The invention discloses a
casting surface treatment defect detection and quality evaluation method and
system, and relates to the technical field of
casting quality evaluation, and the method comprises the steps: collecting the surface data of a to-be-detected
casting, and carrying out the data preprocessing, and obtaining a standardized input
data set and a standardized data subset; calling a corresponding analysis sub-model for each subset, outputting quality features and confidence coefficients, and summarizing the quality features and the confidence coefficients into a sub-source result; environment state information is acquired to determine sub-model weights, and weighted fusion is carried out on sub-source results to obtain an
evaluation result and an overall confidence coefficient; calculating space / feature / time consistency and judging according to a combination rule; when a re-checking condition is met, obtaining a re-checking
label backflow updating
data set, and training an updating model and parameters; and dynamically adjusting the threshold value and the
weight value according to the
performance index for subsequent evaluation. According to the method, multi-
source data and environment information can be fused, weight self-adaption and closed-loop updating are parallel, accuracy and stability are improved, misjudgment and missed judgment are reduced, and complex working condition adaptability and long-term reliability are enhanced.