An enhanced Kurtogram method for fault diagnosis of rolling element bearings

Wang, Dong; Tse, Peter W.; Tsui, Kwok Leung

doi:10.1016/j.ymssp.2012.10.003

Cited by 352 publications

(215 citation statements)

References 24 publications

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“…Firstly, the five sample values from the degradation indicator curve after Karman filtering at every 5 cycles before the 176th cycle are given in Table 2. Then the 10 samples which are most similar with the operated samples are selected as the reference samples according to the new degradation indicator in Equation (1). Time range is ∆T = 5, sampling interval is ∆T = 1.…”

Section: The Estimation Of Rul For An Airplane Engine With Run-to-faimentioning

confidence: 99%

“…Recent developments of complex systems, such as aircraft engines, engineering machines, high-speed vehicles and computer numerical control (CNC) systems have been emphasized by the increasing requirements of on-line health monitoring for the purpose of maximizing its operational reliability and safety [1][2][3]. As the core part and power source of aircrafts, the reliable operation of an aero engine is critical for ensuring the reliability and safety of the aircraft, and to maintain its availability, and reduce its maintenance costs [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Remaining Useful Life Estimation of Aircraft Engines Using a Modified Similarity and Supporting Vector Machine (SVM) Approach

2017

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Abstract:As the main power source for aircrafts, the reliability of an aero engine is critical for ensuring the safety of aircrafts. Prognostics and health management (PHM) on an aero engine can not only improve its safety, maintenance strategy and availability, but also reduce its operation and maintenance costs. Residual useful life (RUL) estimation is a key technology in the research of PHM. According to monitored performance data from the engine's different positions, how to estimate RUL of an aircraft engine by utilizing these data is a challenge for ensuring the engine integrity and safety. In this paper, a framework for RUL estimation of an aircraft engine is proposed by using the whole lifecycle data and performance-deteriorated parameter data without failures based on the theory of similarity and supporting vector machine (SVM). Moreover, a new state of health indicator is introduced for the aircraft engine based on the preprocessing of raw data. Finally, the proposed method is validated by using 2008 PHM data challenge competition data, which shows its effectiveness and practicality.

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Section: The Estimation Of Rul For An Airplane Engine With Run-to-faimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Remaining Useful Life Estimation of Aircraft Engines Using a Modified Similarity and Supporting Vector Machine (SVM) Approach

2017

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“…Then, a band-pass filter is used to filter the uncorrelated noises of the original fault signal. Recently, many new methods have been proposed to determine the bandwidth and central frequency of the band-pass filter [39][40][41][42]. The fast kurtogram method is introduced in this section to choose the proper bandwidth and central frequency of the band-pass filter automatically and intelligently.…”

Section: Fault Detection For the Inner Race Of The Bearingmentioning

confidence: 99%

Enhanced Bearing Fault Detection Using Step-Varying Vibrational Resonance Based on Duffing Oscillator Nonlinear System

Liu

Dai

et al. 2017

Shock and Vibration

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Bearing is a key part of rotary machines, and its working condition is critical in normal operation of rotary machines. Vibrational signals are usually analyzed to monitor the status of bearing. However, information on the status of bearing is always buried in heavy background noise; that is, status information of bearing is weaker than the background noise. Extracting the status features of bearing from signals buried in noise is difficult. Given this, a step-varying vibrational resonance (SVVR) method based on Duffing oscillator nonlinear system is proposed to enhance the weak status feature of bearing by tuning different parameters. Extraction ability of SVVR was verified by analyzing simulation signal and practical bearing signal. Experimental results show that SVVR is more effective in extracting weak characteristic information than other methods, including multiscale noise tuning stochastic resonance (SR), Woods-Saxon potential-based SR, and joint Woods-Saxon and Gaussian potential-based SR. Two evaluation indices are investigated to qualitatively and quantitatively assess the fault detection capability of the SVVR method. The results show that the SVVR can effectively identify the weak status information of bearing.

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“…The kurtosis calculation method in the traditional kurtogram was changed to calculate the power spectrum of the envelope of different nodes of WPT. The power spectrum of the envelope signal reflects the sparsity of the signal and helps to capture the resonance band in the signal [6]. Based on the same idea, Tse and Wang proposed a new method called sparsogram.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the same idea, Tse and Wang proposed a new method called sparsogram. The power spectrum of the envelope was applied to improve the kurtosis index in the kurtogram, so that it reflected the sparsity of signals [6,7]. Gu proposed a method for analyzing kurtograms in the frequency domain [8].…”

Section: Introductionmentioning

confidence: 99%

Teager Energy Entropy Ratio of Wavelet Packet Transform and Its Application in Bearing Fault Diagnosis

Wan

Zhang

2018

Entropy

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Abstract:Kurtogram can adaptively select the resonant frequency band, and then the characteristic fault frequency can be obtained by analyzing the selected band. However, the kurtogram is easily affected by random impulses and noise. In recent years, improvements to kurtogram have been concentrated on two aspects: (a) the decomposition method of the frequency band; and (b) the selection index of the optimal frequency band. In this article, a new method called Teager Energy Entropy Ratio Gram (TEERgram) is proposed. The TEER algorithm takes the wavelet packet transform (WPT) as the signal frequency band decomposition method, which can adaptively segment the frequency band and control the noise. At the same time, Teager Energy Entropy Ratio (TEER) is proposed as a computing index for wavelet packet subbands. WPT has better decomposition properties than traditional finite impulse response (FIR) filtering and Fourier decomposition in the kurtogram algorithm. At the same time, TEER has better performance than the envelope spectrum or even the square envelope spectrum. Therefore, the TEERgram method can accurately identify the resonant frequency band under strong background noise. The effectiveness of the proposed method is verified by simulation and experimental analysis.

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An enhanced Kurtogram method for fault diagnosis of rolling element bearings

Cited by 352 publications

References 24 publications

Remaining Useful Life Estimation of Aircraft Engines Using a Modified Similarity and Supporting Vector Machine (SVM) Approach

Remaining Useful Life Estimation of Aircraft Engines Using a Modified Similarity and Supporting Vector Machine (SVM) Approach

Enhanced Bearing Fault Detection Using Step-Varying Vibrational Resonance Based on Duffing Oscillator Nonlinear System

Teager Energy Entropy Ratio of Wavelet Packet Transform and Its Application in Bearing Fault Diagnosis

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