The invention discloses an aero-engine
turbine blade multispectral
temperature measurement method based on HPSOGA, and belongs to the technical field of
turbine blade
temperature measurement, and the method comprises the following steps: S1, collecting multispectral
radiation data and background reflection
radiation data of a
turbine blade; s2, initializing an HPSOGA
algorithm, and randomly generating an initial particle swarm; s3, calculating an environment complexity factor, updating the dynamic penalty function, and calculating a value of the dynamic penalty function; s4, constructing a multi-objective optimization function; s5, the fitness of all particles is calculated, and an individual optimal solution and a
global optimal solution are obtained; s6, updating the speed and position of each particle by using an HPSOGA
algorithm, and generating new particles; and iteratively executing the steps S3-S6 until the conditions are met, and outputting a
global optimal solution. According to the method, the problems of low
measurement precision, poor stability and the like when the
turbine blade is subjected to
temperature measurement are solved, the dynamic penalty function is introduced, the adaptability and the accuracy of an inversion temperature measurement
algorithm are improved, and the reliability and the stability of temperature and
emissivity calculation are improved by adopting a multi-target optimization strategy.