A multi-view ultrasonic imaging solution for buried sewer pipe inspection

This paper presents an air-coupled ultrasonic imaging method and a characterization approach for robotic sensing in buried pipe systems. Recent advancements demonstrate that air-coupled ultrasonic arrays are capable of imaging complex structures in both open-air and enclosed environments. However, the high element count, large data size, and the velocity limitation of ultrasonic waves in air make air-coupled ultrasonic array less efficient in terms of data acquisition and processing performance, limiting its applications for autonomous robotics. This study aims to improve the efficiency of air-coupled ultrasonic arrays by implementing a multi-view ultrasonic imaging algorithm, which reduces the constraints on the number of required elements. This approach decreases the data size and acquisition time, thereby enhancing inspection efficiency. We also propose a modified image characterization method based on the Radon transform to extract features from 3D ultrasonic images of pipe structures. To assess imaging performance, two ultrasonic arrays with 24 and 64 elements were compared in pipe inspection experiments. Experimental results show that, by using the multi-view imaging technique, a 24-element array design can produce high-quality images with an averaged dimensional characterization error of 2.0 cm comparable to the imaging error (2.8 cm) yielded by a 64-element array by the Tippet's fusion method.