A State-of-the-Art Critique Review of the Role of Decision-Making Techniques in NDT for Condition Monitoring

A State-of-the-Art Critique Review of the Role of Decision-Making Techniques in NDT for Condition Monitoring

Ashish Khaira (Samrat Ashok Technological Institute, India) and Ravi K. Dwivedi (Maulana Azad National Institute of Technology, India)
DOI: 10.4018/978-1-5225-6989-3.ch011
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Nondestructive testing (NDT) is a vital tool in maintenance. Each NDT technique has some benefits and hindrances; therefore, the selection is crucial. Generally, the selection of a technique relies on operating personnel experience, and very few research papers shows uses of the decision-making (DM) approach. It was highlighted by various researchers that if a proper DM approach is used, it will save time and increase fault detection reliability. By keeping this fact in mind, this chapter is an attempt to provide a detailed review of research work from the year 2000-2018 that covered the role of DM techniques while making combinations of NDT for effective condition monitoring. It observed from the literature that very few researchers effectively utilized the power of DM tool. The researcher can use the outcome of this work as a beacon and improve it further.
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Review Of Role Of Decision Making Techniques In Ndts

This section covered the key extracts for the reviewed literature related to decision-making in NDTs. It covered the type of decision making techniques, domain & area of work etc.

D. Horn et al. (2000) investigated statistical methods for combining the results of two complementary inspection techniques, eddy-current and ultrasonic testing for Zr-Nb (2.5%) pressure-tube billets. The reliability of rejection/acceptance decisions based on combined information compared with that based on each inspection technique individually. Combination methods, ranging from a simple OR of individual decisions to more sophisticated data fusion algorithms, are assessed. This paper showed a comparison of the reliability of combined ET and UT measurements to that of each technique taken individually from a database of 108 artificial flaws. This paper also showed the use of probability density function for the likelihood that particular signal amplitude produced by a given phenomenon, such as a flaw of a specific depth, by a PDF which may be obtained from an analysis of the rates at which various signal amplitudes are produced from a narrow range of flaw sizes. The mean amplitude then corresponds to the average of the first moments of the flaw size distributions. An average, weighted by the widths, or second moments, of the flaw size distributions, brings still more a priori information into the decision process. The weighted average and variance is commonly taken as –

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