Time Of Flight Diffraction Technique Research Articles

Artificial Neural Network based Defect Detection of Welds in TOFD Technique

Time of Flight Diffraction Technique is one of the NDE methods, used in weld inspection to identify the weld defects. The classification of defects using the TOFD technique depends on the knowledge and experience of the operator. The classification reliability of defects detected by this technique can be improved by applying the Artificial Neural Network. In this work, four austenitic stainless steel weldments with defects viz, Lack of Fusion, Lack of Penetration, Slag, Porosity and one with out any Defect were fabricated. TOFD experiment is conducted on these weldments. Discrete wavelet transform based denoising methods were applied to denoise the resultant A scan signals. Time scale features are extracted from the denoised signals. A multi layer feed forward network with Resilient Back Propagation algorithm has been applied for classification of the signals. The number of hidden layers in the network are increased from 0 to 6. Various performance functions are also employed to achieve a better classification efficiency. The results are promising to proceed the automatic defect classification by TOFD technique.

Automatic Crack Detection and Characterization During Ultrasonic Inspection

The creation of a non-destructive technique that enables the automatic detection of defects is desirable, and TOFD (Time-Of-Flight Diffraction) technique is gaining rapid prominence due to its high accuracy in detecting, positioning and sizing flaws in steel structures. In this type of imaging, cracks are characterized using sets of hyperbolas, where summit positions correspond to crack tip positions. However, ultrasonic diffracted signals are often too low and difficult to distinguish from noise, and when large structures are inspected, the quantity of data can be extremely large, with the area of interest being very small in comparison to the image size. This paper describes a method that avoids the image formation, replacing it with a sparse matrix (as there is no reason to store and operate on an excessive number of zeros), and automates crack detection by analyzing the curve formed by the sparse matrix elements. The sparse matrix is formed using Split-Spectrum Processing, which enhances the signal-to-noise ratio. The Randomized Hough transform is then applied on the sparse matrix elements to detect the hyperbolas that characterize the crack defects.

Weld crack testing method using ultrasonic TOFD technique

In this paper, both the forward and inverse problems of crack testing using the ultrasonic time-of-flight diffraction (TOFD) B-scan mode are studied. For the forward problem, the propagation behaviour of the ultrasonic beam is described and the electrical and electromechanical elements of the inspection system are characterised using a system efficiency factor. Based on this, a crack testing model is established by employing Kirchhoff approximation theory. By using the model, the ultrasonic TOFD A-scan line is predicted and the B-scan foreground image is synthesised. For the inverse problem, in order to obtain lateral location and buried depth information about the crack in the weld, the B-scan image reconstruction is studied. According to the dynamic relationship between the probes and the crack tip in the course of B-scan testing, the synthetic aperture focusing (SAF) algorithm for image enhancement is developed. The results show that the simulated data are in good agreement with the measured data and the presented SAF algorithm can be validated by the simulation model. Processed by SAF, a high-resolution image can be obtained using transducers with poor sound directivity and lower frequency. In this way, measurements can be taken on the reconstructed image rapidly and with high accuracy.

A comparative evaluation of ultrasonic testing of AISI 316L welds made by shielded metal arc welding and gas tungsten arc welding processes

Ultrasonic testing of austenitic welds prepared by two different welding processes is studied in this paper. The two welding processes considered are shielded metal arc welding (SMAW) and gas tungsten arc welding (GTAW) and the ultrasonic testing technique used is time-of-flight diffraction (ToFD). Identical artificial flaws were implanted in both welds during the welding process. Austenitic characteristics consisting of grain orientation distribution and anisotropy show that the GTAW specimen is more isotropic than the SMAW due to the orientation of its grains. Moreover, comparison of echo amplitudes shows higher attenuation for the weld prepared by the GTAW process. The specimens were examined by the ultrasonic ToFD technique under identical conditions. B-scan images obtained from ToFD measurements of the two welds indicate that inspection of the specimen prepared by the SMAW process is easier than the one made by the GTAW process due to higher scattering of waves in the latter. The measurements also showed that the probe positioning is very important in the detection of diffracted echoes when using the ToFD technique.

