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学者姓名：林京
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Abstract ：
To realize fault identification of unlabeled data and improve model generalization capability, domain adaptation technology has been increasingly applied to intelligent fault diagnosis of machinery. Nevertheless, traditional domain adaptation diagnosis models generally restrict different domains to have the same label space, which does not always hold in complex industrial scenarios. Consequently, a more practical scenario, i.e., partial-set transfer diagnosis, is explored in this article, where the target label space is a subspace of the source domain. A multiweight domain adversarial network (MWDAN) is proposed to solve this issue, in which the weighting mechanism of class-level and instance-level is jointly designed to distinguish the label space and quantify the transferability of data samples. Based on the proposed strategy, the positive transfer between shared classes is promoted while the negative effect caused by outlier classes is circumvented. As a result, MWDAN can learn discriminative representations for accurate fault diagnosis in the target domain. Extensive experiments constructed on two mechanical systems demonstrate the outstanding performance of MWDAN.
Keyword ：
Adaptation models Adversarial learning Data models domain adaptation Fault diagnosis Feature extraction Games Generators mechanical fault diagnosis Task analysis weighting mechanism
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| GB/T 7714 | Jiao, Jinyang , Zhao, Ming , Lin, Jing . Multi-Weight Domain Adversarial Network for Partial-Set Transfer Diagnosis [J]. | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2022 , 69 (4) : 4275-4284 . |
| MLA | Jiao, Jinyang 等. "Multi-Weight Domain Adversarial Network for Partial-Set Transfer Diagnosis" . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 69 . 4 (2022) : 4275-4284 . |
| APA | Jiao, Jinyang , Zhao, Ming , Lin, Jing . Multi-Weight Domain Adversarial Network for Partial-Set Transfer Diagnosis . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2022 , 69 (4) , 4275-4284 . |
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Abstract ：
To meet industrial demand, plenty of research works have been dedicated to monitoring the health status of planetary gearboxes. For the same purpose, a new path is explored based on rotating encoder signal (RES) by considering time-varying speed condition. In proposed method, generalized demodulation is firstly applied on second-order derivative of RES to eliminate the frequency variability caused by time-varying speed, and a combined comb filter is performed in this process to improve the signal-to-noise ratio of demodulated signal. The toothwise meshing information is then integrated as individual samples for the detection of local anomalies induced by gear defect. After reducing the dimensionality of these toothwise samples by reordered kernel principal component analysis, a normalized robust statistical distance is constructed to indicate the anomalies contained in RES. Simulation and experimental cases are provided to reveal the efficacy of the proposed method.
Keyword ：
Demodulation Dimensionality reduction encoder signal analysis fault diagnosis Frequency modulation Gears Noise reduction planetary gearboxes Planets Shafts time-varying speed Vibrations
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| GB/T 7714 | Liang, Kaixuan , Zhao, Ming , Lin, Jing et al. Toothwise Health Monitoring of Planetary Gearbox Under Time-Varying Speed Condition Based on Rotating Encoder Signal [J]. | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2022 , 69 (6) : 6267-6277 . |
| MLA | Liang, Kaixuan et al. "Toothwise Health Monitoring of Planetary Gearbox Under Time-Varying Speed Condition Based on Rotating Encoder Signal" . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 69 . 6 (2022) : 6267-6277 . |
| APA | Liang, Kaixuan , Zhao, Ming , Lin, Jing , Jiao, Jinyang , Ding, Chuancang . Toothwise Health Monitoring of Planetary Gearbox Under Time-Varying Speed Condition Based on Rotating Encoder Signal . | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS , 2022 , 69 (6) , 6267-6277 . |
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Abstract ：
Ultrasonic detection is one of the most commonly used methods in nondestructive testing. Trailing pulses that can be observed in plates and cylindrical rods are a list of longitudinal ultrasonic waves. However, the complexity of trailing pulses brings challenges for ultrasonic–based nondestructive testing. In this paper, a trailing pulses self-focusing method for damage detection in thick plates is proposed by utilizing physical characters of trailing pulses. Firstly, the characteristics of trailing pulses are analyzed by theoretical derivation. Then, three steps of trailing pulses self-focusing method including correlation filtering, energy envelope screening and defect matching are introduced. After that, the trailing pulses of single defect can be focused and the accurate positions of defects can be obtained as well. Finally, a prospective application of trailing pulses, which uses ultrasound phased array (UPA) for nondestructive testing, is discussed. The experiment is carried out on an aluminum plate with a remarkable thickness, which illustrates the effectiveness of the method. © 2018 Elsevier Ltd
Keyword ：
Correlation filtering Energy envelope Longitudinal ultrasonic Prospective applications Self-focusing Theoretical derivations Ultrasonic detection Ultrasound phased arrays
