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Research On Crack Damage Identification And Location Technology Of Metro Bogie Frame Based On Lamb Wave

Posted on:2019-01-08Degree:MasterType:Thesis
Country:ChinaCandidate:J J LvFull Text:PDF
GTID:2382330545965680Subject:Transportation engineering
Abstract/Summary:PDF Full Text Request
Under the complication of alternating load,the subway train bogies are susceptible to forming up fatigue cracks.In particular,if it cannot be discovered and diagnosed in time,it will seriously threaten the safety and reliability of train operation.Despite non-destructive testing technology has been widely used in the overhaul of bogies,but the static of off-line inspections and missed inspections,as the observation,is still unavoidable to be occurred.Lamb wave is,one classification of ultrasonic wave,widely used for crack damage detection,particularly the high sensitivity to the initial damage of the structure.As a consequence,Lamb wave monitoring technology into the real-time monitoring focused on fatigue cracks,especially in the bogie frame of subway trains is introduced.Additionally,it not only provides a new idea for traditional fault diagnosis,but also has gigantic significance in the precaution of unexpected catastrophic events,as well as ensuring the safe operation of trains.The research content and results of this article mainly include:(1)This research paper aims to study on crack damage identification on steel plates using lamb wave.The subway train bogie is welded by numerous steel plates,therefore,the Q345 type steel plate is selected with respect to the basic research object of the particular experiment in regard to crack damage expansion,as well as the optimization of lamb wave excitation signal in terms of number of peaks,signal amplitudes,and center frequencies.By doing this,the decomposition of the original signal using empirical mode is analyzed by time-domain waveform analysis and spectrum analysis effectively identifying the crack damage of steel plate.It hence signifies an accepted reliability on theoretical basis associated with the crack damage detection of the metro bogie frame.(2)The research paper also places an emphasis on the Lamb wave-based crack location technology of steel plates.Firstly,using the time-delay ellipse positioning method to define the crack damage of steel plate.Secondly,the steel plate's scattering wave model is proposed by inserting the constrained equation of lamb wave dispersion in the Rayleign-Lamb wave equation into the classical plate bending wave scattering model.The new model can better describe the relationship between the Lamb wave and the crack damage of the steel plate.Moreover,this research paper also considers the benefit of genetic algorithm in the light of solving in built-up scattering wave model function,following by converting the crack damage identification problem into the optimization problem.Adaptation searches out the extent and location of crack damage.(3)This paper conducts the study on experiment related with the horizontal,vertical,as well as corner cracks of the weld of the bogie frame.The experimental results provenly demonstrate that the effectiveness of active Lamb wave detection method on identifying the extent and location of crack damages in the bogie frame of metro trains.By doing this,the arrival time of the reflected wave packet,the IMF4 spectrum of the reflected signal,the instantaneous amplitude of the transmitted signal,and the IMF1 spectrum of the transmitted signal are proposed to quantitatively analyze and forecast the degree of crack damage.This four indexes also show strong universality.In the positioning technology,the proposed steel scattering wave model identification results are more ideal than the ellipse positioning,the recognition error of the coordinates and damage radius are within 5mm.In addition,the research results are of great significance for the final realization of crack detection of the subway train bogie frames.
Keywords/Search Tags:Metro Bogie Frame, Lamb, Crack damage, Empirical Mode Decomposition, Scatter wave model
PDF Full Text Request
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