Study on the Wear Performance and Wear Prediction of Leaf Spring Calipers under Lubricating Medium Conditions

Abstract

Leaf spring calipers are a kind of pipe detector that installs strain gauges on the detecting arm, and the strain gauges measure the geometrical dimensions of the inner wall of the pipe by detecting the bending strain of the leaf spring and the sensors of the leaf spring caliper are set up on the detecting arm, so it has higher detecting accuracy and smaller structural dimensions. Leaf spring calipers are widely used because of their outstanding advantages, but their detection arms are worn out, and their detection accuracy increases with the detection distance. In this paper, we establish a wear model of the detection arm for the operation of the leaf spring caliper in crude oil and refined product pipelines, and according to the model, we build a wear test system for the detection arm. The wear test system of the inspection arm simulates the wear between the inspection arm made of G61500 (UNIFIED NUMBERING SYSTEM) material and the pipe made of X80 (API SPEC 5L) material. The wear pattern of the inspection arm in crude oil and refined oil pipelines is investigated by adding lubricating media with similar physical parameters to crude oil and refined oil, such as light mineral oil, SAE 5W-30 lubricant, 600XP 680 lubricant. The experimental results are analyzed to explore the wear performance of the leaf spring caliper arm, and the prediction algorithm is used to predict the wear pattern of the leaf spring after lubrication. The results show that the average error between the predicted and actual values meets the accuracy requirements, and the wear prediction model of the detection arm can be used as a correction algorithm for the wear error of the leaf spring caliper to improve the detection accuracy.