A
tool management and control method and
system of a
numerical control machine tool relate to the technical field of
numerical control machine tools. The method comprises the following steps: S1, collecting tool signals and preprocessing; S2, constructing a heterogeneous graph, and calculating the feature correlation between nodes by using a graph attention aggregation mechanism; S3, performing dilated
convolution and gated residual operation on the embedded
tensor on a GPU; S4, constructing a
tool wear evaluation network, and performing channel and
time sequence weighting on the space-time
feature matrix; S5, according to the wear confidence, an improved hierarchical matching
algorithm is used to match the embedded
tensor and the
processing task demand vector; S6, inputting the optimal tool sequence into the
numerical control machine tool terminal, and completing
parallel scheduling and tool position mapping; S7, after
processing is completed, updating the tool whole life cycle
database according to the
health score, and generating a data report containing replacement suggestions and maintenance plans. The present application realizes accurate identification and intelligent scheduling of
tool wear state, and significantly improves tool utilization and numerical control
machine tool operation efficiency.