The intelligent detection and prediction technique of machine tool wear aims to transfer images for machine tool measurement signal, by utilizing fractional-order chaotic synchronization dynamic error attractor. Artificial intelligent and deep learning methods are carried out afterward, in order to distinguish and predict different conditions of tool wear. The technique not only surpasses the existing technology of the world-renowned manufacturing firms, but it is also applied in domestic machine tool firms. The technique is a breakthrough technology on the discrimination and prediction of tool wear for domestic machine tool industry in the futureProducts with this technique will be launch in 2020. It＇s expected to assist factories in enhancing their smart technology and competitiveness. In addition, 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 in international journals.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.