Improved Elman Neural network with Ant Colony Algorithm and its Applications in Fault Diagnosis
In the power plant, the blower fans running conditions related to the power plant production directly, as well as the security situation. This article introduced embedded system monitoring to the Auxiliary power plant machinery diagnostics systems. An on-line mechanical fault diagnosis system was developed based on ant colony algorithm and Elman neural network. This system integrated data acquisition, signal processing, network communications, on-line fault diagnosis and other functions into one. Experiments show that this method is simple and effective. It can also be applied to other fault diagnosis of complex systems and has certain portability.
fault diagnosis Ant Colony Algorithm Elman neural network
Zheng Yao Guohuan Lou Qingxin Zhao
College of Computer and Automatic Control Hebei Polytechnic University Tangshan, China Tangshan Mine Kailuan Group Tangshan, China
国际会议
成都
英文
246-249
2010-06-12（万方平台首次上网日期，不代表论文的发表时间）