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A weighted multi-scale dictionary learning model and its applications on bearing fault diagnosis SCIE
期刊论文 | 2019 , 446 , 429-452 | JOURNAL OF SOUND AND VIBRATION
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Abstract :

Extracting impulsive information under strong background noise and harmonic interference is a challenging problem for bearing fault diagnosis. Multi-scale transforms have achieved great success in extracting impulsive feature information, however, how to choose a suitable transform is a difficult problem, especially in the case of strong noise interference. Therefore, dictionary learning methods have attracted more and more attention in recent years. A weighted multi-scale dictionary learning model (WMSDL) is proposed in this paper which integrates the multi-scale transform and fault information into a unified dictionary learning model and it successfully overcomes four disadvantages of traditional dictionary learning algorithms including lacking the multi-scale property; restricting training samples to local patches; being sensitive to strong harmonic interference; suffering from high computational complexity. Moreover, algorithmic derivation, computational complexity and parameter selection are discussed. Finally, The effectiveness of the proposed method is verified by both the numerical simulations and experiments. Comparisons with other state-of-the-art methods further demonstrate the superiority of the proposed method. (C) 2019 Elsevier Ltd. All rights reserved.

Keyword :

Fault diagnosis Sparse representation Weighted multi-scale dictionary learning Strong interference Planetary bearing

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GB/T 7714 Zhao, Zhibin , Qiao, Baijie , Wang, Shibin et al. A weighted multi-scale dictionary learning model and its applications on bearing fault diagnosis [J]. | JOURNAL OF SOUND AND VIBRATION , 2019 , 446 : 429-452 .
MLA Zhao, Zhibin et al. "A weighted multi-scale dictionary learning model and its applications on bearing fault diagnosis" . | JOURNAL OF SOUND AND VIBRATION 446 (2019) : 429-452 .
APA Zhao, Zhibin , Qiao, Baijie , Wang, Shibin , Shen, Zhixian , Chen, Xuefeng . A weighted multi-scale dictionary learning model and its applications on bearing fault diagnosis . | JOURNAL OF SOUND AND VIBRATION , 2019 , 446 , 429-452 .
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Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis SCIE
期刊论文 | 2019 , 122 , 737-753 | MECHANICAL SYSTEMS AND SIGNAL PROCESSING
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Abstract :

In the early stage of bearing failure, the transient features are not obvious. It is a big challenge to extract the weak transient features under strong background noise. The sparse representation provides an effective and novel path to describe mechanical vibration signals. By the aid of this model, the transients induced by the local fault can be extracted more accurately from the vibration signals. However, the choice of representation dictionaries has a great impact on the results. A satisfactory dictionary should fulfill the following two conditions. Firstly, the atoms in the dictionary must match with the features to be extracted; secondly, the atoms themselves have low coherence with each other to ensure the approximation accuracy by the sparse coding algorithms. Unluckily the existing dictionaries used for fault feature extraction do not fulfill the requirements. The parametric dictionaries like the Gabor dictionary do not fully match with the fault features. The learned dictionaries cannot guarantee the incoherence requirement, besides, the atoms in the learned dictionary may not contain the damped oscillation transient features under the high noise intensity. In order to address above problems, a parametric impulsive dictionary is designed for bearing fault feature extraction in this paper. The parameters of the Laplace wavelets, which are highly matched with the local bearing fault features, are discretized by the modified alternating projection method. The obtained dictionary with a low mutual-coherence is close to being an equiangular tight frame (ETF) which guarantees the accurate recovery of the representation coefficients. Furthermore, the correlation iteration stopping criteria is introduced in the orthogonal matching pursuit (OMP) algorithm. Compared with the classical residual energy stopping criteria, it performs better on feature extraction. The superiority of the proposed method is verified by the numerical simulations. Moreover, a motor bearing experiment and the signal analysis of a real wind turbine generator are carried out to further validate the effectiveness of the method. (C) 2019 Elsevier Ltd. All rights reserved.

