Research on target temperature recognition based on dual band LiTaO3 pyroelectric detector
Aiming at the difficult problem of pyroelectric infrared detectors in the field of temperature recognition,a LiTaO3 pyroelectric multi-element detector based on long/medium wave dual band is designed,and a target temperature recognition model based on machine learning algorithm is established.The change trend of two band radiation and double band ratio under different blackbody temperatures is analyzed,the relationship between double band ratio and blackbody temperature are tested,the errors of double band ratio in simulation and measurement are analyzed,the decision tree based on pyroelectric data,the optimal parameter selection of random forest algorithm,and the recognition accuracy of the built model are studied.The research result shows that the recognition accuracy of the temperature recognition system built based on this detector can reach above 90%,which provides a new technical path for target temperature recognition based on pyroelectric,and broadens the application range of pyroelectric infrared detectors.
dual bandpyroelectric detectordual band ratiomachine learningtarget recognition
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