Title :
A practical bearing fault diagnoser
Author :
Sadoughi, Alireza ; Behbahanifard, Hamidreza
Author_Institution :
Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan
Abstract :
Bearing is an important part of electric machines. In order to avoid unscheduled outputs, it is important to detect an upcoming fault as soon as possible. Since fault in a great number of bearings commences from a single point defect, research on this category of faults has shared a great deal in predictive diagnosis literature. Single point defects will cause certain characteristic frequencies to appear in machine vibration spectrum. Because of impulsive nature of fault strikes, and complex modulations present in vibration signal, a simple spectrum analysis may result in erroneous conclusions.
Keywords :
electric machines; fault diagnosis; machine bearings; vibrations; auto-correlated vibration power signals; bearing fault diagnoser; electric machines; machine vibration spectrum; Autocorrelation; Circuit faults; Condition monitoring; Costs; Fault diagnosis; Frequency; Neural networks; Shafts; Signal processing; Vibration measurement; Apparatus; Autocorrelation; Bearing; Diagnosis; Fault; Intelligent; Vibration;
Conference_Titel :
Condition Monitoring and Diagnosis, 2008. CMD 2008. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1621-9
Electronic_ISBN :
978-1-4244-1622-6
DOI :
10.1109/CMD.2008.4580251