Crack identification at the welding joint with a smart coating sensor

dc.contributor.authorWang, Xin
dc.contributor.examiningcommitteeZhu, Guozhen (Mechanical Engineering) Ho, Carl (Electrical and Computer Engineering)en_US
dc.contributor.supervisorWu, Nan (Mechanical Engineering)en_US
dc.date.accessioned2019-09-04T20:22:58Z
dc.date.available2019-09-04T20:22:58Z
dc.date.issued2019-08en_US
dc.date.submitted2019-08-30T16:40:50Zen
dc.degree.disciplineMechanical Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractIn order to avoid the money loss and injuries caused by the structural damage, early detection of the small cracks in a structure is very important. Conventional damage detection techniques, such as ultrasonic methods, strain energy methods, magnetic field methods, etc., are usually lack of sensitivity or hard to be applied to different surfaces requiring complex sensing systems. In this thesis, a new piezoelectric coating sensor is developed to detect the crack initiation, and it can apply to any surfaces of interest. Two sensitive crack measurement methods, wavelet Entropy and Frequency Comparison Function (FCF), are introduced to evaluate the crack for the structure based on the vibration signals from the new sensor. During operating, the piezoelectric composite coating sensor is applied at the welding joint of a vibrating structure to send warning and dynamic signals for damage detection and evaluation, when the crack occurs. Entropy and FCF methods are introduced to quantify the weak dynamic perturbations, which are caused by the strain concentration and/or crack breathing at the crack tip. A finite element model (FEM) of a welded beam subjected to the dynamic base motions is established for case studies to show the efficiency of the proposed smart coating and measurement methods. The effects of strain/stress concentration and crack breathing on the structural dynamic response are simulated by creating the nonlinear material property around the crack area and the contact pair of the crack walls, respectively. From simulations, both methods are found to be sensitive to the initiated closed crack. The Entropy method can detect a crack of 5% thickness of the beam thickness. Meanwhile, it is feasible and sensitive for both open and closed cracks detection. The FCF method can detect a closed crack with a size of 3% of the beam thickness. In addition, FCF is fast and efficient with no required data pre-progressing, like the filtering and smoothing functions, and can hence be used for real-time crack detection. Experimental validations are conducted for both methods, and the results prove high sensitivity and feasibility of both proposed crack detection methods.en_US
dc.description.noteOctober 2019en_US
dc.identifier.citationWang X and Wu N 2019 Crack identification at welding joint with a new smart coating sensor and entropy Mechanical Systems and Signal Processing 124 65-82en_US
dc.identifier.urihttp://hdl.handle.net/1993/34157
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectdamage detection, piezoelectric sensor, frequency response function, frequency comparison functionen_US
dc.titleCrack identification at the welding joint with a smart coating sensoren_US
dc.typemaster thesisen_US
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