Oil condition monitoring of gears onboard ships using a regression approach for multivariate T2 control charts

Morten Henneberg, Bent Jørgensen, René Lynge Eriksen

Research output: Contribution to journalJournal articleResearchpeer-review


In this paper, we present an oil condition and wear debris evaluation method for ship thruster gears using T2 statistics to form control charts from a multi-sensor platform. The proposed method takes into account the different ambient conditions by multiple linear regression on the mean value as substitution from the normal empirical mean value. This regression approach accounts for the bias imposed on the empirical mean value due to different geographical and seasonal differences on the multi-sensor inputs.
Data from a gearbox are used to evaluate the length of the run-in period in order to ensure only quasi-stationary data are included in phase I of the T2 statistics. Data from two thruster gears onboard two different ships are presented and analyzed, and the selection of the phase I data size is discussed.
A graphic overview for quick localization of T2 signaling is also demonstrated using spider plots.
Finally, progression and trending of the T2 statistics are investigated using orthogonal polynomials for a fix-sized data window.
Original languageEnglish
JournalJournal of Process Control
Pages (from-to)1-10
Publication statusPublished - 1. Oct 2016

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