Wavelet Transforms for Macro Fiber Composites Transducers
العنوان: | Wavelet Transforms for Macro Fiber Composites Transducers |
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المؤلفون: | Fausto Pedro García Márquez, Vichaar Dimlaye, Raúl Ruiz de la Hermosa González-Carrato |
المصدر: | RUIdeRA. Repositorio Institucional de la UCLM instname Lecture Notes in Electrical Engineering ISBN: 9781447145998 |
بيانات النشر: | Springer, 2012. |
سنة النشر: | 2012 |
مصطلحات موضوعية: | Engineering, business.industry, Wavelet transform, Transforms, Signal, Wavelet, Transducer, Nondestructive testing, Pattern recognition, Pattern recognition (psychology), Macro, Composite material, business, Maintenance management, Energy (signal processing), Macro fibre composites transducers |
الوصف: | 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. |
وصف الملف: | application/pdf |
ردمك: | 978-1-4471-4599-8 |
الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1195b1d2ae06b6e91ca3c021924b6a0Test http://hdl.handle.net/10578/14992Test |
حقوق: | OPEN |
رقم الانضمام: | edsair.doi.dedup.....d1195b1d2ae06b6e91ca3c021924b6a0 |
قاعدة البيانات: | OpenAIRE |
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