IoT acoustic sensor design and antenna selection for a wind turbine structural health monitoring system

Recent research has mostly investigated the theoretical performance of various structural acoustic monitoring systems, but there is little data for these systems' real-world performance. Intermittent signal strength, anomalous data loss, and other implementation issues can occur and must be addressed before wide-scale adoption of this technology is possible. Key differences that exist between in-lab testing and real-world implementation that this study addresses are: constant rotational motion, complex blade internal structure, costly cellular data, and remote location. In this paper, we present the design and testing of an acoustic sensor based structural health monitoring system. A field test was conducted to evaluate the performance of antenna candidates. We designed IoT acoustic sensors mounted within wind turbine blades, including a local controller node that aggregates data and pushes them to the cloud via cellular networks, and a cloud dashboard developed on Amazon Web Services. During the six-month (April through October 2022) deployment at National Renewable Energy Laboratory (NREL), acoustic samples as well as other metrics such as temperature, acceleration, wireless signal strength, data transfer latency were collected continuously which enable analysis of the health of the blades and validate the functionality of the monitoring system.