The application discloses an emulsified
asphalt demulsification speed determination method, relates to the online detection and intelligent monitoring technical field of
road engineering materials, and remarkably improves the practicability and reliability of emulsified
asphalt demulsification speed determination through integration of a lightweight
time sequence prediction model and a self-adaptive
processing mechanism; in terms of portability, an
edge model based on a gated recurrent
unit structure is adopted, calculation resource dependence is reduced, the method can be run on a handheld device, the problem of clumsiness of traditional laboratory equipment is avoided, and construction personnel can be conveniently and rapidly deployed on site; real-time performance is enhanced, a self-adaptive sliding window dynamically adjusts window length and step length according to
data stability, the
inference frequency is ensured to match the demulsification process, an
online learning mechanism is combined, the model can instantaneously respond to environmental changes such as temperature fluctuations, and a demulsification speed
estimation value can be outputted without obvious
delay, so that paving and compaction time is guided, and construction interruption is reduced.