Fault Monitoring Of Coal Transportation System Based On Phase-OTDR

Coal is the main industrial energy in China, and its production is an important indicator of the country’s economy. Belt conveyor is the primary transport equipment in the process of coal production with advantages of large volume and continuous transport. For long-distance belt conveyor, promptly discovering and accurately locating the point of failure can reduce the restarting time when the machine goes wrong, which contributes to improving transport efficiency. However, traditional fault protection method employing switch contact output does not have the ability to identify the location. Distributed optical fiber vibration sensor, using fiber as a sensing and transmission media, has the ability of real-timely and remotely monitoring the disturbance along the fiber. In addition, the optical fiber sensor has characters of anti-electromagnetic interference, corrosion resistance, light weight, and small volume, which can be applied in the coal mine with harsh working conditions.Considering the specific conditions and the functional requirements of the core transportation system in Chongqing Coal Academy of Sciences, we employed φ-OTDR systems for health monitoring and alarm of the belt conveyor. Finally, the system achieved timely alarm function within a minute and the accurate alarm rate reached 99%.The main work is as follows:① φ-OTDR system was theoretically analyzed in detail and a physical model to explain the physical mechanisms of φ-OTDR is conducted. We also discussed the performance indicators of φ-OTDR system, such as spatial resolution, dynamic range, frequency response range, etc.② The distributed optical fiber vibration sensing system based on-OTDR was built and its health monitoring was demonstrated. The narrow linewidth laser used in the system has a linewidth of 500 Hz and output power of 7mw. In addition, an EDFA optical amplification system with three WDM is designed. In order to firmly wind the sensing fiber to the roller, we designed the aluminum alloy spiral disc structure which was glued to roller’s axle core.③ We employed Lab VIEW software for data acquisition and processing, and utilized wavelet procedures in Matlab for noise reduction and then extracting conveyor vibration amplitude information. The experiment successfully separates the good wheel from the bad. And the system achieved timely alarm within a minute with an accuracy of 99%. In this paper, the causes of the false alarm rate were also analyzed.The system greatly decreased the time needed for alarming and locating, saved the manpower and the material resources and greatly improved the production efficiency and security reliability, which has broad prospects for practical production.