The Experts below are selected from a list of 3639 Experts worldwide ranked by ideXlab platform
Hongchao Wang - One of the best experts on this subject based on the ideXlab platform.
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Fault diagnosis of Rolling Element Bearing based on a new noise-resistant time-frequency analysis method
Journal of Vibroengineering, 2018Co-Authors: Hongchao WangAbstract:When fault arises in the Rolling Element Bearing, the time-domain waveform of fault vibration signal will take on the characteristic of cyclostationarity, and the spectral correlation (SC) or spectral correlation density (SCD) basing on second order cyclic statistic is an effective cyclostationarity signal processing method. However, when the fault signal is surrounded by strong background noise, the traditional signal processing methods such envelope demodulation analysis and SC would not work effectively. The paper improves the SC method and a new time-frequency analysis method naming improved spectral correlation (ISC) is proposed. The proposed method is much more noise-resistant than SC through the verification of simulation analysis results. Besides, it takes on modulation phenomenon usually when fault arises in the Rolling Element Bearing and the aim of fault feature extraction is to extract the fault characteristic frequency only or cyclic modulation frequency and the modulated frequency or carrier frequency buried in the object vibration signal is neglected. So, the paper improves the ISC further and the improved ISC (IISC) is proposed. The IISC will extract the modulation frequency only and it has the advantages of much clearer expression effect and better extraction effect. The effectiveness and feasibility of the proposed method are verified through the three kinds of fault (inner race fault, outer race fault and Rolling Element fault) of Rolling Element Bearing. Besides, the advantages of the proposed method over the other relative time-frequency analysis methods such as ensemble empirical mode decomposition (EEMD) and spectral kurtosis (SK) are also presented in the paper.
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Feature extraction of the weak periodic signal of Rolling Element Bearing’ early fault based on shift invariant sparse coding
Journal of Vibroengineering, 2018Co-Authors: Baoping Shang, Hongchao WangAbstract:When fault such as pit failure arises in the Rolling Element Bearing the vibration signal of which will take on periodic characteristics, and the abrupt failure of rotating machinery can be avoided effectively if the weak periodic characteristics of the early fault stage is extracted timely. However, the periodic characteristics of Bearing’ early weak fault is hard to be extracted usually and the reasons can be boiled to as following: Firstly, the weak periodic signal of Rolling Element Bearing’ early fault stage is buried by the strong background noise. Secondly, the weak fault cannot show the complete shock attenuation impulsive characteristic due to its weak energy, so the traditional wavelet transform would not work effectively if a proper wavelet basis function fitting for analyzing the impulsive characteristics is not selected. To solve the above two problems, a feature extraction method of the weak periodic signal of Rolling Element Bearing’ early fault based on Shift Invariant Sparse Coding (SISC) originating from sparse representation is proposed in the paper. To capture the underlying structure of machinery fault signal, SICS provides an effective basis functions learning scheme by solving the flowing two convex optimization problems iteratively: 1) L1-regularized least squares problem. 2) L2-constrained least squares problem. The fault feature can be probably contained and extracted if optimal latent component is filtered among these basis functions. The feasibility and effectiveness of the proposed method are verified through the corresponding simulation and experiment.
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Diagnosis of Rolling Element Bearing fault arising in gearbox based on sparse morphological component analysis
Journal of Vibroengineering, 2017Co-Authors: Hongchao Wang, Xiaoyun Gong, Wenliao DuAbstract:It is hard to diagnose the Rolling Element Bearing fault occurring in gearbox due to the complexity and the probable mutual coupling among the kinds of signals. A novel diagnosis method of Rolling Element Bearing fault arising in gearbox based on morphological component analysis (MCA) originating from sparse representation theory is proposed in the paper. By selecting proper dictionaries, different morphological components can be separated successfully from the complex Rolling fault signal arising in gearbox, which helps to improve the efficiency and accuracy of diagnosis result. The effectiveness of the proposed method is verified through simulations firstly. Then the proposed method is used in fault feature extracting of complex vibration signals collected from rotating machinery, and the effectiveness of the proposed method is further verified. Besides, the advantage of the proposed method over other relative method is presented.
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Feature extraction of Rolling Element Bearing’ compound faults based on cyclic wiener filter with constructed reference signals
Journal of Vibroengineering, 2016Co-Authors: Hongchao WangAbstract:Feature extraction of Rolling Element Bearing’s compound faults is a challenging task due to the complexity and the mutual coupling phenomenon among the kinds of faults. A new method based on cyclic wiener filter with constructed reference signals is proposed in the paper. The reference signals of the Rolling Element Bearing’ inner race fault, outer race fault and Rolling Element fault are created respectively based on the Rolling Element Bearing’ theoretical fault frequencies. Here, the created signals are used as the expected responses. Then the observed compound faults signal and the constructed reference signal are input into the cyclic wiener filter together. At last, the envelope demodulation method is applied on the filtered signals respectively and satisfactory fault feature extraction results are obtained. The effectiveness of the proposed method is verified through simulation. Furthermore, the advantages of the proposed method over other signal handling method such as spectral kurtosis (SK) are verified through experiment.
