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Extraction of vibration parameters from optical feedback interferometry signals using wavelets.

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    This study introduces wavelet transform for optical feedback interferometry (OFI) signal analysis, enabling precise detection of physical motion and fringe analysis. The novel algorithm achieves high accuracy in displacement sensing and vibration measurement.

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    Area of Science:

    • Optical physics
    • Signal processing
    • Metrology

    Background:

    • Optical feedback interferometry (OFI) is sensitive to minute physical displacements.
    • Traditional analysis methods can struggle with noise and speckle, limiting precision.
    • Retrieving precise motion data from OFI signals requires advanced signal processing techniques.

    Purpose of the Study:

    • To propose and validate the wavelet transform for fringe detection and analysis in OFI signals.
    • To develop a novel algorithm for simultaneous time-frequency processing of OFI data.
    • To enhance the accuracy of nanometric displacement sensing and vibration analysis.

    Main Methods:

    • Application of wavelet transform for fringe detection in OFI signals.
    • Development of a novel algorithm for simultaneous time and frequency domain processing.
    • Utilizing a complex Morlet wavelet for time-envelope analysis of OFI signals.

    Main Results:

    • Precise fringe detection and amplitude feature extraction with errors as low as 0.1λ.
    • Successful nanometric displacement sensing without direction ambiguity.
    • Accurate measurement of vibration frequency, velocity, and detection of non-periodic events.

    Conclusions:

    • Wavelet transform is a powerful technique for OFI signal analysis, improving precision and robustness.
    • The novel algorithm enables high-accuracy retrieval of physical motion phenomena.
    • This approach broadens the application scope of OFI in metrology and sensing.