Title :
Bearing fault diagnosis with an improved high frequency resonance technique
Author :
Segla, Mawuena ; Wang, Shaoping ; Wang, Fang
Author_Institution :
Sch. of Autom. & Electr. Eng., Beihang Univ., Beijing, China
Abstract :
Efficient detection of bearing failure is one of the most investigated engineering issues in several industries. The proposed method, based on High Frequency Resonance Technique (HFRT) allows detecting precise location of bearing´s failure. The location of resonance area is computed by screening the signal´s frequency spectrum. Some statistical features are adopted to get a preliminary inspection of the raw signal. This method is validated with Seeded Fault Test Data provided by Case Western Reserve University Bearing Data Center.
Keywords :
fault diagnosis; machine bearings; mechanical engineering computing; signal processing; statistical analysis; vibrations; Case Western Reserve University Bearing Data Center; bearing failure detection; bearing fault diagnosis; high frequency resonance technique; seeded fault test data; signal frequency spectrum screening; signal inspection; statistical feature; Accelerometers; Band pass filters; Fault diagnosis; Resonant frequency; Rolling bearings; Transforms; Vibrations; fast Fourier transformation; fault diagnosis; high frequency resonance technique; rolling element bearing; vibration;
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
DOI :
10.1109/INDIN.2012.6301378
