Application of discrete wavelet transform for detection of ball bearing race faults
TL;DR: In this paper, a discrete wavelet transform (DWT) was used to detect single and multiple bearing race faults in the ball bearings of the inner race, outer race, and the combination faults.
About: This article is published in Tribology International.The article was published on 2002-12-01. It has received 281 citations till now. The article focuses on the topics: Discrete wavelet transform & Wavelet.
Citations
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TL;DR: In this paper, a new scheme for the prediction of a ball bearing's remaining useful life based on self-organizing map (SOM) and back propagation neural network methods is presented.
502 citations
Cites background from "Application of discrete wavelet tra..."
...Some have classified bearing conditions and fault diagnosis using fuzzy logic concepts [6], and neural networks approaches [7–9], while others have focused on wavelet analysis approaches to detect bearing faults [2,3,10,11]....
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TL;DR: In this paper, a Hilbert-Huang Transform (HHT) based time domain approach for bearing vibration signature analysis is proposed for bearing bearing vibration analysis and its efficiency is evaluated.
489 citations
TL;DR: In this article, the authors have presented the various signal processing methods applied to the fault diagnosis of rolling element bearings with the objective of giving an opportunity to the examiners to decide and select the best possible signal analysis method as well as the excellent defect representative features for future application in the prognostic approaches.
453 citations
TL;DR: The results show that the machine learning algorithms can be used for automated diagnosis of bearing faults and it is observed that the severe (chaotic) vibrations occur under bearings with rough inner race surface and ball with corrosion pitting.
Abstract: Ball bearings faults are one of the main causes of breakdown of rotating machines. Thus, detection and diagnosis of mechanical faults in ball bearings is very crucial for the reliable operation. This study is focused on fault diagnosis of ball bearings using artificial neural network (ANN) and support vector machine (SVM). A test rig of high speed rotor supported on rolling bearings is used. The vibration response are obtained and analyzed for the various defects of ball bearings. The specific defects are considered as crack in outer race, inner race with rough surface and corrosion pitting in balls. Statistical methods are used to extract features and to reduce the dimensionality of original vibration features. A comparative experimental study of the effectiveness of ANN and SVM is carried out. The results show that the machine learning algorithms mentioned above can be used for automated diagnosis of bearing faults. It is also observed that the severe (chaotic) vibrations occur under bearings with rough inner race surface and ball with corrosion pitting.
363 citations
Cites background from "Application of discrete wavelet tra..."
...Prabhakar, Mohanty, and Sekhar (2002) have considered single and multiple point defects on inner race, outer race and the combination faults and used discrete wavelet transform (DWT) to detect these faults on bearings....
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TL;DR: In this article, the authors present a review of the state-of-the-art in sensors and signal processing methodologies used for tool condition monitoring (TCM) systems in industrial machining applications.
Abstract: This paper presents a review of the state-of-the-art in sensors and signal processing methodologies used for tool condition monitoring (TCM) systems in industrial machining applications. The paper focuses on the technologies used in monitoring conventional cutting operations, including drilling, turning, end milling and face milling, and presents important findings related to each of these fields. Unlike existing reviews, which categorize results according to the methodology used, this paper presents results organized according to the type of machining operation carried out. By extensively reviewing and categorizing over one hundred important papers and articles, this paper is able to identify and comment on trends in TCM research, and to identify potential weaknesses in certain areas. The paper concludes with a list of recommendations for future research based on the trends and successful results observed, thus facilitating the cross-fertilization of ideas and techniques within the field of TCM research.
294 citations
Cites methods from "Application of discrete wavelet tra..."
...Some of these applications include detection of bearing wear as in [ 85 , 86] and other mechanical faults as in [87–89]....
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...The Morlet wavelet is used to denoise vibration signals from gearboxes and rolling bearing systems in [88] while incipient faults in bearings are investigated in [86] and faults in bearing races are considered in [ 85 ]....
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References
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TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Abstract: Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions. In L/sup 2/(R), a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi (x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. Wavelet representation lies between the spatial and Fourier domains. For images, the wavelet representation differentiates several spatial orientations. The application of this representation to data compression in image coding, texture discrimination and fractal analysis is discussed. >
20,028 citations
TL;DR: In this paper, a denoising method based on wavelet analysis is applied to feature extraction for mechanical vibration signals, which is an advanced version of the famous soft thresholding denoizing method proposed by Donoho and Johnstone.
823 citations
TL;DR: In this paper, a model was developed to describe the vibration produced by a single point defect on the inner race of a rolling element bearing under constant radial load, incorporating the effects of bearing geometry, shaft speed, bearing load distribution, transfer function and the exponential decay of vibration.
792 citations
TL;DR: In this paper, a model for the high-frequency vibration produced by a single point defect on the inner race of a rolling element bearing under radial load is extended to describe the vibrations produced by multiple points defects.
303 citations
TL;DR: In this article, the discrete wavelet transform (DWT) is applied to vibration signals to predict the occurrence of spalling in ball bearings, and the DWT yields information on both the time and frequency characteristics of the input signals, and particularly helpful in detecting subtle time localized changes.
167 citations