Health Condition Evaluation Method for Motorized Spindle Based on Rotation Error and Vibration

An assessment method of health condition based on lifetime data of rotation error and vibration is expounded in this paper. The most sensible features within vibration signals are selected by the sensitivity analysis and correlation analysis under healthy condition as well as some typical fault situations. The health condition matrix is established base on dynamic update Self-Organized Map (DSOM). The Confident Value (CV) of each vibration signal acquired by DSOM is integrated using the Kernel Principal Component Analysis (KPCA) to form an Integrated Confident Value (ICV). Finally, the Comprehensive Health Index (CHI) can be defined by quantitative value created by rotation error which is an indirect form of machining precision and health condition. Experiments of condition monitoring for motorized spindle is conducted on the platform where a large amount of health data under normal working conditions are trained. Rotation error is chosen as the standard value of health status, based on which parameters of health status are tested under the condition of rotor imbalance fault. The proposed method based on lifetime data can not only apply to motorized spindle of NC machine tools, but also share inspiration for the maintenance and management of health status of other equipment.