Research On Signal Processing And Defect Reconstruction Technology Of Magnetic Flux Leakage Detection Of Long-distance Oil Pipeline

As the pipeline service time increasing,the pipeline safety problem has become increasingly serious.In recent years,a series of pipeline accidents happened,which has affected the normal construction of the national economy,and endanger the lives and property of citizens.In pipeline safety engineering,pipeline inspection is a basic method to ensure the safety of pipeline,and the magnetic flux leakage detection method is the most commonly used nondestructive testing method.But until now,the related technology of pipeline inspection and defect recognition still belongs to the monopoly of foreign technology,they do not sell products and technology,only provide testing services,charging high service fees.For the consideration of pipeline transportation safety,national security,the cost of testing services and other considerations,it is urgent to develop a high performance pipeline defect detection system with independent intellectual property rights and without the need to rely on foreign technology.In this dissertation,the magnetic flux leakage(MFL)detection system for long-distance oil pipeline is studied.In particular,the technology of pipeline MFL detection,defect recognition and reconstruction is studied deeply.Firstly,the composition of the MFL defect detection system of long distance oil pipeline is determined.Including the PIG(Fluid-driven pipeline robots also known as pipeline pig)which is located inside the pipeline underground,Location marker which is located along the pipeline on the ground and data post processing platform in computer room.According to different functions,the system is divided into five relatively independent functional modules,including the PIG control center,defect detection module,PIG location module,the speed control module and the data post processing platform.Then the work principle and structure of the five modules are analyzed respectively.In order to enhance the passing ability of the PIG,a snake-like module structural is designed for PIG.To enhance the ability to adapt to the diameter changes of pipeline,a ball screw nut adding the flexible support is proposed to improve the design of support wheel for PIG.According to the actual working conditions,the PIG speed control mechanism is chosen based on double discthrottle.Secondly,the on-line denoising algorithm of magnetic flux leakage detection is studied.Considering the embedded working environment,a lifting wavelet denoising algorithm based on improved threshold is proposed to improve the denoising speed and accuracy of MFL detection signals.According to the actual characteristics of the MFL detection signal,the best selection range for wavelet base is determined as db5-7,sym4-6,bior2.6 and bior4.4;The decomposition level is determined to be J(28)3;threshold value estimation is determined to be the Level-Dependent estimation based on Visushrink threshold.The traditional threshold function is improved to further improve the denoising performance,and achieve a better denoising effect.In view of the serious boundary disturbance problem in the online denoising,a non-distortion extension method is proposed,and the work sequence of online segment denoising is designed,so that,almost all boundary interference is avoided.Simulation results show that the proposed algorithm has the advantages of fast speed,good effect,less computation resource usage,no boundary interference and so on.It meets the requirements of the online denoising of the MFL detection signal.Then,the online compression algorithm of magnetic flux leakage detection data is studied.Since the traditional data compression method is difficult to apply in the embedded online work environment,an online compression method for MFL detection data based on compressed sensing(CS)theory is proposed.The wavelet base is determined as the best sparse representation of the magnetic flux leakage signal,and the mathematical expression formula of the wavelet sparse matrix is derived;A measurement matrix optimization algorithm based on Welch bound and PRP conjugate gradient algorithm is proposed,and the validity and superiority of the new algorithm are proved by experiments;An important data segment screening method of the MFL detection data is proposed,which greatly reduces the data storage capacity.The simulation results show that the proposed online compression algorithm has a great advantage of less computation complexity,simple and rapid operation,high compression ratio and high reconstruction precision,and so on.It meets the actual requirements of the online compression of the MFL detection signal.Then,the 2D profile reconstruction technique of pipeline defects is studied.A 2D profile reconstruction technique of Pipeline defects based on the multi-output least squares support vector regression(MO-LSSVR)whose are optimized by parameters the Particle Swarm Optimization(PSO)is proposed.The MO-LSSVR model is derived according to the single-output LSSVR model.2D defect sample data is used to train the MO-LSSVR 2D profile reconstruction model,and the parameters of the penalty parameter and kernel parameter of MO-LSSVR are optimized by the PSO algorithm.Simulation results show that the reconstruction accuracy of the proposed reconstruction algorithm is higher than the traditional algorithm.Finally,the 3D profile reconstruction technique of pipeline defects is studied.According to the idea that the matrix can be transformed into the column vector,the problem of the 3D profile reconstruction is transformed into a vector to vector mapping problem,as same as the 2D profile reconstruction.3D defect sample data after interpolation smoothing is used to train the PSO-MO-LSSVR 3D profile reconstruction model after transforming the matrixs into the column vectors.The predicted results are re-arranged into a matrix to get the discrete lattice of 3D profile.Simulation results show that the proposed algorithm is effective,and the 3D profile of the defect is smooth,the reconstruction error is small.The research results of this dissertation will break the international technical blockade,and provide assistance for the protection of China’s pipeline transportation safety.This study has important theoretical significance and engineering application value.And,the research results can be applied to the gas pipeline or water supply pipeline detection and other similar fields.