Technology of Temperature Field Reconstruction Using Prior Information Based Compressed Sensing
To solve the problem that the randomly placed sensors miss the real hot spots of the processor and affect the re-construction accuracy in the temperature field reconstruction of microprocessor chips using compressed sensing methods,a prior information based compressed sensing method for temperature field reconstruction was proposed.By processing the prior informa-tion of the temperature field,the observation matrix was designed targeted by combining principal component analysis and simula-ted annealing algorithm,and the temperature sensor layout was optimized to improve the reconstruction accuracy.The experimental results show that,compared with EigenMaps-based reconstruction method,the method based on simulated annealing algorithm for sensor layout and the method based on random sampling for compressive sensing temperature field reconstruction,the method im-proved the reconstruction accuracy by at least 29.9%,46.6%and 53.7%in terms of average temperature error,maximum temper-ature error and mean square error,respectively,and has superior temperature field reconstruction performance.
temperature field reconstructioncompressed sensingmeasurement matrixtemperature sensorprior information
NETL
NSTL
万方数据
维普
