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学者姓名：胥永刚
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Abstract ：
Faults in rolling element bearings often cause the breakdown of rotating machinery. Not only the fault type identification but also the fault severity assessment is important. So this paper emphasizes the fault severity assessment. The method proposed in this paper contains two steps: first, identify the fault type based on the combination of empirical mode decomposition (EMD) and fast kurtogram; Second, assess the fault severity. In the first step, the original signal is firstly decomposed into some intrinsic mode functions (IMFs) and the representative IMFs are selected based on correlation analysis, and then the reconstruction signal (RS) is generated; Secondly, the fast kurtogram method is applied to the RS, and the optimum band width and center frequency is obtained. The fault type can be identified based on the fault characteristic frequency marked in the envelope demodulation spectrum. In the second step, the energy percentage of the most fault-related IMF is chosen as an indicator of the fault severity assessment. Experimental data of rolling element bearings inner raceway fault (IRF) with three severities at four running speeds were analyzed. The results show that the IRF identification and fault severity assessment is realized. The breakthrough attempt provides the great potential in the application of condition monitoring of bearings.
Keyword ：
correlation analysis correlation analysis fault severity assessment fault severity assessment rolling element bearings rolling element bearings EMD EMD fast kurtogram fast kurtogram
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| GB/T 7714 | Cheng, Lei , Fu, Sheng , Zheng, Hao et al. Fault identification and severity assessment of rolling element bearings based on EMD and fast kurtogram [J]. | JOURNAL OF VIBROENGINEERING , 2016 , 18 (6) : 3668-3683 . |
| MLA | Cheng, Lei et al. "Fault identification and severity assessment of rolling element bearings based on EMD and fast kurtogram" . | JOURNAL OF VIBROENGINEERING 18 . 6 (2016) : 3668-3683 . |
| APA | Cheng, Lei , Fu, Sheng , Zheng, Hao , Huang, Yiming , Xu, Yonggang . Fault identification and severity assessment of rolling element bearings based on EMD and fast kurtogram . | JOURNAL OF VIBROENGINEERING , 2016 , 18 (6) , 3668-3683 . |
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Abstract ：
Aimed at separating fault information from compound rolling bearing fault signal, a fault diagnosis method was proposed based on dual-tree complex wavelet packet transform and auto-regressive (AR) spectrum. First, the non-stationary and complex signal of compound fault was decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Second, Hilbert envelope was formed from the component that contains the fault information. Finally, the power spectrum was obtained by AR spectrum. Thus, the information of fault feature was separated and identified. Experiments results show that the fault feature of rolling bearing can be separated effectively, and the feasibility and effectiveness of the method are verified.
Keyword ：
Auto-regressive (AR) power spectrum; Compound fault; Dual-tree complex wavelet packet transform; Fault diagnosis Auto-regressive (AR) power spectrum; Compound fault; Dual-tree complex wavelet packet transform; Fault diagnosis
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| GB/T 7714 | Xu, Y.-G. , Meng, Z.-P. , Lu, M. et al. Compound fault diagnosis based on dual-tree complex wavelet packet transform and AR spectrum for rolling bearings [J]. | Journal of Beijing University of Technology , 2014 , 40 (3) : 335-340,347 . |
| MLA | Xu, Y.-G. et al. "Compound fault diagnosis based on dual-tree complex wavelet packet transform and AR spectrum for rolling bearings" . | Journal of Beijing University of Technology 40 . 3 (2014) : 335-340,347 . |
| APA | Xu, Y.-G. , Meng, Z.-P. , Lu, M. , Zhang, J.-Y. . Compound fault diagnosis based on dual-tree complex wavelet packet transform and AR spectrum for rolling bearings . | Journal of Beijing University of Technology , 2014 , 40 (3) , 335-340,347 . |
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Abstract ：
Aiming at non-stationary and modulation characteristics of gear fault vibration signals, a fault diagnosis method was proposed based on dual-tree complex wavelet packet transform and spectral kurtosis. First, the original vibration signal was decomposed into several different frequency band components by dual-tree complex wavelet packet transform, some components that have bigger correlation coefficient were de-noised by the threshold. Second, the best bandwidth and band center of band-pass filter were determined through fast kurtosis diagram of spectral kurtosis. Finally, the envelope demodulation spectrum of filter signal could be obtained by square envelope and Fourier transforms, then the fault information was effectively extracted. The analysis of the gear fault signals shows that the fault feature information of the gear can be effectively extracted to identify the fault, and the proposed method is effective and feasible.
