Fringe projection profilometry (FPP) is widely used because of its many advantages, such as high accuracy, no-scanning properties, and full-field measurement. When fringe projection profilometry is employed, system calibration is one of the vital procedures. The accuracy of system calibration directly affects the quality of measurement results. The traditional calibration methods of measurement system include several calibration contents, like verticality, parallelism and the calibration of system geometric parameters. Aiming at the difficulties of them and the complexity of operation and adjustment process, this paper puts forward corresponding improvements. The calibration of verticality and parallelism uses checkerboard, which eliminates the requirements of hardware preparation for calibration such as standard parts. In the calibration of system parameters, it is not necessary to know the specific value of each parameter, and the parameters can be divided into two parts for calibration. The validity and practicability of the proposed methods have been proved by experiments. We take the ceramic step shape standard part as the tested object. After calibration by the above methods, the maximum measurement error of the fringe projection profilometry measurement system is -0.1400mm and the maximum standard deviation is 0.7251mm.
A visual vibration measurement method based on single-frame coded illumination and compressive sensing is proposed. The projector projects concentric rectangles with different sizes at different time points in a single camera exposure. According to the size of the rectangles, the image collected by the camera is separated into different sub frames. The centroids of the concentric rectangles are considered as the virtual feature points to record the vibration information of the object. The projector operates according to the random unequal interval trigger signal, and the projection is used as the sampling signal to encode the measured object. Discrete cosine transform is used as sparse basis, and sparsity adaptive matching pursuit and spectral projected gradient for L1 minimization (SPGL1) are used for signal reconstruction. Simulation analysis shows that the proposed method is feasible, and SPGL1 algorithm is more suitable for our signal reconstruction. The experiments indicate that the maximum absolute error of the proposed method for frequency measurement is 0.2985 Hz, and the maximum relative error is 1.6587 × 10 − 3. It is also applicable to multi-frequency measurement.
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