شماره مدرك :
7185
شماره راهنما :
6691
پديد آورنده :
حمصيان اتفاق، محمدحميد
عنوان :

پايش تندرستي سازه ها برپايه ي پخش امواج هدايت شونده ي فرا صوت براي آسيب هاي با هندسه خميده

مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
مكانيك
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مهندسي مكانيك
سال دفاع :
1390
صفحه شمار :
پانزده، 117ص.: مصور، جدول، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
حميدرضا ميردامادي، عليرضا فدايي تهراني
استاد مشاور :
سعيد ضيايي راد
توصيفگر ها :
شعاع انحناي ترك , شدت نسبي موج باز تابيده , تحليل وارون , بزرگايابي آسيب , اثر انگشت ديجيتالي آسيب
تاريخ نمايه سازي :
7/8/91
استاد داور :
محمد دانش، مهدي مقيمي زند
تاريخ ورود اطلاعات :
1396/09/20
كتابنامه :
كتابنامه
رشته تحصيلي :
مكانيك
دانشكده :
مهندسي مكانيك
كد ايرانداك :
ID6691
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Structural Health Monitoring Based on Ultrasonic Guided Waves Propagation for Damages with Curved Geometry Mohamad Hamid Hemasian Etefagh Email address hamidhemasian@gmail com Date of Submission March 5 2012 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor s name and Email address Hamid Reza Mirdamadi Assisstant Professor hrmirdamadi@cc iut ac irAlireza Fadaei Tehrani Associate Professor mcjaft@cc iut ac irAbstractDamage identification in industrial products and manufacturing infrastructures at the earliest possible time is anissue that almost all industries are interested in Such a need makes industrial sectors to employ some kinds ofstructural health monitoring SHM configurations to provide better life safety and also to have access toeconomical benefits which are provided by SHM Among the different types of damage identificationapproaches in aerospace structures guided waves have attracted the most interest Utilizing guided waves fordamage identification in thin walled metallic and composite materials and structures has created a promisingoutlook for on line or real time health monitoring of engineering structures Depending up on the kind of signalprocessing method and pattern recognition technique a variety of information can be obtained from guidedwave signals which are classified in time frequency and joint time frequency domains based on the field ofstudy To increase our knowledge about existing damages in a structure after localization and severitydetermination it seems to be necessary to attain more possible information about their geometry It looks thatidentification of crack shape as a subsequent level in damage assessment is important considering this fact thatcracks are not necessarily linear To investigate the feasibility of crack quantification with curved geometryusing Lamb waves at first in this study relative reflection intensity RRI from typical cracks is investigated inan aluminum beam as a 1 D waveguide for propagation of Lamb waves It is then shown that RRI criteria haveno possibility of providing an appropriate signal feature for a typical damage in a structure due to the same RRIvalues in circumstances of different crack shape The feasibility of using energy envelop curve in a capturedsignal from the structure is also evaluated in providing an appropriate feature from a damage signal Thismethod also seems to be not suitable due to the crucial need to wave signal reflections from boundaries Theconcept of digital damage fingerprint DDF has been developed to overcome the uncertainties associated withemploying existent feature extraction methods in evaluation of crack parameters using artificial neural network ANN technique Among different types of feature extraction procedures DDF method is assumed as one ofthe best choices for extraction of an appropriate feature from Lamb wave signals Next in this study for the firsttime the prediction of damage geometry and size for transverse cracks with curved geometry in beam likestructures is systematically scrutinized by using DDF method based on an inverse analysis approach Byutilizing damage parameter database DPD comprising a sufficient number of DDFs training of designatedneural network is then carried out as a powerful tool in the artificial intelligence AI and damage parameterprediction in the beam under study Results indicate that in comparison with signal amplitude frequency contentof received Lamb waves extracted from characteristic points of their signal by using wavelet transform aremore sensitive to crack shape and play an effective role in prediction of crack curvature as a main part ofdamage geometry On the contrary DDFs including signal amplitudes in time domain can predict size of crackwith less error values in comparison with DDFs extracted from frequency content of signals Finally it can beconcluded that an acceptable quantification of crack size and curvature in an
استاد راهنما :
حميدرضا ميردامادي، عليرضا فدايي تهراني
استاد مشاور :
سعيد ضيايي راد
استاد داور :
محمد دانش، مهدي مقيمي زند
لينک به اين مدرک :

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