Kundur Shantisagar, R. Jegadeeshwaran*, G. Sakthivel, T. M. Alamelu Manghai
Structural Durability & Health Monitoring, Vol.13, No.3, pp. 303-316, 2019, DOI:10.32604/sdhm.2019.00355
Abstract The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools. This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach. A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe, where the condition of tool is monitored using vibration characteristics. The vibration signals for conditions such as heathy, damaged, thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system. The descriptive statistical features… More >
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