Abstract
The vibration signals generated by a rotor bearing system are greatly influenced by the occurrence of a fault on the bearings. Monitoring of parameters like peak, overall rms, kurtosis, crest factor, and power from the time domain signal reveals the status of health of bearings supporting the rotor and serves as the easiest approach. However, the majority of these parameters give an estimation of the overall health of the system and not just the bearings. This work addresses the use of Discrete Wavelet Transform (DWT) to filter the bearing related signal and then monitor the health of bearing. The work also discusses on the selection of appropriate sampling frequency for the collection of time domain signal and demonstrates the dependence of parameters on the same. The results indicate that the use of DWT for a signal with higher sampling frequency has increased the accuracy of prediction of estimation of the defect.
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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
Patil MS, Mathew J, RajendraKumar PK (2008) Bearing signature analysis as a medium for fault detection: a review. ASME J. Tribol 130(1):14001
Tandon N, Nakra BC (1992) Comparison of vibration and acoustic measurement techniques for the condition monitoring of rolling element bearings. Tribol Int 25(3):205–212
Tandon N (1994) A comparison of some vibration parameters for the condition monitoring of rolling element bearings. Measurement 12:285–289
Shakya P, Darpe AK, Kulkarni MS (2013) Vibration-based fault diagnosis in rolling element bearings: ranking of various time, frequency and time-frequency domain data-based damage identification parameters. Int J Cond Monit 3(2):1–10
Patidar S, Soni PK (2013) An overview on vibration analysis techniques for the diagnosis of rolling element bearing faults. Int J Eng 4(5):1804–1809
Peng Z, Chu F (2004) Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mech Syst Signal Process 18:199–221
Yan R, Gao RX, Chen X (2014) Wavelets for fault diagnosis of rotary machines: a review with applications. Sig Process 96:1–15
Chebil J, Noel G, Mesbah M, Deriche M (2009) Wavelet decomposition for the detection and diagnosis of faults in rolling element bearings. Jordan J Mech Ind Eng 3(4):260–267
Prabhakar S, Mohanty AR, Sekhar A (2002) Application of discrete wavelet transform for detection of ball bearing race faults. Tribol Int 35(12):793–800
Kumar R, Singh M (2013) Outer race defect width measurement in taper roller bearing using discrete wavelet transform of vibration signal. Measurement 46(1):537–545
Khanam S, Tandon N, Dutt JK (2014) Fault size estimation in the outer race of ball bearing using discrete wavelet transform of the vibration signal. Procedia Technol. 14:12–19
Ingarashi T, Noda B, Matsushima E (1980) A study on the prediction of abnormalities in rolling bearing. JSLE Int 1:7176
Acknowledgments
Authors are thankful to the staff members of Machine Dynamics Laboratory (ITMMEC), IIT Delhi for providing all possible help during experimentations.
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Khanam, S., Tandon, N. (2021). Investigations into Some Parameters of Vibration Signal of Faulty Bearings with Wavelet Transform. In: Singh, M., Rafat, Y. (eds) Recent Developments in Acoustics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-5776-7_23
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DOI: https://doi.org/10.1007/978-981-15-5776-7_23
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