Online tool wear monitoring and estimation using power signals and S-transform

Online tool fault/wear detection in the machining operations is necessary for increasing the productivity and decreasing the operation cost. In this study, an online tool wear estimation algorithm has been developed for milling operation. AC current signal of spindle is used for the detection process due to its applicability and low acquisition cost in the industry. Based on the great potential of time-frequency analysis and its promising results on the similar applications, S-transform is utilized for signal processing and a 2-D correlation analysis determines the state of the fault using the time-frequency domain information. The clear representation of the fault in the time-frequency domain and the accuracy of tool wear estimation by this approach determine the high potential of this algorithm to be used for fault detection in industry.