Vibration signals denoising using minimum description length principle for detecting impulsive signatures

Wang, Yanxue; Xiang, Jiawei; Jiang, Zhansi; Yang, Lianfa; He, Zhengjia

doi:10.1177/0954406213498544

Cited by 6 publications

(5 citation statements)

References 25 publications

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“…From Figure 4, it is easy to find that the noise process is well characterized at the lower thresholdings, and the structural characteristic of the test signal is well processed. 31 Showing the proposed Walsh transform denoising method has theoretical correctness in noise suppression field.…”

Section: Simulation Signal Processingmentioning

confidence: 97%

A multi-sensor fault detection strategy for axial piston pump using the Walsh transform method

Gao

Tang

Xiang

et al. 2018

International Journal of Distributed Sensor Networks

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The axial piston pump is a key component of the industrial hydraulic system, and the failure of pump can result in costly downtime. Efficient fault detection is very important for improving reliability and performance of axial piston pumps. Most existing diagnosis methods only use one kind of the discharge pressure, vibration, or acoustic signal. However, the hydraulic pump is a typical mechanism–hydraulics coupling system, all of the pressure, vibration, and acoustic signals contain useful information. Therefore, a novel multi-sensor fault detection strategy is developed to realize more effective diagnosis of axial piston pump. The presence of periodical impulses in these signals usually indicates the occurrence of faults in pump. Unfortunately, in the working condition, detecting the faults is a difficult job because they are rather weak and often interfered by heavy noise. Therefore, noise suppression is one of the most important procedures to detect the faults. In this article, a new denoising method based on the Walsh transform is proposed, and the innovation is that we use the median absolute deviation to estimate the noise threshold adaptively. Numerical simulations and experimental multi-sensor data collected from normal and faulty pumps are used to illustrate the feasibility of the proposed approach.

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Section: Simulation Signal Processingmentioning

confidence: 97%

A multi-sensor fault detection strategy for axial piston pump using the Walsh transform method

Gao

Tang

Xiang

et al. 2018

International Journal of Distributed Sensor Networks

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show abstract

“…They provided a reflection on the use of discrete wavelet transform through the various parameters used during processing. Wang et al (2014) proposed a sub-band adaptive denoising method for detective impulsive signatures based on the minimum description length principle with improved normalized maximum likelihood density model. In the proposed method, the threshold is determined automatically, and the noise variance does not need to be estimated.…”

Section: Introductionmentioning

confidence: 99%

Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy

Yang

2015

Transactions of the Institute of Measurement and Control

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A denoising method for a hydropower unit vibration signal based on variational mode decomposition (VMD) and approximate entropy is proposed. The signal was decomposed by VMD into discrete numbers of modes, then the approximate entropy of each mode was computed. These modes were reconstructed according to a preset threshold of the approximate entropy. Finally, the denoising of the hydropower unit vibration signal can be achieved. A simulation signal and real signals of hydropower unit vibration were used to verify the proposed method. The results showed that the proposed method had a good denoising performance and was better than the wavelet transform method in the signal-to-noise ratio (SNR), root mean square error (RMSE) and partial correlation index. It was ideally suited for the online denoising of the hydropower unit vibration signal.

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“…Yang et al 4 put forward a roller bearings vibration signal denoising method using improved intrinsic timescale decomposition. Wang et al 5 presented a sub-band adaptive denoising method for detective impulsive signatures based on minimum description length principle with improved normalized maximum likelihood density model. The threshold of the proposed method is established automatically without estimation of the noise variance.…”

Section: Introductionmentioning

confidence: 99%

A method of eliminating the vibration signal noise of hydropower unit based on NA-MEMD and approximate entropy

Yang

2016

Proceedings of the Institution of Mechanical Engineers, Part E:

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A new vibration signal denoising method of hydropower unit based on noise-assisted multivariate empirical mode decomposition (NA-MEMD) and approximate entropy is proposed. Firstly, the NA-MEMD is used to decompose the signal into a number of intrinsic mode functions. Then, the approximate entropy of each component is computed. According to a preset threshold of approximate entropy, these components are reconstructed to denoise vibration signal of hydropower unit. The analysis results of simulation signal and real-world signal show that the proposed method is adaptive and has a good denoising performance. It is very suitable for online denoising of hydropower unit's vibration signal.

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Vibration signals denoising using minimum description length principle for detecting impulsive signatures

Cited by 6 publications

References 25 publications

A multi-sensor fault detection strategy for axial piston pump using the Walsh transform method

A multi-sensor fault detection strategy for axial piston pump using the Walsh transform method

Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy

A method of eliminating the vibration signal noise of hydropower unit based on NA-MEMD and approximate entropy

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