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Energy structures are usually designed even over-designed to perform their function for a certain lifetime, their efficiency and reliability are vital to society as well as the investment return of energy asset owners. To optimize power production costs and long-term profitability, the possible ways are by optimizing operation & maintenance costs and prolonging structure’s operational service life, particularly for offshore energy infrastructures often exposed to rugged weather with limited access and high safety requirements. Hence, data-driven asset managements strategies are gaining tractions. Remote and scalable real-time monitoring aided by analytical software is preferably adopted by asset managers in order to make more informed decisions.
Offshore energy infrastructures including wind turbines, substations, pipelines, platforms are required to be equipped with SHM systems. The NEURON sensor network is able to cover the principle structural components of a wind turbine (nacelle, blades, tower, foundation) to give a global vision about the structural integrity in real-time. Apart from early damage detection to schedule more properly the maintenance, this full-scale SHM helps structural engineers perfom life cycle analysis according to the observed physical properties.
Digitalization has become a consensus in energy industries. The digital twin technology has been developed to stimulate the digital monitoring for real-time fatigue assessment, lifetime prediction, performance optimization, and improved decision making of a physical asset. Playing an integral role in a fully digitalized structure life cycle, the digital twin is essentially built and updated continuously with meaningful input data collected by sensors instrumented on structures. By pairing digital and physical data combined with predictive and diagnostic analytics, this novelty scope helps the industry to increase safety, improve efficiency and gain the best economic-value-based decision.
To help assess the service life and manage the maintenance of energy plants in a cost-effective manner, Morphosense integrates advanced models (digital twin) into the in-house basic monitoring solution NEURON. Take an offshore wind farm for example, the number of instrumented turbines within a wind farm is limited. By applying digital twin with real-time monitoring data of 1 or 2 wind turbines equipped with NEURON system, we are able to evaluate the real condition of the entire farm. Therefore, condition-based operation & maintenance can be achieved to improve the asset availability as well as the lifetime extension.
Morphosense’s solution meets the structural monitoring needs of offshore oil & gaz industry. With the robust IP 68 sensor casing (allowing maximal immersion depth of 100 m) as well as ATEX Z1 (gas) and ATEX Z21 (dust) certification, the NEURON system can safely operates in potentially explosive atmospheres and provides high-quality data to assess the real state of the monitored structures (FPSO, platforms, pipelines etc).