Keyword ：
Dual-tree complex wavelet packet transform; Fault diagnosis; Gear; Spectral kurtosis; Threshold Dual-tree complex wavelet packet transform; Fault diagnosis; Gear; Spectral kurtosis; Threshold
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| GB/T 7714 | Xu, Y.-G. , Meng, Z.-P. , Zhao, G.-L. et al. Application of gear fault diagnosis based on dual-tree complex wavelet packet transform and spectral kurtosis [J]. | Journal of Beijing University of Technology , 2014 , 40 (4) : 488-494 . |
| MLA | Xu, Y.-G. et al. "Application of gear fault diagnosis based on dual-tree complex wavelet packet transform and spectral kurtosis" . | Journal of Beijing University of Technology 40 . 4 (2014) : 488-494 . |
| APA | Xu, Y.-G. , Meng, Z.-P. , Zhao, G.-L. , Lu, M. . Application of gear fault diagnosis based on dual-tree complex wavelet packet transform and spectral kurtosis . | Journal of Beijing University of Technology , 2014 , 40 (4) , 488-494 . |
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Abstract ：
The gear is the key component of rotating machinery, so a fault in the gear will directly affect the condition of the whole machine's operation. It was difficult to extract the fault feature information effectively from the vibration signals of a faulty gear. In the field of fault diagnosis, envelope demodulation was one of the most common signal processing methods. However, a filtering process was required before envelope demodulation. The parameters of a filter were determined by experience, and that has a great influence on the results of signal processing. The discrete wavelet packet transform has a larger energy leakage of frequency band, which obviously affected the results of the envelope demodulation. It is necessary to have a method with a lower energy leakage of the frequency band before envelope demodulation. The dual tree complex wavelet packet transform (DT-CWPT) was a new signal processing method that had many good qualities. Because the energy leakage of the frequency band was smaller when the signal was decomposed by a dual tree complex wavelet packet transform, the dual tree complex wavelet packet transform was used to extract the fault feature information in the field of fault diagnosis. In this paper, first, according to the characteristics of Gaussian white noise, whose frequency was full of the whole frequency band, Gaussian white noise was decomposed by a dual-tree complex wavelet packet transform, and the parts with energy leakage were regarded as a theoretical part band beyond the range of the frequency components. Then the lower energy leakage characteristic of dual tree complex wavelet packet transform was verified by a quantitative analysis method of frequency band energy leakage. A dual tree complex wavelet packet transform has an advantage in the pretreatment of envelope demodulation compared with the method of discrete wavelet packet transform. Secondly, the signal was decomposed layer-by-layer by a dual tree complex wavelet packet transform, and the kurtogram based on a dual tree complex wavelet packet transform could be obtained by computing the spectral kurtosis of every layer's components. According to the standard of maximum kurtosis, the layer of decomposition and the component about the signal can be chosen automatically and accurately. The best layer of the dual tree complex wavelet packet decomposition was the layer of the maximum kurtosis and the component which had the maximum kurtosis was the best component of decomposition. Finally, the vibration signal of the engineering was processed by the method of spectral kurtosis based on a dual tree complex wavelet packet transform, the best decomposition layer and component could be chosen, and the fault feature information was extracted effectively by a Hilbert envelope demodulation, where the feasibility and effectiveness of the method were verified. The research will provide a reference for extracting the fault feature information of a gearbox fault diagnosis in rotating machinery.
