Experimental modal analysis on full-field DSLR camera footage using spectral optical flow imaging (original) (raw)
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This research looks at the possibilities for full-field, non-contact, displacement measurements based on high-speed video analyses. A simplified gradientbased optical flow method, optimised for subpixel harmonic displacements, is used to predict the resolution potential. The simplification assumes an image-gradient linearity, producing a linear relation between the light intensity and the displacement in the direction of the intensity gradient. The simplicity of the method enables each pixel or small subset to be viewed as a sensor. The resolution potential and the effect of noise are explored theoretically and tested in a synthetic experiment, which is followed by a real experiment. The identified displacement can be smaller than a thousandth of a pixel and subpixel displacements are recognisable, even with a high image noise. The resolution and the signal-to-noise ratio are influenced by the dynamic range of the camera, the subset size and the sampling length. Realworld experiments were performed to validate and demonstrate the method using a monochrome high-speed camera. One-dimensional mode shapes of a steel beam are recognisable even at the maximum displacement amplitude
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To measure high-frequency 3D vibrations, multi-camera, high-speed imaging hardware is normally required. An alternative using still-frame cameras was recently introduced with the Spectral Optical Flow Imaging (SOFI) method. In this research, the SOFI method is extended to multiview measurements of spatial operating deflection shapes. This is achieved by utilizing harmonically controlled illumination to perform an analogue Fourier transform on image-intensity data in multiple camera views. The obtained multiview displacement spectra are combined with geometrical data to perform frequency-domain triangulation and reconstruct spatial deflection shapes. By introducing additional camera views into the image-based measurement, its field of view is extended and the signalto-noise ratio of the final result is increased. For linear, time-invariant mechanical structures under stationary excitation, full-field 3D measurements of highfrequency vibrations can be performed using a single still-frame monochrome camera. The proposed method identifies displacements in the frequency domain directly on the camera sensor, resulting in orders-of-magnitude smaller data sizes and post-processing times compared with conventional multiview image-based methods.
Mechanical Systems and Signal Processing, 2018
Instantaneous full-field displacement fields can be measured using cameras. In fact, using high-speed cameras full-field spectral information up to a couple of kHz can be measured. The trouble is that high-speed cameras capable of measuring high-resolution fields-of-view at high frame rates prove to be very expensive (from tens to hundreds of thousands of euro per camera). This paper introduces a measurement setup capable of measuring high-frequency vibrations using slow cameras such as DSLR, mirrorless and others. The highfrequency displacements are measured by harmonically blinking the lights at specified frequencies. This harmonic blinking of the lights modulates the intensity changes of the filmed scene and the camera-image acquisition makes the integration over time, thereby producing full-field Fourier coefficients of the filmed structure's displacements.
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Vibration measurements using optical full-field systems based on high-speed footage are typically heavily burdened by noise, as the displacement amplitudes of the vibrating structures are often very small (in the range of micrometers, depending on the structure). The modal information is troublesome to measure as the structure's response is close to, or below, the noise level of the camera-based measurement system. This paper demonstrates modal parameter identification for such noisy measurements. It is shown that by using the Least-Squares Complex-Frequency method combined with the Least-Squares Frequency-Domain method, identification at high-frequencies is still possible. By additionally incorporating a more precise sensor to identify the eigenvalues, a hybrid accelerometer / high-speed camera mode shape identification is possible even below the noise floor. An accelerometer measurement is used to identify the eigenvalues, while the camera measurement is used to produce the full-field mode shapes close to 10 kHz. The identified modal parameters improve the quality of the measured modal data and serve as a reduced model of the structure's dynamics.
Experimental modal analysis using camera displacement measurements: a feasibility study
Sixth International Conference on Vibration Measurements by Laser Techniques: Advances and Applications, 2004
Recently, a mobile coordinate measurement machine consisting of three CCD cameras was expanded with dynamic measurement capabilities. The system is able to track three LEDs in three directions with a maximum sampling frequency of about 1000 Hz. This offers the possibility to use the measurements for dynamic system identification. To this aim, a vibrating structure is equipped with multiple lightweight infrared LEDs and excited by dynamic excitation sources. Transfer functions between force and displacements are estimated from which the modal parameters of the structure can be identified. The benefits of using the camera displacement measurement system is that information down to 0 Hz can be obtained, that mounting LEDs is much easier than installing traditional displacement transducers (LVDTs) and that the coordinates of the measurement points are also available from the measurements. In this paper a dynamic testing study is performed using a scale model of an airplane. Both LEDs and accelerometers are mounted on the structure allowing a comparison between displacement and acceleration transfer function modal analysis results. The main conclusion is that it is possible to successfully identify the modal parameters of the airplane scale model from the displacement measurements in the complete frequency range of the excitation.
