HELICOPTER TRANSMISSION FAULT DETECTION VIA TIME-FREQUENCY, SCALE AND SPECTRAL METHODS

Abstract The vast majority of the powerful and effective algorithms in signal processing start with the assumption of stationarity. In addition, the deterministic portion of the signal is often assumed to be composed of complex exponentials which are the solutions to linear time-invariant (LTI) differential equations. Many signals do not comply with these assumptions, however, resulting in disappointment when conventional techniques are used. We now have at hand time–frequency (t–f) and scale transform analyses which can provide new insights into the nature of non-stationary signals. This paper describes some results using reduced interference distributions (RIDs) and scale transforms in the analysis of signals obtained from accelerometers placed strategically on a Westland helicopter transmission. Fault detection algorithms for several types of faults were compared and the methods based on the scale transform performed best followed by RID results. More conventional spectral-analysis-based methods were the least effective.

[1]  Robert J. Marks,et al.  The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals , 1990, IEEE Trans. Acoust. Speech Signal Process..

[2]  P. D. McFadden,et al.  Early detection of gear failure by vibration analysis--ii. interpretation of the time-frequency distribution using image processing techniques , 1993 .

[3]  W. J. Williams,et al.  Reduced interference distributions: biological applications and interpretations , 1996, Proc. IEEE.

[4]  William J. Williams,et al.  Improved time-frequency representation of multicomponent signals using exponential kernels , 1989, IEEE Trans. Acoust. Speech Signal Process..

[5]  Olivier Rioul,et al.  Time-scale energy distributions: a general class extending wavelet transforms , 1992, IEEE Trans. Signal Process..

[6]  Leon Cohen,et al.  Generalized ambiguity functions , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  P. D. McFadden,et al.  Early Detection of Gear Failure by Vibration Analysis--I. Calculation of the Time Frequency Distribution , 1993 .

[8]  Boualem Boashash,et al.  Time-Frequency Signal Analysis: Methods and Applications. , 1993 .

[9]  L. Cohen Generalized Phase-Space Distribution Functions , 1966 .

[10]  Jechang Jeong,et al.  Alias-free generalized discrete-time time-frequency distributions , 1992, IEEE Trans. Signal Process..

[11]  Douglas L. Jones,et al.  A signal-dependent time-frequency representation: optimal kernel design , 1993, IEEE Trans. Signal Process..

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

[13]  William J. Williams,et al.  Reduced Interference Time-Frequency Distributions , 1992 .

[14]  Paolo Bonato,et al.  BILINEAR TIME-FREQUENCY TRANSFORMATIONS IN THE ANALYSIS OF DAMAGED STRUCTURES , 1997 .

[15]  William J. Williams,et al.  Discrete scale transform for signal analysis , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[16]  Ingrid Daubechies,et al.  Time-frequency localization operators: A geometric phase space approach , 1988, IEEE Trans. Inf. Theory.

[17]  William J. Williams,et al.  Separating desired image and signal invariant components from extraneous variations , 1996, Optics & Photonics.

[18]  David J. Whitehouse,et al.  The Application of the Wigner Distribution Function to Machine Tool Monitoring , 1992 .

[19]  Alfred O. Hero,et al.  Scale and Translation Invariant Methods for Enhanced Time-Frequency Pattern Recognition , 1998, Multidimens. Syst. Signal Process..

[20]  Leon Cohen,et al.  The scale representation , 1993, IEEE Trans. Signal Process..

[21]  Les E. Atlas,et al.  Construction of positive time-frequency distributions , 1994, IEEE Trans. Signal Process..

[22]  Jechang Jeong,et al.  Kernel design for reduced interference distributions , 1992, IEEE Trans. Signal Process..

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