Keyword ：
Demodulation Demodulation Failure analysis Failure analysis Gaussian noise (electronic) Gaussian noise (electronic) Fault tree analysis Fault tree analysis Optical variables measurement Optical variables measurement Gears Gears Higher order statistics Higher order statistics Gaussian distribution Gaussian distribution Partial discharges Partial discharges Processing Processing Vibrations (mechanical) Vibrations (mechanical) Wavelet analysis Wavelet analysis White noise White noise Wavelet decomposition Wavelet decomposition Rotating machinery Rotating machinery Fault detection Fault detection
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| GB/T 7714 | Xu, Yonggang , Meng, Zhipeng , Zhao, Guoliang et al. Analysis of energy leakage characteristics of dual-tree complex wavelet packet transform and its application on gear fault diagnosis [J]. | Transactions of the Chinese Society of Agricultural Engineering , 2014 , 30 (2) : 72-77 . |
| MLA | Xu, Yonggang et al. "Analysis of energy leakage characteristics of dual-tree complex wavelet packet transform and its application on gear fault diagnosis" . | Transactions of the Chinese Society of Agricultural Engineering 30 . 2 (2014) : 72-77 . |
| APA | Xu, Yonggang , Meng, Zhipeng , Zhao, Guoliang , Fu, Sheng . Analysis of energy leakage characteristics of dual-tree complex wavelet packet transform and its application on gear fault diagnosis . | Transactions of the Chinese Society of Agricultural Engineering , 2014 , 30 (2) , 72-77 . |
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Abstract ：
The operation states of rolling bearings which are the most common and important parts in the mechanical equipment, will affect the whole machine operation condition directly. Due to the working environment of rolling, bearing is complicated, the fault vibration signal of rolling bearing is usually non-stationary, and the strong noise interference is contained in the vibration signal at the same time. So it is important to eliminate the noise interference and extract fault feature information effectively for the rolling bearing. Dual-tree complex wavelet packet transform is a new method of signal processing. Dual-tree complex wavelet packet transform has many good characteristics, for example, approximate shift invariance, good directional selectivity, perfect reconstruction, limited data redundancy, efficient computational efficiency and so on. The high frequency part of dual-tree complex wavelet transform that is not decomposed, is further decomposed by dual-tree complex wavelet packet transform, so as to improve the whole frequency band signal frequency resolution and reduce the loss of information. In view of the above situation, a new fault diagnosis method is proposed based on dual-tree complex wavelet packet transform and threshold de-noising. Firstly, the non-stationary fault signal is decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Secondly, Kurtosis and the cross-correlation coefficient of each component are obtained and compared. Due to the kurtosis reflecting the signal variations, if the kurtosis value is bigger, the degree of the change of signal is bigger too. The correlation coefficient can reflect the proximity between the component and the original signal at the same time, the correlation coefficient is bigger, the more similar with the original signal. Finally, the components that have a bigger value are chosen to be de-noised by a soft threshold and reconstructed by dual-tree complex wavelet packet transform. The noise interference was eliminated effectively, and the effective signal information was retained at the same time. Thus, the fault feature information was extracted. In this paper, the outer bearing fault test and the engineering practical fault data of rolling bearing were analyzed by dual-tree complex wavelet packet transform and threshold de-noising. In order to contrast analysis, the vibration signals were processed by the traditional discrete wavelet packet transform and threshold de-noising. The signal has the better periodic impact obtained by the method proposed in this paper, and the noise was eliminated ideally. So the fault diagnosis method based on dual-tree complex wavelet packet transform and threshold de-noising can effectively eliminate the noise in the vibration signals. Thus, the fault feature information was extracted and the feasibility and effectiveness of this method is verified.
Keyword ：
Partial discharges Partial discharges Wavelet decomposition Wavelet decomposition Fault tree analysis Fault tree analysis Trees (mathematics) Trees (mathematics) Vibration analysis Vibration analysis Computational efficiency Computational efficiency Fault detection Fault detection Higher order statistics Higher order statistics Roller bearings Roller bearings Wavelet analysis Wavelet analysis Bearings (structural) Bearings (structural) Signal analysis Signal analysis
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| GB/T 7714 | Xu, Yonggang , Meng, Zhipeng , Lu, Ming . Fault diagnosis of rolling bearing based on dual-tree complex wavelet packet transform [J]. | Transactions of the Chinese Society of Agricultural Engineering , 2013 , 29 (10) : 49-56 . |
| MLA | Xu, Yonggang et al. "Fault diagnosis of rolling bearing based on dual-tree complex wavelet packet transform" . | Transactions of the Chinese Society of Agricultural Engineering 29 . 10 (2013) : 49-56 . |
| APA | Xu, Yonggang , Meng, Zhipeng , Lu, Ming . Fault diagnosis of rolling bearing based on dual-tree complex wavelet packet transform . | Transactions of the Chinese Society of Agricultural Engineering , 2013 , 29 (10) , 49-56 . |
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Abstract ：
Regarding the strong noise in the vibration signal induced by the roller bearing fault and the difficulty to obtain fault characteristic frequencies in practice, a new fault diagnosis method is proposed based on dual-tree complex wavelet transform (DT-CWT) and singular value difference (SVD) spectrum. Firstly, original fault signals are decomposed into several different frequency band components through DT-CWT; Secondly, the Hankel matrix is constructed by the component which contains the fault information, and the singular value difference spectrum can be obtained after SVD. Then the maximum catastrophe point is used to identify the number of singular-value reconstruction component. Finally, the fault frequency can be identified accurately by the Hilbert envelope spectrum. The results of the experiments and engineering application show that the fault characteristics of the roller bearing can be separated and extracted effectively, getting the feasibility and effectiveness of the method verified.