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Mechanical Systems and Signal Processing, 2021
The use of a high-speed camera for dynamic measurements is becoming a compelling alternative to accelerometers and laser vibrometers. However, the estimated displacements from a high-speed camera generally exhibit relatively high levels of noise. This noise has proven to be problematic in the high-frequency range, where the amplitudes of the displacements are typically very small. Nevertheless, the mode shapes of the structure can be identified even in the frequency range where the noise is dominant, by using eigenvalues from a Least-Squares Complex Frequency identification on accelerometer measurements. The identified mode shapes from the Least-Squares Frequency-Domain method can then be used to estimate the full-field FRFs. However, the reconstruction of the FRFs from the identified modeshapes is not consistent in the high-frequency range. In this paper a novel methodology is proposed for an improved experimental estimation of full-field FRFs using a dynamic substructuring approach. The recently introduced System Equivalent Model Mixing is used to form a hybrid model from two different experimental models of the same system. The first model is the reconstructed full-field FRFs that contribute the full-field DoF set and the second model is the accelerometer measurements that provide accurate dynamic characteristics. Therefore, no numerical or analytical model is required for the expansion. The experimental case study demonstrates the increased accuracy of the estimated FRFs of the hybrid model, especially in the high-frequency range, when compared to existing methods.
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Many civil engineering infrastructures including bridges and buildings have been constructed several years ago. They are facing increasing challenges due to climate change and exposed to various external loads such as earthquakes. Extensive research works have been carried out to enable structural and health monitoring (SHM). Modal identification is a crucial part of SHM. Conventionally, it has been accomplished by accelerometers mounted on the structure. Their use may be extremely accurate. However, only a few sensors is usually set up on the structure which may limit modal identification and SHM performance. Vision-based techniques gained increased acceptance as cheaper and easier solution to perform long-range vibration measurements. Video cameras offer the capacity to collect high-spatial resolution data from a distant scene of interest. Various image processing techniques have been developed to extract motion from subtle time changes in the image brightness. Commonly, these mot...
Full-field dynamic deformation and strain measurements using high-speed digital cameras
26th International Congress on High-Speed Photography and Photonics, 2005
Digital cameras are rapidly supplanting film, even for very high speed and ultra high-speed applications. The benefits of these cameras, particularly CMOS versions, are well appreciated. This paper describes how a pair of synchronized digital high-speed cameras can provide full-field dynamic deformation, shape and strain information, through a process known as 3D image correlation photogrammetry. The data is equivalent to thousands of non-contact x-y-z extensometers and strain rosettes, as well as instant non-contact CMM shape measurement. A typical data acquisition rate is 27,000 frames per second, with displacement accuracy on the order of 25-50 microns, and strain accuracy of 250-500 microstrain. High-speed 3D image correlation is being used extensively at the NASA Glenn Ballistic Impact Research Lab, in support of Return to Flight activities. This leading edge work is playing an important role in validating and iterating LS-DYNA models of foam impact on reinforced carbon-carbon, including orbiter wing panel tests. The technique has also been applied to air blast effect studies and Kevlar ballistic impact testing. In these cases, full-field and time history analysis revealed the complexity of the dynamic buckling, including multiple lobes of out-of-plane and in-plane displacements, strain maxima shifts, and damping over time.
Structural Control and Health Monitoring
Structures with complex geometries, material properties, and boundary conditions exhibit spatially local dynamic behaviors. A high-spatial-resolution model of the structure is thus required for high-fidelity analysis, assessment, and prediction of the dynamic phenomena of the structure. The traditional approach is to build a highly refined finite element computer model for simulating and analyzing the structural dynamic phenomena based on detailed knowledge and explicit modeling of the structural physics such as geometries, materials properties, and boundary conditions. These physics information of the structure may not be available or accurately modeled in many cases, however. In addition, the simulation on the high-spatial-resolution structural model, with a massive number of degrees of freedom and system parameters, is computationally demanding. This study, on a proof-of-principle basis, proposes a novel alternative approach for spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field structural dynamics by an innovative combination of the fundamentals of structural dynamic modeling and the advanced video motion manipulation techniques. Specifically, a low-modal-dimensional yet high-spatial (pixel)-resolution (as many spatial points as the pixel number on the structure in the video frame) modal model is established in the spatiotemporal video domain with full-field modal parameters first estimated from line-of-sight video measurements of the operating structure. Then in order to simulate new dynamic response of the structure subject to a new force, the force is projected onto each modal domain, and the modal response is computed by solving each individual single-degree-of-freedom system in the modal domain. The simulated modal responses are then synthesized by the full-field mode shapes using modal superposition to obtain the simulated full-field structural dynamic response. Finally, the simulated structural dynamic response is embedded into the original video, replacing the original motion of the video, thus generating a new photo-realistic, physically accurate video that enables a