The application provides an AI-based highway bridge and tunnel structure health state evaluation method and
system, which comprises the following steps: according to a continuous damage point position sequence, a clustering
algorithm is used to identify a turning point and divide a life cycle section, and the boundaries of a stable section, a degradation section and an acceleration section are determined; the extension rate data in each life cycle section is obtained, the data between sections is connected through a linear interpolation method for the curve jump position, and a smooth evolution curve is obtained; if there is a symmetric filling residual error in the evolution curve, the error source is judged by comparing the difference of the extension rate of adjacent sections, and the corrected curve parameters are obtained; crack extension characteristics are extracted from the corrected curve parameters, a
time series analysis model is used to predict the evolution trend, and the whole process mapping of the crack from
initiation to extension is determined; according to the whole process mapping of the crack, it is judged whether the extension rate is close to a preset
critical threshold, and a
threshold point of the
remaining life of the structure is obtained.