TY - JOUR
T1 - Benchmarking parameters for remote electrochemical corrosion detection and monitoring of offshore wind turbine structures
AU - Ahuir-Torres, Juan Ignacio
AU - Bausch, Nils
AU - Farrar, Andrew Stephen
AU - Webb, Stephen
AU - Simandjuntak, Sarinova
AU - Nash, Adrian
AU - Thomas, Bob
AU - Muna, Joseph
AU - Jonsson, Carl
AU - Mathew, Diana
PY - 2019/4/25
Y1 - 2019/4/25
N2 - The remote location and position of offshore wind turbine structures severely limits the application of in-situ corrosion detection methods such as ultrasonic, acoustic emission and X-Ray. A Real Time Remote Sensing (RTRS) technology can be implemented to provide autonomous detection and monitoring, providing exhaustive and detailed information on the corrosion process. Utilising the concept of Internet of Things (IoT) through the integration with satellite and terrestrial communication network, iWindCr, a technology development project funded by the Innovate UK, aims to design a Wireless Sensor Network (WSN) of smart miniaturised sensors for corrosion detection and monitoring of the offshore wind turbine structures. This paper discusses the rationale and challenges around the iWindCr WSN design, particularly in the development of a miniaturised system and in relation to the provision of power and power consumption. The later has led to the selection and the integration of the electrochemical analysis techniques, namely Open Circuit Potential (OCP) and Zero Resistance Ammeter (ZRA) on the sensor interface system. The verification of these techniques for the corrosion detection sensor has resulted in a database consisting of the corrosion parameter outputs or threshold values of metals specific to offshore wind turbine structures, in this case tower, foundation and nacelle (gearbox). The database provides end users with the benchmark that can be used to detect physical changes during the course of corrosion or passive film damage. These parameters are incorporated in the user interface data analytics software, enabling the quantification of corrosion or film damage.
AB - The remote location and position of offshore wind turbine structures severely limits the application of in-situ corrosion detection methods such as ultrasonic, acoustic emission and X-Ray. A Real Time Remote Sensing (RTRS) technology can be implemented to provide autonomous detection and monitoring, providing exhaustive and detailed information on the corrosion process. Utilising the concept of Internet of Things (IoT) through the integration with satellite and terrestrial communication network, iWindCr, a technology development project funded by the Innovate UK, aims to design a Wireless Sensor Network (WSN) of smart miniaturised sensors for corrosion detection and monitoring of the offshore wind turbine structures. This paper discusses the rationale and challenges around the iWindCr WSN design, particularly in the development of a miniaturised system and in relation to the provision of power and power consumption. The later has led to the selection and the integration of the electrochemical analysis techniques, namely Open Circuit Potential (OCP) and Zero Resistance Ammeter (ZRA) on the sensor interface system. The verification of these techniques for the corrosion detection sensor has resulted in a database consisting of the corrosion parameter outputs or threshold values of metals specific to offshore wind turbine structures, in this case tower, foundation and nacelle (gearbox). The database provides end users with the benchmark that can be used to detect physical changes during the course of corrosion or passive film damage. These parameters are incorporated in the user interface data analytics software, enabling the quantification of corrosion or film damage.
KW - offshore
KW - wind turbine
KW - corrosion sensor
KW - electrochemical techniques
KW - OCP
KW - ZRA
KW - Wireless Sensor Network (WSN)
KW - Real Time Remote Sensing (RTRS)
KW - IoT
U2 - 10.1002/we.2324
DO - 10.1002/we.2324
M3 - Article
SN - 1095-4244
VL - 22
SP - 857
EP - 876
JO - Wind Energy
JF - Wind Energy
IS - 6
M1 - 0
ER -