پديد آورنده :
آتشي پور، عبدالرحيم
عنوان :
آسيب يابي بر پايه ي امواج هدايت شده براي كاربردهاي پايش تندرستي سازه ها
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
طراحي كاربردي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك
صفحه شمار :
بيست، 113ص.: مصور، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
حميدرضا ميردامادي
استاد مشاور :
رسول امير فتاحي، سعيد ضيايي راد
توصيفگر ها :
تير ضخيم پولادي , ترك , حسگر , كهربفشار , پردازش ديجيتال سيگنال , تبديل موجك پيوسته , نقطه هاي سرشت نماي آسيب , شبيه سازي اجزاي محدود , آزمون هاي آزمايشگاهي , شبكه عصبي مصنوعي
تاريخ نمايه سازي :
17/3/91
استاد داور :
مصطفي غيور، محمد دانش
تاريخ ورود اطلاعات :
1396/10/06
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Guided Wave Based Damage Identification for Structural Health Monitoring Applications Seyed Abdorahim Atashipour sa atashipour@me iut ac ir Date of Submission 2012 1 16 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language ParsiSupervisor Hamid Reza Mirdamadi hrmirdamadi@cc iut ac irAbstractIn this thesis identification of damage in a thick steel beam made of ST 52 is studied based onthe guided ultrasonic wave propagation method At the beginning various inspecting methods areintroduced Regarding many advantages over other methods guided wave based damageidentification is selected for the purpose of structural health monitoring SHM of the structure inhand Fundamentals theoretical and experimental aspects of this method are then illustrated Digital signal processing DSP of guided wave GW signals as the key parameter inidentification process is presented next For this intent various DSP algorithms are introduced Considering the high capability for processing in time frequency domain Wavelet transform ischosen for processing guided wave signals Then a DSP algorithm for identification of damage ispresented and its different aspects are examined in terms of three major steps pre processing processing and post processing With the aim of eliminating unwanted and redundant information a set of signal filtering techniques like sampling windowing averaging DC offsetting normalizing and de noising are applied to raw acquired GW signals Then pre processed signalsare applied to a number of processing procedures in order to extract damage related features Forthis intent continuous wavelet transform CWT together with scaled averaged wavelet power SAP method are used A set of features are then extracted from processed signals in order todetect and characterize different damage parameters Taking advantage of Time of flight ToF feature damage which is in terms of a saw cut generated crack is localized In order to determinethe damage severity crack depth the peak amplitude of damage reflected wave is used which isobtained from the energy distribution of SAP As the next step a novel feature extractiontechnique named Damage Characteristic Points DCPs is presented so that the damage could beanonymously and automatically identified within the use of artificial intelligence AI techniques Using the extracted DCPs a multilayer feedforward artificial neural network ANN is developedand trained As far as developing an efficient damage parameter database using the experimentaltests is pretty expensive and time consuming finite element method FEM through aparameterized modeling is employed for generating the damage parameter database costeffectively For this intent commercial FEM software ABAQUS together with a Python codeare used For evaluating the accuracy of the proposed damage identification scheme experimentaltests are then conducted Two piezo ceramic transducers are employed one for generating and theother one for sensing the GW signals A program compiled in C language is used for remote andprecise control of experimental procedures Experimental as well as numerical validations areimplemented by identifying actual cracks in a steel ST52 alloy specimen by the activeactuator sensor path and the proposed online structural health monitoring system Excellentquantitative diagnosis results for damage parameters presence location and severity areachieved It should be noted that the employed DSP code is developed and implemented inMATLAB Keywords Structural health monitoring Online monitoring Guided ultrasonic wave propagation method Thick steel beam Damage Crack Sensor Actuator Piezoelectric Digital signal processing Continuous wavelet transform Scaled averaged wavelet power Damage characteristic points Finite element simulation Experimental test Artificial neural network
استاد راهنما :
حميدرضا ميردامادي
استاد مشاور :
رسول امير فتاحي، سعيد ضيايي راد
استاد داور :
مصطفي غيور، محمد دانش
