Multidirectional Stereo Vision Sensor With Catadioptric Units for Measuring Geometric Parameters of Pipeline Inner Walls

Abstract

Inner wall detection of precision pipelines with large length-to-diameter ratios is an important task in industrial production, including the measurement of geometric parameters. However, current vision measurement methods have limitations in such confined spaces, suffering from large volumes, high cost, low precision, and efficiency, leading to difficulties in meeting requirements for measuring straight and long pipelines. To address these issues, we propose a stereo vision sensor based on catadioptric units with planar mirrors to obtain characteristics of modularity and scalability, which can achieve multidirectional detection in confined spaces such as pipelines. The sensor is composed of multiple catadioptric units arranged symmetrically around the central axis, forming multidirectional virtual binocular imaging. The geometric model of the catadioptric unit is established for quantitative analysis of performance indicators, including measurement precision, optical path difference (OPD), depth-of-field (DOF), and field-of-view (FOV). The optimized parameters are selected to construct a prototype sensor, which is used for experimental verification of pipeline inner diameter measurement. The results show that the sensor can achieve high-precision and stable measurement. Through expanding and stacking multiple proposed sensors with modularity, the FOV will be increased to improve detection efficiency. The combination with pipeline robots will provide new solutions for the measurement and detection of the inner walls of precision pipelines with large length-to-diameter ratios.