Abstract
Machinery fault detection as part of predictive maintenance based on the machine vibration has been practiced comprehensively in oil and gas industry and power generation plant for maintaining the reliability of the machineries. Despite the advantages, the efforts of identifying machinery fault earlier may lead to inaccurate interpretation and diagnosis due to lack of knowledge, skill and experience. Conventional vibration data acquisition and analysis using single axis accelerometer are time consuming. Therefore, an approach which relies on the visualisation of machine vibration motion technique is proposed. The visualisation of machine vibration motion was performed through a simplified Operating Deflection Shape (ODS) analysis. ODS analysis on a 4 measurement points is enough to show the motion of general machinery arrangement which consist of 2 bearings on the drive side and another 2 bearings on the driven side. The effectiveness of the simplified technique was tested in a laboratory condition before being applied in oil and gas industry. The results show vibration data acquisition is more efficient and time saving by using tri-axis accelerometer and relative phase technique. Furthermore, machinery fault diagnosis can be identified easily, faster and more accurate through visualising the machine vibration motion using a simplified 4-point ODS. This simplified technique is seen as practical approach to be proposed and integrated into conventional machinery fault detection and predictive maintenance based on the machine vibration.
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More From: IOP Conference Series: Materials Science and Engineering
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