Sensing solutions for assessing and monitoring wind turbines

Rolfes, Raimund; Tsiapoki, Stavroula; Häckell, Moritz

doi:10.1533/9781782422433.2.565

Cited by 7 publications

(4 citation statements)

References 32 publications

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“…It remains necessary for making decisions on maintenance or safety related to wind turbine shutdown [76]. FMEA analysis shows that failure detection can vary from simple visual detection to complex tools and methods.…”

Section: Failure Detectionmentioning

confidence: 99%

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Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

2017

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Abstract:Failure mode and effects analysis (FMEA) has been proven to be an effective methodology to improve system design reliability. However, the standard approach reveals some weaknesses when applied to wind turbine systems. The conventional criticality assessment method has been criticized as having many limitations such as the weighting of severity and detection factors. In this paper, we aim to overcome these drawbacks and develop a hybrid cost-FMEA by integrating cost factors to assess the criticality, these costs vary from replacement costs to expected failure costs. Then, a quantitative comparative study is carried out to point out average failure rate, main cause of failure, expected failure costs and failure detection techniques. A special reliability analysis of gearbox and rotor-blades are presented.

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Section: Failure Detectionmentioning

confidence: 99%

“…Besides, Rolfes et al describe in [76] that rotor-blade monitoring systems available on the market must be considered as being in a development stage, since high downtimes are always registered for this sub-system.…”

Section: Failure Detectionmentioning

confidence: 99%

Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

2017

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“…Another region is the splash zone; section of the turbine that is intermittently in or out of seawater during the turbine's lifecycle. This results in increased cyclic wave loading and hence, corrosion related effects are prone to occur especially in high wave conditions 13 . Based on a structural health monitoring system, such effects can be visually observed in advance, and repairs can be arranged before they become catastrophic failures.…”

Section: Operations and Maintenance Of Floating Offshore Wind Farmmentioning

confidence: 99%

Applications of robotics in floating offshore wind farm operations and maintenance: Literature review and trends

et al. 2022

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Marine operations required to transfer technicians and equipment represent a significant proportion of the total cost of offshore wind. The profile of sites being considered for floating offshore wind farms (FOWFs), e.g., further from the shore and in harsher environments, indicates that these costs need to be assessed by taking into account the maintenance requirements and restricted weather windows. There is an immediate need to investigate the potential use of robotic systems in the wind farm's operations and maintenance (O&M) activities, to reduce the need for costly manned visits. The use of robotic systems can be critical, not only to replace repetitive activities and bring down the levelised cost of energy but also to reduce the health and safety risks by supporting human operators in performing the desired inspections.This paper provides a review of the state of the art in the applications of robotics for O&M of FOWFs. Emerging technology trends and associated challenges and opportunities are highlighted, followed by an outline of the agenda for future research in this domain.

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“…Some of the structural health monitoring (SHM) methods and nondestructive evaluation (NDE) techniques applied to rotor blades are acoustic emission, vibration-based methods, strain measurements, ultrasonic wave propagation, and thermography. 2 Each of these requires the application of different sensor types and has advantages and disadvantages with respect to the extent of damage that can be detected, the capability of damage localization and quantification, or the number of required sensors.…”

Section: Introductionmentioning

confidence: 99%

Damage and ice detection on wind turbine rotor blades using a three-tier modular structural health monitoring framework

Tsiapoki

Häckell

Grießmann

et al. 2017

Structural Health Monitoring

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The increasing number of installed wind turbines has led to a greater need for monitoring of their subcomponents. In particular, damages on rotor blades should be detected as early as possible, since they can cause long and hence expensive standstill times. In this work, a three-tier structural health monitoring framework is employed on the experimental data of a 34-m rotor blade for damage and ice detection. The structural health monitoring framework includes the functions of data normalization by clustering according to environmental and operational conditions, feature extraction, and hypothesis testing. In order to assess the framework and the methods applied with respect to ice detection, an ice accretion test was performed by gradually adding masses at the blade tip. First, a modal test by means of manual and impulse excitation was performed on the healthy blade and for all steps of the ice test. Subsequently, to induce damage, the blade was cyclically excited in edgewise direction for over 1 million cycles until failure occurred at the trailing edge. Finally, the initial modal test was repeated on the damaged blade. Modal parameters from system identification and further damage features, also called condition parameters, are presented and compared to each other. Results from the modal test show that structural changes due to damage at the trailing edge and added mass can be detected by changes in the condition parameters. Nevertheless, it is shown that some condition parameters exhibit higher sensitivity to damage than natural frequencies. Furthermore, a correlation between the amount of added mass and the changes in natural frequencies and some of the condition parameters is shown. For the analysis of the fatigue test, condition parameters were determined with and without prior data clustering according to the applied damage equivalent load, resulting in two realizations of the structural health monitoring framework. Results from the fatigue test show that the majority of condition parameters have good detection performance regarding structural change due to fatigue cracks and due to damage at the trailing edge for various confidence intervals. Finally, it is shown that the detection performance in the case of data clustering according to applied damage equivalent load is higher than without data clustering. This emphasizes the need of data normalization by clustering according to the environmental and operational conditions.

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Sensing solutions for assessing and monitoring wind turbines

Cited by 7 publications

References 32 publications

Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

Applications of robotics in floating offshore wind farm operations and maintenance: Literature review and trends

Damage and ice detection on wind turbine rotor blades using a three-tier modular structural health monitoring framework

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