Vibration assisted drilling (VAD) is a type of machining process in which high-frequency vibrations with a small amplitude are induced in the cutting tool to improve the cutting process of hard and brittle materials. These vibrations create an unsteady repetitive processing effect which eventually reduce the cutting forces. It is also crucial to measure these forces in some way because their knowledge directly aids in determining the best machining parameters. Direct and indirect methods can be used to measure these forces, but due to serious limitations of direct measurement methods, an indirect measurement method is required which is capable of online monitoring of high-frequency cutting forces. In this thesis, an indirect method is proposed to estimate thrust force and torque from the voltage signal generated by piezoelectric sensor and torsional deflection signal measured through piezoelectric accelerometer. The estimation of two input signals requires a multi-input multi-output (MIMO) model of VAD system which is developed using Receptance Coupling and Substructure Analysis (RCSA) method. Experimental and numerical methods are used to validate the constituent single-input single-output (SISO) transfer functions of the MIMO model. As the estimated forces are distorted by the dynamics of VAD structure, a Kalman Filter is employed to compensate the dynamics. The accuracy and similarity of results is determined by comparing the estimated cutting force values with the force measured from a load cell in time and frequency domain. The reported experimental results confirm the possibility of using Kalman Filter in estimating high-frequency forces generated in VAD process. / Graduate

The topic of force reconstruction has been studied quite extensively but most of the existing research work that has been done are in the domain of structural and civil engineering construction like bridges and beams. Considerable work in force reconstruction has also being done in fabrication of machines and structures like aircrafts, gear boxes etc. The topic of force reconstruction of the cutting forces during a machining process like turning or milling machines is a recent line of research to suffice the requirement of proactive monitoring of forces generated during the operation of the machine tool. The forces causing vibrations while machining if detected and monitored can enhance system productivity and efficiency of the process. The objective of this study was to investigate the algorithms available in literature for inverse force reconstruction and apply for reconstruction of cutting forces while machining on a computer numerically controlled (CNC) machine. This study has applied inverse force reconstruction technique algorithms 1) Deconvolution method, 2) Kalman filter recursive least square and 3) augmented Kalman filter for inverse reconstruction of forces for multi degree of freedom systems. Results from experiments conducted as part of this thesis work shows the effectiveness of the methods of force reconstruction to monitor the forces generated during the machining process on machine tools in real time without employing dynamometers which are expensive and complex to set-up. This study for developing a cost-effective method of force reconstruction will be instrumental in applications for improving machining efficiency and proactive preventive maintenance. / Graduate

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