Fault prognosis and diagnosis of an automotive rear axle gear using a RBF-BP neural network

Journal of Physics: Conference Series

Volumn 305, Issue 1, 2011, Pages

  Shao, Yimin ^a,c   Liang, Jie ^a   Gu, Fengshou ^b   Chen, Zaigang ^a   Ball, Andrew ^b  

^a CHONGQING UNIVERSITY   (China)

^b UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

^c CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AXLES; BACKPROPAGATION; DAMAGE DETECTION; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; REAR AXLES; TRANSMISSIONS; VIBRATIONS (MECHANICAL);

BACK PROPAGATION NEURAL NETWORKS; LOAD AND SPEED FLUCTUATIONS; NONLINEAR CHARACTERISTICS; RADIAL BASIS FUNCTION(RBF); SECURITY AND RELIABILITIES; SELF-LEARNING ABILITY; TRANSMISSION SYSTEMS; VIBRATION CHARACTERISTICS;

FAULT DETECTION;

EID: 80052042207     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/305/1/012063     Document Type: Conference Paper

References (13)

1. Li C J and Lee H 2005 Gear fatigue crack prognosis using embeded model, gear dynamic model and fracture mechanics Mech. Syst. Signal Process. 19 836-846
2. Zhan Y M and Makis V 2006 A robust diagnostic model for gearboxes subject to vibration monitoring J. Sound Vib. 290 928-955
3. Loutridis S J 2006 Instantaneous energy density as a feature for gear fault detection Mech. Syst. Signal Process. 20 1239-1253
4. Loutridis S J 2008 Gear failure prediction using multiscale local statistics Eng. Struct. 30 1214-1223
5. Kramberger J, Sraml M, Potrc I and Flasker J 2004 Numerical calculation of bending fatigue life of thin-rim spur gears Eng.Frac. Mech. 71 647-656
6. Khan M A,Cooper D,Starr A 2009 BS-ISO helical gear fatigue life estimation and wear quantitative feature analysis Strain 45 358-363
7. Hong S Z,Wei H 2008 Remote fault diagnosis system of rotating machinery based on inspection model Mod. manuf. Eng. 4 23-25
8. Subrahmanya N 2010 A Bayesian machine learning method for sensor selection and fusion with application to on-board fault diagnostics Mech.Syst. Signal Process. 24 182-192
9. Shao Y and Nezu K 2002 Prognosis of remaining bearing life using neural networks J. Syst. Control Eng. 214 217-230
10. Wang J and Hu X 2005 Matlab applications in vibration signal processing (Water conservancy and hydropower press)
11. Wei H K 2005 The structural design of neural network theory and method (Beijing Defense Industry press)
12. Shao Y M, Li X X, Chris K, Mechefske and Chen Z G 2009 Rear axle gear damage prediction using vibration signal preprocessing coupled with RBF neural networks Main. Relia. 4 57-64
13. Zhang X H, Lei Y 2008 Application of BP Neural Network in Mechanical Fault Diagnosis J. noise vib.control 10 95-97 Wealth