Study on Data Processing in Optical Fiber Gas Sensing System Based on Membrane Computing

Abstract

Aiming at the problem of multi point (32 and above) EFPI optical fiber gas sensing system in processing data, for instance, weak ability of parallel data processing, low computational efficiency, slow system response etc., this paper utilizing the advantage like maximum concurrent and distributed of membrane computing system studied a method of parallel data processing. This method adopted a algorithm called Bio-inspired Algorithm based on Membrane Computing-BIAMC compared to the commonly used Genetic Algorithm (GA) has less computational cost and higher computational efficiency. Firstly,4 Standard constrained functions was used as test and contrast function and then the improved algorithm is applied to the parallel data processing, to validate the quantitative analysis and effectiveness, in the end, through the simulation to verify the superiority of the algorithm in robustness and accuracy. The experimental results showed that with taking the parallel feature of data input into consideration the BIAMC which applying to EFPI optical fiber gas sensing system have improved the speed of data processing and the utilization rate of hardware system and the response time of whole system compared to the traditional serial processing method, which provided a new method of parallel data processing in multi-channel sensor system.