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The benefit of Digital Twins depends to a large extent on the quality of the sensor data provided. In many cases, sensor failures are only detected late in operation which can lead to serious consequences. For this reason, one approach to reduce the resulting safety issues is to use redundant sensor systems that monitor the same measureand. However, due to the additional sensors required, this is associated with additional financial and design effort.In this publication an alternative strategy is presented, which provides a redundant sensor system with the help of soft sensors. Soft sensors use already installed physical sensors to anticipate a new measured variable via algorithms. They are often used to avoid placing sensors in inaccessible locations, but are used here to perform redundant computation of already existing metrics. The sensor data of physical and soft sensors are used as input variables for a Digital Twin. Here, these are compared with each other and can be critically questioned by the twin itself. This makes it possible to extend the system boundary of the Digital Twin to the sensors themselves and provided input variables can be checked for their validity. This allows sensor failures to be detected at an early stage and consequential damage to be averted.

Abstract. Motivated by the application of industry 4.0 and Internet of Things (IoT) technologies, the development of cyber physical systems (CPS) is gaining momentum. As CPS require multiple measurement technologies to drive the intended function, e.g., condition monitoring and in situ measurement, the integration of measurement systems into industrial processes or individual products becomes a critical activity within the development process. Development methods like the V-Model support developers with methodological guidelines, but the related methods and models do not provide sufficient information regarding the energy supply of embedded systems. If the measurement system, consisting of sensor, calculation and communication unit is integrated inside an either sealed or moveable system, e.g., in a gearbox, ensuring a reliable communication and energy supply is a challenging task. This contribution therefore focuses on the energy supply, in particular the electric power consumption of autarchic measurement systems, referred to as sensor nodes. Based on a literature review of existing physical principles determining the energy consumption of semiconductors, a simple estimation model is derived. Estimation models in the current literature mainly focus on the effects of source code or software in general without analyzing a possible impact of operation strategies, such as generic data processing logics in practical applications. The model presented in this contribution is therefore used to identify the energy consumption of sensor nodes influenced by ambient and operating conditions of sensor nodes. Strategies are examined experimentally using an exemplary sensor node, a climatic chamber and a sensor-integrated gearbox as the system to be observed. An analysis of the conducted experiments leads to a more precise model, which is evaluated regarding its significance for predicting the energy consumption and the underlying simplifications. Finally, general relations influencing the energy consumption are presented and necessary research suggested.