利用音频特征分析进行机器状态监测

2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN) Pub Date : 2017-03-16 DOI:10.1109/ICSCN.2017.8085717

B. Rubhini, P. Ranjan

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引用次数: 3

摘要

对机器进行连续的状态监测对于提高机器的工作效率，避免意外事故和经济损失是非常重要的。本文主要研究了利用音频信号处理技术进行状态监测。机器的声音携带有关机器状况的信息。利用快速傅里叶变换(FFT)的峰值变化响应(PVR)来观察音频信号特征的变化。本文利用传统的FFT方法证明，利用音频签名足以检测出机器不同加载条件下的异常情况。并对内禀模态函数(IMF)的PVR进行了研究，给出了音频(AF)调制信号振荡能量和频率变化的原因。

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Machine condition monitoring using audio signature analysis

Continuous Condition Monitoring of the machine is importan to improve efficiency of the machine, to avoid unexpected accidents and financial losses. Condition monitoring using audio signal processing is focused in this paper. The sound of the machine carries information about the machine condition. The change in features of audio signal are observed using the Peak Variation Response (PVR) of the Fast Fourier Transform (FFT) of signal. In this paper, the conventional FFT method has been used to prove that, it is sufficient for the detection of abnormalities due to different loading condition of the machine using audio signature. And a study on PVR of Intrinsic Mode Function (IMF) has been carried out to present the cause of variation in the energy and frequency of the oscillations of audio frequency (AF) modulated signals.

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来源期刊

2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)

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