Detection of small gas leaks based on neural networks and D-S evidential theory using ultrasonics

作者：Wang Tao^*; Pei Yu; Xiao Huiheng; Fan Wei

来源：Insight: Non-Destructive Testing and Condition Monitoring , 2014, 56(4): 189-194.

DOI：10.1784/insi.2014.56.4.189

• gas leak detection
• ultrasonics
• neural networks
• data fusion
• evidential theory

This paper presents a method for solving the problem of recognising the leakage state of a measured object by means of a gas leak detection system, using an ultrasonic method based on data fusion and neural networks. The neural network is trained using cross-correlation information from a probe as the prior probability, combined with the Dempster-Shafer (D-S) evidential reasoning method, and then applied in the gas leak ultrasonic detection system. Experimental results show that recognition based on this combination is significantly better than with a single sensor. Consequently, the validity and correctness of this method have been verified.

• 出版日期2014-4
• 单位北京理工大学