A suite of PC based automated TOFD interpretion algorithms have been benchmarked through a series of demonstration trials on both 80mm thick carbon steel submerged arc welded (SAW) testpieces, and 25mm thick carbon steel tungsten inert gas (TIG) welded testpieces. The range of intentionally implanted defects, from root cracks to lack of side wall fusion, were detected with an overall accuracy of 79% on a data set of 174 defects on scans performed at 10-90% weld completion. The trials were performed at the workshops of Nordon & CIE in France and attended by Mitsui Babcock Energy (responsible for ultrasonic data acqusisition), the Institut de Soudure (responsible for manual interpretation of data and subsequent destructive testing of the testpieces), EDF (external sponsors of the work), and the University of Surrey (developers of the software).

TOFD ultrasonic scans of the TIG and SAW testpieces was obtained at various stages of weld completion, typically before and after an intentional defect was implanted, using a MicroPlus system. The scans were mostly obtained during welding, though is some cases this was made impracticakl due to the loss of couplant between the TOFD transmitter and receiver probes and the workpiece surface, and also electromagnetic and electrical switching interference from other welding sources in the workshop. The effects of welding interference on ultrasonic sensors has been discussed recently by Bastos et al (1996) though at our trials we found that the encoder signal was affected much more than the actual ultrasonic signal.

rating	visibility defect	false alarm level
1	detected well	none
2	detected but distorted and/or fragmented	very few isolated or insignificant pixels
3	only partially detected but visible	significant false alarm
4	very poorly detected/obscured by noise	high level of false alarms obscuring defects
5	not detected	unacceptably high

Table 1 - Automatic defect detection and false alarm ratings used in the assessment of the ultrasonic scans

After acquisition each scan was processed by the automated software to locate defect and component echoes. The effectiveness of the automatic defect identification process has been measured using the rating system shown in Table 1 for both the visibility of the defect and the level of associated false alarms. The full effectiveness of the algorithms was quantified by a comparison using full destructive testing of the testpieces, as performed by the Institut de Soudure.

Analysis of the TIG testpieces

The TIG welded testpieces contained a total of 15 defects of 6 types. The defects are abbreviated as follows:

LOFS - lack of side-wall fusion
RC - root crack
P - porosity
LOP - lack of penetration
W - weld inclusion
LOIRF - lack of inter-run fusion.

Three sets of 1m long testpieces were manufactured by Nordon, denoted sample TIG A, TIG B, and TIG C. Defects were intentionally positioned along the length of each weld at various stages of weld completion. Ultrasonic TOFD was performed at approx.: 10, 25, 50, 75, 85 and 90% weld completion.


Table 2 - Results of the automated signal processing software for the detection of defects in the TIG welded testpieces.

From the manual conventional NDT of the welds it can be summarised that the defects present in the TIG testpieces are of the intentional type and are located at the intended location. However, extra unintentional defects are present and the conventional ultrasonics fails to detect several defects (detected by radiography).Table 2 shows the results of the automated signal processing software for the detection of defects in the TIG welded testpieces.

Analysis of the SAW testpieces

The SA welded testpieces contained a total of 15 defects of 6 types. The defects are abbreviated as follows:

LOFS - lack of side-wall fusion
RC - root crack
P - porosity
LOI - lack of root (inter-run) fusion
SI - slag inclusion
LOIRF - lack of inter-run fusion.


Three sets of 1m long testpieces were manufactured by Nordon. Defects were intentionally positioned along the length of each weld at various stages of weld completion. Ultrasonic TOFD was performed at various stages of completion for each testpiece, from: 25, 30, 40, 50, 75, 80 and 100% weld completion.


Table 3 - Results of the automated signal processing software for the detection of defects in the SAW welded testpieces.

From the manual conventional NDT of the welds it can be summarised that the defects present in the SAW testpieces are of the intentional type and are located at the intended location. However, extra unintentional defects are present and the conventional ultrasonics fails to detect several defects (detected by radiography). Table 3 shows the results of the automated signal processing software for the detection of defects in the SAW welded testpieces.

Summary

The results of automatic processing of the high temperature TIG and SA scans acquired during welding have been presented. Overall the automated defect detection algorithms worked very well, demonstrating that weld flaw detection during welding is possible using the ultrasonic time of flight diffraction (TOFD) method. It should be noted that the parameters of the interpretation software required some 'tuning' between scans of different resolutions due to the different spatial resolution occupied by the defect and the differing signal-to-noise of the ultrasonic signal. The poorest performance was with the incomplete TIG welded specimens where the small amount of weld present causes difficulties for the defect detection algorithms.

Table 4: overall detection rate in TIG samples

Table 5: overall detection rate in SAW samples

During the automatic TOFD demonstration trials 64 scans were attempted, with 42 being processed by the signal processing algorithms. The majority of the unprocessed scans were due to either the affects of interference from other workshop welding equipment upon the encoder wheel or the poor quality of the initial TIG scans. With development work the interference problems should be overcome through the use of adequate shielding of the encoder and its cables. Examining the detectability at the various levels of weld completion, Table 4 shows the percentage of defects which can be detected at 25, 50, and 85% completion of the TIG welds. It should be recognised that there were very few TIG scans at low levels of completion which were suitable for processing. Table 5 shows the percentage of defects which can be detected at 25, 50, 80 and 100% weld completion of the SAW welds, again when compared against the interpretation of the testpieces when using conventional NDT techniques.

This note has been taken from the forthcoming paper Bonser, G.R. and Lawson, S.W., Defect detection in partially complete SAW and TIG welds using the ultrasonic time of flight diffraction method, Proc of SPIE Int Symp on Nondestructive Evaluation Techniques for Aging Infrastructure and Manufacturing, San Antonio, Texas, March 1998.

For further information on this, and other automated inspection work, undertaken by the MSRR group contact: :-

Shaun Lawson
Mechatronic Systems and Robotics Research Group,
School of Mechanical and Materials Engineering,
University of Surrey, Guildford, Surrey, GU2 5XH, United Kingdom.
tel : (01483) 259681 fax: (01483) 306039
email: s.lawson@surrey.ac.uk

• NDTnet News issue 02/98: NDT Methods for Flaw Detection during Welding
  The final ultrasonic TOFD trials of the BRITE-EURAM II project 'NDT Methods for Flaw Detection During Welding' took place in Oct 1997.
  
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