The invention relates to the technical field of intelligent manufacturing and
numerical control machining control, and discloses a
machine tool dynamic characteristic sensing and intelligent
machining control method and
system based on a
knowledge graph and a
large model, and the method comprises the following steps: extracting
frequency domain parameters through a
vibration sensor, obtaining vibration displacement in combination with
laser displacement, and comparing the vibration displacement with
modal data to construct a graph;
processing parameters and displacement are synchronously sampled,
time sequence characteristics are extracted to generate tensors, dynamic characteristics are predicted and corrected, and
frequency response adjustment rotating speed is matched to generate optimized track
control parameters which are converted into
G code instructions. According to the method, a dynamic characteristic map is constructed by fusing vibration signals and displacement, a sliding window synchronizes
processing parameters and vibration data, LSTM extracts joint characteristics, GRU predicts rigidity and
damping ratio, an attention mechanism dynamically corrects weight, characteristic
coupling analysis and prediction precision is improved, nonlinear modeling captures
dominant frequency offset and
harmonic distribution, response speed is enhanced, and the method has the advantages of being high in precision and high in precision.
Cutting vibration is inhibited, and the process stability is guaranteed.