The application discloses a crystallizer
heat flux inverse calculation method and
system based on
optical fiber temperature measurement, a medium and equipment, which realizes real-time acquisition of
temperature measurement data through
optical fiber sensors arranged in a slab
continuous casting crystallizer of a steel
plant, and combines with the running
process conditions (steel composition and
casting speed). First, the on-site
temperature measurement data is collected and stored, then the
noise data is processed by using a
smoothing exponential
algorithm according to the data characteristics, then a stable
data source is selected for
big data empirical formula fitting to determine the
empirical formula parameters, thereby providing a reference for setting the initial value of iterative calculation and serving as a way to test the accuracy of model calculation in the future. According to the arrangement characteristics of the
optical fiber temperature measurement sensor,
heat transfer calculation is carried out by using a longitudinal modeling method. In addition, a man-
machine interface based on a Web front-end
visualization technology is further developed to more intuitively and effectively monitor the temperature of the crystallizer part. The method solves the problems of poor accuracy and sensitivity of the previous temperature measurement method relative to optical
fiber temperature measurement, the
data noise processing is adopted for the large amount of data of optical
fiber temperature measurement, and the direct inverse calculation method of the longitudinal
heat flux of the crystallizer is adopted, so that the calculation is simple and the result is accurate.