Keyword ：
Matrix algebra Matrix algebra Failure analysis Failure analysis Partial discharges Partial discharges Wavelet transforms Wavelet transforms Roller bearings Roller bearings Fault detection Fault detection Signal processing Signal processing
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| GB/T 7714 | Xu, Yong-Gang , Meng, Zhi-Peng , Lu, Ming et al. Application of dual-tree complex wavelet transform and singular value difference spectrum in the rolling bearing fault diagnosis [J]. | Journal of Vibration Engineering , 2013 , 26 (6) : 965-973 . |
| MLA | Xu, Yong-Gang et al. "Application of dual-tree complex wavelet transform and singular value difference spectrum in the rolling bearing fault diagnosis" . | Journal of Vibration Engineering 26 . 6 (2013) : 965-973 . |
| APA | Xu, Yong-Gang , Meng, Zhi-Peng , Lu, Ming , Fu, Sheng . Application of dual-tree complex wavelet transform and singular value difference spectrum in the rolling bearing fault diagnosis . | Journal of Vibration Engineering , 2013 , 26 (6) , 965-973 . |
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Abstract ：
Based on the introduction of differential oscillator fundamental, the influence of noise on the oscillator phase diagram is analyzed emphatically, and the linear relationship between the phase diagram size and signal amplitude is derived to make up for the shortage that differential oscillator can't detect the signal amplitude, the setup principle of oscillator system parameter is also presented. The theoretical analysis, simulation test and engineering application show that this method is simple and robust, and has a good anti-noise property, the weak fault signals can be detected from the strong background noise, thereby providing a visual detection method for the incipient fault diagnosis of mechanical equipments.
Keyword ：
Signal detection Signal detection Fault detection Fault detection Phase diagrams Phase diagrams Failure analysis Failure analysis
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| GB/T 7714 | Xu, Yonggang , Feng, Mingshi , Ma, Hailong et al. Method of weak signal detection based on differential oscillator [J]. | Journal of Vibration, Measurement and Diagnosis , 2013 , 33 (2) : 224-230 . |
| MLA | Xu, Yonggang et al. "Method of weak signal detection based on differential oscillator" . | Journal of Vibration, Measurement and Diagnosis 33 . 2 (2013) : 224-230 . |
| APA | Xu, Yonggang , Feng, Mingshi , Ma, Hailong , Xie, Zhicong . Method of weak signal detection based on differential oscillator . | Journal of Vibration, Measurement and Diagnosis , 2013 , 33 (2) , 224-230 . |
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Abstract ：
Aiming at the problem that it is difficult to acquire the feature information of magnetic memory signal for low speed and heavy load gear under fault state, a new method based on the intrinsic time-scale decomposition (ITD) is proposed to achieve the extraction of magnetic memory signal feature. Firstly, the original magnetic memory signals are decomposed into several proper rotation components (PRC) and a monotonous tendency item with ITD method. Then the first four order PRCs are reconstructed to eliminate the large cycle composition in magnetic memory signal and magnetic noise. Finally, the magnetic signal strength of each gear tooth root is extracted using cycle average and local statistic method. Experiment results show that the proposed method is suitable for accurately picking up and judging the effective compositions of the signal, it can effectively extract signal feature and has important application value in potential fault diagnosis of low speed and heavy load gear.
