Application of Wavelet Packet Analysis for Fault Detection in Electro-Mechanical Systems Based on Torsional Vibration Measurement

Li, X.; Qu, Liangsheng; Wen, Gurangrui; Li, C.

doi:10.1006/mssp.2002.1517

Cited by 30 publications

(11 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The module of ) (t q is just the envelope of ) (t x , as shown in (4). 2) Structure analytic signal of sampled series There are mainly three reasons for tooth surface well distributed wear, firstly being invaded by metal particle, dust and grain of sand into working surface of tooth, secondly unsmooth tooth face, thirdly bad lubrication such as lack of lubrication oil , lubrication oil is not clean [4] . Besides, coupling wear, misalignment and torsion resonance will cause large torque changes at the mesh point, which enlarges the impact and accelerates the wear.…”

Section: Hilbert Envelope Demodulation Analysismentioning

confidence: 99%

Adaptive redundant second generation wavelet packet in mine hoist reducer fault detection

Chen

Gao

2011

2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC)

View full text Add to dashboard Cite

The second generation wavelet is a new developed wavelet theory and it has been widely used in signal analysis and processing. This paper analyzes the constructor of adaptive redundant second generation wavelet packet and applies it into mine hoist reducer fault detection. Combining with fault mechanism of reducer, adaptive redundant second generation wavelet packet detected the fault style and fault reasons of reducer effectively, so it is better and efficient.

show abstract

Section: Hilbert Envelope Demodulation Analysismentioning

confidence: 99%

Adaptive redundant second generation wavelet packet in mine hoist reducer fault detection

Chen

Gao

2011

2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC)

View full text Add to dashboard Cite

show abstract

“…(6) and (8), we are able to obtain directly the pseudospectrum of the filtered signal, 10) applying the Discrete Fourier Transform obtaining Eqs. (9) and (10).…”

Section: Generalized Discrete Shannon Functionsmentioning

confidence: 99%

“…(6) and (8), we are able to obtain directly the pseudospectrum of the filtered signal, 10) applying the Discrete Fourier Transform obtaining Eqs. (9) and (10). In these equations we can obtain directly the main frequency of the signal, through the identification of the maximum value of the pseudospectrum and also we can see which are the other frequency components that are remained in this reconstructed signal after the filtering.…”

Section: Generalized Discrete Shannon Functionsmentioning

confidence: 99%

“…With these ideas in mind we revisit the neutronic signal analysis techniques to introduce an elegant method to clean and filter the signals, based on Shannon functions. 10) Shannon sampling theorem for bandlimited signals is one of the cornerstones of signal processing. While the Shannon sampling theorem is based on bandlimited signals, it is natural to investigate other signal classes for which a sampling theorem holds.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of a BWR Stability Behavior using Generalized Discrete Shannon Functions. Application to Ringhals and Forsmark Benchmarks Data

Llorens

Verdú

Hennig

2006

Journal of Nuclear Science and Technology

View full text Add to dashboard Cite

In this paper we have introduced a new methodology to on-line signal conditioning and monitoring to determine the stability parameters of the BWR NPP, that is, the determination of the effective Decay Ratio DR and the frequency of the main oscillation causing instability events. This method is based on the generalized discrete Shannon function convolution, which removes the noise and filters the signal in a specified frequency band. We have focused our attention in noise signals, first on analytic ones to check how the algorithm works, and then we have tested it with some real neutron signals. The algorithm works very well with dirty real signals providing good results, even in the case of short time series. Main attemption has been focused on decomposing signals to detect when a global and/or a regional oscillations are taking place in a BWR. This methodology can be implemented in on-line monitors to determine the stability parameters of the BWR reactors, that is, the determination of the effective decay ratio (DR) and the frequency of the main oscillation causing instability events.

show abstract

“…But the drawback of WT is that the frequency resolution is rather poor in the high-frequency region which the faulty features always exist in could not be resolved. The wavelet packet transform (WPT), a generalization of wavelet bases, is alternative bases formed by taking linear combinations of usual wavelet functions [2]. WPT divides the frequency space into various parts and allows a better time-frequency localization of signal.…”

Section: Introductionmentioning

confidence: 99%

Turbine machine fault diagnosis using modified redundant second generation wavelet packet transform

Zhou

2012

Proceedings of the 10th World Congress on Intelligent Control and Automation

View full text Add to dashboard Cite

Faulty features extraction is an essential problem in the field of large-scale electromechanical equipment faulty diagnosis. Classical vibration faulty features extraction is based on spectral analysis method, while the wavelet transform provides a novel tool to solve this problem. In this paper, the problem of frequency band derangement inhering in redundant second generation wavelet packet transform (RSGWPT) was explained and the causes were pointed out. Then a modified redundant second generation wavelet packet transform which can make the order of decomposed subband signals to be consistent with the linear partition order of frequency band is proposed. The modified RSGWPT discards the split and merge operations in the decomposition and reconstruction stages and directly use the constructed operators to accomplish prediction and update steps. Thus the signal length at each level is the same with the original signal, accordingly more information of the time domain features can be preserved, and at the same time the aliasing of RSGWPT can be inhibited effectively. This method was applied to analyze the simulated signals and the practical turbine machine vibration faulty signals. Testing results show that the proposed improved RSGWPT method is quite effective in extracting the faulty features from the vibration signal, so it can be effectively applied to the fault diagnosis of turbine machine.Index Terms -Turbine machine; Fault diagnosis; Redundant second generation wavelet packet transform.

show abstract

Application of Wavelet Packet Analysis for Fault Detection in Electro-Mechanical Systems Based on Torsional Vibration Measurement

Cited by 30 publications

References 2 publications

Adaptive redundant second generation wavelet packet in mine hoist reducer fault detection

Adaptive redundant second generation wavelet packet in mine hoist reducer fault detection

Analysis of a BWR Stability Behavior using Generalized Discrete Shannon Functions. Application to Ringhals and Forsmark Benchmarks Data

Turbine machine fault diagnosis using modified redundant second generation wavelet packet transform

Contact Info

Product

Resources

About