Count rate meter with a time constant using adaptive digital signal processing

Abstract

Two methods developed to improve the classical time constant count rate meters by using the adaptive signal-processing tools are presented. An optimized detection algorithm that senses the change of the mean count rate was implemented in both methods. Three different types of low-pass filters of various structures with adaptive parameters to implement the control of the mean count rate error by suppressing the fluctuations in a controllable way were considered, and one of them was implemented in both methods. An adaptation algorithm for time constant interval calculation was executed after the low-pass filter was devised and implemented in the first method. This adaptation algorithm makes it possible to obtain shorter time constant intervals for higher stationary mean count rates. The adaptation algorithm for time constant interval calculation executed before the low-pass filter was devised and implemented in the second method. This adaptation algorithm enables sensing of the rapid change of the mean count rate before the fluctuations suppression is carried out. Some parameters were fixed to their optimum values after appropriate optimization procedures had been performed. The implemented low-pass filter has variable number of stationary coefficients depending on the specified error and the mean count rate. It implements the control of the mean count rate error by suppressing the fluctuations in a controllable way. The simulated and realized methods, using the developed algorithms, guarantee: a response time not in excess of 2 s for a mean count rate higher than 2 counts/s and a controllable mean count rate error in the range of 4–10%.