Detection of rolling bearing defects using discrete wavelet analysis
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Tandon N, Choudhury A (1999) A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribol Int 32:469–480
Dyer D, Stewart M (1978) Detection of rolling element bearing damage by statistical vibration analysis. J Mech Des 100:229–235
Boulenger A, Pachaud C (1998) Diagnostic vibratoire en maintenance préventive. Dunod, Paris
Pachaud C, Salvetas R, Fray C (1997) Crest factor and kurtosis contributions to identify defects inducing periodical impulsive forces. Mech Syst Signal Process 11(6):903–916
Heng RBW, Nor MJ (1998) Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition. Appl Acoust 53(1–3):211–226
MacFadden PD, Smith JD (1984) Vibration monitoring of rolling element bearing by the high frequency resonance technique, a review. Tribol Int 17(1):3–10
Chaturvedi GK, Thomas DW (1982) Bearings faults detection using adaptive noise cancelling. J Mech Des 104:280–289
Khemili I, Chouchane M (2005) Detection of rolling element bearing defects by adaptive filtering. Eur J Mech A: Solids 24:293–303
Dron JP, Bolaers F, Rasolofondraibe L (2003) Optimization de la détection des défauts de roulements par débruitage des signaux par soustraction spectrale. Mec Ind 4:213–219
Dron JP, Bolaers F, Rasolofondraibe L (2004) Improvement of the sensitivity of the scalar indicators (crest factor and kurtosis) using a de-noising method by spectral subtraction: application to the detection of defects in ball bearings. J Sound Vib 270:61–73
Bolaers F, Cousinard O, Marconnet P, Rasolofondraibe L (2004) Advanced detection of rolling bearing spalling from de-noising vibratory signals. Control Eng Pract 12:181–190
Qiu H, Lee J, Lin J, Yu G (2006) Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics. J Sound Vib 289:1066–1090
Shao Y, Nezu K (2004) Design of mixture de-noising for detecting faulty bearing signals. J Sound Vib 282:899–917
Lin J (2000) Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis. J Sound Vib 234(1):35–148
Peter W (2000) Wavelets analysis-A flexible and efficient fault diagnostic method for rolling element bearing. In: 7th international congress on sound and vibration, Germany, 4–7 July 2000, pp 507–514
Sun Q, Tang Y (2002) Singularity analysis using continuous wavelet transform for bearing fault diagnosis. Mech Syst Signal Process 16(6):1025–1041
Rubini R, Meneghetti U (2001) Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings. Mech Syst Signal Process 15(2):287–302
Boltezar M, Simonovski I, Furlan M (2003) Faults detection in DC electro motors using the continuous wavelet transform. Meccanica 38:251–264
Yang DM, Stronach AF, MacConnell P (2003) The application of advanced signal processing techniques to induction motor bearing condition diagnosis. Meccanica 38:297–308
Brabhakar S, Mohanty AR, Sekhar AS (2002) Application of discrete wavelet transform for detection of ball bearings race faults. Tribol Int 35:793–800
Nikolaou NG, Antoniadis IA (2002) Rolling element bearing fault diagnosis using wavelet packets. NDT & E Int 35:197–205
Mori K, Kasashima N, Yoshioda T, Ueno Y (1996) Prediction of spalling on a ball bearing by applying discrete wavelet transform to vibration signals. Wear 8:195–162
Li JC, Jun M (1997) Wavelet decomposition of vibrations for detection of bearing-localized defects. NDT & E Int 30(3):143–149
Chinmaya K, Mohanty AR (2006) Monitoring gear vibrations through motor current signature analysis and wavelet transform. Mech Syst Signal Process 20(2):158–187
Wang WJ, MacFadden PD (1996) Application of wavelets to gearbox vibration signals for fault detection. J Sound Vib 192(5):927–939
Zheng H, Li Z, Chen X (2002) Gear faults diagnosis based on continuous wavelet transform. Mech Syst Signal Process 16(2–3):447–457
Yoshida A, Ohue Y, Ishikawa H (2000) Diagnosis of tooth surface failure by wavelet transform of dynamic characteristics. Tribol Int 33:273–279