Abstract
This paper presents a novel pattern recognition approach for a Non Destructive Test (NDT) for pipes. NDT is based on Macro Fibre Composites Transducers (MFC). The signals are analysed employing Wavelet Transforms (WT). WT is an optimum methodology for the detection and diagnosis of particular behaviors that is very effective for maintenance management in NDT of pipes. WT analysis is a windowing technique that allows the use of time intervals when more precise information is required. It leads to WT to be a powerful tool that can reveal characteristics of the signals as trends, breakdown points or self-similarities. In this paper a real case study is presented, where all possible combinations between signals are considered in order to find pattern recognitions. To achieve the results, signals are broken down by mathematical software based on wavelets principles. Similarities are found with an associated energy percentage for each decomposed signal exchanging the waveforms, levels of decomposition and border distortions.
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© 2013 Springer-Verlag London
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de la Hermosa González-Carrato, R.R., Pedro García Márquez, F., Dimlaye, V. (2013). Wavelet Transforms for Macro Fiber Composites Transducers. In: Xu, J., Yasinzai, M., Lev, B. (eds) Proceedings of the Sixth International Conference on Management Science and Engineering Management. Lecture Notes in Electrical Engineering, vol 185. Springer, London. https://doi.org/10.1007/978-1-4471-4600-1_15
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DOI: https://doi.org/10.1007/978-1-4471-4600-1_15
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Publisher Name: Springer, London
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