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The Simulation Analysis Of Cracks' MFL And Research On Pertinent Questions

Posted on:2009-03-28Degree:DoctorType:Dissertation
Country:ChinaCandidate:T L MaFull Text:PDF
GTID:1101360248953796Subject:Chemical Process Equipment
Abstract/Summary:PDF Full Text Request
Crack defect is a biggest kind of the machine function of the influence defect, the crack defect to the safety of the accessory existing important hidden trouble. The primary methods are normal examination and flux leakage examination currently. The normal examination method mainly includes magnetic powder method, permeation method, radial method and ultrasonic method. The flux leakage method includes vacuum method, fluxmeter method, measurement of liquid surface method etc.This text with Magnetic flux leakage of the crack defect for research object, use academic analysis, finite element analysis, experiment research method to carry on the analysis for Magnetic flux leakage testing of the crack defect, and apply neural network to to carry on intelligent identify for the signal of Magnetic flux leakage testing of the crack defect. Magnetic flux leakage (MFL) testing has been applied extensively in recent years, particularly the research and the expanding application to the corrosion pit inspection; Magnetic flux leakage (MFL) testing has already been a comparatively mature inspective technique. There may also form a lot of more dangerous crack defect except corrosion defect. But resultantly a lot of factors to influence the examination result, this increases a large number of difficulties for MFL examination and evaluation to crack defect.The formerly analysis for Magnetic flux leakage testing of the crack defect, mainly to circular materials, such as pipeline, wooden club, wire rope etc. To research, this text aims at the crack defect for tank floor plate to open out research. Several steel plates weld the tank floor plate, during welded hot distortion and used period, there easily form crack defect in the welding line. However currently the MFT examination and evaluation for the crack defect has been not enough in-depth, so there lack more accurate data when examined the crack defect. This text keeps the crack defect of tank floor plate simplification and turns into a few kinds comparatively suppleness analysis model in figure, namely the V shape section crack defect, rectangle section crack defect and combinational form section crack defect. Theoretically apply equivalent strip dipole to analyze magnetic flux leakage field for the crack defect, and with Maxwell equations for the theoretic foundation, and apply ANSYS the finite element software to make the simulation analysis of the finite element for magnetic flux leakage field for crack defect, to find out the crack parameter namely the depth, the width, the ratio of depth and width, the space between parallel crack etc. For the influence of the crack flux leakage field, and analyze exterior examination condition, such as sensor liftoff, the height of air, gathering magnetism structure etc. For the influence of the cracks'flux leakage field. Aim at the actual circumstance for Magnetic flux leakage testing engineering, sets up the experiment system for the crack Magnetic flux leakage testing and pass experiment to identify the analytical result for spouse dipole model and finite element analysis.Apply ANSYS to carry though the simulation and analysis of the finite element to gain data, pick up characteristic quantity of the magnetic flux leakage field for crack defect, and research the foundational theory of neural network, according to the characteristic of the signal of magnetic flux leakage, found the geometry parameter of the crack defect to predict BP neural network model, and synthetically use the data which the finite element analysis gain and the data which the Magnetic flux leakage testing of the crack defect gain during the crack analysis as the training stylebook of BP network, equip BP neural network, analyze and make sure the parameter characteristic of the equivalent depth and width of the defect, and identify the dependability of the network to the forecast of the crack defect.
Keywords/Search Tags:crack, magnetic flux leakage field, finite element analysis, gathering magnetism signal identification, BP neural network
PDF Full Text Request
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