Keyword :

Sparse representation Parametric impulsive dictionary design Bearing fault diagnosis Correlation stopping criteria

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GB/T 7714 Sun, Ruo-Bin , Yang, Zhi-Bo , Zhai, Zhi et al. Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis [J]. | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2019 , 122 : 737-753 .
MLA Sun, Ruo-Bin et al. "Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis" . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING 122 (2019) : 737-753 .
APA Sun, Ruo-Bin , Yang, Zhi-Bo , Zhai, Zhi , Chen, Xue-Feng . Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2019 , 122 , 737-753 .
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Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimization EI SCIE Scopus
期刊论文 | 2019 , 114 , 25-34 | MECHANICAL SYSTEMS AND SIGNAL PROCESSING
WoS CC Cited Count: 1 SCOPUS Cited Count: 2
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Abstract :

Manifold is considered to be a low dimensional surface embedded in a high dimensional vector space, and manifold learning is to find this surface based on data points sampled from this vector space. Neighborhood construction is a critical step in manifold learning to retain local relationship of data, i.e., neighbors and the connection weights. Current methods for manifold learning, including locally linear embedding, locality preserving projection, etc., assume fixed and linear neighborhood, thus lacking in adaptability for handling nonlinear system states caused by variations in machine condition or operation. To overcome this limitation, an enhanced manifold learning method is developed by utilizing kernel sparse representation to determine data neighbors and connecting weights. This enhanced manifold learning method maps data into a feature space where a kernel function is adopted to represent data by its neighbors nonlinearly. The number of data neighbors and connecting weights are determined adaptively by kernel sparse representation. It is found that the developed method enables state-related feature fusion and redundant feature elimination, thus is more effective for dimensionality reduction and feature extraction than traditional manifold learning. Analysis using vibration data measured on a gearbox with multiple faults of varying severity degrees confirmed the performance of the developed method. (C) 2018 Elsevier Ltd. All rights reserved.

Keyword :

Kernel sparse representation Gearbox fault diagnosis Manifold learning Locally linear embedding Adaptive neighborhood

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GB/T 7714 Sun, Chuang , Wang, Peng , Yan, Ruqiang et al. Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimization [J]. | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2019 , 114 : 25-34 .
MLA Sun, Chuang et al. "Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimization" . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING 114 (2019) : 25-34 .
APA Sun, Chuang , Wang, Peng , Yan, Ruqiang , Gao, Robert X. , Chen, Xuefeng . Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimization . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2019 , 114 , 25-34 .
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Multi harmonic spindle speed variation for milling chatter suppression and parameters optimization EI SCIE
期刊论文 | 2019 , 55 , 268-274 | Precision Engineering
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Abstract :

As one of the most common obstacles in milling process, regenerative chatter will result in lessened productivity, poorer product surface finish and decreased cutting life of the tool. In order to suppress chatter, the spindle speed variation (SSV) has been proposed and researched for a long time. However, the previous researches mainly focus on the basic waveform variation, such as sine, cosine, square and triangular waveforms and didn't consider the effect of phase on milling stability, which weren't suitable to the complex and high spindle speed milling conditions. Based on the previous studies, this paper proposes the concept of multi harmonic spindle speed variation (MHSSV) including the phase factor for chatter suppression. The dynamic equations with MHSSV are derived to describe the milling process. Due to the existence of the milling period and the speed variation period, the least common multiple of these two periods is adopted as the Floquet period in semi-discretization method (SDM) for stability analysis. Because the speed variation function can be described by some finite parameters, the genetic algorithm is used to optimize these parameters in order to suppress chatter more effectively. As a result, the optimized milling process has higher stability limits, especially in the high speed zone, which validates the effectiveness of the multi harmonic spindle speed variation. In addition, the numerical simulation of milling process is implemented and verifies the correctness of the proposed method. © 2018 Elsevier Inc.

