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- De Backer, Jeroen, 1987-
(författare)
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Robotic Friction Stir Welding for Flexible Production
- 2012
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Friction Stir Welding (FSW) is a modern welding process that joins materials by frictional heat, generated by a rotating tool. Unlike other welding processes, the material never melts, which is beneficial for the weld properties. FSW is already widely adopted in several industries but the applications are limited to simple geometries like straight lines or circular welds, mostly in aluminium. The welding operation is performed by rigid FSW machines, which deliver excellent welds but puts limitations on the system in terms of flexibility and joint geometries. Therefore, several research groups are working on the implementation of the FSW process on industrial robots. A robot allows welding of three-dimensional geometries and increases the flexibility of the whole system. The high process forces required for FSW, in combination with the limited stiffness of the robot brings some extra complexity to the system. The limitations of the robot system are addressed in this licentiate thesis.One part of the thesis studies the effect of robot deflections on the weld quality. A sensor-based solution is presented that measures the path deviation and compensates this deviation by modifying the robot trajectory. The tool deviation is reduced to an acceptable tolerance and root defects in the weld are hereby eliminated. The sensor-based method provided better process understanding, leading to a new strategy that uses existing force-feedback for path compensations of the tool. This method avoids extra sensors and makes the system less complex. Another part of this work focuses on the extra complexity to maintain a stable welding process on more advanced geometries. A model is presented that allows control of the heat input in the process by control of the downforce. Finally, the robot’s limitations in terms of maximal hardness of the materials to be welded are investigated. Parameter tuning and implementation of preheating are proposed to allow robotic FSW of superalloys.
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| 2. |
- Myklebust, Andreas, 1985-
(författare)
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Modeling and Estimation for Dry Clutch Control
- 2013
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Increasing demands on comfort, performance, and fuel efficiency in vehicles lead to more complex transmission solutions. One such solution is the Automated Manual Transmission (AMT). It works just like an ordinary manual transmission but the clutch and gear selection are computer controlled. In this way high efficiency can be accomplished with increased comfort and performance. To be able to control and fully utilize an AMT it is of great importance to have knowledge about how torque is transmitted in the clutch. The transmitted torque in a slipping dry clutch is therefore studied in experiments with a heavy duty truck (HDT). It is shown that material expansion with temperature can explain torque variations up to 700 Nm for the same clutch actuator position. A dynamic clutch temperature model that can describe the torque variations is developed. The dynamic model is validated in experiments, and shown to reduce the error in transmitted torque from 7 % to 3 % of the maximum engine torque compared to a static model.The clutch model is extended with lock-up/break-a-part dynamics and an extra state describing wear. The former is done using a state machine and the latter using a slow random walk for a parameter corresponding to the clutch disc thickness. An observability analysis shows that the augmented model is fully or partially observable depending on the mode of operation. In particular, by measuring the actuator position the temperature states are observable, both during slipping of the clutch and when it is fully closed. An Extended Kalman Filter (EKF) was developed and evaluated on measurement data. The estimated states converged from poor initial values, enabling prediction of the translation of the torque transmissibility curve. The computational complexity of the EKF is low and it is thus suitable for real-time applications.The clutch model is also integrated into a driveline model capable of capturing vehicle shuffle (longitudinal speed oscillations). Parameters are estimated to fit an HDT and the complete model shows good agreement with data. It is used to show that the effect of thermal expansion, even for moderate temperatures, is significant in launch control applications.An alternative use of the driveline model is also investigated here. It is found that the amplitude discretization in production road-slope sensors can excite vehicle shuffle dynamics in the model, which is not present in the real vehicle. To overcome this problem road-slope information is analyzed and it is shown that a third-order butterworth low-pass filter can attenuate the vehicle shuffle, while the shape of the road profile is maintained. All experiments in the thesis are performed using production HDTs only, i.e. production sensors only. Since all modeling, parameter estimation, observer design and validation are performed with production sensors it is straight forward to implement the results in a production HDT following the presented methodology.
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