A New Improved Kurtogram and Its Application to Bearing Fault Diagnosis

Zhang, Xinghui; Kang, Jianshe; Xiao, Lei; Zhao, Jingzhe; Teng, Hualiang

doi:10.1155/2015/385412

Cited by 42 publications

(50 citation statements)

References 28 publications

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“…To overcome the limitation of kurtogram, a method for the selection of optimal bandpass filter to calculate SK, termed as protrugram, is proposed in [8]. An improved kurtogram was proposed in [10] based on wavelet packet. It is an intrinsic demand of the SK to separate the impulsive components into subband signals adaptively and then calculate the value of kurtosis.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Spectral Kurtosis Method Based on Optimal Filter

Yang¹,

Yu²

2017

Shock and Vibration

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As a useful tool to detect protrusion buried in signals, kurtosis has a wide application in engineering, for example, in bearing fault diagnosis. Spectral kurtosis (SK) can further indicate the presence of a series of transients and their locations in the frequency domain. The factors influencing kurtosis values are first analyzed, leading to the conclusion that amplitude, not the frequency of signals, and noise make major contribution to kurtosis values. It is helpful to detect impulsive components if the components with big amplitude are removed from composite signals. Based on this cognition, an adaptive SK algorithm is proposed in this paper. The core steps of the proposed SK algorithm are to find maxima, add window around maxima, merge windows in the frequency domain, and then filter signals according to the merged window in the time domain. The parameters of the proposed SK algorithm are varying adaptively with signals. Some experimental results are presented to demonstrate the effectiveness of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

“…Empirical mode decomposition (EMD) is a method to deal with nonstationary signals adaptively [15]. Inspired by our previous work [15,16] and the work done in [8][9][10][11][12][13][14], an adaptive SK algorithm is proposed in this paper. In Section 2, kurtosis and SK are reviewed briefly.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Spectral Kurtosis Method Based on Optimal Filter

Yang¹,

Yu²

2017

Shock and Vibration

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show abstract

“…Using kurtosis value to estimate the strength of cyclical shocks pulse signal was defective, it leaded to the determined optimal band might be not accurate sometime. Faced with this shortcoming, Zhang [26] and McDonald [27] used correlated kurtosis (CK) to replace kurtosis to solve the problem and applied this approach in fault diagnosis of bearing and gearbox. Obviously, the SK and based on its various methods have been widely used in the fault diagnosis of rotating machinery.…”

Section: Introductionmentioning

confidence: 99%

A new improved Kurtogram and its application to planetary gearbox degradation feature analysis

Ni¹,

Zhao²,

Hu³

et al. 2017

J. vibroeng.

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Because of various advantages of planetary transmission system, it has been widely used in modern industry. And study on planetary gearbox degradation feature analysis method has important significance for mechanical system prognostics and health management (PHM). In order to analysis the degradation characteristic of planetary gearbox, Energram is proposed in this paper based on Kurtogram. Kurtogram is used for finding the optimal frequency band to rotating machinery fault diagnosis by calculating kurtosis. Similarly, Energram is used to show the energy trend of each frequency band by calculating energy, and arithmetic Energram is used to show the change of frequency band energy. The principle and application of Energram and arithmetic Energram are described by experimental data examples in this paper. A detailed study of planetary gearbox degradation characteristics is expressed in case study, which including Energram, arithmetic Energram and four particular comparative analyses. And the conclusions of each comparative analysis are given.

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“…However, this artificial method has some limitations in the real applications. Zhang et al [1] studied the characteristics of demodulated resonance technique and applied it on train and off train failure diagnosing on power car and passenger trains bogie. Barszcz and Sawalhi [2] presented a method for FD of rolling bearings based on combining EEMD adaptive denoising with adaptive demodulated resonance.…”

Section: Introductionmentioning

confidence: 99%

Gearbox Fault Diagnosis of Wind Turbine by KA and DRT

Heidari

2016

Journal of Energy

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The spectral kurtosis analysis (KA) is used to select the filter parameters (FPs) combined with the application of the demodulation resonance technique (DRT) for a gearbox fault diagnosis (FD) of wind turbine. Based on the proposed method, the FPs can be selected automatically according to the kurtosis maximization principle. By changing of the shaft speed under the variable loads conditions, the natural frequency (NF) of the gearbox will be shifted and will affect the accuracy of the detection of the faults. So, the effect of the external loads on the NF of the gearbox is examined based on the simulation of the gearbox. In addition, the fast kurtogram (FK) combined with the demodulated resonance technology is used to process the simulated faulty signal of a gearbox. The results show that the FD of the gearbox is modified by correcting the NF shifts due to the variation of the operating loads.

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A New Improved Kurtogram and Its Application to Bearing Fault Diagnosis

Cited by 42 publications

References 28 publications

An Adaptive Spectral Kurtosis Method Based on Optimal Filter

An Adaptive Spectral Kurtosis Method Based on Optimal Filter

A new improved Kurtogram and its application to planetary gearbox degradation feature analysis

Gearbox Fault Diagnosis of Wind Turbine by KA and DRT

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