Abstract Geometric deformations, which represent a specific subset of pipeline anomalies characterized by shape irregularities rather than material loss or cracking, are among the most common types of anomalies in oil and natural gas pipelines. These deformations can weaken the structural integrity of pipelines, leading to explosions and leaks. For these reasons, pipelines should be inspected periodically against possible geometric deformations. The inspection is usually carried out with devices called smart pigs, which are equipped with a wheel-type caliper (CL) sensor. In this paper, an experimental rig for the development of a wheel-type CL sensor is designed and the mechanical, hardware, and software structures of the design are presented. On the proposed rig, the effect of the default angle of the CL inspection arm on the accuracy of sizing the height and length of convex/concave deformations has been experimentally investigated. The experimental results proved the theoretical hypothesis based on the angular change–spring force relationship, demonstrating that the default angle indirectly affects measurement performance through its influence on the spring force. Thus, increasing the default angle in the inspection of concave structures (up to 28% in height, 6% in length) and decreasing the default angle in the inspection of convex structures (up to 5% in height, 15% in length) increased the sizing performance regardless of the pigging speed. This study provides a reference for determining the appropriate CL arm posture for inspections to be carried out to characterize a specific geometric deformation type. It also guides the development of CL sensors by detailing the mechanical, hardware, and software structures of the experimental rig.
Parlak et al. (Fri,) studied this question.