The present study uses a method to address microvibrations effects on an optical satellite by combining simulations and experiments based on high-precision acceleration sensors. The displacement and angular displacement of each optical component can be obtained by introducing flywheel perturbation data from a six-component test bench to the finite element model of the optical satellite. Combined with an optical amplification factor inferred from the linear optical model, the pixel offset of the whole optical system is calculated. A high accuracy and broad frequency range for a new microvibration measurement experimental system is established to validate the simulation. The pixel offset of the whole optical system can be measured by testing the acceleration signals of each optical component and calculating optical amplification factors. The results are consistent with optical imaging test results, indicating correctness of the experimental scheme and the effectiveness of the simulation. The results suggest that the effect of microvibrations on a camera can be verified by using mechanical simulators instead of a whole optical camera for the experiment scheme, which is demonstrated to be an effective way for increasing efficiency in jitter measurements.

In this paper, a liquid multi-parameter decoupling method with only one Lamb wave sensor is presented. In a Lamb wave sensor, antisymmetric modes (A₀₁ mode for low frequency, A₀₃ mode for high frequency) and symmetric modes (S₀ mode) are used to detect multiple parameters of a liquid, such as its density, sound velocity, and viscosity. We found they can play very different roles in the detections. For example, the A₀₁ mode is very sensitive to the liquid’s density but the A₀₃ mode is sensitive to the sound velocity. Here, the A₀ mode is used to identify the density of the detected liquid and with this density value we obtained the viscosity by the amplitude shifts of the S₀ mode. This could be a way to distinguish an unknown liquid with high sensitivity or to solve the problem of selectivity of label-free detection on biosensors.