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Title: | Design and Development of Magnetorheological Fluid Damper to Suppress the Tool Vibration In Hard Turning Operation |
Authors: | Aralikatti, Suhas S. |
Supervisors: | Kumar, Hemantha |
Keywords: | Fault diagnosis;Machine learning;Hard turning;Tool life |
Issue Date: | 2023 |
Publisher: | National Institute Of Technology Karnataka Surathkal |
Abstract: | The state of the cutting tool determines the quality of the surface finish produced on the machined parts. A faulty tool produces poor surface and inaccurate geometry leading to the rejection of parts. It is necessary to monitor tool conditions to have consistent quality and economic production. Condition monitoring is ineffective without the implementation of a real-time corrective strategy. In the present study, fault classification of single-point cutting tools for hard turning has been carried out by employing signal processing and machine learning technique using cutting force signals and vibration signals. A comparison of the performance of classifiers was made between cutting force and vibration signal to choose the best signal acquisition method in classifying the tool fault conditions using the machine learning technique. A set of four tool conditions, namely healthy, worn flank, broken insert and extended tool overhang, have been considered for the study. These faulty tools produce undesired vibration that reduces machine quality and production rate. The adverse effect of tool vibration leads to loss of geometric tolerance, accelerated tool wear, poor surface finish and machine instability. The author designed a current- controlled compact magnetorheological fluid (MRF) damper consisting of an electromagnetic coil in the piston as a corrective measure. The damper is fitted onto the lathe machine with the optimal fluid composition to evaluate its performance in controlling the tool vibration. The optimal composition of MRF is identified by a genetic algorithm through the central composite design of the experiment. To cross- verify the algorithm's output values, a validation study is done. A comparison between optimal in-house MR fluid and commercial MR fluid is conducted. The comparison demonstrates that in-house prepared MR fluid performs equally well compared to commercial fluid. The MR damper effectively damps high-amplitude vibration at aggressive cutting conditions. The L9 Taguchi design of the experiment opted to arrive at minimal machining parameters to evaluate the performance of the damper in machining two workpiece materials, namely oil-hardened nickel steel (OHNS) and high carbon high chromium (HCHCR) die steel. The surface roughness and tool vibration iiiare reduced with the damper. It is noted that in-house MR fluid performed equally well as commercial MR fluid. The tool wear study is also carried out to monitor the influence of external damping over tool life. The stability lobe diagram is obtained analytically with experimental validation to mark the stability limit of the machining condition. The stability boundary increases with the damper enabling aggressive cutting conditions. The designed MR damper is controlled by a real-time controller considering the vibration-limiting feedback approach. The Bouc-Wen model is used to estimate the damping force based on the vibration feedback of the tool. The tool wear, surface roughness, and amplitude of tool vibration are evaluated with and without a semi-active MR damper. The above-developed MR damper forms an external adaptor to control the tool vibration that can be installed on the lathe. To improve the design configuration of the MR damper, an internally damped novel tool holder is designed that houses MR fluid in its axial hollow section. The MR fluid is activated by the internal electromagnet coil wound around the inverse beam supported at the inner wall of the hollow portion. The developed MR tool damper reduces the tool vibration with the electric current supply. |
URI: | http://idr.nitk.ac.in/jspui/handle/123456789/17766 |
Appears in Collections: | 1. Ph.D Theses |
Files in This Item:
File | Description | Size | Format | |
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177011-ME020- SUHAS S. ARALIKATTI.pdf | 14.35 MB | Adobe PDF | View/Open |
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