تعيين مشخصات ترك مايل در تير يك سر در گير و نيروي كمانش ستون تركدار با استفاده از روش طراحي آزمايش، شبكه عصبي و الگوريتم ژنتيك

چكيده انگليسي :

Identification of Slant Cracks in a Cantilever Beam and Buckling Load of a Cracked Column by Using Design of Experiment Neural Network and Genetic Algorithm Mohammad Hajhosseini Mohammad hajhosseini@yahoo com Date of Submission 2011 09 21 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language FarsiSupervisor Hassan Nahvi hnahvi@cc iut ac irAbstract Most of the failures that cause serious damage to the structures can be attributed to cracks Crack in astructure introduce local flexibility and changes in the stiffness and dynamic behavior of the structure Many studies have been done on identification of the crack location and depth using vibration parametersof the structures The objective of any damage assessment technique is to inquire whether any structuraldamage such as the initiation of a crack has occurred and if so to determine its specifications Crackdetection based on modal frequency has been a common and widely used approach Cracks present aserious threat to the performance of beam like structures In this paper the flexural vibration of a cantileverbeam having a slant crack is considered The beam natural frequencies are obtained for various cracklocations depths and angles using the finite element method These natural frequencies and crackspecifications are then used to train a neural network The input of the neural network is the crackspecifications and the output is five natural frequencies of the beam With the trained neural network genetic algorithm is then used to determine the beam crack specifications by minimizing the differencesfrom the measured frequencies Simulations are performed to evaluate performance of the neural network Results show that the proposed scheme can detect slant cracks in cantilever beams with good accuracy Buckling is defined as the change of equilibrium state of a column or rod from one configuration to anotherat a critical compressive load In columns the maximum compressive load that the column can carry isusually limited by the buckling phenomenon In the second part of the thesis buckling load of a columnhaving a slant crack is obtained by using a proposed scheme Two main approaches are usually used fordetecting buckling load destructive and non destructive methods In destructive method the compressiveload is applied to the structure until it will be buckled Today neural network NN is used as a non destructive method for predicting buckling load In this study a fixed free column having a slant crack withthree specifications location L depth D and angle is considered A scheme that its inputs and outputare respectively five natural frequencies and the buckling load of the cracked column is proposed Thisscheme includes neuro genetic technique and one separate neural network At first the neuro genetictechnique detects the specifications of the crack of the column and then the neural network predicts thebuckling load of the column having a slant crack with these specifications Results show that the proposedscheme can precisely detect buckling load in columns The column and the beam that are considered in thisstudy have similar shape and material properties so results of beam crack specifications can be used fordetecting column crack specifications To train the neural network many actual sets of input output data arerequired The actual data are obtained using the finite element method via Ansys software for a number ofcracks with different specifications To determine different specifications of the crack full factorial designis employed The full factorial design is a comprehensive method which considers the effects of originalfactors Keywords Slant crack Natural frequency Buckling load Full factorial design Neural network Genetic algorit

حاج حسيني، محمد

تعيين مشخصات ترك مايل در تير يك سر در گير و نيروي كمانش ستون تركدار با استفاده از روش طراحي آزمايش، شبكه عصبي و الگوريتم ژنتيك

فركانس هاي طبيعي , روش طراحي آزمايش