Prediction method for tool remaining life of numerical control machine tool based on hybrid neural model

US11927937B1 · kind B1 · utility

Assignee

• INSTITUTE OF INDUSTRIAL INTERNET, CHONQING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS · CN

Inventors

• Qingqing Huang · Palo Alto, US
• Yan Han · Arlington, US
• Zhen Kang · Wuxi, CN
• Yan Zhang · Cincinnati, US
• Ping Wang

Key dates

• Filing date: Oct 31, 2023
• Grant date: Mar 12, 2024
• Expiry date: Oct 31, 2043

Classification

• Technology area (CPC G): Physics
• CPC primary: G05B2219/37434
• WIPO field: Control
• WIPO sector: Instruments

Abstract

Disclosed is a prediction method for tool remaining life of a numerical control machine tool based on a hybrid neural model, including: constructing a hybrid neural network model, specifically including the following steps: constructing sample data according to the sampling frequency of tool data; obtaining a first feature vector representing the tool life by utilizing a convolutional neural network and a long short-term memory network; generating working condition signals of sampling points into a second feature vector representing the tool life by utilizing an NFM neural network; and inputting a current working time of a tool and the acquired feature vectors into a multi-layer perceptron for fusion to predict the tool life.