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Fault diagnosis of Rolling Element Bearing compound faults based on sparse no-negative matrix factorization-support vector data description
Journal of Vibration and Control, 2016Co-Authors: Hongchao WangAbstract:The bispectrum of Rolling Element Bearing compound faults contains abundant fault characteristic information, and how to extract the fault feature effectively is a key problem. The fault diagnosis method of Rolling Element Bearing compound faults based on Sparse No-Negative Matrix Factorization (SNMF)-Support Vector Data Description (SVDD) is proposed in the paper. The figure handling method SNMF is used firstly in fault feature extraction of the bispectrums of Rolling Element Bearing different kinds of compound faults and the sparse coefficient matrices of the bispectrums are obtained. The sparse coefficient matrices are used as training and test input vectors of SVDD. At last, the three kinds of Rolling Element Bearing compound faults (inner race outer race compound faults, outer race Rolling Element compound faults and inner race outer race Rolling Element compound faults) are classified correctly. In order to verify the advantages of the proposed method, the diagnosis results of the same three kinds o...
Fanrang Kong - One of the best experts on this subject based on the ideXlab platform.
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stochastic resonance with woods saxon potential for Rolling Element Bearing fault diagnosis
Mechanical Systems and Signal Processing, 2014Co-Authors: Siliang Lu, Qingbo He, Fanrang KongAbstract:Abstract This paper proposes a weak signal detection strategy for Rolling Element Bearing fault diagnosis by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods–Saxon (WS) potential. The WS potential has the distinct structure with smooth potential bottom and steep potential wall, which guarantees a stable particle motion within the potential and avoids the unexpected noises for the SR system. In the Woods–Saxon SR (WSSR) model, the output signal-to-noise ratio (SNR) can be optimized just by tuning the WS potential's parameters, which delivers the most significant merit that the limitation of small parameter requirement of the classical bistable SR can be overcome, and thus a wide range of driving frequencies can be detected via the SR model. Furthermore, the proposed WSSR model is also insensitive to the noise, and can detect the weak signals with different noise levels. Additionally, the WS potential can be designed accurately due to its parameter independence, which implies that the proposed method can be matched to different input signals adaptively. With these properties, the proposed weak signal detection strategy is indicated to be beneficial to Rolling Element Bearing fault diagnosis. Both the simulated and the practical Bearing fault signals verify the effectiveness and efficiency of the proposed WSSR method in comparison with the traditional bistable SR method.
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Stochastic resonance with Woods–Saxon potential for Rolling Element Bearing fault diagnosis
Mechanical Systems and Signal Processing, 2014Co-Authors: Siliang Lu, Qingbo He, Fanrang KongAbstract:Abstract This paper proposes a weak signal detection strategy for Rolling Element Bearing fault diagnosis by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods–Saxon (WS) potential. The WS potential has the distinct structure with smooth potential bottom and steep potential wall, which guarantees a stable particle motion within the potential and avoids the unexpected noises for the SR system. In the Woods–Saxon SR (WSSR) model, the output signal-to-noise ratio (SNR) can be optimized just by tuning the WS potential's parameters, which delivers the most significant merit that the limitation of small parameter requirement of the classical bistable SR can be overcome, and thus a wide range of driving frequencies can be detected via the SR model. Furthermore, the proposed WSSR model is also insensitive to the noise, and can detect the weak signals with different noise levels. Additionally, the WS potential can be designed accurately due to its parameter independence, which implies that the proposed method can be matched to different input signals adaptively. With these properties, the proposed weak signal detection strategy is indicated to be beneficial to Rolling Element Bearing fault diagnosis. Both the simulated and the practical Bearing fault signals verify the effectiveness and efficiency of the proposed WSSR method in comparison with the traditional bistable SR method.
Aleksandar Miltenovic - One of the best experts on this subject based on the ideXlab platform.
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Vibration response of rigid rotor in unloaded Rolling Element Bearing
International Journal of Mechanical Sciences, 2010Co-Authors: Radoslav Tomovic, Vojislav Miltenovic, Milan Banic, Aleksandar MiltenovicAbstract:Rolling Element Bearings appear in nearly 90% of all rotating machinery. Their dynamic performance is often the limiting factor in the performance of the machines that use them. The specific construction of a Bearing has a decisive influence on its dynamic behaviour. The paper defines a new vibration model of a rigid rotor supported by Rolling Element Bearings. By application of the defined model, the parametric analysis of the influence of internal radial clearance value and number of Rolling Elements influence on rigid rotor vibrations in unloaded Rolling Element Bearing was performed. The defined vibration model and parametric analysis were verified experimentally. The results of experimental analysis are also presented in this paper. © 2009 Elsevier Ltd. All rights reserved.