Keyword :

Chatter suppression Milling process Multiharmonic Parameters optimization Speed variations

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GB/T 7714 Wang, Chenxi , Zhang, Xingwu , Yan, Ruqiang et al. Multi harmonic spindle speed variation for milling chatter suppression and parameters optimization [J]. | Precision Engineering , 2019 , 55 : 268-274 .
MLA Wang, Chenxi et al. "Multi harmonic spindle speed variation for milling chatter suppression and parameters optimization" . | Precision Engineering 55 (2019) : 268-274 .
APA Wang, Chenxi , Zhang, Xingwu , Yan, Ruqiang , Chen, Xuefeng , Cao, Hongrui . Multi harmonic spindle speed variation for milling chatter suppression and parameters optimization . | Precision Engineering , 2019 , 55 , 268-274 .
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A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates EI Scopus SCIE
期刊论文 | 2019 , 209 , 233-241 | Composite Structures
WoS CC Cited Count: 1 SCOPUS Cited Count: 1
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Abstract :

Ultrasonic guided wave is a promising tool for structural health monitoring and nondestructive testing. Numerous signal processing methods have been proposed to detect and localize anomalies based on ultrasonic guided waves for plate-like structures. However, imaging performance is limited in these methods, such as large spot size and significant artifacts. To achieve a better imaging performance of Lamb waves, a weighted sparse reconstruction-based anomaly imaging method is proposed for plate-like structures. Scattering signals are sparsely decomposed in a dictionary pre-constructed from Lamb wave propagation and scattering models. The pixel value at each location of the imaging region can be obtained by solving a weighted sparse reconstruction problem. To verify the accuracy and effectiveness of the proposed method, experiments on a carbon fiber reinforced plastic with and without additional mass are conducted. The experimental results show that the proposed method can achieve anomaly imaging with smaller spot size and fewer artifacts. © 2018 Elsevier Ltd

Keyword :

Anomaly detection Composite laminate Imaging performance Plate-like structure Scattering model Scattering signals Sparse reconstruction Ultrasonic guided wave

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GB/T 7714 Xu, Cai-bin , Yang, Zhi-bo , Zhai, Zhi et al. A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates [J]. | Composite Structures , 2019 , 209 : 233-241 .
MLA Xu, Cai-bin et al. "A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates" . | Composite Structures 209 (2019) : 233-241 .
APA Xu, Cai-bin , Yang, Zhi-bo , Zhai, Zhi , Qiao, Bai-jie , Tian, Shao-hua , Chen, Xue-feng . A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates . | Composite Structures , 2019 , 209 , 233-241 .
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Multi harmonic and random stiffness excitation for milling chatter suppression EI Scopus SCIE
期刊论文 | 2019 , 120 , 777-792 | Mechanical Systems and Signal Processing
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Abstract :

© 2018 Elsevier Ltd In cutting process, as one of the most unfavorable factors, the regenerative chatter results in serious degradation of the part surface quality, tool life and machining efficiency. According to the previous research, single frequency stiffness excitation (SFSE) is able to suppress chatter vibration effectively, where the stiffness varies in sine, cosine, square and triangle waveforms. However, the real vibrations in milling process are very complex and the SFSE can vary just in simple forms without considering phase variation. In order to mitigate chatter more effectively, this paper proposed multi harmonic stiffness excitation (MHSE) and random stiffness excitation (RSE). Due to the existence of delay item, the stiffness excitation parameters cannot be optimized with analytic methods. Therefore, with regard to MHSE, the Fourier series is used to expand the function of stiffness variation and the genetic algorithm is employed to optimize the frequency, amplitude and phase. From SFSE to MHSE, the stiffness variation can also be extended to RSE, where the variation waveform seems periodic on the whole time domain but stochastic within one period. This function of stiffness excitation cannot be described by specific parameters; thus, the random walk methodology is implemented for random waveforms optimization. The optimized random waveform is used to guide the stiffness variation for increasing the stability lobe diagrams (SLD) and suppressing chatter vibration. The simulation results show that the SLDs with MHSE and RSE are higher than those under SFSE. Finally, the milling experiments are implemented on a three-axis milling machine to validate the optimized parameters on chatter suppression. Under stiffness excitation, the chatter frequency in milling process vanishes, which shows that the proposed method can suppress chatter effectively.

