Surface cracks in metals and their characterization using Rayleigh waves

Over recent years there has been an increasing interest in the initial testing and in-service inspection of many engineering products, particularly in relation to items such as aircraft, oilrigs, pressure vessels and pipelines. (Thompson 1976, Lumb 1977) For this purpose a wide range of nondestructive testing techniques has been developed, for both defect location and sizing. these have included the use of X-rays, electromagnetic induction and dye penetration, with the addition, in recent years, of the increasingly important methods which use ultrasonic waves. There is a wide range of methods of ultrasonic testing which use the different types of elastic waves and display the resulting information in a variety of ways

Performance Evaluation of the FBG Sensing Device and Comparison with Piezoelectric Sensors for Acoustic Emission Detection

In-service structural health monitoring (SHM) of engineering structures has assumed a significant role in assessing their safety and integrity. As the most mature technique in fiber-optic field, Fiber Bragg Grating (FBG) sensors have emerged as a reliable, in situ and nondestructive tool for monitoring and diagnostics in large-scale structure. Main objectives of this work are to evaluate and compare the acoustic emission (AE) sensing characteristics simultaneously with FBG sensor array and piezoelectric (PZ) sensors. The pencil-lead-break (PLB) test, ball dropping test and the excitation from the PZ transducer are treated as the AE source which conducted on the platy and blocky structure respectively for acoustic wave. The source repeatability will be verified to choose the source with more stable performance. A commercial 4-channel FBG AE detection device was used to compare with the PZ sensor on the amplitude and frequency response which can indicate the sensitivity of the sensors. The low sensitivity and low sampling rate are the main issue for the engineering application of the FBG sensors. Besides, the sensitivity and directional dependence of the FBG sensor have been discussed. It shows that the encapsulation method of the FBG sensor will impact both of them significantly

Analysis of critically refracted longitudinal waves

Fabrication processes, such as, welding, forging, and rolling can induce residual stresses in metals that will impact product performance and phenomena such as cracking and corrosion. To better manage residual stress tools are needed to map their distribution. The critically refracted ultrasonic longitudinal (LCR) wave is one such approach that has been used for residual stress characterization. It has been shown to be sensitive to stress and less sensitive to the effects of the texture of the material. Although the LCR wave is increasingly widely applied, the factors that influence the formation of the LCR beam are seldom discussed. This paper reports a numerical model used to investigate the transducers\u27 parameters that can contribute to the directionality of the LCR wave and hence enable performance optimization when used for industrial applications. An orthogonal test method is used to study the transducer parameters which influence the LCR wave beams. This method provides a design tool that can be used to study and optimize multiple parameter experiments and it can identify which parameter or parameters are of most significance. The simulation of the sound field in a 2-D water-steel model is obtained using a Spatial Fourier Analysis method. The effects of incident angle, standoff, the aperture and the center frequency of the transducer were studied. Results show that the aperture of the transducer, the center frequency and the incident angle are the most important factors in controlling the directivity of the resulting LCR wave fields

NDE and SHM in the age of Industry 4.0

Condition based maintenance is now routinely applied to rotating machinery, with data transmitted wirelessly and reviewed automatically, to give a prognostic or remaining life estimate. The challenge is implementing integrated NDE/SHM strategies for structural assessment. However, advances in computer and communications technology, the internet of things and management of big data are starting to offer the digital infrastructure which can be combined with new sensor systems to enable SHM/prognostics to be applied to structural materials. Some challenges and opportunities which assess and demonstrate how NDE and SHM can potentially be revolutionized in the age of Industry 4.0 are outlined