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vibration response of rigid rotor in unloaded Rolling Element Bearing
International Conference on Advances in Materials and Processing Technologies (AMPT), 2010Co-Authors: Radoslav Tomovic, Vojislav Miltenovic, Milan Banic, Aleksandar MiltenovicAbstract:Rolling Element Bearings appear in nearly 90% of all rotating machinery. Their dynamic performance is often the limiting factor in the performance of the machines that use them. The specific construction of a Bearing has a decisive influence on its dynamic behaviour. The paper defines a new vibration model of a rigid rotor supported by Rolling Element Bearings. By application of the defined model, the parametric analysis of the influence of internal radial clearance value and number of Rolling Elements influence on rigid rotor vibrations in unloaded Rolling Element Bearing was performed. The defined vibration model and parametric analysis were verified experimentally. The results of experimental analysis are also presented in this paper.
Siliang Lu - One of the best experts on this subject based on the ideXlab platform.
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stochastic resonance with woods saxon potential for Rolling Element Bearing fault diagnosis
Mechanical Systems and Signal Processing, 2014Co-Authors: Siliang Lu, Qingbo He, Fanrang KongAbstract:Abstract This paper proposes a weak signal detection strategy for Rolling Element Bearing fault diagnosis by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods–Saxon (WS) potential. The WS potential has the distinct structure with smooth potential bottom and steep potential wall, which guarantees a stable particle motion within the potential and avoids the unexpected noises for the SR system. In the Woods–Saxon SR (WSSR) model, the output signal-to-noise ratio (SNR) can be optimized just by tuning the WS potential's parameters, which delivers the most significant merit that the limitation of small parameter requirement of the classical bistable SR can be overcome, and thus a wide range of driving frequencies can be detected via the SR model. Furthermore, the proposed WSSR model is also insensitive to the noise, and can detect the weak signals with different noise levels. Additionally, the WS potential can be designed accurately due to its parameter independence, which implies that the proposed method can be matched to different input signals adaptively. With these properties, the proposed weak signal detection strategy is indicated to be beneficial to Rolling Element Bearing fault diagnosis. Both the simulated and the practical Bearing fault signals verify the effectiveness and efficiency of the proposed WSSR method in comparison with the traditional bistable SR method.
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Stochastic resonance with Woods–Saxon potential for Rolling Element Bearing fault diagnosis
Mechanical Systems and Signal Processing, 2014Co-Authors: Siliang Lu, Qingbo He, Fanrang KongAbstract:Abstract This paper proposes a weak signal detection strategy for Rolling Element Bearing fault diagnosis by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods–Saxon (WS) potential. The WS potential has the distinct structure with smooth potential bottom and steep potential wall, which guarantees a stable particle motion within the potential and avoids the unexpected noises for the SR system. In the Woods–Saxon SR (WSSR) model, the output signal-to-noise ratio (SNR) can be optimized just by tuning the WS potential's parameters, which delivers the most significant merit that the limitation of small parameter requirement of the classical bistable SR can be overcome, and thus a wide range of driving frequencies can be detected via the SR model. Furthermore, the proposed WSSR model is also insensitive to the noise, and can detect the weak signals with different noise levels. Additionally, the WS potential can be designed accurately due to its parameter independence, which implies that the proposed method can be matched to different input signals adaptively. With these properties, the proposed weak signal detection strategy is indicated to be beneficial to Rolling Element Bearing fault diagnosis. Both the simulated and the practical Bearing fault signals verify the effectiveness and efficiency of the proposed WSSR method in comparison with the traditional bistable SR method.
Radoslav Tomovic - One of the best experts on this subject based on the ideXlab platform.
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Vibration response of rigid rotor in unloaded Rolling Element Bearing
International Journal of Mechanical Sciences, 2010Co-Authors: Radoslav Tomovic, Vojislav Miltenovic, Milan Banic, Aleksandar MiltenovicAbstract:Rolling Element Bearings appear in nearly 90% of all rotating machinery. Their dynamic performance is often the limiting factor in the performance of the machines that use them. The specific construction of a Bearing has a decisive influence on its dynamic behaviour. The paper defines a new vibration model of a rigid rotor supported by Rolling Element Bearings. By application of the defined model, the parametric analysis of the influence of internal radial clearance value and number of Rolling Elements influence on rigid rotor vibrations in unloaded Rolling Element Bearing was performed. The defined vibration model and parametric analysis were verified experimentally. The results of experimental analysis are also presented in this paper. © 2009 Elsevier Ltd. All rights reserved.
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vibration response of rigid rotor in unloaded Rolling Element Bearing
International Conference on Advances in Materials and Processing Technologies (AMPT), 2010Co-Authors: Radoslav Tomovic, Vojislav Miltenovic, Milan Banic, Aleksandar MiltenovicAbstract:Rolling Element Bearings appear in nearly 90% of all rotating machinery. Their dynamic performance is often the limiting factor in the performance of the machines that use them. The specific construction of a Bearing has a decisive influence on its dynamic behaviour. The paper defines a new vibration model of a rigid rotor supported by Rolling Element Bearings. By application of the defined model, the parametric analysis of the influence of internal radial clearance value and number of Rolling Elements influence on rigid rotor vibrations in unloaded Rolling Element Bearing was performed. The defined vibration model and parametric analysis were verified experimentally. The results of experimental analysis are also presented in this paper.
