Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/8589
Load Cell Optimization
A load cell is a small object which has only one goal and that is to measure load. This is an old invention from the mid-eighteenth century and remains very popular today. Load cells are only one portion of a bigger totality. That is why the shape of the load cell changes between objects. Optimization of a load cell is an effective way to get the highest signal from the cell.
The main object of this thesis is optimization of a load cell which is a part of the Rheo Knee® from Össur. This knee is in use today, which means that the load cell has a certain shape. The optimization of the load cell has to use that knee as a frame of reference. In this thesis the optimization deals with getting the highest strain from the load cell. Finite element analysis was used to calculate the strain and the stresses and two optimization algorithms were used, Grid Search and Constrained Evolutionary Optimization, to find new values for parameters which resulted in higher strain.
There were seven parameters which were optimized, for example the thickness of the load cell and the ring, the width, etc. By changing these parameters differently the strain value rose by 41%. The main constraint in this optimization was the maximum allowable stress value. The Grid Search algorithm gave a good explanation of this limitation and in the Constrained Evolutionary Optimization the feasible solutions were 24% of all the runs.