The invention relates to a dangerous condition early warning and forecasting method for
pipe jacking downward penetrating process of an existing box
culvert. The method comprises the steps that 1, multiple characteristic parameter data of the existing box
culvert and the surrounding soil bodies of the existing box
culvert are collected through a monitoring device; 2, format
processing is conductedon the collected data; 3, the
soil strength in a disturbance zone is obtained through inversion by using a dichotomous
displacement ratio method; 4, multiple characteristic parameters, the weight ofthe
soil strength of the disturbance zone affecting culvert safety coefficients and gray relational grade are obtained through a
hierarchical analysis gray relational grade method; 5, a long and
shortterm memory circulation neural
network model is established to predict the destruction occurring time of the existing box culvert; 6, a Kalman filtering method is adopted to predict the destruction occurring time of the existing box culvert; 7, prediction results of step 5 and step 6 are combined to conduct early warning and forecasting on dangerous conditions before the critical destruction occurring prediction time. Compared with the prior art, the method can more reasonably perform quantification early warning and forecasting on the dangerous condition for
pipe jacking downward penetratingof the existing box culvert in a manner which is more closer to actual conditions.