Wear Performance and Wear Prediction of Coating of Shrapnel Detector Arm for Oil and Gas Pipelines

A leaf spring caliper is a device used to detect the geometry and defects of the inner wall of oil and gas pipelines. The detection principle involves installing strain gauges on the detecting arm, which can be bent elastically. The strain gauge signal is connected to the voltage-detecting equipment to detect the inner wall of the pipeline through the voltage signal. This equipment has the advantages of high detection accuracy and small structure size. However, the detection arm of the leaf spring caliper works via contact detection, and the detection arm will be worn out when working, thus reducing the detection accuracy. This paper establishes a wear model of the leaf spring caliper and constructs a wear test system based on the model. The wear test system simulates wear between the detection arm material 51CrV4 (ISO 683-2-2016) and the oil pipeline material L555Q (ISO 3183:2012). By changing the coating material of the detection arm, such as nickel-phosphorus coating, epoxy acrylic resin coating, or polytetrafluoroethylene (PTFE) coating, the wear pattern of the detection arm is explored and the experimental results are analyzed and summarized to select the most suitable coating material. A polynomial fit to the test data, followed by a Reye–Archard wear model fit, was performed to finally derive the wear function for leaf springs with different coating materials. A prediction algorithm was used to predict the wear pattern of the detector arm, and the extended wear length was calibrated. The results show that the average error between the predicted data and the actual observed data is in accordance with the experimental expectations. Therefore, the wear prediction model and its corresponding wear function can be applied to wear error correction to improve the detection accuracy of leaf spring calipers.