Diesel Engine Fault Diagnosis Based on DT-CWPT and RBF Neural Network
Aiming at the large amount of vibration signal and data redundancy on the cylinder head of diesel engine, this paper uses DT-CWPT to process the acquired signal, including data denoising processing and feature vector extraction. After the wavelet decomposition is collected, the dimension of the signal is reduced, and the excess signal components can be filtered out, the fault features are highlighted, and the information contained in the signal is not damaged, and the accuracy of the fault diagnosis is improved; the RBF neural network has an excellent mode. Recognition performance, relative to the neural network has a rapid diagnosis ability; particle swarm optimization algorithm to optimize the RBF neural network basis function, can improve the diagnostic speed of RBF neural network. Finally, the research is applied to the actual experiment to verify the superiority of the method.
 CHENG Rui-qi,CUI Jian-jun. Characteristic Analysis of Spectrographic Oil Data and Fault Diagnosis for Diesel Engines[J].Mechanical Science and technology, 2000, 41(2):289-294.
 CHEN Bao-jia,LI Li,ZHANG Yuan. Application of Scale Wave Power Spectrum to Fault Diagnos is of Internal Combustion Engine[J]. Transactions of CSICE, 2006, 24(3):284-287.
 QIAN Shu-hua,WANG Xin-qing,LI Huan-liang. Application of Quadric Time-Frequency Distribution to Mechanical Fault Diagnosis[J]. Journal of Southwest Jiaotong University, 2003,5(38): 578-580.
 Cao Jian-jun,Zhang Pei-lin, Zhang Yin-tang. Feature Extraction and Optimal Selection Algorithm of the Vibration Signal of an Engine Cylinder Head[J]. Mechanical Science and Technology for Aerospace Engineering,2008, 9(9):1199-1206.
 CHEN Hua-li,LIU Kang,CHENG Geng-guo. Study and Simulation on Signal Adaptive De-noising Method[J]. Computer Simulation,2011, 28(1):344-387.
 DENG Jun, Wang Jing. On Fault Diagnosis for Diesel Engines Based on Correlation Dimension of Diesel’s Vibration Signals[J]. Ship & ocean engineering,2009, 38(1):36-38.
 FAN Jin-yu, HUANG Jia-liang. Application Research of Neural Network Technology in Online Diagnosis of Marine Diesel Engine Faults[J]. China ship repair,2006, 25(6):49-52.
Copyright (c) 2019 EPH - International Journal of Science And Engineering (ISSN: 2454 - 2016)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
- All contributor(s) agree to transfer the copyright of this article to EPH Journal.
- EPH Journal will have all the rights to distribute, share, sell, modify this research article with proper reference of the contributors.
- EPH Journal will have the right to edit or completely remove the published article on any misconduct happening.