Gear Fault Diagnosis Based on Dual Parameter Optimized Resonance-Based Sparse Signal Decomposition of Motor Current

Na, Chai; Yang, Ming; Ni, Qinan; Xu, Dianguo

doi:10.1109/tia.2018.2821099

Cited by 36 publications

(14 citation statements)

References 34 publications

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“…However, the boundary effects affect estimation accuracy. Figure 8b shows the FM frequency 2 Hz more clearly and gets rid of the high frequency harmonics by scaling the time axis and Equation (13)…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…FromFigure 8a, Hilbert transform can present high-order harmonics. However, the boundary effects affect estimation accuracy.Figure 8bshows the FM frequency 2 Hz more clearly and gets rid of the high frequency harmonics by scaling the time axis and Equation(13). The time span inFigure 8ais different fromFigure 8bdue to time axis expansion and contraction.…”

mentioning

confidence: 91%

“…STFT is used in [12] for blade crack detection of wind turbine to identify time-varying fault frequencies. In [13], motor current signature analysis is applied based on two sets of over complete wavelets; the gear fault-related component is highlighted under different operating conditions. In [14], SVD filtering combines the parameter estimation technique of rotation invariant signal to detect broken rotor bars under variable operating conditions.…”

Section: Introductionmentioning

confidence: 99%

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A Synchronous Sampling Based Harmonic Analysis Strategy for Marine Current Turbine Monitoring System under Strong Interference Conditions

et al. 2019

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Affected by high density, non-uniform, and unstructured seawater environment, fault detection of Marine Current Turbine (MCT) faces various fault features and strong interferences. To solve these problems, a harmonic analysis strategy based on zero-crossing estimation and Empirical Mode Decomposition (EMD) filter banks is proposed. First, the detection problems of rotor imbalance fault under strong interference conditions are described through an analysis of the fault mechanism and operation environment of MCT. Therefore, against various fault features, a zero-crossing estimation is proposed to calculate instantaneous frequency. Last, and in order to solve the problem that the frequency and amplitude of the operating parameters are partially or completely covered by interference, a band-pass filter based on EMD is used, together with a characteristic frequency selected by a Pearson correlation coefficient. This strategy can accurately detect the multiplicative faults under strong interference conditions, and can be applied to the MCT fault detection system. Theoretical and experimental results verify the effectiveness of the proposed strategy.

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Section: Simulation Results and Analysismentioning

confidence: 99%

mentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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A Synchronous Sampling Based Harmonic Analysis Strategy for Marine Current Turbine Monitoring System under Strong Interference Conditions

et al. 2019

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“…It can be seen from equation 9 that the frequency doubled component n f r of the signal is generated by Fourier decomposition. Therefore, the local fault of the gear will result in the appearance of a component f e ± n f r , (n = 1, 2, 3, • • • ) in the current spectrum [17,28]. BA can be defined as the 2-D Fourier Transform of the third-order cumulant (TOC) of the current signal, so fault characteristic frequency components also appear in the bispectrum spectrum.…”

Section: Mathematical Model Of Fault Currentmentioning

confidence: 99%

Study on the Fault Diagnosis Method of Scraper Conveyor Gear under Time-Varying Load Condition

Zhao

Wang

2020

Applied Sciences

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Vibration signal is often used in traditional gear fault diagnosis techniques. However, the working face of the scraper conveyor is narrow, harsh and easily explosive, so it is inconvenient to obtain vibration signals by installing sensors. Motor current signature analysis (MCSA) is a fault-diagnosis method without sensor installation, which is easier to realize in the mine. Therefore, a fault diagnosis method for local gear fault, which is based on bispectral analysis (BA) of analytical signal envelope obtained by processing a stator current under time-varying load condition, is proposed in our paper. In this method, the fault frequency component is enhanced by eliminating the interference of fundamental frequency and coal flow impact. Then, the enhanced fault frequency component is extracted by BA, and a quantitative analysis of the fault strength under time-varying load is carried out from the perspective of energy. Finally, the proposed method is verified on the number HB-kpl-75 scraper conveyor reducer, and the results show that this method can successfully diagnose the failure of the scraper conveyor gear under time-varying load conditions.

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“…Sparse representation has been used in feature extraction, signal denoising, and fault classification in the field of fault diagnosis. N. Chai et al used resonance-based sparse signal decomposition (RSSD) to remove the interference from the gear meshing-related components in the current signal [13]. L. Ren et al used a joint model based on sparse representation classification (SRC) [14] and SVM in the roller bearing fault diagnosis [15].…”

Section: Introductionmentioning

confidence: 99%

Sparse Representation and SVM Diagnosis Method Inter-Turn Short-Circuit Fault in PMSM

et al. 2019

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Permanent magnet synchronous motors (PMSM) has the advantages of simple structure, small size, high efficiency, and high power factor, and a key dynamic source and is widely used in industry, equipment and electric vehicle. Aiming at its inter-turn short-circuit fault, this paper proposes a fault diagnosis method based on sparse representation and support vector machine (SVM). Firstly, the sparse representation is used to extract the first and second largest sparse coefficients of both current signal and vibration signals, and then they are composed into four-dimensional feature vectors. Secondly, the feature vectors are input into the support vector machine for fault diagnosis, which is suitable for small sample. Experiments on a permanent magnet synchronous motor with artificially set inter-turn short-circuit fault and a normal one showed that the method is feasible and accurate.

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Gear Fault Diagnosis Based on Dual Parameter Optimized Resonance-Based Sparse Signal Decomposition of Motor Current

Cited by 36 publications

References 34 publications

A Synchronous Sampling Based Harmonic Analysis Strategy for Marine Current Turbine Monitoring System under Strong Interference Conditions

A Synchronous Sampling Based Harmonic Analysis Strategy for Marine Current Turbine Monitoring System under Strong Interference Conditions

Study on the Fault Diagnosis Method of Scraper Conveyor Gear under Time-Varying Load Condition

Sparse Representation and SVM Diagnosis Method Inter-Turn Short-Circuit Fault in PMSM

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