Keyword :

Genetic algorithm Milling chatter suppression Multi harmonic stiffness excitation Parameters optimization Random stiffness excitation Random walk methodology

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GB/T 7714 Wang, Chenxi , Zhang, Xingwu , Liu, Jinxin et al. Multi harmonic and random stiffness excitation for milling chatter suppression [J]. | Mechanical Systems and Signal Processing , 2019 , 120 : 777-792 .
MLA Wang, Chenxi et al. "Multi harmonic and random stiffness excitation for milling chatter suppression" . | Mechanical Systems and Signal Processing 120 (2019) : 777-792 .
APA Wang, Chenxi , Zhang, Xingwu , Liu, Jinxin , Yan, Ruqiang , Cao, Hongrui , Chen, Xuefeng . Multi harmonic and random stiffness excitation for milling chatter suppression . | Mechanical Systems and Signal Processing , 2019 , 120 , 777-792 .
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Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators EI Scopus SCIE
期刊论文 | 2019 , 120 , 808-835 | Mechanical Systems and Signal Processing
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Abstract :

© 2018 Elsevier Ltd Milling, as the most widely used processing method, plays an important role in advanced manufacturing. However, milling chatter has severely restricted the development of advanced manufacturing industry. Therefore, it is of great theoretical significance and application value to study the active control of milling chatter. This paper focuses on the design of robust controller for chatter suppression. At first, the milling dynamic equations with active control force are established and simplified with the approximate linear time-invariant model for robust controller design. Then, the perturbation modeling of modal parameters and milling parameters are built and analyzed. Based on the perturbation models, the control algorithm is designed. The numerical simulation in milling process verifies the effectiveness of the designed controller. In order to validate the practical effect, the flank milling and end milling tests are implemented, respectively. The experimental results show that the designed algorithm is able to suppress chatter greatly and lead to the better workpiece surface, which prove the effectiveness and robustness of the designed controller.

Keyword :

Milling chatter suppression Pade approximation Parameters perturbation Piezoelectric stack Robust active control Zero order Fourier expansion

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GB/T 7714 Zhang, Xingwu , Wang, Chenxi , Liu, Jinxin et al. Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators [J]. | Mechanical Systems and Signal Processing , 2019 , 120 : 808-835 .
MLA Zhang, Xingwu et al. "Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators" . | Mechanical Systems and Signal Processing 120 (2019) : 808-835 .
APA Zhang, Xingwu , Wang, Chenxi , Liu, Jinxin , Yan, Ruqiang , Cao, Hongrui , Chen, Xuefeng . Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators . | Mechanical Systems and Signal Processing , 2019 , 120 , 808-835 .
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Group sparse regularization for impact force identification in time domain SCIE
期刊论文 | 2019 , 445 , 44-63 | JOURNAL OF SOUND AND VIBRATION
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Impact force identification remains a challenging inverse problem, where a small error in structural responses may lead to a large deviation in the actual solution. Recently, sparse regularization has attracted a lot of interest in the field of force identification. However, the standard sparse regularization method for force identification does not consider the intrinsic structure of impact force, i.e., the nonzero elements occur in groups, called group sparsity. In this paper, by exploiting the group sparse structure of impact force time history, we develop a general group sparse regularization method based on minimizing mixed l(2,1)-norm for the inverse problem of impact force identification. First, the number and size of groups including a complete profile of impact force are determined for penalizing the sum of the l(2)-norm of groups associated with the pulse profile of impact force. Second, a general group sparse optimization model based on the mixed l(2,1)-norm penalty for impact force identification is constructed in time domain, leading to a non-smooth convex optimization problem. Third, given the transfer function and the impact response, an accelerated gradient descent method is developed to solve such a group sparse regularization model. Finally, experiments including identification of single and consecutive impact forces are conducted on a clamped-free thin plate to illustrate the effectiveness and applicability of the proposed approach. Experimental results demonstrate that the classical Tikhonov regularization methods can only identify the single impact force from weakly noisy responses; the group sparse regularization method can efficiently identify both single and consecutive impact forces from heavily noisy responses, and has a slightly better improvement of the peak force amplitude than the standard sparse regularization method. (C) 2019 Elsevier Ltd. All rights reserved.

