Sliding Wear Particle Mass Distribution Assessment for Wear Mode Diagnosis

Surapol Raadnui
Submission Type: 
Full Paper
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phmc_15_003.pdf1.73 MBAugust 12, 2015 - 6:10pm

Condition based maintenance has been coming to the fore especially in recent decades and it is at the expense of conventional maintenance strategies. Wear particle tribology-based predictive maintenance is based on continuous monitoring, evaluating its condition and uses knowledge of technical diagnostics and prognostics. The use of sliding wear particle mass distribution as a means for distinguishing different modes of wear and determining its transitory behavior is evaluated in terms of the quantitative analysis of the multi-filtergram slides produced from a series of wear tests from a multiple point contact sliding wear tester. In this particular research, a four ball machine was used throughout. At the end of each test the wear debris generated was collected and then separated using a multi-filtergram maker which resulted in the wear debris being extracted due to their specific size ranges. Each filtergram patch of each specific size range was subsequently weighed to obtain “wear particle mass distribution” which in turn can be used to produce a histogram plot of the particle mass distribution. Various distribution functions have been fitted with the data. The results obtained from different sliding wear modes are presented; they confirm that changes in the mean and the variance of the selected statistical distributions provide clear indications of the type and extent of the sliding wear as it progresses.

Publication Year: 
2015
Publication Volume: 
6
Publication Control Number: 
003
Page Count: 
7
Submission Keywords: 
Mass Distribution; Predictive Maintenance; Wear Particle Analysis
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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