Preset time count rate meter using adaptive digital signal processing

Abstract

Two presented methods were developed to improve classical preset time count rate meters by using adapt able signal processing tools. An optimized detection algorithm that senses the change of mean count rate was implemented in both methods. Three low-pass filters of various structures with adaptable 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 implemented in both methods. An adaptation algorithm for preset time interval calculation executed after the low-pass filter was devised and implemented in the first method. This adaptation algorithm makes it possible to obtain shorter preset time intervals for higher stationary mean count rate. The adaptation algorithm for preset time interval calculation executed before the low-pass filter was devised and implemented in the second method. That adaptation algorithm enables sensing of a rapid change of the mean count rate before fluctuations suppression is carried out. Some parameters were fixed to their optimum values after appropriate optimization procedure. Low-pass filters have variable number of stationary coefficients depending on the specified error and the mean count rate. They implement control of the mean count rate error by suppressing fluctuations in a controllable way. The simulated and realized methods, using the developed algorithms, guarantee that the response time shall not exceed 2 s for the mean count rate higher than 2 s-1 and that controllable mean count rate error shall be within the range of ?4% to ?10%.