A model of the random background noise acting on particle signals is established to study the impact of the background
noise of the photoelectric sensor in the laser airborne particle counter on the statistical character of the aerosol scattering
pulse signals. The results show that the noises broaden the statistical distribution of the particle's measurement. Further
numerical research shows that the output of the signal amplitude still has the same distribution when the airborne particle
with the lognormal distribution was modulated by random noise which has lognormal distribution. Namely it follows the
statistics law of invariance. Based on this model, the background noise of photoelectric sensor and the counting
distributions of random signal for aerosol's scattering pulse are obtained and analyzed by using a high-speed data
acquisition card PCI-9812. It is found that the experiment results and simulation results are well consistent.
In order to accurately measure counting efficiency of laser airborne particle counter, the characteristics and shortages of
the signal amplitude response functions of domestic instruments were analyzed firstly. Then the design of performance
optimization for optical sensors was developed through using sheath air inlets to replace the original inlets, which can
cause the signal amplitude response functions to be described by the normal distribution. Base on these, a new method
for calculating counting efficiency was presented. Through analyzing the relation between signal amplitude response
function and coordinate origin, the counting efficiency for mono-disperse particles can be confirmed. If the signal
amplitude response function intersected with the coordinate axis, fitting the incomplete curve into the complete curve
using non-linear Least Square Method, then the counting efficiency can be defined as the ratio of the included area of the
incomplete curve to the complete curve. If the whole signal amplitude response function totally diverged from the
coordinate origin, it proved that the counting efficiency of mono-disperse particles was up to 100%. The theory and
experiments prove that this method is simple, useful and practical. It also offers the clear guidance direction for
appraising performance of the instrument.
The light scattering signal amplitude distribution of aerosols, which was measured by the single particle counting
technique, was applied to calculate aerosol mass concentration using an inversion algorithm. Therefore, how to
accurately extract the information of the signal amplitude distribution is a crucial problem for aerosol mass concentration
inversion. In view of mass concentration inversion accuracy and stability are related to information extraction methods,
the linear and non-linear segmentation methods were presented. Experimental results indicate the information entropy of
the signal amplitude distribution obtained by the non-linear segmentation method is clearly larger in the same number of
signal subsets, and when inversion accuracy achieves stability, the ratio of information entropy to the number of signal
subsets is also larger than that of the linear segmentation method, leading to rapid stability of inversion accuracy. The
study of the information entropy characteristic of the signal amplitude distribution of aerosol provides theoretical
guidance for the circuit design of an optical particle counter.
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