Matching pursuit of an adaptive impulse dictionary for bearing fault diagnosis

Wang, Jing; Zhang, Jisheng; Chang, C.P.; Tian, Feng; Cui, Lingli

doi:10.1016/j.jsv.2013.12.029

Cited by 164 publications

(57 citation statements)

References 23 publications

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“…Du [21] proposed a nuclear norm minimization that uses a weighted low-rank sparse model for bearing fault detection. Cui [22,23] introduced composite dictionary multi-atom matching and a matching pursuit algorithm based on an adaptive impulse dictionary for gear-box and bearing fault diagnosis. The defect-induced impulses redundant dictionary and matching pursuit (MP) approach was proposed by He in [24].…”

Section: Introductionmentioning

confidence: 99%

Incipient Fault Diagnosis of Rolling Bearings Based on Impulse-Step Impact Dictionary and Re-Weighted Minimizing Nonconvex Penalty Lq Regular Technique

Liang

2017

Entropy

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Abstract:The periodical transient impulses caused by localized faults are sensitive and important characteristic information for rotating machinery fault diagnosis. However, it is very difficult to accurately extract transient impulses at the incipient fault stage because the fault impulse features are rather weak and always corrupted by heavy background noise. In this paper, a new transient impulse extraction methodology is proposed based on impulse-step dictionary and re-weighted minimizing nonconvex penalty Lq regular (R-WMNPLq, q = 0.5) for the incipient fault diagnosis of rolling bearings. Prior to the sparse representation, the original vibration signal is preprocessed by the variational mode decomposition (VMD) technique. Due to the physical mechanism of periodic double impacts, including step-like and impulse-like impacts, an impulse-step impact dictionary atom could be designed to match the natural waveform structure of vibration signals. On the other hand, the traditional sparse reconstruction approaches such as orthogonal matching pursuit (OMP), L1-norm regularization treat all vibration signal values equally and thus ignore the fact that the vibration peak value may have more useful information about periodical transient impulses and should be preserved at a larger weight value. Therefore, penalty and smoothing parameters are introduced on the reconstructed model to guarantee the reasonable distribution consistence of peak vibration values. Lastly, the proposed technique is applied to accelerated lifetime testing of rolling bearings, where it achieves a more noticeable and higher diagnostic accuracy compared with OMP, L1-norm regularization and traditional spectral Kurtogram (SK) method.

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Section: Introductionmentioning

confidence: 99%

Incipient Fault Diagnosis of Rolling Bearings Based on Impulse-Step Impact Dictionary and Re-Weighted Minimizing Nonconvex Penalty Lq Regular Technique

Liang

2017

Entropy

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“…For this reason the initial assessment of the capabilities of the method were done by seeding the signature of typical mechanical faults in the acquired vibration signal. In research it is normal practice to use simulated vibration data for the study of different mechanical faults, rotor unbalance, shaft misalignment and bearing faults being the most common examples [36][37][38][39][40][41][42][43][44]. This approach allowed an initial validation of the method under different fault scenarios.…”

Section: Simulation Of Mechanical Faults In Vibration Datamentioning

confidence: 99%

Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

Ruiz-Cárcel

Jaramillo

Ottewill

et al. 2016

Mechanical Systems and Signal Processing

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a b s t r a c tThe detection and diagnosis of faults in industrial processes is a very active field of research due to the reduction in maintenance costs achieved by the implementation of process monitoring algorithms such as Principal Component Analysis, Partial Least Squares or more recently Canonical Variate Analysis (CVA). Typically the condition of rotating machinery is monitored separately using vibration analysis or other specific techniques. Conventional vibration-based condition monitoring techniques are based on the tracking of key features observed in the measured signal. Typically steady-state loading conditions are required to ensure consistency between measurements.In this paper, a technique based on merging process and vibration data is proposed with the objective of improving the detection of mechanical faults in industrial systems working under variable operating conditions. The capabilities of CVA for detection and diagnosis of faults were tested using experimental data acquired from a compressor test rig where different process faults were introduced. Results suggest that the combination of process and vibration data can effectively improve the detectability of mechanical faults in systems working under variable operating conditions.

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“…It is of great significance to perform dynamic modeling and failure mechanism analysis on key parts of gearbox such as gears and bearings [1][2][3]. The large inertia load in the space drive system has a significantly wide range of applications, because the load inertia of the entire system is relatively high compared to the transmission part, posing new problems and challenges in the transmission accuracy, life, reliability, and safety of the spacecraft transmission system.…”

Section: Introductionmentioning

confidence: 99%

Transmission Error Analysis and Disturbance Optimization of Two‐Stage Spur Gear Space Driven Mechanism with Large Inertia Load

Cui

2018

Shock and Vibration

Self Cite

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For the nonlinear disturbance actual issues of the model space drive mechanism two-stage spur gear system, a nonlinear dynamic model of 14-DOF (degree of freedom) two-stage spur gear with time-varying stiffness and damping was established. This model has been developed previously by the authors to access the large inertia on the dynamic response of spur gear space driving mechanism, and its effectiveness was proved by a motion simulation experiment. In this paper, the profile error (PE) and the index error (IE) were enhanced in the dynamic model. The effects of profile error, index error, and variable load torque on transmission error (TE) were analyzed, while the optimization was proposed according to the analyzed result. The peak-to-peak value of the optimized load transmission error (LTE) was reduced by 60.7%, which improved the transmission accuracy and reduced the phenomenon of disturbance. The research of nonlinear dynamical model of two-stage spur gear and the TE of the large inertia load were enriched, which provided an important reference for the actual design of the gear system.

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Matching pursuit of an adaptive impulse dictionary for bearing fault diagnosis

Cited by 164 publications

References 23 publications

Incipient Fault Diagnosis of Rolling Bearings Based on Impulse-Step Impact Dictionary and Re-Weighted Minimizing Nonconvex Penalty Lq Regular Technique

Incipient Fault Diagnosis of Rolling Bearings Based on Impulse-Step Impact Dictionary and Re-Weighted Minimizing Nonconvex Penalty Lq Regular Technique

Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

Transmission Error Analysis and Disturbance Optimization of Two‐Stage Spur Gear Space Driven Mechanism with Large Inertia Load

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