The invention relates to
random model updating method based on an interval response surface model. The method is characterized by including the steps of firstly, building a second-order polynomial response surface model without cross terms according to experiment design and
regression analysis; secondly, using a square completing method to convert a polynomial response
surface expression into perfect square; thirdly, substituting interval parameters into the response
surface expression to allow the definite response surface model to be changed into the interval response surface model; fourthly, performing interval calculation on the interval response surface model to obtain predicted structural response intervals, and combining the predicted structural response intervals with actual response intervals to build a target function; fifthly, building a optimization inversion problem to identify
interval distribution of parameters. By the method, the expansion problem of interval calculation is avoided, fast calculation of structural response intervals is considered, finite element analyzing calculation and sensitivity matrix building during (interval)
random model updating are avoided, a large amount of calculation time and cost is saved, and ill-conditioned optimization is avoided as much as possible.