Research on Mechanical Fault Diagnosis Based on Cascaded Bistable Stochastic Resonance and Fractal Box Dimension

Yan, Hao; Dong, Jing; Wang, Tai Yong; Wan, Jian; Zhang, Pan

doi:10.4028/www.scientific.net/amm.141.434

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Multifractal is defined on fractal set, which is made of singular measure of multiple scaling exponents and can be expressed as the union of fractal subset with different dimensions. 34 The probability distribution in i th box is defined by the following equation 34,35 where d i ( ɛ ) is the number in the i th box with box size ɛ and N ɛ is the total number of boxes. where q is the weighting factor.…”

Section: Methodsmentioning

confidence: 99%

Experimental study on the vibration characteristic responses on the surface damage of wheel materials

Tian

Zhang

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part J:

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The objective of the study was to explore the vibration signal responses on the surface damage of wheel materials using a JD-1 wheel–rail simulation facility. Vibration signals were extracted using the methods of local mean decomposition and Hilbert envelope spectrum. The surface damage of wheel rollers varies with different tangential forces. The results indicate that the surface damage of wheel materials has a corresponding characteristic frequency under different tangential forces conditions. When surface cracks appear on the surface of wheel rollers, the characteristic frequency of wheel roller is about 1830 Hz. However, the characteristic frequencies are about 800 Hz and 73 Hz for peeling and spalling damage on wheel roller. Multifractal dimensions of the vibration signals quantificationally identify and distinguish the surface damage types of wheel rollers, which can provide a meaningful guidance for the subsequent online detection of surface damage of wheel materials.

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Section: Methodsmentioning

confidence: 99%

Experimental study on the vibration characteristic responses on the surface damage of wheel materials

Tian

Zhang

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part J:

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“…Wang et al [14]proposed a multi-parameter synchronous optimization adaptive stochastic resonance algorithm based on genetic algorithm and applied it to fault detection of rolling bearing. Hao et al [15] proposed a mechanical fault diagnosis method based on cascade bistable stochastic resonance and multifractal, which can effectively eliminate the high frequency noise and enhance the energy of the low frequency signal, and the fractal dimension obtained from this method is more accurate, and the nonlinear characteristics of the mechanical vibration signal can be measured more accurately, so as to achieve the purpose of mechanical fault diagnosis. Shi et al [16] developed a fault diagnosis method for rotating machinery based on AMD and stochastic resonance.…”

Section: Introductionmentioning

confidence: 99%

Rotating Elements Fault Diagnosis Method Based on Stochastic Resonance with Triple-well Potential System of Genetic Algorithm

ZiWen

Bao²,

Xiao

et al. 2020

Preprint

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In engineering applications, the fault signal of rotating elements is easily submerged in the background noise. In order to solve this problem, a rotating body fault diagnosis method based on stochastic resonance with triple-well potential system of genetic algorithm is proposed. In this method, the signal-to-noise ratio(SNR) of the Triple-well potential system is used as the fitness function of the genetic algorithm, and several parameters of the system are optimized at the same time, which effectively improves the feature extraction effect of the weak fault of the rotating body. The results of simulation and engineering experiments show that this method has better detection effect than bistable stochastic resonance method, and can effectively detect the fault signal submerged by noise, which has a good engineering application prospect.

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“…Bistable system is a math model for studying SR. Yonggang adopts twice‐sampling frequency transformation and sets bistable system parameters artificially to achieve the SR of weak periodic signal. Li et al and Hao et al use bistable system and twice‐sampling frequency transformation to remove the noise of periodic signal. But they do not elaborate how to select effective bistable system parameters.…”

Section: Introductionmentioning

confidence: 99%

Faulty line detection method based on B-spline bistable denoising for distribution network

Gao

Cheng

Wang

et al. 2018

Int Trans Electr Energ Syst

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Summary Neutral‐point ineffectively grounded power system earthed through arc suppression coil is widely used in medium‐voltage distribution system; it is called small current‐to‐ground system (SCGS) in China. When single‐phase‐to‐earth fault occurs at SCGS, the fault current is weak and the noise impairs the feature of fault current, both of which make faulty line detection difficult. Hence, this paper proposes a B‐spline bistable denoising method (BSBD) to process the transient zero‐sequence current. This proposed method consists of 2 approaches: (1) using B‐spline fitting method to improve the deficiency of bistable system and (2) the genetic algorithm used to obtain the parameters of B‐spline bistable system. Then, a faulty line detection criterion (FLDC) based on BSBD and polarity parameter is presented. Electromagnetic transients program is used for testing the BSBD and FLDC. Extensive case studies prove the effectiveness of BSBD and FLDC.

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Research on Mechanical Fault Diagnosis Based on Cascaded Bistable Stochastic Resonance and Fractal Box Dimension

Cited by 3 publications

References 4 publications

Experimental study on the vibration characteristic responses on the surface damage of wheel materials

Experimental study on the vibration characteristic responses on the surface damage of wheel materials

Rotating Elements Fault Diagnosis Method Based on Stochastic Resonance with Triple-well Potential System of Genetic Algorithm

Faulty line detection method based on B-spline bistable denoising for distribution network

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