Time-to-count Methods Of Measurement, A Preliminary Study

For the nuclear radiation detector with total quantity measures with step-by-step counting form probe, dead time, saturation current, high-end pulse overlapping etc. is the major factor to affect detection efficiency. Ascertaining the measurement system resolution ratio or correct to dead time be in progress to cut down measurement error in the past exactly is a very complicated job, which can not solve the problem in essence. With controlling the high voltage of detection element, Time-To-Count measures method measures time before the first pulse counting under high voltage, calculates radiation intensity, thereby canceling the affection of dead time etc. and improves the detection efficiency. The Theory basis of the method is the radioactivity of single radioactive source obeying Poisson location.The theoretical principle of Time-To-Count measures method has been discussed first in this paper, and then using Monte Carlo simulation to simulate Time-To-Count technology by computer, and accomplished Time-To-Count measures method experiment using J32 Geiger-Muller Counter and J33 Geiger-Muller Counter based on pulse counting measure method. In the Time-To-Count measures method experiment, we use single chip system to measure time before counting, accomplish timing, controlling, measuring, data processing work., and calculate radiation intensity by formula R=k/(?) without using any math compensation after measuring the time before counting. The paper analyzes the key factors of Time-To-Count measures method based on a large amount of experiment data, compares to local pulse counting method and shows the advance of Time-To-Count measures method.Experiment result shows that, the linearity measure range of J32 Geiger-Muller Counter is 500μR/h～8000μR/h by pulse counting method, and the same of J33 Geiger-Muller Counter is 50μR/h～5000μR/h, but both of the linearity measure range is 20μR/h～30000μR/h by Time-To-Count measures method. The front and back strides over amounts four levels, and the data linearity is not still changed into bad indication.