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Controlling the sensor properties of smart structures produced by metal forming

Krech, Martin and Andreas, Trunk and Groche, Peter (2018):
Controlling the sensor properties of smart structures produced by metal forming.
In: Journal of Materials Processing Technology, pp. 541-550, 262, [Article]

Abstract

A rotary swaging process is presented which allows the manufacturing of smart structures by forming hollow shafts and joining sensor elements simultaneously. A reasonable form- and force-fit of the sensor element is required to ensure the desired sensory properties of the structure, such as linearity, long-term stability and repeatability. However, the conjoint forming process is subjected to uncertainty which leads to fluctuations of the remaining pre-tension forces. In order to increase the adjustability and accuracy of the process, the utilization of the sensor signals for a control approach is investigated. A prediction model is established on the base of a correlation analysis. It was found that the sensor forces occurring during the integration process can be used as a measure to predict the resulting pre-tension with sufficient accuracy. In order to manipulate the process in a beneficial way a control variable has to be identified. Therefore, several test series are conducted to investigate the suitability of infeed speed and mandrel force as possible control variables. A prerequisite is that the joining process can be manipulated, while the resulting geometry of the part remains unchanged. A possible time slot for an intervention is determined and a first control approach is implemented. Two different target values of the pre-tension force are tested. Compared to open loop controlled processes the accuracy of the targeted pre-tension condition could be improved significantly.

Item Type: Article
Erschienen: 2018
Creators: Krech, Martin and Andreas, Trunk and Groche, Peter
Title: Controlling the sensor properties of smart structures produced by metal forming
Language: English
Abstract:

A rotary swaging process is presented which allows the manufacturing of smart structures by forming hollow shafts and joining sensor elements simultaneously. A reasonable form- and force-fit of the sensor element is required to ensure the desired sensory properties of the structure, such as linearity, long-term stability and repeatability. However, the conjoint forming process is subjected to uncertainty which leads to fluctuations of the remaining pre-tension forces. In order to increase the adjustability and accuracy of the process, the utilization of the sensor signals for a control approach is investigated. A prediction model is established on the base of a correlation analysis. It was found that the sensor forces occurring during the integration process can be used as a measure to predict the resulting pre-tension with sufficient accuracy. In order to manipulate the process in a beneficial way a control variable has to be identified. Therefore, several test series are conducted to investigate the suitability of infeed speed and mandrel force as possible control variables. A prerequisite is that the joining process can be manipulated, while the resulting geometry of the part remains unchanged. A possible time slot for an intervention is determined and a first control approach is implemented. Two different target values of the pre-tension force are tested. Compared to open loop controlled processes the accuracy of the targeted pre-tension condition could be improved significantly.

Journal or Publication Title: Journal of Materials Processing Technology
Volume: 262
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institut für Produktionstechnik und Umformmaschinen (PtU)
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 805: Control of Uncertainty in Load-Carrying Structures in Mechanical Engineering
Date Deposited: 01 Aug 2018 08:42
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