@inproceedings{scholars1562,
            note = {cited By 6; Conference of 1st International Conference on Informatics and Computational Intelligence, ICI 2011 ; Conference Date: 12 December 2011 Through 13 December 2011; Conference Code:88517},
            year = {2011},
         journal = {Proceedings - 1st International Conference on Informatics and Computational Intelligence, ICI 2011},
             doi = {10.1109/ICI.2011.11},
         address = {Bandung},
           pages = {3--7},
           title = {Condition monitoring system for induction motor using fuzzy logic tool},
          author = {Janier, J. B. and Fazrin Zaim Zaharia, M.},
        keywords = {Computer-based system; Condition monitoring systems; Cost saving; Early detection; Faulty condition; Fuzzy inference systems; Inference systems; Maintenance activity; Predictive maintenance; System reliability, Artificial intelligence; Condition monitoring; Induction motors; Information science; Maintenance; Vibration analysis, Fuzzy logic},
        abstract = {Condition monitoring (CM) is a process which monitors the condition of equipment throughout its serviceable life in order to opt for Predictive Maintenance (PdM). This approach is based on the equipment's condition to determine at which point during future maintenance activities will be necessary. Implementing PdM will result in substantial cost savings and higher system reliability. This paper is focused on developing a computer based system applying Fuzzy Logic in order to identify and estimate the condition of an induction motor. Based on the vibration analysis characteristics of the motor, an unusual increase in the vibration could be an indicator of faulty condition. An inference system of the Fuzzy Logic was created and was able to classify the motor as 'acceptable' of the vibration ranges from 1.8mm/s to 4.5 mm/s or 'monitor closely' of the vibration ranges from 4.5 mm/s to 7.1 mm/s respectively. Early detection of unusual vibration increase of the motor is an important part of predictive maintenance (PdM). {\^A}{\copyright} 2011 IEEE.},
            isbn = {9780769546186},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857144659&doi=10.1109\%2fICI.2011.11&partnerID=40&md5=5dafaea0e5c5964808026c6c01fce58d}
}