Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade
Open accessAbstract
Condition monitoring (CM) of wind turbine blades has significant benefits for wind farm operators and insurers alike. Blades present a particular challenge in terms of operations and maintenance: the wide range of materials used in their construction makes it difficult to predict lifetimes; loading is stochastic and highly variable; and access can be problematic due to the remote locations where turbines are frequently located, particularly for offshore installations. Whilst previous works have indicated that Micro Electromechanical Systems (MEMS) accelerometers are viable devices for measuring the vibrations from which diagnostic information can be derived, thus far there has been no analysis of how such a system would be powered. This paper considers the power requirement of a self-powered blade-tip autonomous system and how those requirements can be met. The radio link budget is derived for the system and the average power requirement assessed. Following this, energy harvesting methods such as photovoltaics, vibration, thermal and radio frequency (RF) are explored. Energy storage techniques and energy regulation for the autonomous system are assessed along with their relative merits. It is concluded that vibration (piezoelectric) energy harvesting combined with lithium-ion batteries are suitable selections for such a system.
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Previous wireless solutions installed on wind turbines mainly included vibration measurements on the wind turbine tower for SHM monitoring purposes rather than acquiring aerodynamic data directly on the blade(s).
“However, previous designs mainly included vibration measurements [4], [17] on the wind turbine tower for SHM monitoring purposes rather than proposing a solution capable of acquiring aerodynamic data directly on the blade(s).”
From Aerosense: A Self-Sustainable and Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines (2023) · cites this paper as [17]
The Introduction describes the proposed wireless monitoring system as being within or on a turbine blade near its tip, not on the tower. It also says earlier studies used accelerometers to assess blade vibrations. The paper concerns vibration-based condition monitoring rather than aerodynamic-data acquisition, but it contradicts the claim about where this cited system measures vibrations. (LLM, conf=0.86)
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Experimental — accuracy not yet measuredWhen the distance between transmitter and receiver is not constant, an RTPC algorithm can significantly reduce power consumption by always keeping the TX power at the optimal point required for the current distance.
“As noted already by O. Esu et al. [17], when the distance between transmitter and receiver is not constant, an RTPC algorithm can significantly reduce power consumption by always keeping the TX power at the optimal point required for the current distance.”
From Aerosense: A Self-Sustainable and Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines (2023) · cites this paper as [17]
Section 3.1 (page not provided) says the transmitter–receiver distance varies as the blade rotates and estimates that adjusting transmit power with blade position could save approximately half the radio transmit power. It presents this as a conditional calculation, not as evidence that an RTPC algorithm always maintains optimal power or has achieved that saving. (LLM, conf=0.88)
Experimental — accuracy not yet measured
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Research works printed but not linked: 27
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Sorted by citations
Polonelli, T., Muller, H., Kong, W., Fischer, R., Benini, L., & Magno, M. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3224307 · Cited by 35 · see citing works
- Authors
- Esu, O. O., Lloyd, S. D., Flint, J. A., & Watson, S. J.
- Affiliations
- Loughborough University (GB)
- Corresponding author
- Flint, J.A.
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 97
- Pages
- 89-96
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W2398855768
- Cited by
- 27
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2022: 6 · 2021: 5 · 2020: 2 · 2019: 4 · 2018: 4 · 2017: 2
- FWCI
- 2.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Renewable Energy (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by)
- Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by)
- Funders
- Loughborough University
- Engineering and Physical Sciences Research Council (EP/L014106/1)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Innovative Energy Harvesting Technologies
- Physical Sciences › Engineering › Aerospace Engineering › Wind Energy Research and Development
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Keywords
- wind turbine blades, condition monitoring, MEMS accelerometer, blade vibration, self-powered devices, energy harvesting, piezoelectric energy harvesting, link budget, energy storage, lithium-ion batteries, offshore wind turbines
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