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Weld monitoring, testing and analysis refers primarily to technological methods and actions to test or assure the quality of welds, and secondarily to technological methods to confirm the presence, location and coverage of welds.[original research?] In manufacturing, welds are commonly used to join two or more metal surfaces. Because these connections may encounter loads and fatigue during product lifetime, there is a chance that they may fail if not created to proper specification.

Weld testing and analysis

Methods of weld testing and analysis are used to assure the quality and correctness of the weld after it is completed. This term generally refers to testing and analysis focused on the quality and strength of the weld, but may refer to technological actions to check for presence, position and extent of welds.[citation needed] These are divided into destructive and non-destructive methods. A few examples of destructive testing include macro etch testing, fillet weld break tests, transverse tension tests, and guided bend tests. [1] Other destructive methods include acid etch testing, back bend testing, tensile strength break testing, nick break testing, and free bend testing. [2] Some non-destructive methods are fluorescent penetrate tests, magnaflux tests, eddy current (electromagnetic) tests, hydrostatic testing, tests utilizing magnetic particles, X-rays and gamma ray based methods and acoustic emission methods.[2] Other methods include ferrite testing and hardness testing.[2]

Imaging-based methods

X-ray

X-ray based weld inspection may be manual, done by an inspector on X-ray based images or video, or automated using machine vision.[citation needed]

Visible light imaging

Inspection may be manual, done by an inspector using imaging equipment, or automated using machine vision.[citation needed] Since the similarity of materials between the weld and the workpiece, and between good and defective areas provides little inherent contrast, the latter usually requires methods other than simple imaging.[citation needed]

One (destructive) method involves microscopic analysis of a cross section of the weld.[3]

Ultrasonic and acoustic based methods

Ultrasonic testing utilizes the principle that a gap in the weld changes the propagation of ultrasonic sound through the metal. One common method uses single probe ultrasonic testing involving operator interpretation of an oscilloscope-type screen.[4] Another senses using a 2D array of ultrasonic sensors.[4] Acoustic emission methods monitor for sound created bu the loading or flexing of the weld. [2]

Peel testing of spot welds

This method includes tearing the weld apart and measuring the size of the remaining weld.[4]

Weld monitoring

Weld monitoring methods are used to assure the quality and correctness of the weld during the process of welding. The term is generally applied to automated monitoring for weld-quality purposes and secondarily for process-control purposes such as vision-based robot guidance.[citation needed] Visual weld monitoring is also performed during the welding process.[citation needed]

On vehicular applications, weld monitoring has the goal of enabling improvements in the quality, durability, and safety of vehicles - with cost savings in the avoidance of recalls to fix the large proportion of systemic quality problems that arise from suboptimal welding.[citation needed] Quality monitoring in general of automatic welding can save production downtime, and can reduce the need for product reworking and recall.[citation needed]

Industrial monitoring systems encourage high production rates and reduce scrap costs.[5]

Transient thermal analysis method

Transient thermal analysis is used for range of weld optimization tasks.[6]

Signature image processing method

A WeldPrint analyzer, which uses SIP for the industrial analysis of weld quality

Signature Image Processing (SIP) is a technology for analyzing electrical data collected from welding processes. Acceptable welding requires exact conditions; variations in conditions can render a weld unacceptable. SIP allows the identification of welding faults in real time, measures the stability of welding processes, and enables the optimization of welding processes.

Development

The idea of using electrical data analyzed by algorithms to assess the quality of the welds produced in robotic manufacturing emerged in 1995 from research by Associate Professor Stephen Simpson at the University of Sydney on the complex physical phenomena that occur in welding arcs. Simpson realized that a way of determining the quality of a weld could be developed without a definitive understanding of those phenomena.[7][8][9] The development involved:

