A Review of Time Synchronous Average Algorithms

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Published Mar 26, 2021
Eric Bechhoefer Michael Kingsley

Abstract

Time Synchronous Average (TSA) is an essential algorithmic tool for determining the condition of rotating equipment. Given its significance to diagnostics, it is important to understand the algorithms performance characteristics. This paper addresses four topics in relation to the TSA performance characteristics. The first topic is the evaluation of the performance (measured against gear fault detection) of 6 different TSA algorithms. The second topic is quantifying the ergodicity/noise reduction as a function of the number of revolutions in the TSA and show that noise reduction is 1/sqrt(number of revolutions). The third topic examines TSA techniques when no tachometer signal is available.The final topic shown is the distribution of the magnitude of TSA orders associated with fault and nominal components are Rice and Rayleigh distributed.

How to Cite

Bechhoefer, E. ., & Kingsley, M. . (2021). A Review of Time Synchronous Average Algorithms. Annual Conference of the PHM Society, 1(1). Retrieved from https://papers.phmsociety.org/index.php/phmconf/article/view/1666
Abstract 39 | PDF Downloads 21

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Keywords

condition monitoring, time domain analysis

References
(Comber, 2007) Combet, L., Gelman L., “An automated methodology for performing time synchronous averaging of a gearbox signal without seed sensor”, Mechanical Systems and Signal Processing, Volume 21, Issue 6, August 2007, 2590-2606.
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(Bechhoefer 2007) Eric Bechhoefer, Andreas Bernhard, “A Generalized Process for Optimal Threshold Setting in HUMS” IEEE Aerospace Conference, Big Sky, 2007.
Section
Technical Papers

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