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Valve regulated lead acid battery diagnostic system based on infrared thermal imaging and fuzzy algorithm

Author

Listed:
  • Neeraj Khera

    (Amity University)

  • Shakeb A. Khan

    (Jamia Millia Islamia, Central University)

  • Obaidur Rahman

    (Jamia Millia Islamia, Central University)

Abstract

In recent times, advanced inspection technique like infrared thermography (IRT) has been used widely for fault diagnosis of electrical equipment in non-contact, non-destructive and non-invasive manner. Manual classification of faults from the IRT images requires more time and effort. In this work, an intelligent scheme for predictive fault diagnosis in VRLA battery is presented for scheduling its preventive maintenance. IR images of pristine and aged VRLA battery in uninterrupted power supply application are acquired using IR camera at different discharging cycles. Image processing of IR images is performed for detection of faults. In order to intelligently classify the faults a fuzzy inference system is developed. Proposed scheme for automatic diagnosis and classification of faults in VRLA battery is implemented using LabVIEW 2015 software. The output information defining the condition of VRLA battery is displayed on front panel of LabVIEW and stored in MS Excel file with the time stamp at hard disk of host computer for further reliability analysis. Based on occurrence of major faults in VRLA battery, alert signal is send to intended users at both onsite and remote locations. To facilitate remote condition monitoring of VRLA battery, front panel information is continuously provided to remote user using web publishing tool of LabVIEW. Using proposed technique, the fault diagnosis of lead acid batteries in different battery applications can similarly be performed in non-invasive manner.

Suggested Citation

  • Neeraj Khera & Shakeb A. Khan & Obaidur Rahman, 2020. "Valve regulated lead acid battery diagnostic system based on infrared thermal imaging and fuzzy algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 614-624, June.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:3:d:10.1007_s13198-020-00958-z
    DOI: 10.1007/s13198-020-00958-z
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    References listed on IDEAS

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    1. Mohammad Ali Farsi & S. Masood Hosseini, 2019. "Statistical distributions comparison for remaining useful life prediction of components via ANN," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 429-436, June.
    2. Bahman Shabani & Manu Biju, 2015. "Theoretical Modelling Methods for Thermal Management of Batteries," Energies, MDPI, vol. 8(9), pages 1-25, September.
    3. Neeraj Khera & Shakeb A. Khan & Tariqul Islam & A. K. Agarwala, 2016. "An intelligent technique for condition based self-maintenance of aluminum electrolytic capacitors," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(1), pages 25-34, March.
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