Estimating machining forces from vibration measurements

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dc.contributor.authorJoddar, Manish Kumar
dc.contributor.supervisorAhmadi, Keivan
dc.contributor.supervisorNadler, Ben
dc.date.accessioned2019-12-11T19:31:48Z
dc.date.available2019-12-11T19:31:48Z
dc.date.copyright2019en_US
dc.date.issued2019-12-11
dc.degree.departmentDepartment of Mechanical Engineering
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractThe 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.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/11358
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectInverse reconstruction of forcesen_US
dc.subjectDeconvolution Methoden_US
dc.subjectKalman filter recursive least squareen_US
dc.subjectAugmented Kalman filteren_US
dc.subjectRegularization of ill-posed problemen_US
dc.titleEstimating machining forces from vibration measurementsen_US
dc.typeThesisen_US

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