| Petroleum threads,as a specialized thread in the petroleum industry,play a role in transmitting torque when connecting upper and lower drill pipes.With the rapid development of the petroleum industry,the requirements for the machining accuracy of petroleum thread are becoming higher and higher.Due to the accurate measurement technology of petroleum thread profile accuracy is an important factor to determine the machining accuracy of petroleum thread,on-machine measurement method,which has the unique advantages of high precision,high efficiency and low error,is widely used in the measurement of petroleum thread profile.At the same time,it also solves the problem of difficult measurement of thread profile parameters caused by inconvenient loading and unloading of long and heavy petroleum threads.This thesis focuses on the research of an on-machine measurement system for petroleum threads based on linear laser displacement sensors.The specific content is as follows:Firstly,the measurement principle of petroleum thread profile based on laser triangulation is studied.According to the shape characteristics of petroleum thread profile,the on-machine measurement experimental scheme of petroleum thread based on linear laser displacement sensor is designed.According to the measurement scheme,the appropriate experimental equipment is selected,and the on-machine measurement system of petroleum thread based on linear laser displacement sensor is built to realize the collection,transmission and processing of petroleum thread profile data.At the same time,in order to ensure the accurate measurement of the profile of the petroleum thread,the pose calibration scheme of the linear laser displacement sensor is designed.Secondly,aiming at the problem of noise in the petroleum thread profile data collected by the on-machine measurement system,a thread profile data denoising method based on variational mode decomposition(VMD)algorithm is proposed.In order to avoid the influence of the artificially selected modal decomposition number and penalty factor on the decomposition performance of VMD algorithm,the Aquila Optimizer algorithm is used to optimize the two parameters with the minimum envelope entropy as the fitness function.The VMD algorithm of parameter optimization is used to process the thread profile data,and the low-frequency modal components are selected for reconstruction to achieve better noise reduction effect.Thirdly,aiming at the problem of the petroleum thread profile data after noise reduction cannot represent the complete profile information of petroleum thread,an improved BP neural network algorithm is proposed to fit the thread profile piecewise,and combining with the least square method to described the fitted curve mathematically,and the regression model of each segment curve is obtained.The target parameters of the thread profile are calculated in real time by using the regression model coefficient.At the same time,the improved arithmetic optimization algorithm(IAOA)is used to solve the problem of slow convergence speed of BP neural network algorithm and easy to fall into local optimization.Finally,according to the on-machine measurement plan for the profile of petroleum threads,an on-machine measurement experiment for petroleum threads was conducted using the SCK230 CNC thread repair machine tool as the carrier and a linear laser displacement sensor as the measurement tool.And In order to facilitate the processing of thread profile data,a data processing system is developed by using the functions of MATLAB GUI.The petroleum thread on-machine measurement system based on linear laser displacement sensor designed in this thesis has high measurement accuracy,repeatability and efficiency. |
