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Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

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Abstract

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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Authors and Affiliations

  1. Korea Gas Technology Corporation, 839, Bongsan, Yuseong, Daejeon, 305-506, Korea

    Hack-Eun Kim & Sung-Soo Hwang

  2. CRC for Integrated Engineering Asset Management, School of Engineering Systems, Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia

    Andy C. C. Tan & Joseph Mathew

  3. Department of Energy and Mechanical Engineering, Institute of Marine Industry, Gyeongsang National Univ., 445 Inpyeong, Tongyoung, Gyeongnam, 650-160, Korea

    Byeong-Keun Choi

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  1. Hack-Eun Kim
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  3. Andy C. C. Tan
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Correspondence to Hack-Eun Kim.

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Recommended by Editor Sung-Lim Ko

Hack-Eun Kim is the Senior Manager of R&D Team in Korea Gas Technology (KOGAS-Tech) located Daejeon, Korea. He received his PhD degree in mechanical engineering from Queensland University of Technology, Brisbane, Australia. He received master of engineering in mechanical from Gyeongsang National University, Gyeongnam. He was recipient of Top-up Scholarships from “QUT Built Environment and Engineering Research” and ‘Cooperative Research Centre for Integrated Engineering Asset Management (CIEAM)’. His interests in research include condition monitoring, diagnosis and prognosis for intelligent maintenance decision support and engineering asset management.

Sung-Soo Hwang is the General Manager of Incheon LNG Receiving Terminal Office in Korea Gas Technology (KOGAS-Tech) located Incheon, Korea. He is currently Ph.D candidate and received master of engineering in mechanical system from Korea Polytechnic University, Gyeonggi, Korea. He was recipient of “Award of Best Achievement” from chancellor during his master course. His interests in research include fluid dynamics analysis, condition monitoring and fault diagnosis. He has worked as an acknowledged expert of mechanical and maintenance in natural gas industry over 25 years.

Andy C. C Tan received his BSc(Eng) and Ph.D degrees in mechanical engineering from the University of Westminster, London. His research interests include noise and vibration condition monitoring and sensors for active vibration control. He is a pioneer of artificial heart pump project in Queensland, Australia and a professor of mechanical engineering at the Faculty of Built Environment and Engineering of the Queensland University of Technology. His academic interests include dynamics of mechanical systems, noise and vibrations and mechanism design. In engineering education, he receives international recognition for pioneering the first joint degrees program. He is a Fellow of the Institution of Engineers, Australia.

Joseph Mathew is the Chief Executive Officer of the Cooperative Research Centre in Infrastructure and Engineering Asset Management (CIEAM) located Brisbane, Australia. He was previously Queensland University of Technology’s Head of School in the School of Mechanical, Manufacturing and Medical Engineering. Prior to arriving in Brisbane in 2000, Joe was Monash University’s Professor of Manufacturing and Industrial Engineering in Melbourne. He has also served as Executive Director of Monash’s Centre for Machine Condition Monitoring from 1993–1997. He has presented numerous invited lectures and addresses to professional societies and industrial organisations on engineering asset management, machine condition monitoring, and vibrations and noise control. He serves as Chairman of the Board of the International Society of Engineering Asset Management (ISEAM), Chairman of the ISO’s subcommittee ISO/TC 108/SC 5 on Condition Monitoring and Diagnostics of Machines and as General Chair for the World Congress on Engineering Asset Management (WCEAM).

Byeong-Keun Choi is an Associate Professor at the Department of Energy and Mechanical Engineering at Gyeongsang National University in Korea. He received his Ph.D. degrees in Mechanical Engineering from Pukyong National University, Korea, in 1999. Dr. Choi worked at Arizona State University as an Academic Professional from 1999 to 2002. Dr. Choi’s research interests include vibration analysis and optimum design of rotating machinery, machine diagnosis and prognosis and acoustic emission. He is listed in Who’s Who in the World, among others.

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Kim, HE., Hwang, SS., Tan, A.C.C. et al. Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation. J Mech Sci Technol 26, 3571–3585 (2012). https://doi.org/10.1007/s12206-012-0850-4

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