Using Image Processing And Quantitative Technique To Determine The Onset Of Gear Failure

Tengku Ahmad Hafiz, Tengku Din (2015) Using Image Processing And Quantitative Technique To Determine The Onset Of Gear Failure. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 Pages) Using Image Processing And Quantitative Technique To Determine The Onset Of Gear Failure.pdf - Submitted Version Download (309kB)

Abstract

The aim of this study is to predict the onset of gear failure based on operating hours. Wear Debris Analysis (WDA) has been proven useful in providing valuable information as it also provides supporting indication of the nature and severity of gear failure. It is important to analyse the basic features of wear debris for prediction of component machine condition. In this research, a back to back test rig was used to study the effect of deterioration stage of gear against abnormal loading time. This thesis proposes an offline sampling technique which uses image processing and particle counts to diagnose the condition of machinery. It emphasizes on using size, shape and surface texture of the particles generated over time to predict onset of gear failure. Therefore, maintenance action can be taken before gears reach catastrophic failure. By the end of the experiment, result shows an increasing of operating time, there will be an increasing of size and increasing the number of particle count of wear particles that generated from friction between two surfaces of gears.

Actions (login required)

View Item