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With Junhong Zhou

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Associate Professor

Junhong Zhou

Associate Professor
Ph.D (Mechatronics and Design), Nanyang Technological University , Singapore
Cluster:
Engineering
Email

SIT Appointments

  • Associate Professor
    – Present

Education

  • Ph.D (Mechatronics and Design)
    Nanyang Technological University , Singapore
  • M. Eng (Electrical and Computer Engineering)
    National University of Singapore , Singapore
  • B.Eng (Automation and Control)
    Tsinghua University , China

Achievements

  • Best Paper in the Special Session of Advanced Signal processing tools for failure detection and diagnosis, Annual Conference of the IEEE Industrial Electronics Society (IECON) 2013
    –
  • Best Paper Award, IASTED International Conference on Engineering and Applied Science (EAS 2012), Colombo, Sri Lanka
    –
  • The Best Application Paper, The Eighth Asian Control Conference (ASCC 2011), Kaohsiung, Taiwan
    –
  • Research Scholarship
    –

Professional Memberships

  • Institute of Electrical and Electronics Engineers (IEEE), Member
    – Present

Corporate Experience

  • Principal research engineer, Singapore Institute of Manufacturing Technology (SIMTech), A*Star
    –
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Research Interests

  • Data analytics, machine learning,

    Smart manufacturing

    Condition based maintenance

    industrial internet of things (IIoT)

Current Projects

  • Industry 4.0 Setup for Machine Connectivity in MRO Shop Floor
    – Present

    A-Star SERC Aerospace Programme (SIAEC) funded project. 

    The project is to research the Brownfield machine connectivity for first mile of digitalization to fast convert an existing MRO production line to an Industry 4.0 line.

    I'm the Co-Principal investigator for the project

    Project grant is $443k

  • NRF Cities of Tomorrow - An integrated smart solution for lift safety monitoring and fault predictive diagnosis
    – Present

    The approved grant for the project  is $2103k. 

    I'm the Co-Principal investigator for the project

    The project is to develop of data analytics methods and system platform for lift safety monitoring and fault prognosis.

Past Projects

  • Data analytics for aircraft systems failure prediction
    –

    A-Star SERC Aerospace Programme (SIAEC) funded project. 

    The project is to develop of data analytics methods and system platform for aircraft systems failure prediction.

    I'm the Co-Principal investigator for the project

    Project grant is $403k

  • Disruptive Big Data Analytics Approaches and Data Management Strategy for Complex System Health Management
    –

    A-Star SERC Aerospace Programme (SIAEC) funded project. 

    The project is to investigate the data management strategies and existing technologies (with the support of co-sponsors) for aircraft and engine data and to develop innovative machine learning approaches or alternative reasoning approaches to model and classify failure progression and system usage profiles in support of time to fail estimations.

    Project grant is $388k

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Journal Papers

  • Geramifard, J. X. Xu and J. H. Zhou, "Diagnostics and Prognostics of Engineering Systems: Methods and Techniques", pp. 205-228, IGI Global, Hershey, PA

  • X. J. Wang, J. H. Zhou, H. C. Yan, C. K. Pang, “Quality monitoring of spot welding with advanced signal processing and data-driven techniques”, Transactions of the Institute of Measurement and Control,

  • H. C. Yan,J. H. Zhou,C. K. Pang, “Gaussian Mixture Model Using Semisupervised Learning for Probabilistic Fault Diagnosis Under New Data Categories”, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Volume: 66 , Issue: 4

  • H. C. Yan,J. H. Zhou,C. K. Pang, "Machinery Degradation Inspection and Maintenance Using A Cost-Optimal Non-Fixed Periodic Strategy", IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

  • H. C. Yan,J. H. Zhou,C. K. Pang, "Gamma process with recursive MLE for wear PDF prediction in precognitive maintenance under aperiodic monitoring", IEEE Transactions on Mechatronic

  • M. Luo, B. Hu, H. C. Yan, J. H. Zhou and C. K. Pang, "Data-Driven Two-Stage Maintenance Framework for Degradation Prediction in Semiconductor Manufacturing Industries", Computers & Industrial Engineering

