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Research On Hybrid Magnetic Parameter Stress Detection Technology

Posted on:2022-11-19Degree:MasterType:Thesis
Country:ChinaCandidate:Q H LiuFull Text:PDF
GTID:2480306764966399Subject:Electric Power Industry
Abstract/Summary:PDF Full Text Request
Ferromagnetic materials are resistant to bending,tension and compression,fatigue and corrosion,so they are widely used in railway transportation,oil pipelines,aerospace,national defence,nuclear industry and other fields.In the process of material processing and manufacturing,such as welding,cutting,casting,heat treatment and other processes,it is easy to form stress concentration or residual stress.Therefore,early stress detection and evaluation are necessary.The residual stress and material property evaluation of ferromagnetic components are affected by various factors,such as the inhomogeneity of the structure and the anisotropy of the material.However,the characteristic parameters provided by a single detection method are limited,and different non-destructive testing methods have different sensitivity to material properties.For example,magnetic Barkhausen noise signals are sensitive to changes in the microstructure of materials;eddy currents are sensitive to the physical properties of materials near the surface.Therefore,different eigenvalues extracted by multiple methods can complement each other for the robust detection of stress information.In The thesis,the stress detection technology is studied by combining the magnetic Barkhausen noise method,the eddy current method,the alternating magnetic field method and the incremental magnetic permeability method.The main research contents are divided into the following parts:1)Based on the basic theory of electromagnetic field,magnetic domain dynamics theory and stress theory,explain the stress generation and expansion mechanism and the relationship between stress and various parameters of materials in principle,to conduct the multi-parameter evaluation of stress.Based on the above theory,a hybrid magnetic parameter detection method is proposed,and theoretical models of force and magnetic parameters and force and detection signal are established to explore the main effects of different magnetization stages on stress assessment.2)Using COMSOL multi-physics transient analysis to carry out finite element numerical simulation of hybrid magnetic parameter sensor,including sensor material parameter setting,excitation coil turns,receiver modelling,electromagnetic shielding and excitation parameters,to study multi-method fusion sensors structure.The signal receiver adopts a high spatial resolution magnetic head,which can measure the micron-scale area of the material,obtain local micro-stress information,and improve the stress resolution and microstructure resolution.3)Probe manufacturing and experimental platform construction,including winding of excitation coil,selection of detection coil,processing of magnetic yoke and probe fixture,construction of related hardware analogue circuits(signal excitation source,power amplification,signal conditioning,data acquisition,etc.),Stretching device and magneto-optical Kerr magnetic domain observation platform.A series of experiments were carried out to verify the relationship between the eigenvalues of the magnetic parameters and the stress of each method,and combined with the magneto-optical Kerr magnetic domain observation,the mechanism was explained from the microstructure.The thesis combines the magnetic parameters extracted by the four methods to study the stress detection technology,establish a theoretical model and build an experimental verification platform.The experiments combined with the simulation effectively demonstrate the correctness of the theoretical model,and verify that multiple methods and multiple magnetic parameters can improve stress assessment.Reliability,the minimum relative error of the final stress assessment is 5%,and the root mean square error is 21.5 MPa.
Keywords/Search Tags:Stress Detection, Hybrid Multiparameter, Barkhausen Noise, Micromagnetic, COMSOL Simulation
PDF Full Text Request
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