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基于小波包分析的供热管道泄漏检测
Leakage Detection of Heating Pipeline Based on Wavelet Packet Analysis

DOI: 10.12677/jsta.2024.124064, PP. 591-599

Keywords: 供热管道,泄漏检测,小波包分析,信号处理
Heating Pipeline
, Leak Detection, Wavelet Packet Analysis, Signal Processing

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Abstract:

随着供热管道的规模不断扩大和使用年限的增加,泄漏问题日益成为供热系统中的一个重大挑战。因此及时检测并准确定位供热管道的泄漏点显得尤为重要。针对传统泄漏检测方法在应对复杂环境和干扰源方面的不足,本研究分析了小波变换方法在传感器信号中提取泄漏特征的效能,发现小波包变换更适宜用于提取泄漏信号的特征。故而本研究基于性能评估和实际需求,选择小波包变换作为泄漏检测的核心。首先使用此算法处理管道内泄漏产生的声波信号,通过提取特定频段的信号进行小波分解和重构,有效地滤除了大部分干扰和噪声。其次进一步计算各特征值并执行阈值判定用以检测泄漏。实验结果证明,这种方法可以有效地区分噪声和泄漏信号,准确地检测泄漏。
With the continuous expansion of the scale of heating pipelines and the increase of service life, the leakage problem has increasingly become a major challenge in the heating system. Therefore, it is particularly important to detect and accurately locate the leakage point of the heating pipeline in time. Aiming at the shortcomings of traditional leakage detection methods in dealing with complex environments and interference sources, this study analyzes the effectiveness of wavelet transform method in extracting leakage features from sensor signals, and finds that wavelet packet transform is more suitable for extracting the characteristics of leakage signals. Therefore, based on performance evaluation and actual needs, this study chooses wavelet packet transform as the core of leak detection. Firstly, this algorithm is used to process the acoustic signal generated by the leakage in the pipeline. By extracting the signal of a specific frequency band for wavelet decomposition and reconstruction, most of the interference and noise are effectively filtered out. Secondly, the eigenvalues are further calculated and the threshold determination is performed to detect the leakage. The experimental results show that this method can effectively distinguish noise and leakage signals and accurately detect leakage.

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