  • C. K. Pang,J. H. Zhou,H. C. Yan, "PDF and Breakdown Time Prediction for Unobservable Wear Using Enhanced Particle Filters in Precognitive Maintenance", IEEE Transactions on Instrumentation and Measurement, pp. 649-659, vol. 64, no. 3

  • O. Geramifard, J. X. Xu, J. H. Zhou and X. Li, "Multi-Modal Hidden Markov Model-based Approach for Tool Wear Monitoring", IEEE Transactions on Industrial

  • C. K. Pang, J. H. Zhou and X. Y. Wang, "A MIXED TIME-/CONDITION-BASED PRECOGNITIVE MAINTENANCE FRAMEWORK FOR ZERO-BREAKDOWN INDUSTRIAL SYSTEMS", Control and Intelligent Systems, vol. 41(3), pp. 127-135

  • G. Omid, J. X. Xu, J. H. Zhou and X. Li, "A Physically Segmented Hidden Markov Model Approach for Continuous Tool Condition Monitoring: Diagnostics and Prognostics", IEEE Transactions on Industrial Informatics, vol. 8(4), pp. 964-973

  • J. H. Zhou, C. K. Pang, F. L. Lewis and Z. W. Zhong, "Dominant Feature Identification for Industrial Fault Detection and Isolation Applications", Expert Systems with Applications , vol. 38(8), pp. 10676-10684

  • J. H. Zhou, C. K. Pang, Z. W. Zhong and F. L. Lewis, "Tool Wear Monitoring Using Acoustic Emissions By Dominant Feature Identification", IEEE Transactions on instrumentation and measurement, vol. 60(2), pp. 547-559

  • X. Li, M. J. Er, B. S. Lim, J. H. Zhou, O. P. Gan and L. Rutkowski, "Fuzzy Regression Modelling for Tool Performance Prediction and Degradation Detection", International Journal of Neural Systems, vol. 20(5), pp. 405-419

  • J. H. Zhou, C. K. Pang, F. L. Lewis and Z. W. Zhong, "Intelligent Diagnosis and Prognosis of Machine Tool Wear Using Dominant Feature Identification", IEEE Transactions on Industrial Informatics, vol. 5(4), pp. 454-464

  • J. H. Zhou, C. K. Pang, F. L. Lewis, Z. W. Zhong; “Intelligent Diagnosis and Prognosis of Machine Tool Wear Using Dominant Feature Identification”; IEEE Transactions on Industrial Informatics (2009), vol. 4; pp.454-464;

  • X. Li, D. M. Shi, V. Charastrakul and J. H. Zhou, "Advanced P-Tree Based K-Nearest Neighbors for Customer Preference Reasoning Analysis", Journal of Intelligent Manufacturing, vol. Number 5, pp. 569-579

  • J. H. Zhou, Z. W. Zhong, M. Luo and C. Shao, "Wavelet-based correlation modeling for health assessment of fluid dynamic bearings in brushless DC motors", International Journal of Advanced Manufacturing Technology, vol. 41(5-6), pp. 421-429

  • X. Li, J. H. Zhou, W. F. Lu; Quantification of Customer Multi-Preference and Motivation through Data and Text Mining in New Product Design, Publication year 2006; vol. 1, pp. 99-118, Integrated Intelligent Systems for Engineering Design, Amsterdam, Berlin, Oxford, Tokyo, Washington DC, IOS Press

  • W.K. Ho, C.C. Hang and J.H. Zhou; “Self-Tuning PID Control of a plant with under-Damped Response with Specifications on Gain and Phase Margins”; IEEE Transactions Control System Technology, vol. 5; No.4, pp. 446-452

  • W. K. Ho, C.C. Hang, J. H. Zhou; “Performance and Gain and Phase Margins of well-known PI Tuning Formulas”; IEEE Transitions on Control Systems Technology, Vol 3; Pages 245-248;

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Teaching Modules

Electronics and Data Engineering, BEng (Hons)

  • EDE3101 - Data Analytics
  • EDE3102 - Machine Learning
  • EDE3104 - Internet of Things

Mechanical Engineering, BEng (Hons)

  • MEC2361 - Industrial Internet of Things and Data Analytics 1
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