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- W2967842629 endingPage "110650" @default.
- W2967842629 startingPage "110628" @default.
- W2967842629 abstract "The development in materials technology has produced stronger, lighter, stiffer, and more durable electrically insulating composites which are replacing metals in many applications. These composites require alternative inspection techniques because the conventional nondestructive testing (NDT) techniques such as thermography, eddy currents, ultrasonic, X-ray and magnetic particles have limitations of inspecting them. Microwave NDT technique employing open-ended rectangular waveguides (OERW) has emerged as a promising approach to detect the defects in both metal and composite materials. Despite its promising results over conventional NDT techniques, OERW microwave NDT technique has shown numerous limitations in terms of poor spatial resolution due to the stand-off distance variations, inspection area irregularities and quantitative estimation in imaging the size of defects. Microwave NDT employing OERW in conjunction with robust artificial intelligence approaches have tremendous potential and viability for evaluating composite structures for the purpose mentioned here. Artificial intelligence techniques with signal processing techniques are highly possible to enhance the efficiency and resolution of microwave NDT technique because the impact of artificial intelligence approaches is proven in various conventional NDT techniques. This paper provides a comprehensive review of NDT techniques as well as the prospect of using artificial intelligence approaches in microwave NDT technique with regards to other conventional NDT techniques." @default.
- W2967842629 created "2019-08-22" @default.
- W2967842629 creator A5050432910 @default.
- W2967842629 creator A5070795428 @default.
- W2967842629 creator A5077500785 @default.
- W2967842629 date "2019-01-01" @default.
- W2967842629 modified "2023-10-11" @default.
- W2967842629 title "Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review" @default.
- W2967842629 cites W115978284 @default.
- W2967842629 cites W1517228774 @default.
- W2967842629 cites W1681488479 @default.
- W2967842629 cites W1808644423 @default.
- W2967842629 cites W1933440764 @default.
- W2967842629 cites W1973770010 @default.
- W2967842629 cites W1993705000 @default.
- W2967842629 cites W1995274025 @default.
- W2967842629 cites W2017060721 @default.
- W2967842629 cites W2019328284 @default.
- W2967842629 cites W2020017954 @default.
- W2967842629 cites W2020399164 @default.
- W2967842629 cites W2031394302 @default.
- W2967842629 cites W2032574977 @default.
- W2967842629 cites W2039051707 @default.
- W2967842629 cites W2041674628 @default.
- W2967842629 cites W2050937193 @default.
- W2967842629 cites W2068754941 @default.
- W2967842629 cites W2094826374 @default.
- W2967842629 cites W2103384342 @default.
- W2967842629 cites W2111711808 @default.
- W2967842629 cites W2117698744 @default.
- W2967842629 cites W2129685038 @default.
- W2967842629 cites W2135928490 @default.
- W2967842629 cites W2151179524 @default.
- W2967842629 cites W2161969291 @default.
- W2967842629 cites W2166207675 @default.
- W2967842629 cites W2172622713 @default.
- W2967842629 cites W2244704669 @default.
- W2967842629 cites W2299055326 @default.
- W2967842629 cites W2300817297 @default.
- W2967842629 cites W2308318555 @default.
- W2967842629 cites W2316337463 @default.
- W2967842629 cites W2325859395 @default.
- W2967842629 cites W2326901388 @default.
- W2967842629 cites W2338755356 @default.
- W2967842629 cites W2346079081 @default.
- W2967842629 cites W2346915204 @default.
- W2967842629 cites W2487528369 @default.
- W2967842629 cites W2496789290 @default.
- W2967842629 cites W2501037751 @default.
- W2967842629 cites W2528113352 @default.
- W2967842629 cites W2547022318 @default.
- W2967842629 cites W2548221165 @default.
- W2967842629 cites W2578818152 @default.
- W2967842629 cites W2736248650 @default.
- W2967842629 cites W2751479287 @default.
- W2967842629 cites W2756177686 @default.
- W2967842629 cites W2763991458 @default.
- W2967842629 cites W2765608173 @default.
- W2967842629 cites W2777753262 @default.
- W2967842629 cites W2784032815 @default.
- W2967842629 cites W2788398366 @default.
- W2967842629 cites W2789966638 @default.
- W2967842629 cites W2791002084 @default.
- W2967842629 cites W2792193328 @default.
- W2967842629 cites W2793310054 @default.
- W2967842629 cites W2793321472 @default.
- W2967842629 cites W2798072988 @default.
- W2967842629 cites W2798930538 @default.
- W2967842629 cites W2803771634 @default.
- W2967842629 cites W2803869221 @default.
- W2967842629 cites W2810925282 @default.
- W2967842629 cites W2811122339 @default.
- W2967842629 cites W2883486562 @default.
- W2967842629 cites W2884106773 @default.
- W2967842629 cites W2885333330 @default.
- W2967842629 cites W2888055863 @default.
- W2967842629 cites W2890796842 @default.
- W2967842629 cites W2898834475 @default.
- W2967842629 cites W2899691698 @default.
- W2967842629 cites W2900087722 @default.
- W2967842629 cites W2900330699 @default.
- W2967842629 cites W2900996099 @default.
- W2967842629 cites W2902551404 @default.
- W2967842629 cites W2902704683 @default.
- W2967842629 cites W2903136512 @default.
- W2967842629 cites W2903794297 @default.
- W2967842629 cites W2908830316 @default.
- W2967842629 cites W2910875667 @default.
- W2967842629 cites W2911842137 @default.
- W2967842629 cites W2911964244 @default.
- W2967842629 cites W2912215394 @default.
- W2967842629 cites W2937924703 @default.
- W2967842629 cites W2947605871 @default.
- W2967842629 doi "https://doi.org/10.1109/access.2019.2934143" @default.
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