Wear Measurement by Real-Time Condition Monitoring Using Ferrography

Abstract

Condition monitoring apreventive maintenance is applied in a variety of industries such as advanced combustion engine, metal working, manufacturing, artificial intelligence (AI) expert systems, aircraft engines, and heavy earth moving machines (HEMM). Machine condition monitoring improves the overall equipment effectiveness as well as the quality of product and prevents downtimes. Condition monitoring monitors important parameters such aspressure, temperature, load, and wear particles and predicts about failure that will about to happen. From the analysis, it will be suggested whether to go for scheduled maintenance or to replace the wear out parts to prevent substantial damages to the whole unit. Thus it improves the health of machine parts. There are so many methods for condition monitoring such as vibration analysis, oil analysis, noise analysis, acoustic emission analysis, thermography, etc. In this paper, oil analysis by ferrography is mainly focused. In ferrography, wear particles from machine components arestudied through analysis of contaminants obtained from used lubricating oil, which can be used to predict and identify errors that occurred in the machinery. Ferrography is carried out ona quantitative and qualitative basis. Both are equally important for determining the root cause of machine component failure. Direct reading (DR) ferrography is used for quantitative analysis to determine the concentration of wear particles. Analytical ferrography is used for qualitative analysis to find the morphology of wear particle (number, shape, size, mechanism of wear). By using this analysis, replacement of wear-out parts, change of degraded lubricant or scheduled maintenance is suggested to increase the life of machinery.