The invention provides a bridge health state intelligent monitoring method and
system based on
cloud computing, and the method mainly comprises the steps: 1, determining a key stress part according to a bridge design drawing and finite
element analysis; 2, applying a fluorescent
coating to the selected area in the step 1 by using a spraying process, wherein the
coating coverage area per
square meter is not less than 80%; the
fluorescence monitoring module monitors the change of a
fluorescent particle coating through an optical sensor (a
CCD camera or a
spectrograph) and a
data collector and carries out calculation, according to the
system and the method, the sensitivity of fluorescent particles to mechanical stress is utilized, calculation is combined with
wavelength and position offset, tiny anomalies can be detected, and early warning is achieved; fluorescent signals are used in sunny weather and sound
waves are used in rainy and foggy weather, so that all-weather stable monitoring is ensured; the fluorescent coating covers key parts, and the
sound wave device performs multi-point monitoring, so that the traditional blind area problem is solved; large-scale data are processed in real time through
cloud computing, and evaluation precision is improved through
machine learning; the coating and the
sound wave device are simple and convenient to install without transforming a bridge structure, and the maintenance cost is low.