The Research of Intelligent Fault Diagnostic System for Diesel Engine Based on Virtual Instrument

Dan Feng Hu; Min Qian; Ling Ling Chen

doi:10.4028/www.scientific.net/AMM.525.746

Paper Titles

Dynamic Intelligence Scouting and Monitoring System
p.727

Research of the FEM Mesh Generation Based on Patran
p.731

SIWPSO-Based Controller Design for AUV
p.736

ICE Fault Diagnosis Method Based on Mutual Information and WVD Time-Frequency Analysis
p.741

The Research of Intelligent Fault Diagnostic System for Diesel Engine Based on Virtual Instrument
p.746

An Improved Algorithm on Point Cloud Optimization for Unmanned Aerial Vehicles
p.752

With Expander Three-Dimensional Model as an Expander, Application of 3DS Max Technology in Multimedia Teaching
p.759

Mining Engineering Professionals Motivated to Improve their Proficiency in English
p.765

Study on Tender Offers Decision-Making Based on the Sand Table Experiment
p.770

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 525The Research of Intelligent Fault Diagnostic...

The Research of Intelligent Fault Diagnostic System for Diesel Engine Based on Virtual Instrument

Abstract:

Introduced the system structure, working principle and diagnostic algorithm of a data acquisition and fault diagnostic system for diesel engines. The system is composed of a portable computer, a multi-channels data acquisition device and some sensors. Through behavior of the diesel and the characteristic values of signals, we can finish the non-disassemble examining and fault diagnosing. The structure and policy of the diagnostic expert system are also discussed.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 525)

Pages:

746-751

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.525.746

Citation:

Cite this paper

Online since:

February 2014

Authors:

Dan Feng Hu*, Min Qian, Ling Ling Chen

Keywords:

Diesel Engine, Fault Diagnostic System, Virtual Instrument (VI)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Chen, H. X., Chua, Patrick S. K., & Lim, G. H. Fault degradation assessment of water hydraulic motor by impulse vibration signal with Wavelet Packet Analysis and Kolmogorov–Smirnov Test. Mechanical Systems and Signal Processing, 2008( 22), 1670–1684.

DOI: 10.1016/j.ymssp.2008.01.009

Google Scholar

[2] Lei, Yaguo, He, Zhengjia, Zi, Yanyang, & Hua, Qiao. Fault diagnosis of rotatingmachinery based on multiple ANFIS combination with gas. Mechanical Systems and Signal Processing, 2007(21), 2280–2294.

DOI: 10.1016/j.ymssp.2006.11.003

Google Scholar

[3] Wu, Jian-Da, & Liu, Chiu-Hong. An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network. Expert Systems with Applications, 2009, 36(3), 4278–4286.

DOI: 10.1016/j.eswa.2008.03.008

Google Scholar

[4] Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent fault diagnosis and prognosis for engineering systems. USA: John Wiley & Sons.

DOI: 10.1002/9780470117842

Google Scholar

[5] Shen Qing, An introduction to pattern recognition, Hefei, University of Science and Technology of China press, (1991).

Google Scholar

[6] Liu Jianmin, holding on, Fuel injection pressure sensor voltage wave engine engineering, 1996(1), P35-40.

Google Scholar

[7] Zhu Honghui, Tong force. A virtual instrument soft panel design practical technology. Automation and instrumentation, ninety-first, 2000 (5): 32 ～ 34.

Google Scholar

[8] Zha, X. F. Artificial intelligence and integrated intelligent information systems. USA: Idea Group Publishing, (2006).

Google Scholar