Non-Destructive Testing and Diagnostic of Rotating Machinery Faults in Petrochemical Processing Plant

4th International Conference on Mechanical and Aeronautical Engineering

机械制造;航空航天工程

Chao, Ong Zhi^1 ; Mohd Mishani, Mohd Bakar^1 ; Yee, Khoo Shin^1 ; Ismail, Zubaidah^2

Department of Mechanical Engineering, University of Malaya, Kuala Lumpur

5060, Malaysia^1

Department of Civil Engineering, University of Malaya, Kuala Lumpur

50603, Malaysia^2

关键词: Machinery fault detection;    Machinery fault diagnosis;    Non destructive testing;    Operating deflection shape analysis;    Petrochemical processing;    Power generation plants;    Single axis accelerometers;    Tri-axis accelerometers;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/491/1/012007/pdf
DOI  :  10.1088/1757-899X/491/1/012007

学科分类：航空航天科学

来源: IOP

【 摘 要 】

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.