%0 Journal Article
%T Monitoring Machines by Using a Hybrid Method Combining MED, EMD, and TKEO
%A Mourad Kedadouche
%A Marc Thomas
%A Antoine Tahan
%J Advances in Acoustics and Vibration
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/592080
%X Amplitude demodulation is a key for diagnosing bearing faults. The quality of the demodulation determines the efficiency of the spectrum analysis in detecting the defect. A signal analysis technique based on minimum entropy deconvolution (MED), empirical mode decomposition (EMD), and Teager Kaiser energy operator (TKEO) is presented. The proposed method consists in enhancing the signal by using MED, decomposing the signal in intrinsic mode functions (IMFs) and selects only the IMF which presents the highest correlation coefficient with the original signal. In this study the first IMF1 was automatically selected, since it represents the contribution of high frequencies which are first excited at the early stages of degradation. After that, TKEO is used to track the modulation energy. The spectrum is applied to the instantaneous amplitude. Therefore, the character of the bearing faults can be recognized according to the envelope spectrum. The simulation and experimental results show that an envelope spectrum analysis based on MED-EMD and TKEO provides a reliable signal analysis tool. The experimental application has been developed on acoustic emission and vibration signals recorded for bearing fault detection. 1. Introduction The bearing may be considered as one of the most stressed parts in rotating machines. Early stage bearing defects excite first the resonance frequencies which manifest in the high frequency domain. High frequency resonance technique (HFRT) is thus mostly used in industry since it allows the extraction of components information representing defects on rotating machinery [1]. A band-pass filtering around the excited resonance frequency followed by an amplitude demodulation step exhibits the modulation frequencies representative of the fault characteristic frequency of the bearing and its associated harmonics [2, 3]. Spectral analysis of this signal (amplitude and number of harmonics) can reveal the severity of defects [4]. However, the major challenge in the application of the HFRT technique is the proper selection of the center frequency and bandwidth of the band-pass filter. Many researches have focused on the development of efficient and robust methods for estimating the proper center frequency and optimum bandwidth of the band-pass filter. Spectral Kurtosis has been proposed by Antoni and Randall [5]. However Kurtosis has its own limitation, especially when the signal is submerged by a strong and non-Gaussian noise with sudden high peaks where kurtosis shows extremely high values [6]. Other methods were developed. Barszcz and
%U http://www.hindawi.com/journals/aav/2014/592080/