In laser particle size measurement, the instrument based on traditional Fourier transform structure is disadvantaged in the
narrow measurable dynamic size range. So it is hardly to be used to measure broadly distributed particle. The presented
technology is based on Fresnel diffraction theory. The formula of combined spectrum technology by detecting signals on
coaxial focal planes is educed. In the proposed method, the two lenses are set coaxially and signals are detected on the
back focal plane of the first lens and the combined back focal plane of the two lenses. The detected signals are then
combined. The data are processed with a no-model algorithm. Thus, the measurable dynamic range can be broadened as
no component of the sizer is changed. Experimental results of some samples show that the particulate in the size range of
5 ~ 3500 µm can be measured simultaneously.
KEYWORDS: 3D image reconstruction, Digital holography, Foam, Digital imaging, Holograms, Holography, Polymers, Digital recording, Charge-coupled devices, Image sensors
A method for the measurement of low-density microporous polymeric foams with digital microscopic image plane holography is studied. An image plane hologram of microporous foam is recorded in an optical system of a Mach-Zender interferometer by CCD sensor, and the magnified image, which contains the quantitative information of the intensity and the phase of the microporous foam, is reconstructed numerically from the captured single interference pattern by twice
fast Fourier transform and digital filter processing of frequency spectrum. And the morphometry and the pore diameter of
the microporous foam under test can be obtained. A theoretical analysis has been performed and experimental results of
the polymeric foam are also given. The experimental results show that the method presented in this paper is feasible,
easy in data processing.
In order to ameliorate convergence of the algorithm to invert the particle-size distribution (PSD) from laser diffraction data, an improved conjugate gradient algorithm (ICGA) is proposed. This method is independent of any given a priori information of the particle-size distribution. In the algorithm, each objective function is constructed according to an equation of the system of equations. Then iterations are carried out continuously between objective functions by choosing conjugate gradient directions, and thus the objective functions are tied up. An iteration step-adjusting parameter is introduced, which depends on the row index vectors of the matrix equation. Two narrowly distributed particulate-certified reference materials, their mixture, and a widely distributed particle plate are used as samples to verify the algorithm. Experimental results show that the ICGA is sufficiently convergent and that the convergence points are stable. The presented method can be used to invert unimodal and multimodal PSD with high precision.
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