Title :
Hierarchical structure neural network and it´s application in unusual sound recognition
Author :
Zhen Zhu ; Hu, Xue-jun ; Wang, Jun
Author_Institution :
Foshan Univ., Guangdong, China
Abstract :
This paper describes a novel method by using hierarchical structure neural network for unusual sounds recognition. Above all, it discusses the principle of the inspecting system against theft that is used in pipeline transportation. Then the paper presents the structure of neural network, the sampling and the neural network train. The system achieves inspection preventing theft and caution by sound detecting, processing and recognizing. It is attested through actual application that the system capability is stable, the correct recognition ratio attains to 100%, and the error warning ratio is below 1%. In addition, the system can be expanded according to requirement.
Keywords :
acoustic measurement; acoustic signal processing; inspection; neural nets; pipelines; hierarchical structure neural network; neural network train; pipeline transportation; signal processing; sound detection; sound processing; unusual sound recognition; Acoustic sensors; Inspection; Intelligent networks; Monitoring; Neural networks; Petroleum; Pipelines; Signal analysis; Signal processing; Transportation;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1260137