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| GB/T 7714 | Shao, Yongsheng , Zeng, Liang , Lin, Jing et al. Trailing pulses self-focusing for ultrasonic-based damage detection in thick plates [J]. | Mechanical Systems and Signal Processing , 2019 , 119 : 420-431 . |
| MLA | Shao, Yongsheng et al. "Trailing pulses self-focusing for ultrasonic-based damage detection in thick plates" . | Mechanical Systems and Signal Processing 119 (2019) : 420-431 . |
| APA | Shao, Yongsheng , Zeng, Liang , Lin, Jing , Wu, Wentao , Zhang, Hui . Trailing pulses self-focusing for ultrasonic-based damage detection in thick plates . | Mechanical Systems and Signal Processing , 2019 , 119 , 420-431 . |
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Abstract ：
Parameter-adaptive variational mode decomposition (VMD) has attenuated the dominant effect of prior parameters, especially the predefined mode number and balancing parameter, which heavily trouble the traditional VMD. However, parameter-adaptive VMD still encounters some problems when it is applied to the data from industry applications. On one hand, the mode number chosen using parameter-adaptive VMD is not the optimal. Numbers of redundant modes are decomposed. On another hand, parameter-adaptive VMD has much space for the improvement when it is applied to compound-fault diagnosis. To solve these issues and further enhance its performance, an improved parameter-adaptive VMD (IPAVMD) is proposed in this paper. Firstly, a new index, called ensemble kurtosis, is constructed by combining with kurtosis and the envelope spectrum kurtosis. It can simultaneously take the cyclostationary and impulsiveness into consideration. Secondly, the optimization objective function of grasshopper optimization algorithm is improved based on the ensemble kurtosis. The improved method chooses the mean value of the ensemble kurtosis of all modes rather than that of the individual mode as objective function. Thirdly, to extract all potential fault information, an iteration algorithm is used in the new method. Benefiting from these improvements, the proposed IPAVMD outperforms the traditional parameter-adaptive VMD and further expands the application to compound-fault diagnosis. It has been verified by a series of simulated signals and a real dataset from the axle box bearings of locomotive.
Keyword ：
Compound-fault diagnosis Feature extraction Improved parameter-adaptive VMD Iteration Parameter-adaptive VMD
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| GB/T 7714 | Miao Yonghao , Zhao Ming , Lin Jing . Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition. [J]. | ISA transactions , 2019 , 84 : 82-95 . |
| MLA | Miao Yonghao et al. "Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition." . | ISA transactions 84 (2019) : 82-95 . |
| APA | Miao Yonghao , Zhao Ming , Lin Jing . Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition. . | ISA transactions , 2019 , 84 , 82-95 . |
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Abstract ：
Since multicomponent modulation and complicated interference simultaneously exist in the vibration signals caused by the bearing compound fault, the fault feature becomes rather weak and is hard to be extracted. Therefore, the diagnosis of bearing compound fault is always considered as the bottle neck issue of machinery condition monitoring. The decomposition methods which can separate the individual component into different modes with appropriate criterion provide an alternative for solving this issue. However, various weaknesses, including mode mixing, depending on predefined mode number and poor noise suppression, seriously restrict their application range. To overcome the disadvantages, a novel decomposition method, swarm decomposition (SWD), is initially introduced in the diagnosis of the machinery fault. Inspired by the swarm intelligence, SWD can intelligently decompose the signal by using the swarm filtering and iterative algorithm. A series of analysis, including an impulse responses test and a numerical validation, verifies SWD has a remarkable performance in the decomposition of multicomponent modulation signal. Yet, the superiority also relies on the choice of thresholds. Therefore, a novel nature-inspired meta-heuristic optimization algorithm, whale optimization algorithm (WOA), is applied to solve the problem. Benefiting from the virtues of SWD and WOA, the proposed optimal swarm decomposition (OSWD) is more suitable for the weak feature extraction from multicomponent modulation signal. Finally, to further highlight its superiority in the diagnosis of the bearing compound fault, a number of simulation and real datasets from the axle box bearings of locomotive are applied. Results show that OSWD can be considered as an alternative to address the bottle neck issue from the bearing compound fault. © 2018 Elsevier Ltd
Keyword ：
Bearing fault diagnosis Compound fault diagnosis Individual components Machinery condition monitoring Meta-heuristic optimizations Mode decomposition Numerical validations Optimization algorithms
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| GB/T 7714 | Miao, Yonghao , Zhao, Ming , Makis, Viliam et al. Optimal swarm decomposition with whale optimization algorithm for weak feature extraction from multicomponent modulation signal [J]. | Mechanical Systems and Signal Processing , 2019 , 122 : 673-691 . |
| MLA | Miao, Yonghao et al. "Optimal swarm decomposition with whale optimization algorithm for weak feature extraction from multicomponent modulation signal" . | Mechanical Systems and Signal Processing 122 (2019) : 673-691 . |