  1. a method for handling sampled data blocks by treating them as phase-space portrait signatures with appropriate image processing. Typically, one second's worth of sampled welding voltage and current data are collected from GMAW pulse or short arc welding processes. The data is converted to a 2D histogram, and signal-processing operations such as image smoothing are performed.[10]
  2. a technique for analyzing welding signatures based on statistical methods from the social sciences, such as principal component analysis. The relationship between the welding voltage and the current reflects the state of the welding process, and the signature image includes this information. Comparing signatures quantitatively using principal component analysis allows for the spread of signature images, enabling faults to be detected[11] and identified[12] The system includes algorithms and mathematics appropriate for real-time welding analysis on personal computers, and the multidimensional optimization of fault-detection performance using experimental welding data.[13] Comparing signature images from moment to moment in a weld provides a useful estimate of how stable the welding process is.[14][15] "Through-the-arc" sensing, by comparing signature images when the physical parameters of the process change, leads to quantitative estimates—for example, of the position of the weld bead.[16]

Unlike systems that log information for later study or that use X-rays or ultrasound to check samples, SIP technology looks at the electrical signal and detects faults when they occur.[17] Data blocks of 4,000 points of electrical data are collected four times a second and converted to signature images. After image processing operations, statistical analyses of the signatures provide quantitative assessment of the welding process, revealing its stability and reproducibility, and providing fault detection and process diagnostics.[18] A similar approach, using voltage-current histograms and a simplified statistical measure of distance between signature images has been evaluated for tungsten inert gas (TIG) welding by researchers from Osaka University.[19]

Industrial application

SIP provides the basis for the WeldPrint system (owned by the University of Sydney). WeldPrint was developed[according to whom?] with the assistance of an Australian government R&D Start grant (1999–2001), after support by the Australian Research Council for the fundamental research (1997–2001). The system consists of a front-end interface and software based on the SIP engine, and relies on electrical signals alone. It is designed to be non-intrusive and sufficiently robust to withstand harsh industrial welding environments. The first major purchaser of the technology, GM Holden[20][21][22] provided feedback that allowed the system to be refined in ways that increased its industrial and commercial value. Improvements in the algorithms, including multiple parameter optimization with a server network, have led to an order-of-magnitude improvement in fault-detection performance over the past five years.[when?]

The technology in use on the shop floor of Melbourne firm Unidrive, which used WeldPrint to monitor the quality of steering-column component welds in more than half a million Australian vehicles in the period 2001–2006

WeldPrint for arc welding became available in mid-2001. About 70 units have been deployed since 2001 - about 90% of them used on the shop floors of automotive manufacturing companies and of their suppliers. Industrial users include Lear (UK), Unidrive, GM Holden, Air International and QTB Automotive (Australia). Units have been leased to Australian companies such as Rheem, Dux, and OneSteel for welding evaluation and process improvement.

The WeldPrint software received the Brother business software of the year award (2001); in 2003, the technology received the A $100,000 inaugural Australasian Peter Doherty Prize for Innovation;[23][24] and WTi, the University's original spin-off company, received an AusIndustry Certificate of Achievement in recognition of the development.[citation needed]

SIP has opened opportunities for researchers to use it as a measurement tool both in welding[25] and in related disciplines, such as structural engineering.[26] Research opportunities have opened up in the application of biomonitoring of external EEGs, where SIP offers advantages in interpreting the complex signals[27]

