Time-of-flight diffraction ultrasonics

About: Time-of-flight diffraction ultrasonics is a research topic. Over the lifetime, 544 publications have been published within this topic receiving 3189 citations.

T-shaped welded joint TOFD (Time of Flight Diffraction) detection comparison test block

Abstract: A T-shaped welded joint TOFD (Time of Flight Diffraction) detection comparison test block is suitable for the check of an instrument during T-shaped welding seam TOFD detection The comparison test block is formed by cutting a steel board according to the practical welding angle dimension line of a checked welding seam, the thickness of the steel board is greater than the width of a TOFD probe wedge, three through holes being Phi 2 mm in diameter are located in a simulated T-shaped joint region of the comparison test block from top to bottom, which are used for identifying the covering of a TOFD detection acoustic beam, and meanwhile used for regulating the detection sensitivity The comparison test block is easy to process, convenient to carry, and can fully satisfy the T-shaped welding seam TOFD detection demand

Influence of Surface Condition on the Inspection of Steel Bridge Elements Using the Time-of-Flight Diffraction Method

Abstract: Prior studies on the time-of-flight diffraction (TOFD) method have focused primarily on ground smooth, clean surfaces of steel. In practice, however, the surface of an existing bridge element will be covered with rust or have several layers of paint. The main objective of this study was to evaluate the influence of the surface condition of steel elements (i.e., painted or rusted) on the ability of the method to accurately detect and size flaws. These objectives were met by performing a number of tests on plates with saw cuts or implanted fatigue cracks with different surface conditions. These included ground smooth and polished, rusted, and painted surfaces. The data show that rusted surfaces will reduce the amplitude of the ultrasonic signals, but they will not impair the ability of the TOFD method to detect and accurately size flaws. A painted surface will also cause a reduction in signal amplitude. More important, however, is the appearance of additional wave signals that could be interpreted as false indications. While these additional signals do not obscure the presence of actual flaws or affect the accuracy of the TOFD method to size the flaws, they make flaw detection more difficult. Based on the results of this study, recommendations for field inspection on rusted or painted surfaces using the TOFD method are provided.

Crack development monitoring method and its device by ultrasonic tofd method

Abstract: PROBLEM TO BE SOLVED: To provide a crack development monitoring method by ultrasonic TOFD (Time of Flight Diffraction) method and its device for accurately measuring a crack depth while an installation is operated and automatically monitoring the development of the crack. SOLUTION: Data on the change of propagation velocity of ultrasonic longitudinal wave with temperature in a specimen 1 are previously stored in a data storage means 5. When a data processing means 7 calculates a crack depth in the specimen 1 from measured data by the TOFD method, the propagation velocity of ultrasonic longitudinal wave corresponding to the temperature of the specimen 1 in measuring is acquired for use from the data on the change stored in the storage means 5. COPYRIGHT: (C)2006,JPO&NCIPI

Acousto-optic method for nondestructive testing

Abstract: An alternative method for nondestructive testing based on light diffraction by ultrasonic waves is presented. It enables us to make more accurate measurements of intensity and phase of reflected waves, and therefore detailed information about the reflecting system can be obtained. Applications are numerous but special attention is payed to examination of the quality of coupling systems.

Neural Networks to Select Ultrasonic Data in Non Destructive Testing

Abstract: In recent years, research concerning the automatic interpretation of data from non destructive testing (NDT) is being focused with an aim of assessing embedded flaws, quickly and accurately in a cost effective fashion. This is because data yielded by NDT techniques or procedures are usually in the form of signals or images which often do not present direct information of the structure’s condition. Signal processing has provided powerful techniques to extract the desired information on material characterization and defect detection from ultrasonic signals. The imagery available can add additional and significant dimension in NDT information. The task of this work is to minimize the volume of data to process replacing ultrasonic images type TOFD by sparse matrix, as there is no reason to store and operate on a huge number of zeros, especially when large structures are inspected. A combination of two types of neural networks, a perceptron and a Self Organizing Map (SOM) of Kohonen is used to distinguish between a noise signal from a defect signal in one hand, and to select the sparse matrix elements which correspond to the locations of the defects in the other hand. This new approach to data storage will provide an advantage for the implementations on embedded systems as it allows the normalization of the sparse matrix by fixing its dimension.