Study Of Bearing Rolling Element Defect Using Emperical Mode Decomposition Technique

  Purnima Trivedi,  Dr. P.K. Bharti

Bearing failure is one of the major causes of breakdown in rotating machinery. Failure of bearings can results in costly downtime. Therefore condition monitoring of bearings plays an important role in machine maintenance. In condition monitoring the observed signal is often corrupted by noise during the transmission system. It is important to detect the elementary fault in advance before failure occurs. Therefore it is important to understand the behavior of the occurrence of faults and condition monitoring of the bearings. Among the various methods available for diagnosis and condition monitoring of bearing elements, vibration measurement is the most common one. The present study is focused on the fault diagnosis of taper roller bearings (NBC Bearing number: 30205). The experimental study has been made for the analysis of groove defect on the roller. Width and depth of the defect were approximately 1.40 mm and 0.30 mm respectively and were throughout the length of the roller. These defects were produced by using the Electric Discharge Machining (EDM). The present research work involves the application of Empirical Mode Decomposition (EMD) technique along with the envelope for the analysis of groove defect on the rollers. EMD is adaptive signal decomposition method, which is able to decompose non-linear and non-stationary data into a sequence of amplitude modulation/ frequency modulation (AM/FM) components or a like. These independent components to be obtained are called intrinsic mode functions (IMFs). The selection of appropriate IMFs is also done in order to extract the exact location of defects on the rollers. The selection of the IMF is based on the maximum kurtosis criteria. Kurtosis reveals the occurrence of defects in rotating machinery. For the normal bearing kurtosis is near about 3 and bearing with considerable defect have higher value of kurtosis. Thus kurtosis can be taken as the selection criteria for the selection of IMF. Therefore IMF with maximum kurtosis was selected for the analysis of defects in the rollers. The proposed method is also compared with the traditional FFT which was directly applied to the raw signal of the faulty bearing. By comparison, between the proposed method and FFT, it is concluded that, the EMD method gives better result as well as defects can be easily identified by EMD. Whereas, it is difficult to identify defects by FFT. The results obtained by the proposed method are very close to the theoretical values of the defects. The roller defect frequency, for single roller groove deviate 2.1 % from the theoretical value of the roller defect frequency.

Keywords- Fast Fourier Transformation (FFT), Empirical Mode Decomposition (EMD), Intrinsic Mode Functions (IMFs), Kurtosis, Electric Discharge Machining (EDM), Condition Monitoring, Envelope detection, Hidden Markov Models, Artificial Neural Network, Ball pass frequency inner race (BPFI), Discrete wavelet transforms (DWT), Crest factor.

Unique Identification Number - IJEDR1702096
Page Number(s) - 553-565
Pubished in - Volume 5 | Issue 2 | April 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Purnima Trivedi,  Dr. P.K. Bharti,   "Study Of Bearing Rolling Element Defect Using Emperical Mode Decomposition Technique", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.553-565, April 2017, Available at :http://www.ijedr.org/papers/IJEDR1702096.pdf