Keyword :

Impact force identification Group sparse regularization Tikhonov regularization Accelerated gradient descent Mixed l(2,1)-norm

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GB/T 7714 Qiao, Baijie , Mao, Zhu , Liu, Jinxin et al. Group sparse regularization for impact force identification in time domain [J]. | JOURNAL OF SOUND AND VIBRATION , 2019 , 445 : 44-63 .
MLA Qiao, Baijie et al. "Group sparse regularization for impact force identification in time domain" . | JOURNAL OF SOUND AND VIBRATION 445 (2019) : 44-63 .
APA Qiao, Baijie , Mao, Zhu , Liu, Jinxin , Zhao, Zhibin , Chen, Xuefeng . Group sparse regularization for impact force identification in time domain . | JOURNAL OF SOUND AND VIBRATION , 2019 , 445 , 44-63 .
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A Review of the Damage Detection and Health Monitoring for Composite Structures EI Scopus CSCD
期刊论文 | 2018 , 38 (1) , 1-10 | Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
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Abstract :

Composite structures are important for aero-engine, the wings and main body of aircraft, wind turbine, these components play an important role in aviation, mechanical and civil engineering. However, the safety of composite structures are affected by the complexity and defect in manufactures, which is always the bottleneck of composite material application. Thus, the damage detection and health monitoring become the hot topic in a lot of regions. Based on the demonstration of the development and applications, the key technologies of the title issue are discussed and concluded. © 2018, Editorial Department of JVMD. All right reserved.

Keyword :

Aero-engine Damage monitoring Development and applications Health monitoring Hot topics Key technologies Main bodies Material application

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GB/T 7714 Chen, Xuefeng , Yang, Zhibo , Tian, Shaohua et al. A Review of the Damage Detection and Health Monitoring for Composite Structures [J]. | Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis , 2018 , 38 (1) : 1-10 .
MLA Chen, Xuefeng et al. "A Review of the Damage Detection and Health Monitoring for Composite Structures" . | Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis 38 . 1 (2018) : 1-10 .
APA Chen, Xuefeng , Yang, Zhibo , Tian, Shaohua , Sun, Yu , Sun, Ruobin , Zuo, Hao et al. A Review of the Damage Detection and Health Monitoring for Composite Structures . | Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis , 2018 , 38 (1) , 1-10 .
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基于工程活动链的智能盆栽养护平台的设计与制作
期刊论文 | 2018 , (4) , 59-62,75 | 实验室研究与探索
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Abstract :

以工业产品研发的全寿命周期活动为主线设计制作了一款智能盆栽养护平台.采用Arduino作为控制器,利用光传感器、土壤湿度传感器以及水位检测传感器检测盆栽的环境信息,实现对盆栽自动浇水和自动补光的功能.平台的外形结构满足了功能需求,并将3D打印技术应用于外形结构的制作中.通过该项目实践过程,锻炼了学生的科研创新和实践能力,帮助学生建立多学科交叉的意识和大工程观,让学生从多学科空间去观察、思考问题.

Keyword :

智能盆栽养护平台 工程活动链 多学科交叉融合

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GB/T 7714 杨立娟 , 陈雪峰 , 张楠 et al. 基于工程活动链的智能盆栽养护平台的设计与制作 [J]. | 实验室研究与探索 , 2018 , (4) : 59-62,75 .
MLA 杨立娟 et al. "基于工程活动链的智能盆栽养护平台的设计与制作" . | 实验室研究与探索 4 (2018) : 59-62,75 .
APA 杨立娟 , 陈雪峰 , 张楠 , 郭艳婕 , 田绍华 . 基于工程活动链的智能盆栽养护平台的设计与制作 . | 实验室研究与探索 , 2018 , (4) , 59-62,75 .
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