Performance Evaluation Test of the Time-of-Flight Diffraction Technique for Welded Joints of Steel Bridges

Abstract Ultrasonic testing can be applied to welded joints of steel bridges following a revision of the Japanese Specifications for Highway Bridges. The time-of-flight diffraction (TOFD) technique and the pulse echo technique are possible testing methods. However, the efficiency of the TOFD technique for steel bridges has until now not been investigated completely. A round robin test project using testing systems of several different companies was organized by the Ministry of Construction for this purpose. The performance of each participant system was evaluated and applicability of the TOFD technique was investigated.

Simulation of the TOFD technique using the finite element method

The ultrasonic Time-of-Flight Diffraction (TOFD) technique is a well-known technique for defect sizing. This technique has been applied to thick sections (>15 mm). The application of the TOFD technique to thin sections like pressure vessels and piping requires simulation of this technique. Simulation gives ideas about the expected results from experiments where real experiments are not possible or are difficult to conduct. Further, simulation helps us to derive the optimum choice of experimental parameters. This paper discusses the application of the finite element technique to simulate the ultrasonic time-of-flight diffraction (TOFD) technique. The diffracted and reflected signals in TOFD techniques for vertical and inclined defects were simulated using plane strain elements. The simulated results are compared with the experimental observations. FEM simulation of wave propagation in complex joints such as a T-joint with embedded flaws is also discussed.

The use of artificial neural network in the classification of pulse-echo and TOFD ultra-sonic signals

The present work evaluates the application of artificial neural networks for pattern recognition of ultrasonic signals using pulse-echo and TOFD (Time of Flight Diffraction) techniques in weld beads. In this study pattern classifiers are implemented by artificial neural network of backpropagation type using MATLAB®. The ultrasonic signals acquired from pulse-echo and TOFD were introduced, separately, in the artificial neural network with and without preprocessing. The preprocessing was only used to smoothen the signal improving the classification. Four conditions of weld bead were evaluated: lack of fusion (LF), lack of penetration (LP), porosity (PO) and non-defect (ND). The defects were intentionally inserted in a weld bead of AISI 1020 steel plates of 20 mm thickness and were confirmed using radiographic tests. The results obtained show that it is possible to classify ultrasonic signals of weld joints by the pulse-echo and TOFD techniques using artificial neural networks. The results showed a performance superior a 72% of success for test. Although the preprocessing of the signal improved the classification performance of the signals acquired by the TOFD technique considerably, the same didn't happen with the signals acquired by the pulse-echo technique.

Welding defect pattern recognition in TOFD signals Part 1. Linear classifiers

The time-of-flight diffraction (TOFD) technique has been widely used for automatic weld inspection. Despite the high speed of inspection high reliability in sizing and the low rate of false indications, the classification of defects obtained by the TOFD technique is still frequently questioned since it depends mainly on the knowledge and experience of the operator. This dependence on the operator has led to attempts to automatically classify the defects detected during inspection and neural networks are powerful tools that can he used for this objective. The use of non-linear classifiers to improve the performance reached by linear classifiers, presented in previous works, is the main objective of this work. A-scan signals were obtained during the inspection of test samples containing well-controlled weld defect previously characterised by X-rays. After the inspection, the signals were divided into three classes; according to the type of defect found (lack of fusion, lack of penetration and porosity). Another class of signal was acquired from regions with no defects. Non-hierarchical and hierarchical non-linear classifiers, implemented by an artificial neural network, were used in the classification of these signals. The backpropagation learning rule was used to train the neural network. The performance of these two different classifiers was evaluated and compared. The non-linear classifiers had good results in the recognition of welding defect patterns of TOFD signals. The rate of success reached 100% and 98% for training and test respectively, against 99% and 96% for the linear classifiers, which were obtained in the last works.

