Marş motoru akım sinyalleri wavelet analiz sonuçlarının bulanık mantık ile sınıflandırılarak arıza tespiti

Marş motorları ağır yük altında çalışan seri sargılı doğru akım motorlarıdırlar. Marş motorları içten yanmalı motorların (İYM) başlatılmalarını sağladıklarından marş motorunun arızalanması durumunda içten yanmalı motorlar çalıştırılamazlar. Marş motorunun çektiği akım ve uçlarında düşen gerilimin değeri zamana bağlı olarak değişmektedir. Zamana bağlı olarak değişen (durağan olmayan) sinyallerin incelenmesinde Wavelet Analizi (WA), Hızlı Fourier Dönüşümüne göre daha iyi sonuç vermektedir. Bu çalışmada, arızalı marş motorunun, akım ve gerilim sinyalleri, bir ölçüm düzeneği kullanılarak ölçülmüş ve arızalı marş motoruna ait akım sinyalleri wavelet analizi ile bileşenlerine ayrıştırılmıştır. Bu ayrıştırmadan elde edilen katsayılar kullanılarak marş motorlarında ve marş sisteminde gözlenen arızalar Bulanık Mantık (BM) ile sınıflandırılmıştır. Hata teşhisi için MATLAB’ ta grafik ara yüzlü bir yazılım geliştirilmiştir. Geliştirilen bu hata teşhis sistemi ile marş motorlarında en sık gözlenen altı çeşit arıza başarıyla teşhis edilmiştir.

Fault diagnosis in starter motors by classification of wavelet analysis results of faulty starter motor's current signals using fuzzy logic

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.

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