An Efficient Method for Measuring Oil Casing Thread Geometric Parameters Using Point Cloud Data

This During the oilfield development process, a large number of oil casing pipes are used, and the geometric accuracy of their threaded connections is crucial for their sealing performance and connection reliability. Traditional contact-based measurement methods suffer from low detection efficiency and can cause wear on workpieces. To address this challenge, this paper proposes a digital measurement method for oil casing threads that combines multi-level point cloud optimization (MPO) with curve fitting. First, laser triangulation technology is used to collect high-density point cloud data from the thread surface. A multi-level point cloud optimization (MPO) strategy is introduced, which combines global and local filtering methods to effectively remove outliers and reduce data redundancy, while preserving key thread features. Next, cubic spline interpolation is applied for curve fitting, ensuring smoothness and continuity during profile reconstruction. This approach allows for the highprecision extraction of critical geometric parameters such as pitch and tooth height. Experiments were conducted on a 7.0 in TP-G2 special thread coupling as the measurement target, and the results show that the measurement accuracy of this method can reach 0.05 mm, meeting the processing precision requirements. This method provides an efficient and reliable technical solution for the digital measurement of oil casing threads.