Industrial Applications of Ultrasonic Time-of-Flight-Diffraction(TOFD) Techniques for Various Field Targets

The ultrasonic time-of-flight-diffraction (TOFD) technique has been used mainly to detect and precisely size flaws in welded butt joints. But industrial applicability of the conventional TOFD technique is restricted due to inspection targets’shape complexity and ultrasonic noise. In order to increase the applicability of the TOFD technique for real industrial targets, various improved TOFD techniques have been developed. In this paper, industrial applications and limitations of the conventional TOFD technique and newly developed TOFD technologies, which can overcome those limitations, are presented.

Crack Initiation, Propagation, and Arrest in 316L Model Pipe Components under Thermal Fatigue

Abstract There is a continuing need for reliable thermal fatigue analysis tools to ensure that high safety levels are maintained in the main coolant lines of light water reactors. As a contribution to this effort, a combined experimental and numerical investigation has been conducted on cylindrical components of 316L stainless steel subjected to cyclic thermal shocks of varying intensity. It exploits a dedicated rig in which the tubular test pieces are subjected to induction heating and water quenching. Under the applied loading, a network of cracks initiates at the inner surface; some of these propagate further through the wall thickness. The number of cycles to crack initiation is estimated from surface replicas taken during intermittent stops, whereas the crack depth of fatigue cracks is measured using an ultrasound time of flight diffraction technique (TOFD). The analysis is done by a sequentially coupled thermal-stress finite element analysis using a cyclic plasticity model. Predictions of the crack initiation life (based on crack initiation curves as well as crack propagation models for microstructurally short cracks) are in good agreement with the test results. Crack propagation for small fatigue cracks was estimated by plastic strain amplitude based propagation formulas, whereas long crack propagation is analyzed by Paris law type criteria using ΔK as well as ΔCTOD.

Pattern Recognition of Weld Defects in Preprocessed TOFD Signals Using Linear Classifiers

The TOFD (“Time of Flight Diffraction”) technique is being widely used for automatic weld inspection, especially in the petrochemical industry, where welding quality is essential to avoid productivity losses. Although it provides high speed inspection, high sizing reliability and low rate of false defect indications, the classification of defects using ultrasound signals generated by the TOFD technique is still frequently questioned, because it depends heavily on the knowledge and experience of the operator. However, the use of computational tools for signal preprocessing and pattern recognition, such as the artificial neural networks, improves the classification reliability of defects detected by this technique. In this present work, three kinds of defects: lack of fusion (LF), lack of penetration (LP) and porosity (PO) were inserted into the specimens durin the welding process, generating pattern defects. The position, type and dimension of each inserted defect were recorded using conventional ultrasonic and radiographic techniques. The Fourier Transform and Wavelet Transform were used for preprocessing A-scan signals acquired during weld inspection by TOFD technique. This study was able to show the versatility of Wavelet Transform to preprocess these kinds of signals, since the correct scale in Continuous Wavelet Transform had been selected to supply a neural network. Hierarchical linear classifiers were implemented into the neural network in order to distinguish the main defects in welded joints detected by the TOFD technique. The results show the good success rate of welding defect recognition in preprocessed TOFD signals, mainly using Wavelet Transform. On the whole, the results obtained were very promising and could give relevant contributions to the development of an automatic system of detection and classification of welding defects inspected by the TOFD technique.

Time-of-flight diffraction (TOFD) technique for accurate sizing of cracks embedded in sub-cladding

This paper deals with an experimental study for evaluation of the TOFD technique for determination of size of cracks embedded in sub-cladding. It extends the results presented in the previous papers ( 1 , 2 ) . The studywas confined to simulated cracks (machined slits) underneath the cladding. It was found that crack heights ranging from 1.68 mm to 19.04 mm underneath stainless steel, Inconel and ferritic cladding could be sized with an accuracy of ′0.2 mm. Difficulty was experienced using TOFD to size cracks starting from the interface between Inconel/stainless steel cladding and the ferritic base ie (5 mm/6 mm below the scanning surface). However, these cracks could be detected and sized by scanning through the cladding from the opposite surface of the blocks. Even the small cracks of the order of 1.9 mm could be detected as long as they are not influenced by the lateral wave. Experimental errors are presented.