Keyword ：
Feature extraction Feature extraction Magnetic storage Magnetic storage Magnetism Magnetism Extraction Extraction Signal processing Signal processing
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| GB/T 7714 | Xu, Yonggang , Xie, Zhicong , Cui, Lingli et al. Study on feature extraction method of gear magnetic memory signal based on ITD [J]. | Chinese Journal of Scientific Instrument , 2013 , 34 (3) : 671-676 . |
| MLA | Xu, Yonggang et al. "Study on feature extraction method of gear magnetic memory signal based on ITD" . | Chinese Journal of Scientific Instrument 34 . 3 (2013) : 671-676 . |
| APA | Xu, Yonggang , Xie, Zhicong , Cui, Lingli , Wang, Jing . Study on feature extraction method of gear magnetic memory signal based on ITD . | Chinese Journal of Scientific Instrument , 2013 , 34 (3) , 671-676 . |
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Abstract ：
The upper and lower limits of detected frequency for differential resonator were obtained by experimental method. The detected upper limit frequency only need to satisfy the sampling theorem while the detected lower one is related to sampling frequency. Under the condition of certain sampling frequency, the lower detecting frequency of differential resonator was about 1/650 of sampling frequency. When the sampling frequency was too high, whether converging to the pole or the polar ring, the phase diagram of differential resonator would present as a pie. Applying this method to the high speed rolling mill fault diagnosis, the phase diagram of the vibration signals changed from pole to polar ring, which implied the running state from normal to incipient fault, thereby providing an effective technology for condition monitoring and fault diagnosis of mechanical equipment.
Keyword ：
Resonators Resonators Phase diagrams Phase diagrams Failure analysis Failure analysis Vibrations (mechanical) Vibrations (mechanical) Flow visualization Flow visualization Poles Poles Roller bearings Roller bearings Condition monitoring Condition monitoring Fault detection Fault detection
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| GB/T 7714 | Xu, Yong-Gang , Ma, Hai-Long , Feng, Ming-Shi et al. Differential Resonator Method for Incipient Failure Visual Detection of Bearings [J]. | Journal of Beijing University of Technology , 2012 , 38 (7) : 979-987 . |
| MLA | Xu, Yong-Gang et al. "Differential Resonator Method for Incipient Failure Visual Detection of Bearings" . | Journal of Beijing University of Technology 38 . 7 (2012) : 979-987 . |
| APA | Xu, Yong-Gang , Ma, Hai-Long , Feng, Ming-Shi , Cui, Ling-Li . Differential Resonator Method for Incipient Failure Visual Detection of Bearings . | Journal of Beijing University of Technology , 2012 , 38 (7) , 979-987 . |
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Abstract ：
When chaotic oscillator changing from chaotic state to large-scale periodic state, its phase diagram symmetry will obviously changed. Hu invariant moment is adopted to describe the different state of chaotic oscillator phase diagram. The threshold value of chaos oscillator under the large-scale periodic state is ascertained by the curve of invariant moment-periodic driving force. According to the difference of Hu invariant moment value for different chaotic oscillator phase diagram, the state of chaos oscillator can be automatically identified. Finally, the simulated and engineering vibration signals are analyzed, and the results show that invariant moment can accurately identify the state of chaotic oscillator and have better noise-tolerance.
Keyword ：
Signal detection Signal detection Circuit oscillations Circuit oscillations Crystal symmetry Crystal symmetry Phase diagrams Phase diagrams Failure analysis Failure analysis Vibration analysis Vibration analysis
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| GB/T 7714 | Xu, Yonggang , Ma, Hailong , Feng, Mingshi et al. New method for weak signal detection based on invariant moment [J]. | Journal of Vibration, Measurement and Diagnosis , 2012 , 32 (4) : 568-571 . |
| MLA | Xu, Yonggang et al. "New method for weak signal detection based on invariant moment" . | Journal of Vibration, Measurement and Diagnosis 32 . 4 (2012) : 568-571 . |
| APA | Xu, Yonggang , Ma, Hailong , Feng, Mingshi , Cui, Lingli . New method for weak signal detection based on invariant moment . | Journal of Vibration, Measurement and Diagnosis , 2012 , 32 (4) , 568-571 . |
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