Technical Name |
Application of Intelligent Fractional-order Chaos Mapping for Machine Tool Cutting States Monitoring and Prediction |
Project Operator |
National Chin-Yi University of Technology |
Project Host |
姚賀騰、汪正祺、郭應標、謝錦聰、簡柏霖、朱玟霖、蘇曉毅 |
Summary |
The technique aims to transfer measurement signal into images by utilizing Fractional-order Chaos Dynamic Error attractor. Artificial intelligent and deep learning methods are carried out afterwards to distinguish and predict different conditions of tool wear. The breakthrough technique not only surpasses the existing technology of the world-renowned manufacturing firms, but also applied in domestic firms. |
Scientific Breakthrough |
1. Products with this technique will be launch in 2020. It's expected to assist factories enhancing their smart technology and competitiveness. 2. The research team led by Professor Yau is the first to propose the research of Feature Extraction in Electrical and Mechanical System Fault with Fractional-order Chaos Dynamic Error Conversion. Currently, relevant researches have been published to international journals. |
Industrial Applicability |
The Technology of Intelligent Fractional-order Chaos System for Dynamic Error Conversion Feature Extract has been applied to solve the processing states monitoring and prediction in Intelligent Machinery and Intelligent Manufacturing. It can enhance the international competitiveness that rely on domestic machine tool factory and traditional processing industry. |
Keyword |
Machine tool monitoring Cutting chatter Machine tool wear Deep learning Machine spindle life prediction Artificial intelligence(AI) Chaotic system Frequency domain response Grey prediction Convolutional neural networks |