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Research on fault mode and diagnosis of methane sensor
Authors:WANG Qi-jun  CHENG Jiu-long
Affiliation:1. Huainan Vocational & Technical College, Huainan, Anhui 232001, China
2. Shandong University of Science and Technology, Qingdao, Shandong 266510, China
Abstract:To improve the reliability of coal mine safety monitoring systems we have analyzed the characteristics of a methane sensor, an important component of the monitoring system of production safety in a coal mine and studied the main type and mode of faults when the sensor was used on-line. We introduced a new method based on artificial neural network to detect faults of me-thane sensors. In addition, using the output information of a single methane sensor, we established a sensor output model of a dy-namic non-linear neural network for on-line fault detection. Finally, the fault of the heating wire of the sensor was simulated, indi-cating that, when the methane sensor had a fault, the predicted output of the neural network clearly deviated from the actual output,exceeding the pre-set threshold and showing that a fault had occurred in the methane sensor. The result shows that the model has good convergence and stability, and is quite capable of meeting the requirements for on-line fault detection of methane sensors.
Keywords:methane sensor  fault characteristics  fault diagnosis  neural network
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