Design And Implementation Of Sensor Dynamic Compensation Filter Based On DSP

With the vigorous development of information technology,the Internet of Things technology has been widely used in various fields such as logistics,transportation,medical treatment and agriculture.More and more test tasks require the network as a test platform to achieve intelligent perception that combines high precision,high speed,diversity and flexibility.The collection of information in the Internet of Things mainly depends on the sensor network located in the perception layer.The quality of the data obtained by the sensor nodes will directly affect the perception accuracy of the sensor network.However,due to the limitations of the sensor manufacturing process and technical level,many sensors have poor dynamic characteristics.In practical applications,there are problems such as slow dynamic response speed and large dynamic error.Therefore,traditional sensors are in urgent need of transformation.In order to compensate the dynamic characteristics of the sensor,this paper focuses on the design method of the dynamic compensator integrated with the swarm intelligence algorithm.In order to ensure the real-time performance of the dynamic compensation,this paper also studies the DSP implementation of the sensor dynamic compensation filter.First of all,this paper analyzes the dynamic characteristics of the sensor,and it is clear that the source of the dynamic error is the limited working frequency band of the sensor.Secondly,in order to compensate for the poor dynamic characteristics of the sensor,the principle of dynamic compensation and the specific method of applying particle swarm optimization algorithm to design the dynamic compensator are elaborated in detail.The design method is derived from the idea of inverse modeling of the system,without the need to know the dynamic model of the sensor.Therefore,the influence of dynamic modeling errors on the compensation result is avoided.Finally,the Simulink toolbox is used to build a number of typical control system models to simulate the dynamic characteristics of the sensor.The algorithm simulation experiments on the MATLAB platform prove that this method is indeed feasible in improving the dynamic characteristics of the sensor.In order to achieve real-time compensation of sensor dynamic errors,this paper selects a digital signal processor with excellent data processing capabilities to design a real-time sensor dynamic compensation system.The sensor model is simulated using a second-order active analog low-pass filter circuit.The TMS320C6713 digital signal processor is selected as the control and processing core,and a multi-channel real-time data acquisition system is designed.On the basis of this system,the DSP implementation of sensor dynamic compensation filter is studied.