Nondestructive inspection (NDI) based on ultrasound is widely used. A relatively recent development for industrial applications is the use of ultrasonic array technology. Here, ultrasonic beams generated by array transducers are controlled by a computer. This makes the use of arrays more flexible than conventional single-element transducers. However, the inspection techniques have principally remained unchanged. As a consequence, the properties of these techniques, as far as characterization and sizing are concerned, have not improved. For further improvement, in this paper we apply imaging theory developed for seismic exploration of oil and gas fields on the NDI application. Synthetic data obtained from finite difference simulations is used to illustrate the principle of imaging. Measured data is obtained with a 64-element linear array (4 MHz) on a 20-mm thick steel block with a bore hole to illustrate the imaging approach. Furthermore, three examples of real data are presented, representing a lack of fusion defect, a surface breaking crack, and porosity

Inverse wave field extrapolation: a different NDI approach to imaging defects

NDT inspection of an austenitic weld between two CRA Clad pipes (2) using a phased ultrasonic transducer array system (8a, 8b) is described. The method may be performed during laying of gas/oil fatigue sensitive pipelines, for example, at sea. Two types of UT inspection may be generated simultaneously by a Phased Array on each side (Upstream and Downstream) of a girth weld. Firstly, mode converted longitudinal waves are used. These waves have properties that they propagate well. Shear waves (10) are also used. The combination of these two ultrasonic waves, with the addition of surface waves (7), enables 100% of the girth weld to be inspected to the standard required in fatigue sensitive welds, such as Steel Catenary Risers. Shear waves (10) and compression waves are emitted substantially contemporaneously. Defects may be detected and measured using time of flight information and amplitudes of radiation detected on reflection and on diffraction from the defect.

A method for testing pipeline welds using ultrasonic phased arrays

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.

http://www.scielo.br/pdf/jbsmse/v27n4/26954.pdf

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

Provided is an ultrasonic flaw detecting method, in which an angle probe is arranged on the outer face of a welded steel pipe, such that the propagation direction of a transverse-wave ultrasonic beam in the welded steel pipe may be substantially perpendicular to the longitudinal direction of a weld beam and such that the transverse ultrasonic beam having a deflection angle of 40 degrees or more and less than 55 degrees may propagate to that one of the two toes of the weld beam in the inner face of the welded steel pipe, which is less distant from the angle probe. The flaw of the welded steel pipe is detected by the angle probe arranged, so that it is decided on the basis of the flaw detection result whether or not the toes of the inner face extending from the toes to the inside of the mother material and inclined in the radial direction of the welded steel pipe to the side opposite to the weld bead are cracked. As a result, it is possible to improve the detecting performance of that cracking of the inner face toes, which occurs at the toes of the weld bead on the inner face of the welded steel pipe.

Ultrasonic flaw detecting method, manufacturing method for welded steel pipe, and ultrasonic flaw detecting apparatus

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.

Welding defect pattern recognition in TOFD signals. Part 2. Non-linear classifiers

As an alternative to radiography, afield-proven mechanised ultrasonic inspection system, is discussed. Called 'Rotoscan', this system has been developed for inspection of girth welds during construction of long-distance pipelines, both on- and offshore. The system is characterised by high inspection speed and instant recording of results. Unlike radiography, it provides immediate feedback to the welders. Recent technical improvements in flaw sizing and recording have allowed the application of rejection/acceptance criteria of weld defects based on fracture mechanics. The development and actual use of such modern acceptance criteria support the introduction of mechanised UT Worldwide applications proved that, contrary to expectations, ultrasonic inspection does not lead to higher weld repair rates than radiography. Between early 1989 and now, over 5000 km of pipeline (400,000 welds) were inspection by our organisation. Recent introduction of C-scan mapping enable the system to cope with most existing UT procedures and acceptance criteria, because of its capability to detect and quantify volumetric defects. Moreover, the integrated simultaneous TOFD function enables defect height estimation. The present system is capable of achieving a high Probability OfDetection (POD) together with a low False Call Rate (FCR). In the meantime, Rotoscan has been qualified in various countries, for different customers and for a variety of weld processes, pipe diameters and wall thicknesses. Because of its features, the now mature system has demonstrated its capabilities also for use on lay barges as an alternative to high-speed radiography.

Mechanised UT on girth welds during pipeline construction : a mature alternative to radiography

This month`s article provides an inspection solution for the inspection of girth welds found in long-distance pipelines. The mechanization of the process increases the speed of the inspection and also improves the probability of detection. This article may trigger ideas and solutions where mechanizing the inspection process can provide significant benefits.

Mechanized ultrasonic testing on girth welds during pipeline construction

After many decades of application, industry has completely accepted NDT as an inevitable but invaluable part of production and maintenance of components. Its application has been well-regulated, acceptance criteria for weld defects exist, good schemes for personnel qualification are in place and equipment has evolved to a standard of near-perfection. NDT has become a commodity. Pioneering years are over. However, such a situation implies a risk. Industry tends to cut costs on commodities such as NDT, especially when they are needed because the code says so. And therefore NDT costs are under pressure, and competition is heavy. This paper will highlight some NDT applications whereby NDT can be transformed from a 'necessary evil' into a situation that is 'of added value'to the user. Thus NDT can move from an activity that has to be done because it is required by the code, to a solution to a problem that can improve safety, enhance quality and save money. Examples will cover maintenance inspection such as corrosion detection in piping and tanks, and also routine weld inspection. The need for acceptance criteria for weld defects adapted for modern NDT techniques will be highlighted, because these form (in many cases) the key to benefit. Last but not least, new methods will be discussed which contribute to NDT as being a benefit.

F. H. Dijkstra

Papers

Mechanised UT on girth welds during pipeline construction : a mature alternative to radiography

Mechanized ultrasonic testing on girth welds during pipeline construction

NDT: Necessary evil or benefit?

Time of flight diffraction and acceptance criteria : A perfect team

Ultrasonic weld inspection of clad materials