| APA | Miao, Yonghao , Zhao, Ming , Makis, Viliam , Lin, Jing . Optimal swarm decomposition with whale optimization algorithm for weak feature extraction from multicomponent modulation signal . | Mechanical Systems and Signal Processing , 2019 , 122 , 673-691 . |
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Abstract ：
The effective extraction of weak fault features is crucial in condition monitoring and fault diagnosis of rolling bearings. Sparse coding, as a promising tool for signal denoising and feature extraction, has attracted a lot of attention in recent years. However, many challenges still exist when sparse coding is applied to the bearings detection under harsh working conditions. Specifically, the predefined dictionary-based sparse coding (PDSC) usually needs prior knowledge about the target signal, while the learning dictionary-based sparse coding (LDSC) is susceptible to interfering components produced by other rotating parts, thus bringing difficulties for early fault identification. To overcome these disadvantages, a hierarchical discriminating sparse coding (HDSC) method is presented in this paper, which could process the raw signals directly and utilize hierarchical concept to isolate interferences. In addition, a novel index termed envelope harmonic-to-noise ratio (EHNR) is introduced to give the instruction on reasonably choosing the parameters in the process of HDSC. The advantages of HDSC over traditional approaches are validated on the simulated signals and real vibration data from locomotive bearing. The results demonstrate that the proposed method can successfully extract the weak fault feature even in the presence of strong noise and ambient interferences. © 2018 Elsevier Ltd.
Keyword ：
Dictionary-based Harmonic to noise ratios Prior knowledge Rolling bearings Simulated signals Sparse coding Traditional approaches Weak fault feature extraction
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| GB/T 7714 | Jiao, Jinyang , Zhao, Ming , Lin, Jing et al. Hierarchical discriminating sparse coding for weak fault feature extraction of rolling bearings [J]. | Reliability Engineering and System Safety , 2019 , 184 : 41-54 . |
| MLA | Jiao, Jinyang et al. "Hierarchical discriminating sparse coding for weak fault feature extraction of rolling bearings" . | Reliability Engineering and System Safety 184 (2019) : 41-54 . |
| APA | Jiao, Jinyang , Zhao, Ming , Lin, Jing , Liang, Kaixuan . Hierarchical discriminating sparse coding for weak fault feature extraction of rolling bearings . | Reliability Engineering and System Safety , 2019 , 184 , 41-54 . |
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Abstract ：
For the sake of reducing the computational load and enhancing the implementation possibility, a dual time-scale extended Kalman filter is developed in this paper. First, a conventional multistate mathematical selective catalytic reduction (SCR) model is simplified into a single-state SCR model. This simplification would reduce the computational cost a lot. Inspired by the fact that the variation of NH3 coverage ratio between two cells changes relatively slow, then, the dual time-scale extended Kalman filter is proposed. The dual time-scales include one fast time-scale for the average NH3 coverage ratio and a slow time-scale for the difference of NH3 coverage ratios between the actual cell and the average value. In the dual time-scale scenario, it is unnecessary to estimate the NH3 coverage ratio of each SCR cell every time. Finally, simulation results for a medium-duty diesel engine through the MATLAB/SIMULINK show the proposed method has good performance and lower computational load.
Keyword ：
computational load dual time-scale Kalman filter NH3 coverage ratio Two-cell selective catalytic reduction
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| GB/T 7714 | Jiang, Kai , Zhang, Hui , Lin, Jing . NH3 Coverage Ratio Estimation of Diesel-Engine SCR Systems by a Dual Time-Scale Extended Kalman Filter [J]. | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY , 2018 , 67 (4) : 3625-3629 . |
| MLA | Jiang, Kai et al. "NH3 Coverage Ratio Estimation of Diesel-Engine SCR Systems by a Dual Time-Scale Extended Kalman Filter" . | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 67 . 4 (2018) : 3625-3629 . |
| APA | Jiang, Kai , Zhang, Hui , Lin, Jing . NH3 Coverage Ratio Estimation of Diesel-Engine SCR Systems by a Dual Time-Scale Extended Kalman Filter . | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY , 2018 , 67 (4) , 3625-3629 . |
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Abstract ：
Time-domain averaging (TDA), as an effective signal processing technique for periodic signal enhancement has been widely used for fault detection of gearboxes and bearings. TDA normally requires a tachometer signal to provide an accurate estimation of fundamental frequency. However, tachometer is unavailable or difficult to use in many applications. In this paper, an adaptive fundamental-frequency determination method without tachometer signal is proposed. Firstly, the effect of fundamental-frequency estimation error on direct TDA is investigated, and it indicates that minor error of estimation can cause severe deterioration in curve of attenuation coefficient. Secondly, harmonic-to-noise ratio (HNR) is proposed to evaluate the result of direct TDA for a given fundamental frequency, and it is utilized to optimize the fundamental frequency from a number of candidates. Finally, average waveform is obtained by implementing direct TDA with the optimized fundamental frequency. Examples of gear faults are given to verify the proposed method. The derived fundamental frequency is accurate, and average waveforms indicate the presence of gear faults successfully.
