Development of Fault Diagnosis System For High Speed Spindle
Date Issued
2015
Date
2015
Author(s)
Hsieh, Nan-Kai
Abstract
During the long machining cycles, the vibration and accompanied noise produced by the machine tool may cause unduly mechanical wear and, consequently malfunction. The inadequate facility limits an effective malfunction pre-warning diagnosis and this often leads to the sudden failure of the spindle. Therefore, it is necessary to rely on the real-time monitor system to enhance the reliability of the machine tool. This research collects the information in the process of production and maintenance, from which the common faults are summarized, and then a constant-preload spindle is used to collect vibration signals and simulate each failure mode. This research also proposes the multi-scale entropy (MSE), in addition to the most common detection of vibration signals, the Fourier analysis. It is used to observe the amplitude of each frequency at each instant. The MSE can be used to calculate the MSE curve which can then be used to correctly identify some defect modes. In order to prevent the failure without warning, this research is designed to extract the threshold of each fault condition by repetitive experiments to develop the defect diagnosis system (DDS). The main objective of the DDS is applied to detect the faults before the run-in period of spindle so that any potential errors can be identified and recognized. These potential damaging factors are detected from the spindle to avoid breaking the bearing during the run-in period. At present, the DDS is applied successfully in the production line for quality control. and the recognition rate of DDS is high up to 90 percent .
Subjects
High Speed Spindle
Vibration Signal
Fourier Transform
Multi-scale entropy
Defect Diagnosis System
Type
thesis