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Efficient Algorithm for Frequency Estimation Used in Structural Damage Detection

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Proceedings of the 13th International Conference on Damage Assessment of Structures

Abstract

In damage detection processes, the accuracy of estimating the eigenfrequencies of structures is crucial because the frequencies are not highly sensitive to damage. This paper analyses the accuracy of the Discrete Fourier Transform when estimating the frequency and amplitude of sine waves, identifies its limitations and proposes an algorithm to significantly improve the attained results. Standard methods used to evaluate the eigenfrequencies fail because the results depend on the position of the spectral lines, which are related to the acquisition time. Frequently, interpolation involving the amplitude peaks displayed on several spectral lines located around the maximizer is employed to improve the frequency readability. The estimated results are improved indeed, but the achieved precision still depends on the acquisition time. We develop an algorithm that uses the maximizer of signals with different time lengths, which are obtained from the original acquired signal by cropping. The three selected maximizer are used for parabolic interpolation input data. The maximum of the regression curve represents a precise estimate of the amplitude, associated with the true frequency of the targeted harmonic component. The efficiency of the algorithm is demonstrated for harmonic and multi-harmonic signals.

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Correspondence to Dorian Nedelcu or M. Abdel Wahab .

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Gillich, GR., Nedelcu, D., Malin, CT., Biro, I., Abdel Wahab, M. (2020). Efficient Algorithm for Frequency Estimation Used in Structural Damage Detection. In: Wahab, M. (eds) Proceedings of the 13th International Conference on Damage Assessment of Structures. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-8331-1_20

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  • DOI: https://doi.org/10.1007/978-981-13-8331-1_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8330-4

  • Online ISBN: 978-981-13-8331-1

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