Variable processing time prediction method considering equipment deterioration
In response to the issue of the fixed standard results for process time at different stages of service life,a variable process time prediction method considering equipment degradation was proposed.For one single condition,a process time prediction method based on BiGCU-MHResAtt model was constructed,and BiGCU was used to ex-tract the local features.The influence relationships between different features were captured with multiple head re-sidual self-attention networks,and the Remaining Useful Life(RUL)was optimized with a fully connected layer while implementing machining time rate prediction through Weibull probability distribution function.For multiple working conditions,a large dataset and feature transfer model were designed in combination with the single working condition model.Clustering and curve fitting were employed to generate a machining time prediction spectrum.The effectiveness of the proposed method was validated through model training and prediction by using the C-MAPSS dataset.
BiGCU-MHResAtt-Weibull modelequipment deteriorationvariable processing timeremaining useful life prediction
NETL
NSTL
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