A State of Art Critique Review of Role of Optimization in NDTS for Effective Condition Monitoring

A State of Art Critique Review of Role of Optimization in NDTS for Effective 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.ch009


Nondestructive testing (NDT) techniques play a pivotal role in a condition-based monitoring system. Generally, using an optimization technique for optimizing the available solution gives added advantage. By keeping this fact in mind, this chapter is an attempt to provide a detailed review of research work from 2000-2018 that covered the role of optimization for effective condition monitoring using NDTs. It was observed from literature that little work found related to NDT process optimization. The researcher and practitioner can use the outcome of this work as a beacon and improve it further.
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Review Of Optimization Techniques In Ndts

The following section covers more than a decade research and the contribution of different researchers in the field of NDTs by using optimization techniques.

Zhongqing Su et al. (2006) comprehensively reviewed lamb wave-based damage identification methodology for composite structures, addressing the advances and achievements in these techniques in the past decades using forward (direct) algorithm, Inverse algorithm (General inverse approaches, Artificial intelligence, Tomography) etc. Major importance is given to the unique characteristics and mechanisms of Lamb waves in laminated composites; approaches in wave mode selection, generation and collection. Furthermore, it was needed to select appropriate lamb modes in terms of identification of individual types of damage. The excitation frequency, waveform, cycle number and other signal characteristics should be comprehensively considered during mode selection and diagnostic waveform design. Undesired modes can only be suppressed rather than completely eliminated. The multi-mode purification is an intriguing but challenging issue. Damage identification is normally a typical yet complex inverse pattern recognition problem and cannot be effectively solved by traditional logic approaches. Detecting multiple damages is another issue worthy of investigation. The use of Lamb waves seems more viable than other tools for its exclusive responses to different damage status, but more complex scattering phenomena complicate the lamb wave signal interpretation, and distinguishing such signals remains problematic.

Z. Hameeda et al. (2009) reviewed different techniques, methodologies and algorithms, including Global Fault Detection System, Artificial intelligence, FDI (fault detection and isolation), Recursive isolation developed to monitor the wind turbine performance as well as an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. The bicoherency or the skewness function, or simply the bicoherence is:

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