Probabilistic Latent Component Analysis for Gearbox Vibration Source Separation

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Joshua Isom Madhusudana Shashanka Ashutosh Tewari Aleksandar Lazarevic

Abstract

Probabilistic latent component analysis (PLCA) is applied to the problem of gearbox vibration source separation. A model for the probability distribution of gearbox vibration employs a latent variable intended to correspond to a particular vibration source, with the measured vibration at a particular sensor for each source the product of a marginal distribution of vibration by frequency, a marginal distribution of vibration by shaft rotation, and a sensor weight distribution. An expectation-maximization algorithm is used to approximate a maximum-likelihood parameterization for the model. In contrast to other unsupervised source-separation methods, PLCA allows for separation of vibration sources when there are fewer vibration sensors than vibration sources. Once the vibration components of a healthy gearbox have been identified, the vibration characteristics of damaged gearbox elements can be determined. The efficacy of the technique is demonstrated with an application on a gearbox vibration data set.

How to Cite

Isom, J., Shashanka, M., Tewari, A., & Lazarevic, A. (2010). Probabilistic Latent Component Analysis for Gearbox Vibration Source Separation. Annual Conference of the PHM Society, 2(1). https://doi.org/10.36001/phmconf.2010.v2i1.1889
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Keywords

vibration, gearbox, source separation

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Section
Technical Papers