الفهرس | Only 14 pages are availabe for public view |
Abstract Welded joints are used in many industries and its failures are due to inaccurate determination, sizing, measuring and evaluation of their discontinuities. The reliable detection of discontinuities is one of the most important tasks in nondestructive tests. Phased Array Ultrasonic Test (PAUT) offers significant technical advantages for weld inspections over conventional ultrasonic and Radiography Test (RT). The PAUT beams can be steered, scanned, swept and .~ focused electronically which improve the accuracy and quantitative characterization of locating discontinuities. from the experimental work, the discontinuities length and depth measuring accuracy improved by 70%, 40% & 50% by doubling the frequency, number of piezoelectric elements and probe pitch respectively. The proposed system named Phased Array for characterizing Discontinuities ”PACD” transform 20 S-scan images into 3D images (volumetric scan) which is more reliable, accurate and easily interpretation. The system is also checking the circularity, rectangularity and irregularity of each discontinuity and determine the location and calculate the width, length of each discontinuity and the echo width and height of the A-scan. After that PACD input learned artificial neural network (ANN) to characterize 12 types of common welding discontinuities (toe crack, root crack, transverse crack, cluster porosity, lack of penetration, porosity, burn through, root undercut, longitudinal crack, cap undercut and slag). After verification the PACD system can be easily characterized welding discontinuities types with high accuracy. Keywords: Ultrasonic Test (UT), Phased Array (PA) Technique, Welding Discontinuities & Artificial Neural Network (ANN). |