Big-data-mining-based tool wear state prediction method under variable working condition

Abstract

The invention discloses a big-data-mining-based tool wear state prediction method under a variable working condition. The method is used for solving the technical problem that an existing tool wear state prediction method is poor in accuracy. By means of the technical scheme, the large data technology is adopted, complete sample data under the variable working condition factor are obtained, the FFNN data mining method is improved, the incremental learning capacity is achieved, the new condition can be continuously fused, and the more accurate predication model is obtained. Due to consideration of the complete sample data affecting tool wear and incremental learning of the new tool state feature vector, the new condition is continuously fused and learnt, the more accurate prediction model is obtained, and the basis is provided for further analysis of relevant factors affecting tool wear. Compared with the prior art, the newly-added condition is learnt, and accuracy of the tool wear state predication under the variable working condition is improved. Through detection, according to the minimum error result, the err is equal to 0.03933, and the predication accuracy rate is improved by more than 96%.

Description

technical field [0001] The invention relates to a tool wear state prediction method, in particular to a tool wear state prediction method under variable working conditions based on big data mining. Background technique [0002] The prediction of tool wear state is of great significance to make full use of tool life, ensure the surface quality of workpieces, and reduce the damage caused by tool wear to machine tools and other equipment. The existing tool wear prediction methods mainly include: machine learning method based on signal characteristics in the cutting process and empirical formula method based on experimental verification. [0003] The document "Prediction of Tool VB Value Based on Principal Component Analysis and BP Neural Network, Journal of Beijing University of Aeronautics and Astronautics, 2011, Vol.37(3), p364-367" discloses a tool wear method based on an improved BP neural network. predictive algorithm. In this method, the acoustic emission signal, cuttin...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the poor accuracy of the existing tool wear state prediction methods, the present invention provides a tool wear state prediction method under variable working conditions based on big data mining

Images