We have developed a novel light scattering measurement system based on a microfluidic trap to measure the elastic light scattering of micro-particles. The particles were captured from the sample suspension by a microfluidic chip with a hydrodynamic trapping, which were stably immobilized at the predetermined position by the pressure gradient and friction in the micro-channel. The trapped particles were illuminated by a He-Ne laser after refractive index matching, and a narrow-field photodetector designed by the spatial filter and a photomultiplier mounted on a homocentric rotating platform was used to detecting the scattering light. In this paper, we have improved this measurement system. By reducing the background scattering of microfluidic chip to improve the signal-noise ratio and using precise control, we measured the 23.75μm diameter polystyrene microsphere’s light scattering distribution, the results showed a good agreement on the trend with the curves of theoretical result. At the same time, using the microfluidic trap, we captured two particles (same size and different size) in a fixed orientation with touching components and obtained the light scattering distribution.
In the past few years, optical metrology has found numerous applications in scientific and commercial fields owing to its
non-contact nature. One of the most popular methods is the measurement of 3D surface based on fringe projection
techniques because of the advantages of non-contact operation, full-field and fast acquisition and automatic data
processing. In surface profilometry by using digital light processing (DLP) projector, many factors affect the accuracy of
3D measurement. However, there is no research to give the complete error analysis of a 3D imaging system. This paper
will analyze some possible error sources of a 3D imaging system, for example, nonlinear response of CCD camera and
DLP projector, sampling error of sinusoidal fringe pattern, variation of ambient light and marker extraction during
calibration. These error sources are simulated in a software environment to demonstrate their effects on measurement.
The possible compensation methods are proposed to give high accurate shape data. Some experiments were conducted to
evaluate the effects of these error sources on 3D shape measurement. Experimental results and performance evaluation
show that these errors have great effect on measuring 3D shape and it is necessary to compensate for them for accurate