Yu Yicheng, Worley Rob, Anderson Sean, Horoshenkov Kirill V
Department of Mechanical Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom.
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, United Kingdom.
J Acoust Soc Am. 2023 Jan;153(1):367. doi: 10.1121/10.0016856.
An acoustic method for simultaneous condition detection, localization, and classification in air-filled pipes is proposed. The contribution of this work is threefold: (1) a microphone array is used to extend the usable acoustic frequency range to estimate the reflection coefficient from blockages and lateral connections; (2) a robust regularization method of sparse representation based on a wavelet basis function is adapted to reduce the background noise in acoustical data; and (3) the wavelet components are used to localize and classify the condition of the pipe. The microphone array and sparse representation method enhance the acoustical signal reflected from blockages and lateral connections and suppress unwanted higher-order modes. Based on the sparse representation results, higher-level wavelet functions representing the impulse response are used to localize the position of the sensor corresponding to a blockage or lateral connection with higher spatial resolution. It is shown that the wavelet components can be used to train and to test a support vector machine (SVM) classifier for the condition identification more accurately than with a time domain SVM classifier. This work paves the way for the development of simultaneous condition classification and localization methods to be deployed on autonomous robots working in buried pipes.
提出了一种用于在充气管中同时进行状态检测、定位和分类的声学方法。这项工作的贡献有三个方面：（1）使用麦克风阵列扩展可用声学频率范围，以估计来自堵塞和横向连接的反射系数；（2）采用基于小波基函数的稀疏表示的鲁棒正则化方法来降低声学数据中的背景噪声；（3）利用小波分量对管道状态进行定位和分类。麦克风阵列和稀疏表示方法增强了从堵塞和横向连接反射的声学信号，并抑制了不需要的高阶模式。基于稀疏表示结果，使用表示脉冲响应的高级小波函数以更高的空间分辨率定位与堵塞或横向连接对应的传感器位置。结果表明，与时域支持向量机分类器相比，小波分量可用于训练和测试支持向量机（SVM）分类器以更准确地进行状态识别。这项工作为开发可部署在地下管道作业的自主机器人上的同时状态分类和定位方法铺平了道路。
