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Early Detection of Defects through the Identification of Distortion Characteristics in Ultrasonic Responses

Author

Listed:
  • Pietro Burrascano

    (Dipartimento di Ingegneria, Università di Perugia, 06125 Perugia, Italy)

  • Matteo Ciuffetti

    (Dipartimento di Ingegneria, Università di Perugia, 06125 Perugia, Italy)

Abstract

Ultrasonic techniques are widely used for the detection of defects in solid structures. They are mainly based on estimating the impulse response of the system and most often refer to linear models. High-stress conditions of the structures may reveal non-linear aspects of their behavior caused by even small defects due to ageing or previous severe loading: consequently, models suitable to identify the existence of a non-linear input-output characteristic of the system allow to improve the sensitivity of the detection procedure, making it possible to observe the onset of fatigue-induced cracks and/or defects by highlighting the early stages of their formation. This paper starts from an analysis of the characteristics of a damage index that has proved effective for the early detection of defects based on their non-linear behavior: it is based on the Hammerstein model of the non-linear physical system. The availability of this mathematical model makes it possible to derive from it a number of different global parameters, all of which are suitable for highlighting the onset of defects in the structure under examination, but whose characteristics can be very different from each other. In this work, an original damage index based on the same Hammerstein model is proposed. We report the results of several experiments showing that our proposed damage index has a much higher sensitivity even for small defects. Moreover, extensive tests conducted in the presence of different levels of additive noise show that the new proposed estimator adds to this sensitivity feature a better estimation stability in the presence of additive noise.

Suggested Citation

  • Pietro Burrascano & Matteo Ciuffetti, 2021. "Early Detection of Defects through the Identification of Distortion Characteristics in Ultrasonic Responses," Mathematics, MDPI, vol. 9(8), pages 1-14, April.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:8:p:850-:d:535425
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    Cited by:

    1. Osman Taylan & Mohammad Amir Sattari & Imene Elhachfi Essoussi & Ehsan Nazemi, 2021. "Frequency Domain Feature Extraction Investigation to Increase the Accuracy of an Intelligent Nondestructive System for Volume Fraction and Regime Determination of Gas-Water-Oil Three-Phase Flows," Mathematics, MDPI, vol. 9(17), pages 1-15, August.

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