Wind turbines are impressive technical systems, and today virtually uninterrupted availability is expected from them, even under the harshest environmental conditions. Continuous condition monitoring helps to avoid costly failures and to optimize maintenance intervals. Wireless sensor nodes (WSNs) are an attractive solution for the condition monitoring of many systems, as there is no need for expensive, heavy and failure-prone cabling. However, WSNs must supply their own energy.
Designing energy-autonomous wireless sensor systems must take into account numerous factors that influence the energy budget: How much energy can be harvested from the environment, for example via solar cells? How much energy can be stored, and for how long? How much energy is required for sensing, data processing and wireless data transmission? Conventional design approaches are based on simplified assumptions, which makes it difficult to predict actual availability across the full range of possible operating conditions. This often leads to suboptimal decisions as well as costly prototype tests.
The WSN*Explorer design software developed by MCL closes this gap. It offers comprehensive options for visualizing the design space of wireless sensor nodes in the context of condition monitoring and allows developers to freely configure many variants of a WSN. For all variants, energy harvesting, intermediate storage and energy consumption are modeled. Special attention is paid to the energy consumption of the algorithms executed on the WSN. Instead of being merely estimated, this is measured automatically for different variants, resulting in a significantly higher reliability of the predictions. In addition, there is a connection to weather databases, enabling realistic modeling of energy harvesting.
This allows developers of WSN-based condition monitoring systems to realistically compare a large number of different system variants under diverse operating conditions even before building prototypes: How large does the solar panel really need to be so that the sensor can be reliably supplied with energy even during a rainy autumn? How does the situation change if the turbine is not located in Austria but installed in the Baltic Sea? How does the energy demand of different fault-detection algorithms compare?
Impact and effects
The WSN*Explorer significantly accelerates development cycles for wireless condition monitoring systems. What previously required building physical prototypes and porting algorithms to the respective hardware can now be evaluated automatically. Development time is reduced from months to weeks, and both risk and design costs decrease. Rapidly finding optimal combinations of hardware components and software algorithms (HW/SW co-design) is particularly helpful when exploring alternative energy harvesting approaches and when deploying AI-based algorithms for anomaly detection.
In 2023, the Austrian company eologix sensor technology (founded in 2014) merged with the Australian company Ping Services (founded in 2018) and relocated its headquarters to new premises in Graz, Austria. Since then, EOLOGIX-PING has grown from an initial team of four people to around 35.
Beyond wind turbines, the WSN*Explorer approach is applicable to many condition monitoring use cases, such as industrial, infrastructure and environmental monitoring.
Project coordination (Story)
Dr. Manfred Mücke
Group Leader Embedded Computing
Materials Center Leoben Forschung GmbH
T +43 (0) 3842 45922-610
manfred.muecke(at)mcl.at
IC-MPPE / COMET-Zentrum
Materials Center Leoben Forschung GmbH
Vordernberger Straße 12
8700 Leoben
T +43 (0) 3842 45922-0
mclburo(at)mcl.at
www.mcl.at
Project Partners
- Materials Center Leoben Forschung GmbH, Leoben, Austria
- eologix sensor technology flexco, Graz, Austria
- Know Center Research GmbH, Graz, Austria