See also

References

  1. ^ http://www.esabna.com/us/en/education/knowledge/weldinginspection/Destructive-Testing-of-Welds.cfm Destructive Testing of Welds by ESAB [unreliable source?]
  2. ^ a b c d http://www.angelfire.com/my/welding/test.html[unreliable source?]
  3. ^ http://www.clemex.com/pdf/reports/WeldingAnalysis692.pdf Welding Analysis - Image Analysis Report #692 Clemex Technologies Inc. [unreliable source?]
  4. ^ a b c http://www.nvlpubs.nist.gov/nistpubs/jres/109/2/j92den.pdf Spot Weld Analysis with 2D ultrasonic Arrays Journal of Research of the National Institute of Standards and Technology Volume 109, Number 2, March-April 2004 A.A. Denisov, C.M Shakarji, B.B. Lawforfd, R. Gr. Maev J.M Paille
  5. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1117/12.448639, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1117/12.448639 instead. "Reliable monitoring methods are essential for maintaining a high level of quality control in laser welding. In industrial processes, monitoring systems allow for quick decisions on the quality of the weld, allowing for high productions rates and reducing overall cost due to scrap."
  6. ^ http://www.ansys.net/ansys/papers/ARTICLE1.pdf Transient Thermal Analysis of Spot Welding Electrodes by K.S. Yeung and P.H. Thorton January 1999 Supplement to the Welding Journal, American Welding Society and the Welding Research Council
  7. ^ Simpson SW and Gillespie P (1998) "In-process monitoring of welding processes—a commercial success", Australasian Welding Journal, 43, 16–17
  8. ^ Simpson SW, Weld quality measurement, WIPO PCT WO9845078 (1998); US 6288364 (2001); Australia 741965 (2002); Europe (14 countries) 1007263 (2003); Canada 2285561 (2004); South Korea 0503778 (2005)
  9. ^ Simpson SW, Welding assessment, WIPO PCT WO0143910 (2001); Australia 763689, US 6660965 (2003); Canada 2393773 (2005); PAs: Japan 2001-545030 (2001); China 00817251.X, S. Korea 2002-7007624, India IN/PCT/2002/00740 2002), Brazil PI0016401-1, EU 00984649.4 (2002)
  10. ^ Simpson SW (2007) "Signature images for arc welding fault detection", Science & Technology of Welding and Joining, 12(6), 481–86
  11. ^ Simpson, SW (2007) "Statistics of signature images for arc welding fault detection", Science & Technology of Welding and Joining, 12(6), 557–64
  12. ^ Simpson SW (2008) "Fault identification in gas metal arc welding with signature images", Science & Technology of Welding and Joining, 13(1), 87–96
  13. ^ Simpson SW, "Statistics of signature images for arc welding fault detection", Science & Technology of Welding and Joining, 12(6), 557–64, 2007
  14. ^ Simpson SW (2008) "Signature image stability and metal transfer in gas metal arc welding", Science & Technology of Welding and Joining, 13(2), 176–83
  15. ^ Simpson SW (2009) "Automated fault detection in gas metal arc welding with signature images", Australasian Welding Journal – Welding Research Supplement, 54, 41–47
  16. ^ Simpson SW (2008) "Through The arc sensing in gas metal arc welding with signature images", Science & Technology of Welding and Joining, 13(1), 80–86
  17. ^ http://ats.business.gov.au/companies-and-technologies/building-and-construction/welding-technologies-innovations
  18. ^ Simpson, SW (2007) "Statistics of signature images for arc welding fault detection", Science & Technology of Welding and Joining, 12(6), 557–64
  19. ^ Matsubara T, Terasaki H, Otsuka H, and Komizo Y (2010) "Developments of real-time monitoring method of welding" (paper RAJU-VE1), Proceedings of the Visual-JW2010
  20. ^ "Holden orders award-winning weldprint welding technology", Techwatch, Price Waterhouse Coopers, 12(6), 2002,
  21. ^ "Holden purchases award winning weldprint welding technology", Australian Technology Showcase http://www.techshowcase.nsw.gov.au/ News and Events (2002)
  22. ^ "University weld checker to be used by Holden", Australian Innovation Magazine, 3–5/02, 29
  23. ^ "Bright sparks join forces to take out Doherty Prize", The Australian (national newspaper)—Higher Education Supplement, 2 April 2003
  24. ^ *"Weldprint Wins Award". Innovations. Radio Australia. 11 May 2003. Retrieved 19 January 2011.
  25. ^ Nguyen NT, Mai Y-W, Simpson SW and Ohta A (2004) “Analytical approximate solution for double-ellipsoidal heat source in finite thick plate”, Welding J, 83, 82s
  26. ^ The LH and Hancock GJ (2005) "Strength of welded connections in G450 sheet steel", J Struct Eng, 131, 1561
  27. ^ "Car plant technology has medical spin-off", UniNews, USyd, 34(1), 1 (2002)

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