Identification of the defective transmission devices using the wavelet transform

In this paper, a system is described that uses the wavelet transform to automatically identify the particular failure mode of a known defective transmission device. The problem of identifying a particular failure mode within a costly failed assembly is of benefit in practical applications. In this system, external acoustic sensors, instead of intrusive vibrometers, are used to record the acoustic data of the operating transmission device. A skilled factory worker, who is unfamiliar with statistical classification, helps to determine the feature vector of the particular failure mode in the feature extraction process. In the automatic identification part, an improved learning vector quantization (LVQ) method with normalizing the inputting feature vectors is proposed to compensate for variations in practical data. Some acoustic data, which are collected from the manufacturing site, are utilized to test the effectiveness of the described identification system. The experimental results show that this system can identify the particular failure mode of a defective transmission device and find out the causes of failure successfully.

[1]  Dennis P. Townsend,et al.  Vibration Signature Analysis of a Faulted Gear Transmission System , 1996 .

[2]  古井 貞煕,et al.  Digital speech processing, synthesis, and recognition , 1989 .

[3]  P. D. McFadden,et al.  APPLICATION OF WAVELETS TO GEARBOX VIBRATION SIGNALS FOR FAULT DETECTION , 1996 .

[4]  Sigeru Omatu,et al.  New and Used Bill Money Classification Using Spectral Information Based on Acoustic Data of Banking Machine , 1997 .

[5]  David L. Donoho,et al.  A First Course in Wavelets with Fourier Analysis , 2002 .

[6]  A. Nejat Ince,et al.  Digital Speech Processing , 1992 .

[7]  M. V. Velzen,et al.  Self-organizing maps , 2007 .

[8]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[9]  James J. Zakrajsek A Review of Transmission Diagnostics Research at NASA Lewis Research Center. , 1994 .

[10]  Sigeru Omatu,et al.  Quality Evaluation of Machines Using the LVQ (Special Issue on the Application of Signal Processing(2)) , 2003 .

[11]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[12]  Francis J. Narcowich,et al.  A First Course in Wavelets with Fourier Analysis , 2001 .

[13]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[15]  Jean-Michel Poggi,et al.  Wavelets and their applications , 2007 .