Methodology for evaluating neural networks inputs for gear fault detection

In this paper, the Artificial Neural Network (ANN) inputs selection for detecting and quantifying the progressive value of an incipient defect in gears is carried out by experimental design evaluation. Several parameters in time-domain (Root Mean Squared, Crest Factor, Energy Ratio, FM0, Kurtosis, FM4, NA4, M6A, NB4) and multiscale Hilbert-wavelet transformations are evaluated as a possible inputs. Suitable inputs, according to the proposed evaluating methodology, do enhance ANN performance.

[1]  Nguyen Phong Dien,et al.  Fault diagnosis in gears operating under non-stationary rotational speed using polar wavelet amplitude maps , 2004 .

[2]  Marianne Mosher,et al.  Evaluation of Standard Gear Metrics in Helicopter Flight Operation , 2002 .

[3]  B. David Forrester,et al.  Advanced vibration analysis techniques for fault detection and diagnosis in geared transmission systems , 1996 .

[4]  Zhipeng Feng,et al.  Application of atomic decomposition to gear damage detection , 2007 .

[5]  Józef Korbicz,et al.  Confidence estimation of the multi-layer perceptron and its application in fault detection systems , 2008, Eng. Appl. Artif. Intell..

[6]  Ibrahim Esat,et al.  ARTIFICIAL NEURAL NETWORK BASED FAULT DIAGNOSTICS OF ROTATING MACHINERY USING WAVELET TRANSFORMS AS A PREPROCESSOR , 1997 .

[7]  B. Samanta,et al.  Gear fault detection using artificial neural networks and support vector machines with genetic algorithms , 2004 .

[8]  H. Zheng,et al.  GEAR FAULT DIAGNOSIS BASED ON CONTINUOUS WAVELET TRANSFORM , 2002 .

[9]  Nii O. Attoh-Okine,et al.  The Hilbert-Huang Transform in Engineering , 2005 .

[10]  Robert B. Randall,et al.  Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter , 2007 .

[11]  Neural networks for instrumentation, measurement and related industrial applications , 2003 .

[12]  Cheng-Kuo Sung,et al.  Locating defects of a gear system by the technique of wavelet transform , 2000 .