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- W3017576761 abstract "Structural health monitoring (SHM) of components is becoming an important part of maintenance and component evaluation throughout many engineering industries. Evaluation of defects and damage plays an important role in reducing maintenance and testing costs, and thus has become an important part of the costs of businesses. In this work a nonlinear ultrasound subtraction techniques is proposed which looks to evaluate barely visible impact damage (BVID) in a composite structure using a sparse array of piezoelectric transducers. Evaluation of the elastic responses of composite structures can become difficult due to the complexity of these types of structures, with variations is attenuation, dispersion and fibre orientation. The method proposed looks to simplify damage detection without the calculation of time-of-arrival (TOA), dispersion curves and the frequency dependence of damage. The method relies on the excitation of the structure with three separate signals at both 0° and 180° degree phases. The three signals used are a single frequency, swept frequency and combination of both. The novelty of the method relies on a delay which is added between the signals, this delay is used to promote nonlinear ultrasonic interactions within the material. A hybrid modulation subtraction (HMS) method is then used to filter out linear components and retain the nonlinear modulated components in the signal. A sparse array of transducers and sensors are used to investigate a region with barely visible impact damage. The method does not rely on the a priori knowledge of wave velocity or the dispersion curves. The results show that it is possible to identify the defect region using the modulated nonlinear responses of the structure." @default.
- W3017576761 created "2020-05-01" @default.
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- W3017576761 date "2020-04-22" @default.
- W3017576761 modified "2023-10-16" @default.
- W3017576761 title "A nonlinear ultrasonic hybrid modulation subtraction method for structural health monitoring using sparse arrays" @default.
- W3017576761 doi "https://doi.org/10.1117/12.2559063" @default.
- W3017576761 hasPublicationYear "2020" @default.
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