Fault severity assessment of rolling bearing based on optimized multi-dictionaries matching pursuit and Lempel–Ziv complexity

Dang, Pengfei; Yang, Zhengxin; Wen, Baogang; Wang, Minggang; Han, Qingkai

doi:10.1016/j.isatra.2021.01.042

Cited by 18 publications

(8 citation statements)

References 27 publications

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“…14 Dang et al, combined Lempel-Ziv complexity, multiple dictionary matching pursuit and particle swarm algorithm, and evaluated the seriousness of bearing failures by calculating the Lempel-Ziv complexity of reconstructed signals. 15 A large amount of noise exists as serious interference to identification of failure in engineering practice. Therefore, how to retain as many failure characteristics as possible and effectively reduce noise components is an important direction for failure diagnosis of equipment.…”

Section: Introductionmentioning

confidence: 99%

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A novel method to identify the multiple faults of intermediate bearing based on multiscale Lempel–Ziv complexity enhancement

Guo

Cong

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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In order to solve the difficulty to correctly identify a compound failure in intermediate bearing of aircraft engine, the paper has brought forward the method of strengthening fault feature information of intermediate bearing with weighted multiscale Lempel–Ziv complexity parameter. The method works by combining multiscale Lempel–Ziv complexity parameter (M-LZC) with wavelet transform (WT) and singular value decomposition (SVD) and implements the feature extraction and identification of compound failure in intermediate bearing. Firstly, failure information from different frequency bands of casing vibration signals is separated and signals are denoised based on WT and SVD difference spectrum. Secondly, concerning that the larger Lempel–Ziv complexity (LZC) of signal is, the more abundant failure information in signal will be; meanwhile, so as to avoid “excessive coarse graining” caused by traditional binarization method, M-LZC values of component signals after denoising are used to describe the failure feature information included in component signals. Thirdly, to further strengthen the failure feature information of intermediate bearing, larger weight value will be endowed to the component signals containing more abundant failure feature information. Failure information is boosted by M-LZC weight coefficient of component signal. Finally, component signals of an enhanced feature are reconstructed and the spectrum of reconstructed signal is used to make precise identification of compound failure type of intermediate bearing in aircraft engine.

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Section: Introductionmentioning

confidence: 99%

“…14 Dang et al, combined Lempel–Ziv complexity, multiple dictionary matching pursuit and particle swarm algorithm, and evaluated the seriousness of bearing failures by calculating the Lempel–Ziv complexity of reconstructed signals. 15…”

Section: Introductionmentioning

confidence: 99%

A novel method to identify the multiple faults of intermediate bearing based on multiscale Lempel–Ziv complexity enhancement

Guo

Cong

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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show abstract

“…Along this line, Cui et al used Sparsogram algorithm to select the optimal frequency band, and the LZC of the frequency band was calculated [9]. Dang et al presented an effectively fault severity evaluation method based on optimized multi-dictionaries matching pursuit and LZC [10]. Moreover, Cui et al proposed a novel double-dictionary matching pursuit method to decompose and reconstructed signal, and then the LZC was adopted to realize the fault severity assessment [11].…”

Section: Introductionmentioning

confidence: 99%

“…estimated variance of the -th r feature value.It is worth noting that the smaller Laplacian score implies the better feature. According to equation(10), the smaller numerator  …”

mentioning

confidence: 99%

Bearing fault severity assessment using variable-step multiscale fusion Lempel-Ziv complexity

Zhou

Shi

Huang

et al. 2022

J. Phys.: Conf. Ser.

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Most research on bearing health condition monitoring is devoted to distinguish the defective condition from the healthy condition. In practice, the fault severity assessment is also critical for performing the prognostics and maintenance of bearings. Lempel-Ziv complexity (LZC) has been widely used for the bearing quantitative fault diagnosis. However, the original LZC extracts fault information only at the single scale and often fails to portray the fault features. Then, the multiscale LZC is proposed to more comprehensively extract the fault information. However, multiscale analysis would shorten the length of time series and lead to inaccurate calculation results as the scale factor increases. As such, this paper proposes a novel bearing fault severity assessment method using variable-step multiscale fusion Lempel-Ziv complexity (VSMFLZC) to facilitate the quantitative fault diagnosis of bearings. The variable step length strategy is developed in the proposed method to optimize the coarse-grained procedure. Then, Laplace score is applied to evaluate the features and weights at each scale to obtain the proposed VSMFLZC. By such a fusion algorithm, the sequence can be converted into a single but comprehensive evaluation indicator for the fault severity assessment. The experimental results indicate that the proposed method outperforms the original LZC and multiscale LZC, where the fault features can be more comprehensively extracted and the fault severity assessment of rolling bearing can be successfully realized.

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“…Doubledictionary matching pursuit and LZC were also integrated to assess bearing fault severity [18]. Along this line, Dang et al [19] proposed a novel fault severity evaluation method combining the optimized multi-dictionaries matching pursuit with LZC.…”

Section: Introductionmentioning

confidence: 99%

Fault severity assessment for rotating machinery via improved Lempel–Ziv complexity based on variable-step multiscale analysis and equiprobable space partitioning

Zhou¹,

Shi²,

Luo³

et al. 2022

Meas. Sci. Technol.

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Fault severity assessment for rotating machinery is critical since it can reduce downtime and guarantee the reliability of the equipment. Lempel-Ziv complexity (LZC) has been widely used for the fault severity assessment. However, LZC is of a single-scale analysis and 0-1 encoding, which cannot fully explore the features of vibration signals measured from rotating machinery. This paper, thus, proposes an improved LZC based on the variable-step multiscale analysis (VSMA) and equiprobable space partitioning (ESP) strategies to fully explore features of vibrations of rotating machinery. The VSMA is proposed to overcome the drawback that the single-scale analysis fails to comprehensively uncover features and solve the problem that the traditional multiscale analysis significantly reduces the length of sequences. With the VSMA, a string of time series under different scales can be generated. The ESP is developed to transform the time series into symbolic series, with the capability of reserving the features of vibration signals and being more robust against noise, particularly for non-stationary signals. Then, the ESP based variable-step multiscale LZCs (i.e., ESP-VSMLZCs) are obtained. To fuse the obtained ESP-VSMLZCs and obtain a comprehensive indicator for fault severity assessment, Laplacian score weighting is adopted. As such, a single ESP based variable-step multiscale fusion LZC (ESP-VSMFLZC) indicator can be obtained. The proposed indicator is verified by simulated data from a bearing dynamic model and experimental data measured from rotating machinery.

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Fault severity assessment of rolling bearing based on optimized multi-dictionaries matching pursuit and Lempel–Ziv complexity

Cited by 18 publications

References 27 publications

A novel method to identify the multiple faults of intermediate bearing based on multiscale Lempel–Ziv complexity enhancement

A novel method to identify the multiple faults of intermediate bearing based on multiscale Lempel–Ziv complexity enhancement

Bearing fault severity assessment using variable-step multiscale fusion Lempel-Ziv complexity

Fault severity assessment for rotating machinery via improved Lempel–Ziv complexity based on variable-step multiscale analysis and equiprobable space partitioning

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