Two New Methods of Preset Time Mean Count Rate Metering Using Adaptive Digital Signal Processing

Abstract

Two new methods developed to improve the classical preset time 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 low-pass filters of various structures with adaptive parameters to implement the control of the mean count rate error were considered. An adaptation algorithm for preset time interval calculations was devised and implemented in both methods differing only in the place of its execution (before or after the low-pass filters). The simulated and realized methods, using the developed algorithms, guarantee: the response time not in excess of 2s for the mean count rate higher than 2c/s and the controllable mean count rate error in the range of ±4% to ±10%.