. At the same time, it is equipped with robot automatic cleaning device to ensure the clean and efficient operation of the robot.
Combining multi-dimensional sensing technology, artificial intelligence and data analytics, infrared thermal imaging and AI recognition technology are used to monitor belt wear and tear, high definition cameras and vision algorithms are used to detect belt deviation, and vibration and temperature sensors are used to monitor idler lag.

The image data is obtained in real time through the high-speed industrial camera, and then through the AI recognition algorithm of the software, when the comprehensive change characteristics exceed the set threshold, it is considered that the belt is torn vertically, and the analysis system sends an alarm signal to the user to stop the tripping of the coal conveying belt. Realize 24-hour all-weather belt tear detection, can set the alarm value independently, when it is greater than the set value, automatically realize the sound and light alarm, the software automatically recognizes the belt tear, displays the tear image, and automatically generates the detection report. At the same time, it is equipped with an automatic robot cleaning device to ensure the clean and efficient operation of the robot.

Outlook

Promote the construction of smart power plants, further enhance the automation and intelligent operation level of coal transportation systems, and bring more improvements to power plant operations, which can be promoted and applied in the intelligent transformation of coal transportation systems in more power plants.