Keyword ：
Fundamental frequency Gear faults Harmonic-to-noise ratio Periodic signal Time-domain averaging
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| GB/T 7714 | Xu, Xiaoqiang , Lin, Jing , Yan, Chang . Adaptive determination of fundamental frequency for direct time-domain averaging [J]. | MEASUREMENT , 2018 , 124 : 351-358 . |
| MLA | Xu, Xiaoqiang et al. "Adaptive determination of fundamental frequency for direct time-domain averaging" . | MEASUREMENT 124 (2018) : 351-358 . |
| APA | Xu, Xiaoqiang , Lin, Jing , Yan, Chang . Adaptive determination of fundamental frequency for direct time-domain averaging . | MEASUREMENT , 2018 , 124 , 351-358 . |
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Abstract ：
In this paper, a systematic framework is established for health assessment of rotating machinery using a rotary encoder. In this framework, spectral quadratic weighting is first developed to convert encoder signals into acceleration series. Comb filtering is then introduced to remove the interferences resulting from drive/load variations. Finally, an adaptive denoising scheme based on Gini index is proposed to enhance the impulses caused by mechanical defects. The simulation and experimental results show that the proposed method is sensitive to incipient faults, and offers a promising tool for health assessment of rotating machinery. © 1982-2012 IEEE.
Keyword ：
Adaptive denoising Encoder signal analysis (ESA) Encoder signals Health assessments Incipient faults Mechanical defects Quadratic weighting Systematic framework
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| GB/T 7714 | Zhao, Ming , Lin, Jing . Health assessment of rotating machinery using a rotary encoder [J]. | IEEE Transactions on Industrial Electronics , 2018 , 65 (3) : 2548-2556 . |
| MLA | Zhao, Ming et al. "Health assessment of rotating machinery using a rotary encoder" . | IEEE Transactions on Industrial Electronics 65 . 3 (2018) : 2548-2556 . |
| APA | Zhao, Ming , Lin, Jing . Health assessment of rotating machinery using a rotary encoder . | IEEE Transactions on Industrial Electronics , 2018 , 65 (3) , 2548-2556 . |
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Abstract ：
Lamb wave testing is promising for damage detection and evaluation in large-area structures. The dispersion of Lamb waves is often unavoidable, restricting testing resolution and making the signal hard to interpret. A smoothed Capon algorithm is proposed in this paper to estimate the accurate path length of each wave packet. In the algorithm, frequency domain whitening is firstly used to obtain the transfer function in the bandwidth of the excitation pulse. Subsequently, wavenumber domain smoothing is employed to reduce the correlation between wave packets. Finally, the path lengths are determined by distance domain searching based on the Capon algorithm. Simulations are applied to optimize the number of smoothing times. Experiments are performed on an aluminum plate consisting of two simulated defects. The results demonstrate that spatial resolution is improved significantly by the proposed algorithm.
Keyword ：
dispersion high resolution Lamb wave smoothed Capon algorithm
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| GB/T 7714 | Cao, Xuwei , Zeng, Liang , Lin, Jing et al. Improving the resolution for Lamb wave testing via a smoothed Capon algorithm [J]. | MEASUREMENT SCIENCE AND TECHNOLOGY , 2018 , 29 (4) . |
| MLA | Cao, Xuwei et al. "Improving the resolution for Lamb wave testing via a smoothed Capon algorithm" . | MEASUREMENT SCIENCE AND TECHNOLOGY 29 . 4 (2018) . |
| APA | Cao, Xuwei , Zeng, Liang , Lin, Jing , Hua, Jiadong . Improving the resolution for Lamb wave testing via a smoothed Capon algorithm . | MEASUREMENT SCIENCE AND TECHNOLOGY , 2018 , 29 (4) . |
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