Research on prognostics and health management technology of numerical control equipment

Abstract

Scheduled maintenance and corrective maintenance both construct the tradition l maintenance policy of numerical control equipment, which may bring some problems such as excessive maintenance and inadequate maintenance. Aiming at this phenomena, Prognostics and Health Management (PHM) technology is introduced to improve the reliability and availability of numerical control equipment. Before using this technology, Failure Mode Effects and Criticality Analysis (FMECA)should be firstly made for all the subsystems of numerical control equipment. FMECA is indispensable before PHM, and its purpose is to identify the key subsystems which are suitable for using PHM technology, find out the failure mechanisms of this subsystems, and provide references for building failure mechanism models and defining conditional parameters being monitored. Then a PHM system of numerical control equipment is designed. In this system, every conditional parameter of key subsystems is monitored by various sensors according to its respective failure mechanisms. A method based on multi - sensor data fusion is built to process information from sensors. The method uses the neural network algorithm. Applying the method can analyze the operation condition of numerical control equipment, and then prognoses its performance degradation, life evaluation, machining accuracy, and reliability. All the results can supply helpful evidence for making maintenance policy. Finally, key issues of implementing PHM theology in numerical control equipment are cited with the goal of better practical uses.