Time-of-flight diffraction (TOFD) technique for accurate sizing of surface-breaking cracks

This paper deals with an experimental study for evaluation of TOFD technique for determination of size of the surface breaking cracks. The study was confined to simulated cracks. The steel test blocks used for the study contained 0.5mm wide vertical slits of various heights ranging from 0.91mm to 30mm. Another set of blocks contained inclined slits (10°, 15°) inclination of various heights ranging from 2.56mm to 19.82mm. Both the vertical and inclined slits were opened to the top surface. TOFD equipment Model MICROPLUS of M/S AEA Technology, UK with manual scanner along with longitudinal angle beam probes of 45° - 4MHz were used for the study. The blocks were scanned along the slits / defects and across the slits. The scanned images were analysed for the sizing. The results of the study indicated an average error of ±0.13 for depth in vertical slits and ±0.05 for inclined slits whereas the average error in length measured was ±0.36mm for vertical slits and ±0.29mm for inclined slits. However difficulty was experienced using TOFD to size defects extending less than about 2mm depth. This is due to the presence of the lateral wave, which obscures the tip-diffracted signals from the defects close to the surface and also due to the inherent lack of time resolution near the surface.

A quality assurance technique for resistance spot welding using a neuro-fuzzy algorithm : S.R. Lee, Y.J. Choo, T.Y. Lee, M.H. Kim, S.K. Choi, v20, n5, 2001, pp320–328

Ultrasonic testing of austenitic welds prepared by two different welding processes is studied in this paper. The two welding processes considered are shielded metal arc welding (SMAW) and gas tungsten arc welding (GTAW) and the ultrasonic testing technique used is time-of-flight diffraction (ToFD). Identical artificial flaws were implanted in both welds during the welding process. Austenitic characteristics consisting of grain orientation distribution and anisotropy show that the GTAW specimen is more isotropic than the SMAW due to the orientation of its grains. Moreover, comparison of echo amplitudes shows higher attenuation for the weld prepared by the GTAW process. The specimens were examined by the ultrasonic ToFD technique under identical conditions. B-scan images obtained from ToFD measurements of the two welds indicate that inspection of the specimen prepared by the SMAW process is easier than the one made by the GTAW process due to higher scattering of waves in the latter. The measurements also showed that the probe positioning is very important in the detection of diffracted echoes when using the ToFD technique.

PISC II parametric study on flaw characterisation using the tandem and TOFD techniques

Studies on the effect of flaw characteristics and selected inspection parameters on the detection and sizing of flaws in ferritic steel blocks have been performed by the United Kingdom Atomic Energy Authority (UKAEA) as part of a larger Commission of the European Communities (CEC) Parametric Study programme. The techniques included in the UKAEA studies were the 45° tandem and the time-of-flight diffraction (TOFD) techniques. The purpose of the work was to acquire reliable experimental data that could be used both to test and verify theoretical models and to contribute to the resolution of anomalies encountered in PISC round-robin inspection exercises. Thirteen test blocks, fabricated by JRC, Ispra, were selected for the UKAEA studies with flaws covering a range of shapes, sizes, roughnesses and orientations. Beam-skew has a pronounced effect on signal amplitude for the tandem technique, with tilt angle having a significant but smaller effect. The signals from ‘rough flaws’ exceed those from smooth defects for skew angles of 5° to 10°. The TOFD technique proved less sensitive to skew and sized flaws to better than 2 mm. However, limitations in its range of application demonstrate the need for diversity in techniques for flaw sizing.