Fault diagnosis in starter motors by classification of wavelet analysis results of faulty Starter motor's current signals using fuzzy logic Marş motoru akim si̇nyalleri̇ wavelet anali̇z sonuçlarinin Bulanik mantik i̇le siniflandirilarak ariza tespi̇ti̇

Bayir R., BAY Ö. F.

Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.22, sa.2, ss.363-374, 2007 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 2
  • Basım Tarihi: 2007
  • Dergi Adı: Journal of the Faculty of Engineering and Architecture of Gazi University
  • Derginin Tarandığı İndeksler: Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.363-374
  • Anahtar Kelimeler: Fault diagnosis, Fuzzy logic, Starter motor, Wavelet analysis
  • Gazi Üniversitesi Adresli: Evet

Özet

Starter motors are serial wound dc motors work under heavy duty. Starter motors are used to run the internal combustion engine (ICE). Internal combustion engines can not be run when starter motor is defective. The values of current drawn by starter motor and the voltage across the starter motor vary depending on time. In the analysis of time dependent signals (unstable signals), Wavelet Analysis (WA) is used. In this study, the current and the voltage signals of starter motors are measured by using a measurement rig and current signals of a starter motor is decomposed to its components with the help of Wavelet Analysis. With the use of coefficients derived from the decomposition, defects observed in starter motors and starter system is classified using fuzzy logic. A graphical user interface (GUI) software has been developed by using MATLAB for fault diagnosis. By using this developed fault diagnosis system, six defects seen in starter motors frequently have been diagnosed successfully.