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燃煤电厂锅炉压力管道爆管故障频发,严重威胁到电厂锅炉的安全运行,为提高对该类爆管事故的及早发现与实时监测的能力,提出了一种基于音频特定频段相关特征值的对爆管事故的识别方法。该方法通过采集锅炉本体周围的相应危险点的声音信号,经滤波、基于LPC距离的端点检测算法和自适应的抗噪音频特征参数提取算法等,对其做相应的频谱特性分析,以提取爆管音频的频率与幅值的特征值,并进行自动识别。试验分析结果表明,该研究有效地解决了锅炉爆管事故的及早发现与实时监测问题。
In order to improve the early detection and real-time monitoring of such a squib accident, this paper proposes a method based on the eigenvalues of specific frequency band The method of identifying the squib accident. In this method, the sound signals of the corresponding dangerous points around the boiler body are collected, filtered, the endpoint detection algorithm based on LPC distance and the algorithm of extracting the anti-noise and audio frequency characteristic parameters are analyzed and the corresponding spectral characteristics are analyzed, Tube frequency and amplitude of the eigenvalues, and automatic identification. The experimental results show that the research effectively solves the problem of early detection and real-time monitoring of boiler tube explosion accident.