Pattern classifier for fault diagnosis of helicopter gearboxes

Abstract Application of a diagnostic system to a helicopter gearbox is presented. The diagnostic system is a nonparametric pattern classifier that uses a multi-valued influence matrix (MVIM) as its diagnostic model and benefits from a fast learning algorithm that enables it to estimate its diagnostic model from a small number of measurement-fault data. To test this diagnostic system, vibration measurements were collected from a helicopter gearbox test stand during accelerated fatigue tests and at various fault instances. The diagnostic results indicate that the MVIM system can accurately detect and diagnose various gearbox faults so long as they are included in training.

[1]  David G. Lewicki,et al.  Full-scale transmission testing to evaluate advanced lubricants , 1992 .

[2]  Robert B. Randall,et al.  A New Method of Modeling Gear Faults , 1982 .

[3]  Stephen I. Gallant.  Automated generation of connectionist expert systems for problems involving noise and redundancy , 1988, Int. J. Approx. Reason..

[4]  R. Palmer,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[5]  Erland Yhland,et al.  Analysis of Bearing Vibration , 1970 .

[6]  P. McFadden.  Examination of a technique for the early detection of failure in gears by signal processing of the time domain average of the meshing vibration , 1987 .

[7]  J. Mathew,et al.  The condition monitoring of rolling element bearings using vibration analysis , 1984 .

[8]  H. Saunders,et al.  Mechanical Signature Analysis—Theory and Applications , 1988 .

[9]  B. Datner,et al.  Analysis of Roller/Ball Bearing Vibrations , 1979 .

[10]  Janos J. Gertler,et al.  Analytical Redundancy Methods in Fault Detection and Isolation , 1991 .

[11]  K. Danai,et al.  FAULT-DIAGNOSIS WITH PROCESS UNCERTAINTY , 1991 .

[12]  J. I. Taylor,et al.  Identification of Bearing Defects by Spectral Analysis , 1980 .

[13]  P. D. McFadden,et al.  A Signal Processing Technique for Detecting Local Defects in a Gear from the Signal Average of the Vibration , 1985 .

[14]  Kourosh Danai,et al.  A Method of Fault Signature Extraction for Improved Diagnosis , 1991, 1991 American Control Conference.

[15]  L. F. Pau.  Failure Diagnosis and Performance Monitoring , 1986, IEEE Transactions on Reliability.

[16]  L. D. Mitchell,et al.  Detection of a Misaligned Disk Coupling Using Spectrum Analysis , 1984 .

[17]  R. M. Stewart,et al.  Detection of Rolling Element Bearing Damage by Statistical Vibration Analysis , 1978 .

[18]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[19]  Hsinyung Chin,et al.  Improved flagging for pattern classifying diagnostic systems , 1993, IEEE Trans. Syst. Man Cybern..

[20]  P. D. McFadden,et al.  Detecting Fatigue Cracks in Gears by Amplitude and Phase Demodulation of the Meshing Vibration , 1986 .

[21]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .