Multiple linear regression model-based belt weigher main error factor analysis method

The invention discloses a multiple linear regression model-based belt weigher main error factor analysis method. The method includes the following steps that: a belt weigher experiment platform is set up, main error factors such as tensions, temperatures and equivalent flow rates are changed according to actual situations, the tensions, temperatures, equivalent flow rates, calibration values and hopper weighers of various test points are recorded, and the relative errors of the calibration values and hopper weighers are calculated; the correlation coefficients of the main error factors of a belt weigher are calculated, and the correlation of the main error factors is judged; the relations of the factors are determined according to the correlation, and a multiple linear model is set and solved; residual sum of squares, determination coefficients and MS variance of residuals are adopted as check indexes, and the regression effect of the established model is evaluated; and the test values of the test points are