Title :
Detection of generalized-roughness bearing fault using statistical-time indices of instantaneous frequency of motor voltage space vector
Author :
Dalvand, Fardin ; Keshavarzi, Mahmoud ; Kalantar, Asadollah ; Cheraghdar, Almas
Author_Institution :
Iranian Oil Pipelines & Telecommun. Co., Iran
Abstract :
This paper proposes a new approach to detect generalized-roughness bearing faults via motor voltage monitoring which has not been studied in the literature yet. The proposed method detects the bearing faults using analysis of instantaneous frequency of voltage signals. Our proposed method is superior to previous ones in a number of aspects. First, obtaining voltage signals is easier than other signals such as vibration, sound pressure, and temperature. Second, it is computationally simple method. Third, our proposed method is non-invasive. The Experimental results show that these impacts are so strong that even simple time-domain indices are able to detect bearing defects. The experimental results confirm the effectiveness of the proposed method.
Keywords :
fault diagnosis; machine bearings; time-domain analysis; voltage measurement; computationally simple method; generalized-roughness bearing fault detection; instantaneous frequency; motor voltage monitoring; motor voltage space vector; noninvasive method; statistical-time indices; time-domain indices; voltage signals; Decision support systems; Electrical engineering; Magnetic fields; Rotors; Stator windings; Time-domain analysis; Bearing; condition monitoring; fault detection; induction motors (IMs); instantaneous frequency (IF); motor voltage; statistical indices;
Conference_Titel :
Electrical Engineering (ICEE), 2015 23rd Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-1971-0
DOI :
10.1109/IranianCEE.2015.7146460