Probabilistic Latent Component Analysis for Gearbox Vibration Source Separation

Joshua Isom, Madhusudana Shashanka, Ashutosh Tewari, and Aleksander Lazarevic
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Full Paper
phmc_10_060.pdf6.33 MBAugust 30, 2010 - 2:52pm

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.

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Submission Keywords: 
source separation
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