The application discloses a kind of based on multi-
modal fusion's flocculating agent residual influence evaluation method and
system, the method includes the following steps: S1, by
surface charge sensor, optical sensor and
surface roughness detector, the electrical characteristic data, optical characteristic data and geometric morphological characteristic data of the surface of measured mechanism
sand sample are collected;S2, corresponding multidimensional
feature vector is extracted;S3, the multidimensional
feature vector is input into the multi-
modal fusion prediction model that is trained in advance, and the predicted fluidity
loss rate value of the measured mechanism
sand sample is obtained;S4, the predicted fluidity
loss rate value is compared with preset safety threshold, and the corresponding flocculating agent residual
evaluation result is generated.Thereby, by comparison with safety threshold, the influence of PAM residual amount on the fluidity of
mortar is preliminarily screened, to provide basis for subsequent
processing decision, and prediction is carried out in combination with
machine learning model, in combination with
machine learning and chemical detection means,
sand sample detection is realized.