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Contactless interaction based on capacitive sensing in the sanitary sector



Dipl.-Ing. Leonhard Haslinger

In recent years, a trend in the sanitary sector to replace classic single-lever mixers by electronic faucets is recognizable. This way resources and operating costs can be saved. Such electrically-actuated systems provide various opportunities. To identify the user's intention in the sanitary sector, capacitive sensors have an especially large potential. Their simplicity and robustness combined with universal application possibilities and a low power consumption is advantageous compared to other technologies. Since no optical path is necessary, the components can be protected against acts of vandalism. It is also possible to recognize more complex user intentions, which could be used in the Ambient Assisted Living (AAL) sector or for the general increase in comfort.

The aim of this project is to develop more robust capacitive sensors for a reliable recognition of user's intention in the sanitary sector. The user should be able to communicate intentions contactless and intuitive. A frequent source of errors for contactless sensors in wet areas is water. This factor must be considered in the context of signal processing and if necessary further diminished. Concepts to reduce water induced errors are the acceleration of the drops by electrowetting but also through the use of surface acoustic waves (so-called lamb-waves).

Figure 1: Modes for contactless capacitance measurements. Figure 2: X.act 3-axis system by Linos Photonics. Figure 3: Normalized capacitance values for a vertical sensor distance z=2mm and a hexagonal sensor electrode.

The most important contactless capacitance measurement methods for this work are the loading mode and the shunt mode. In Figure 1 the operating principles are schematically illustrated for these modes. The measurement setup in Figure 2 consists of a X.act 3-axis system by Linos Photonics, which is used for adjusting the relative position of the electrodes. Furthermore, Figure 2 shows the sensor and the measuring electrode made of copper and the loading mode sensor. Finally, with the measured data the parameters of a nonlinear model are identified, which can be further used for real-time applications. In Figure 3, the normalized capacitance values of the measurement as well as the identified model for a vertical sensor distance z=2mm and a hexagonal sensor electrode are shown.