Vibration-based SHM System: Application to Wind Turbine Blades

Tcherniak, Dmitri; Mølgaard, Lasse Lohilahti

doi:10.1088/1742-6596/628/1/012072

Cited by 30 publications

(37 citation statements)

References 3 publications

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“…For practical applications in large wind turbine blades, this localization accuracy is considered to be acceptable and contains much more information on the damage position than conventional techniques such as vibration‐based SHM approaches . The modal properties monitoring is only able to identify relatively large defects in the rotor blades, but information on the damage location can be obtained only in special cases …”

Section: Resultsmentioning

confidence: 99%

Radar‐based structural health monitoring of wind turbine blades: The case of damage localization

et al. 2018

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This short communication reports on a radar approach for structural health monitoring of wind turbine blades. Therefore, a bistatic frequency‐modulated continuous wave (FMCW) radar in the frequency range from 33.4 to 36.0 GHz has been developed and tested experimentally using a laboratory wind turbine demonstrator. A differential damage localization framework is presented here that exploits signal differences between measurements from the intact and the damaged structure for 3D imaging of the defect. We have achieved the localization of a 30‐mm cut in a glass fiber composite structure as well as the localization of a water pack at the backside of the specimen with a localization error of several centimeters.

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Section: Resultsmentioning

confidence: 99%

Radar‐based structural health monitoring of wind turbine blades: The case of damage localization

et al. 2018

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“…Even though several available sensor types can be applied for CM of blades, e.g., strain gauges, vibrational sensors, fiber optics, and acoustic emission sensors [11,12], the CM of blades is still in the developmental stage [13]. Laboratory testing [14] and prototype testing have been made, and studies of the rentability have been performed [15], but the long-term reliability and durability have yet to be tested, and only a few turbines have blade CM systems installed. Therefore, methods that rely solely on online CM will have limited applicability for blades of wind turbines currently installed, unless CM systems are installed later, which is more expensive compared to sensors embedded during production [11].…”

Section: Deterioration Modelling For Wind Turbine Bladesmentioning

confidence: 99%

Bayesian Estimation of Remaining Useful Life for Wind Turbine Blades

Nielsen

Sørensen

2017

Energies

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Abstract:To optimally plan maintenance of wind turbine blades, knowledge of the degradation processes and the remaining useful life is essential. In this paper, a method is proposed for calibration of a Markov deterioration model based on past inspection data for a range of blades, and updating of the model for a specific wind turbine blade, whenever information is available from inspections and/or condition monitoring. Dynamic Bayesian networks are used to obtain probabilities of inspection outcomes for a maximum likelihood estimation of the transition probabilities in the Markov model, and are used again when updating the model for a specific blade using observations. The method is illustrated using indicative data from a database containing data from inspections of wind turbine blades.

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“…Therefore, the present paper serves to investigate this in the context of a pre-and post-damage operating Vestas V27 wind turbine blade instrumented with an actuator plus 12 accelerometers. In this regard, it is noticed that the actuator excitation, as originally suggested in [14], serves to excite the high-frequency vibration interval. This is of general interest as studies have proved that the low-frequency content, which is typically excited in ambient vibrations, is insensitive towards blade damages [7], [10].…”

Section: Introductionmentioning

confidence: 96%

Damage detection in an operating Vestas V27 wind turbine blade by use of outlier analysis

Ulriksen

Tcherniak

Damkilde

2015

2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings

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The present paper explores the application of a well-established vibration-based damage detection method to an operating Vestas V27 wind turbine blade. The blade is analyzed in a total of four states, namely, a healthy one plus three damaged ones in which trailing edge openings of increasing sizes are introduced. In each state, the blade is subjected to controlled actuator hits, yielding forced vibrations that are measured in a total of 12 accelerometers; of which 11 are used for damage detection. The dimensionality of these acceleration data is reduced by means of principal component analysis (PCA), and then a reduced set of selected principal scores are employed as damage features in the Mahalanobis metric in order to detect damageinduced anomalies.

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Vibration-based SHM System: Application to Wind Turbine Blades

Cited by 30 publications

References 3 publications

Radar‐based structural health monitoring of wind turbine blades: The case of damage localization

Radar‐based structural health monitoring of wind turbine blades: The case of damage localization

Bayesian Estimation of Remaining Useful Life for Wind Turbine Blades

Damage detection in an operating Vestas V27 wind turbine blade by use of outlier analysis

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