Login | Register

Intelligent Eddy Current Current Crack Detection System Design Based on Neuro-Fuzzy Logic

Title:

Intelligent Eddy Current Current Crack Detection System Design Based on Neuro-Fuzzy Logic

Xu, Baoguang (2014) Intelligent Eddy Current Current Crack Detection System Design Based on Neuro-Fuzzy Logic. Masters thesis, Concordia University.

[img]
Preview
Text (application/pdf)
Xu_MASc_F2014.pdf - Accepted Version
4MB

Abstract

The purpose of this study is to develop an artificial intelligent eddy current crack detection system in collaboration with 6-Degree-of-Freedom (DOF) robotic arm in order to provide the end users with reliable crack information.
In this particular study, the main focus is on data fusion which includes signal filtering, signal feature extraction, feature recognition, and final decision making. Various features such as the amplitude, phase angle and width of the loop from the measured differential eddy current test (ECT) signals are extracted to represent the changes of the electrical impedance of the ECT probe due to crack presence. Furthermore, a data base has been built for the extracted features from the known notch cracks purchased from Olympus. An adaptive neuro-fuzzy inference engine is trained to map the complex and nonlinear relationship between the extracted features and the crack information. The experimental tests show that not only the developed intelligent system is able to extract signal features and provide the user with 1. defect presence, 2. predict the depth of unknown crack based on the trained fuzzy logic engine. In addition, in terms of experimental setup, a data acquisition system implemented with 6 DOF robot arm for ECT is established. Extra works such as coordinate calibration, prototype probe holder design, on-line crack position location detection has also been carried out.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science
Item Type:Thesis (Masters)
Authors:Xu, Baoguang
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical Engineering
Date:13 July 2014
Thesis Supervisor(s):Xie, Wenfang and Viens, Martin
ID Code:978748
Deposited By: BAOGUANG XU
Deposited On:04 Nov 2014 17:10
Last Modified:18 Jan 2018 17:47
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Back to top Back to top