Fault Diagnosis for Diesel Engine Based on Immune Wavelet Neural Network
This paper proposes the wavelet neural network (WNN) based on clonal selection algorithm (CLONALG) for using in fault diagnosis of marine diesel engine. CLONALG initializes the WNNs weights and biases, the ergodic weights and biases are used for further net-training. The fault diagnosis for marine diesel engine is conducted by using the well-trained wavelet network, in order to illustrate the performance of this model. The results obtained indicate that the WNN based on CLONALG can avoid the local extremum, and the convergence, generalization and the capability of fault diagnosis are all improved.
Fault diagnosis Clonal selection Immune algorithm Wavelet neural network
Chuang Zhang Chen Guo Yunsheng Fan
Information Science and Technology College Dalian Maritime University Dalian China
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
522-526
2010-03-27(万方平台首次上网日期,不代表论文的发表时间)