声学
泄漏(经济)
希尔伯特-黄变换
声压
频谱泄漏
信号(编程语言)
光谱图
材料科学
计算机科学
电子工程
快速傅里叶变换
工程类
物理
白噪声
电信
语音识别
算法
宏观经济学
经济
程序设计语言
作者
Pei Luo,Wenkai Yang,Mingyang Sun,Guoqing Shen,Shiping Zhang
标识
DOI:10.1088/1361-6501/ad10f8
摘要
Abstract Acoustic signal detection technology has significant advantages in detecting the leakage and bursting of heat exchange pipes in boilers. To address the current lack of sound signal data for steam medium leakages and the problem of large errors in the complex sound field environment of power plants, we performed an innovative experimental comparative analysis of leakage acoustic signals under a dual medium of compressed air and steam to provide a reference for detecting leakage acoustic signals. During the experiment, the time and frequency domains were analyzed by changing the pressure of the leakage pipeline and aperture of the leakage hole, and the spectrogram and power spectrum of the leakage acoustic signal were obtained using fast Fourier transform and autocorrelation analysis. The results showed that the signal value of the leakage medium increased with increasing pipeline pressure and leakage aperture and that the energy of the steam leakage acoustic signal was greater than that of compressed air under the same pressure and aperture because of its larger specific heat capacity. In addition, the complete empirical mode decomposition of adaptive noise (CEEMDAN) algorithm was introduced into the denoising decomposition of the leakage sound signal in the furnace, and the average error of the time delay value of the leakage acoustic signal calculated using the CEEMDAN algorithm was observed to be within 5%.
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