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• W4210241297 endingPage "108879" @default.
• W4210241297 startingPage "108879" @default.
• W4210241297 abstract "Experimental Modal Analysis (EMA) allows to assess the dynamical properties of a mechanical component or structure by estimating the modal parameters. Whereas EMA is usually based on local accelerometers or laser vibrometer data, in this paper we focus on camera-based EMA as cameras offer full field and contact-less data. However, besides few very specific controlled cases, camera-based EMA is limited by the low frame rate of the camera in comparison to accelerometers and vibrometers. In this paper we propose a novel acquisition scheme that allows to estimate modal parameters above the Nyquist–Shannon limit (i.e., half of the camera frame rate) by employing a random sampling scheme in time in combination with one accelerometer. With this information we reconstruct the Impulse Response Function (IRF) modal model through a nonlinear optimization problem, where the accelerometer ensures a global solution by providing an initial guess of the eigenfrequencies. We investigate numerically the accuracy of the methodology by simulating multiple damped sine waves. Furthermore, we present an experimental validation on a clamped–clamped beam excited by an impact hammer. Thereby, the displacement information is captured by a single camera triggered by random pulses, and computed by Lucas–Kanade (LK) optical flow. The complexity and modal assurance criterion (MAC) of the modes show that all modes whose amplitudes are higher than the noise level are measured successfully with only one excitation hit, where the highest mode, at 218 Hz, is measured with a random sampling scheme comparable to 50 fps (to reach 218 Hz, a regular sampling with 436 fps would be required)." @default.
• W4210241297 created "2022-02-08" @default.
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• W4210241297 date "2022-05-01" @default.
• W4210241297 modified "2023-09-30" @default.
• W4210241297 title "Camera-based experimental modal analysis with impact excitation: Reaching high frequencies thanks to one accelerometer and random sampling in time" @default.
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• W4210241297 doi "https://doi.org/10.1016/j.ymssp.2022.108879" @default.
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