... to denoise the bearing vibration signal. bearing fault identification feature extraction Kalman filter signal-to-noise ratio Ball bearings are the most frequently used components in rotary machines for their load carrying capacity, low coefficient of friction, and reliability. Since...

...Qingbo He; Ruxu Du; Fanrang Kong This paper proposes a new feature extraction method based on Independent Component Analysis (ICA) and reconstructed phase space. The ICA-based phase space feature unifies the system dynamics embedded in vibration signal and higher-order statistics expressed in phase...

... classification accuracy of 97% was obtained over a range of rotating speeds. 08 07 2010 30 10 2010 09 09 2011 09 09 2011 fault diagnosis feature extraction materials testing neural nets pattern classification rolling bearings vibrations Using Parzen’s window...

... the vibration signals before feature extraction. Time- and frequency-domain features are all extracted to represent the operation conditions of the bearings totally. Sensitive features are selected after feature extraction. And then, multiple classifiers based on W K NN are combined to overcome the two...

...Ruqiang Yan; Robert X. Gao; Changting Wang A systematic experimental study is presented in this paper on evaluating the effectiveness of a unified, multidomain algorithm for defect feature extraction in bearing condition monitoring and health diagnosis. The algorithm decomposes vibration signals...

...R. Tafreshi; F. Sassani; H. Ahmadi; G. Dumont This paper presents a novel wavelet-based methodology for feature extraction and classification. To compare the performance of the proposed approach with major existing methods, a number of sets of real-world machine data acquired by mounting...

... are preprocessed using Laplace-wavelet transform for features’ extraction. The extracted features for wavelet transform coefficients in time and frequency domains are applied as input vectors to artificial neural networks (ANNs) for rolling bearing fault classification. The Laplace-Wavelet shape and the ANN...

... that the physical experience and judgment of the engineer is always of great help in the feature extraction process. It is extremely true. However, only the experts may possess the physical experience and judgment, and other users require a good deal of expertise to apply them successfully ( 13 ). Condition...

...Ruqiang Yan; Robert X. Gao This paper presents a signal decomposition and feature extraction technique for the health diagnosis of rotary machines, based on the empirical mode decomposition. Vibration signal measured from a defective rolling bearing is decomposed into a number of intrinsic mode...

...Hasan Ocak; Kenneth A. Loparo In this paper, we introduce a new bearing fault detection and diagnosis scheme based on hidden Markov modeling (HMM) of vibration signals. Features extracted from amplitude demodulated vibration signals from both normal and faulty bearings were used to train HMMs...

... bearings with and without defects. The signature varies with the location and severity of bearing defects, load and speed of the shaft, and different bearing housing structures. More specifically, the proposed technique contains effective feature extraction, good learning ability, reliable feature fusion...