The application belongs to the technical field of
intelligent management of ancient buildings, and provides an ancient building wood component diagnosis and prevention
intelligent management method combined with digital twinning, comprising:
processing the
main diagnosis surface image of the wood component by using a damage diagnosis model to obtain damage
state recognition results; integrating the static attribute data of the wood component, and environment
exposure data, damage
state recognition results and maintenance data to obtain a structured digital twinning archive; obtaining the
feature vector of the wood component at each historical time point based on the structured digital twinning archive, and stacking them in
time sequence into a three-dimensional feature
tensor; inputting the three-dimensional feature
tensor into a multi-task
time series prediction model to obtain the future damage prediction result of the wood component and the damage influence weight of the historical time point; calculating the SHAP value of the index; generating damage cause description; matching the damage cause description with a
decision rule library to obtain the maintenance decision instruction of the wood component and sending it. The accuracy and forward-looking nature of the future damage prediction result of the wood component are improved, and a decision
closed loop is formed.