A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

Malekimoghadam, Reza; Krause, Stefan; Czichon, Steffen

doi:10.1007/978-981-15-9121-1_29

Cited by 8 publications

(6 citation statements)

References 84 publications

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“…A transition from NDT employing ultrasonic testing or transducers to permanent structural health monitoring systems with AI tools and a more sophisticated wireless smart sensor network has been prominent in recent years [33]. Structural health monitoring is a section of CM, which monitors the integrity of constitutive components in terms of Smart, functional sensors [22]. It even helps prevent catastrophic failures, with serious influence on the safety of workers and the environment [18].…”

Section: New Methods Of Clustering Keyword Co-occurrence Networkmentioning

confidence: 99%

“…The work [22] presented a review and classification of numerous structural health monitoring methods as strain measurement utilizing Fiber Bragg Gratings and optical fiber sensors, vibration-based method, active/passive acoustic emission method, ultrasonic methods, and thermal imaging method, relying on the latest studies and positive modern techniques. Since cost-effectiveness, comprehensiveness, and accuracy are the radical features in choosing the structural health monitoring method, the authors provided an extensive summarized review, including methods limitations/capabilities and sensor types.…”

Section: Literature Reviewmentioning

confidence: 99%

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The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Viet

Kravets

2022

Energies

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The development of emerging technologies not only has recently affected current industrial production but also has generated promising manufacturing opportunities that impact significantly on social and economic factors. Exploring upcoming renovation tendencies of technologies prematurely is essential for governments, research and development institutes, and industrial companies in managing strategies to achieve dominant advantages in business competitiveness. Additionally, the prospective changes, the scientific research directions, and the focus of technologies are crucial factors in predicting promising technologies. On the other hand, Industry 4.0 revolutionizes standards and models by accompanying significant technology developments in numerous sectors, including the sector of Smart energy. Moreover, asset performance management is always a prominent topic that has attained prevalence over the last decade because numerous challenges force all industrial companies to optimize their asset usability. However, to the best of our knowledge, no study reported an analysis of technology trends of asset performance management in the Smart energy sector by using proper data mining methods. Hence, this paper aims to fill in this gap and provide an analysis of technology trends of asset performance management in the Smart energy sector by structuring and exploring research subjects, considering problems, and solving methods with numerous experiments on scientific papers and patent data.

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Section: New Methods Of Clustering Keyword Co-occurrence Networkmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Viet

Kravets

2022

Energies

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“…An alternative testing method is ’Through Transmission Testing’. In this method, an ultrasonic transmitter is installed on one side of the material and a receiver is installed on the opposite side [ 54 ]. This method detects, verifies and measures the growth rate of breaks in channelling, vessels, round and hollow shapes, and sometimes non-barrel-shaped vessels.…”

Section: Sensorsmentioning

confidence: 99%

Condition Monitoring of Additively Manufactured Injection Mould Tooling: A Review of Demands, Opportunities and Potential Strategies

Weinert

Tormey

O’Hara

et al. 2023

Sensors

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Injection moulding (IM) is an important industrial process, known to be the most used plastic formation technique. Demand for faster cycle times and higher product customisation is driving interest in additive manufacturing (AM) as a new method for mould tool manufacturing. The use of AM offers advantages such as greater design flexibility and conformal cooling of components to reduce cycle times and increase product precision. However, shortcomings of metal additive manufacturing, such as porosity and residual stresses, introduce uncertainties about the reliability and longevity of AM tooling. The injection moulding process relies on high volumes of produced parts and a minimal amount of tool failures. This paper reviews the demands for tool condition monitoring systems for AM-manufactured mould tools; although tool failures in conventionally manufactured tooling are rare, they do occur, usually due to cracking, deflection, and channel blockages. However, due to the limitations of the AM process, metal 3D-printed mould tools are susceptible to failures due to cracking, delamination and deformation. Due to their success in other fields, acoustic emission, accelerometers and ultrasound sensors offer the greatest potential in mould tool condition monitoring. Due to the noisy machine environment, sophisticated signal processing and decision-making algorithms are required to prevent false alarms or the missing of warning signals. This review outlines the state of the art in signal decomposition and both data- and model-based approaches to determination of the current state of the tool, and how these can be employed for IM tool condition monitoring. The development of such a system would help to ensure greater industrial uptake of additive manufacturing of injection mould tooling, by increasing confidence in the technology, further improving the efficiency and productivity of the sector.

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Section: Introductionmentioning

confidence: 99%

“…In the past decades, much work has been done toward investigations of wind turbine SHM, and the use of various sensing systems for SHM of different parts of wind turbines, including blades, has been reviewed. [7][8][9][10][11][12][13][14] These reviews have shown that vibration-based sensing systems represent a viable option for blade SHM, due to their comparatively low system cost, straight-forward installation, high maturity, and potentially high sensitivity to damages. To minimize turbine downtime, caused by blade damage, damages need to be detected and contained at an early stage, before they grow to a critical size, requiring costly and time-consuming down-tower repairs or even replacements with new blades.…”

mentioning

confidence: 99%

Feasibility study on a full‐scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium‐frequency active vibrations

et al. 2023

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The present work investigates the performance of different features, extracted from vibration‐based data, for structural health monitoring of a 52‐meter wind turbine blade during fatigue testing. An active vibration monitoring system was used during the test campaign, providing periodic excitation of single frequencies in the medium‐frequency range, and using accelerometers to measure the vibration output on different parts of the blade. Based on previous work from the authors, data is available for the wind turbine blade in healthy state, with a manually induced damage, and with progressively increasing damage severity. Using the vibration data, different signal processing methods are used to extract damage‐sensitive features. Time series methods and time‐frequency domain methods are used to quantify the applied active vibration signal. Using outlier analysis, the health state of the blade is classified, and the classification accuracy through use of the different features is compared. Highest performance is generally obtained by auto‐regressive modeling of the vibration outputs, using the auto‐regressive parameters as features. Finally, suggestions for future improvements of the present method toward practical implementation are given.

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A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

Cited by 8 publications

References 84 publications

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Condition Monitoring of Additively Manufactured Injection Mould Tooling: A Review of Demands, Opportunities and Potential Strategies

Feasibility study on a full‐scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium‐frequency active vibrations

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