【24h】

Leak detection using the pattern of sound signals in water supply systems

机译:使用供水系统中的声音信号模式进行泄漏检测

获取原文
获取原文并翻译 | 示例

摘要

Water supply systems in Japan contribute significantly to improve public health. Unfortunately, there are many age-deteriorated pipes of various sizes and leaks frequently occur. Particularly devastating are hidden leaks occurring underground because when left undetected for years these leaks result in secondary damage. Thus, early detection and treatment of leaks is an important civil engineering challenge. At present the acoustic method is the most popular leak detection method. The purpose of this study is to propose an easy and stable leak detection method using the acoustic method assisted by pattern recognition techniques. In the proposed method we collect in the form of digital signals sound and pseudo-sound samples of underground leaking pipes. Principal component analysis (PCA) of the power spectrum of one leak sound is made, and a new coordinate system is constructed. We project the other sounds in the coordinate system, and evaluate if the sounds are similar to the sample sound or not by comparing the residual between the original and the projection. Next, we evaluate the DSF (Damage Sensitive Feature), which is a function of the first three AR model. At last, the feature vectors are created by combining the residuals, the DSF, and the damping ratio of the AR model, and a leak detection method is proposed using the Support Vector Machine (SVM) based upon them. In this study, it is shown that the residual and DSF are useful indices for leak detection. Furthermore, the proposed method shows high accuracy in recognizing leaks.
机译:日本的供水系统极大地改善了公众健康。不幸的是,有许多不同尺寸的老化管道,并且经常发生泄漏。地下发生的隐蔽泄漏尤其具有破坏性,因为多年未发现时,这些泄漏会造成二次损坏。因此,泄漏的早期检测和处理是土木工程的重要挑战。当前,声学方法是最流行的泄漏检测方法。这项研究的目的是提出一种简单,稳定的检漏方法,该方法采用模式识别技术辅助的声学方法。在提出的方法中,我们以数字信号的形式收集地下泄漏管道的声音和伪声音样本。进行了一次泄漏声功率谱的主成分分析(PCA),并建立了新的坐标系。我们在坐标系中投影其他声音,然后通过比较原始声音和投影之间的残差来评估这些声音是否与样本声音相似。接下来,我们评估DSF(损伤敏感特征),它是前三个AR模型的函数。最后,通过结合残差,DSF和AR模型的阻尼比来创建特征向量,并基于支持向量机(SVM)提出了一种泄漏检测方法。在这项研究中,表明残留量和DSF是检测泄漏的有用指标。此外,所提出的方法在识别泄漏方面显示出高精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号