Study On Temperature Compensation Algorithm Of Infrared Thermal Imaging System Front-End

Infrared detector is used as the core of the infrared thermal imaging system,it determines the thermal imaging and temperature measurement quality.However,infrared detector is disturbed by many factors in infrared temperature measurement process,these factors lead to low temperature measurement accuracy,it can not meet the needs of high-precision temperature measurement.Therefore,the research of temperature compensation algorithm for infrared thermal imaging system's detector will be of great significance to promote the further development of infrared technology.There are many factors that affect the infrared temperature measurement accuracy,this paper deduces the infrared temperature measurement formula and error formula based on the infrared radiation law,and analyses the influence of relevant factors detailedly,and obtains the corresponding compensation measures,this paper mainly conducts the research of ambient temperature and measurement distance.For ambient temperature compensation,this paper presents a method for infrared temperature compensation algorithm of neural network based on current compensation method,and designs the ambient temperature compensation model based on PSO-BP.Taking the infrared temperature measurement system whose core is infrared thermopile sensor as the research object,this paper adopts PSO-BP neural network algorithm for data fusion,compensates the effects of ambient temperature effectively,and proves the superiority of PSO-BP algorithm.For measurement distance compensation,The least square method is adopted to compensate the each set of data collected by infrared temperature measurement system,and get the error correction formula that is proved to be effective.Finally,by comparing the distance compensation experiment based on the least square method and PSO-BP algorithm respectively,verifies the effectiveness of the two methods.