基于小波模极大多重分形分析的振动信号异常检测

2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT) Pub Date : 2019-01-01 DOI:10.1109/ICEICT.2019.8846448

Zhiguo Zhang, Xue Liu, Hongping Wang

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引用次数: 1

摘要

提出了一种基于小波模极大值多重分形分析的遥测振动信号异常检测方法，解决了频域分析的复杂性、非平稳非线性问题。首先对振动信号进行零漂校正和趋势项消除。然后采用小波模极大多重分形分析方法对振动信号进行分解和多重分形分析。最后将特征参数输入到SVM分类器中，根据分类结果对遥测振动信号进行异常检测。实测数据验证了该方法的有效性。

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Anomaly Detection of Vibration Signals based on Wavelet Modulus Maximal Multifractal Analysis

A method for detecting abnormality of telemetry vibration signal based on multi-fractal analysis of wavelet modulus maxima was proposed to solve the complexity, non-stationary nonlinearly of frequency domain analysis. First, zero drift correction and trend item elimination are performed on the vibration signal. Then the wavelet modulus maximum multifractal analysis method is used to decompose and multifractal analysis of vibration signals. Finally, the characteristic parameters are input to the SVM classifier, and the anomaly detection of the telemetry vibration signal is performed according to the classification result. The measured data verifies the effectiveness of the method.

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来源期刊

2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)

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