A review of ground‐based radar as a noncontact sensor for structural health monitoring of in‐field wind turbines blades

Ochieng, Francis Xavier; Hancock, Craig M.; Roberts, Gethin Wyn; Kernec, Julien Le

doi:10.1002/we.2252

Cited by 30 publications

(10 citation statements)

References 81 publications

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“…Recent technological developments have made the noncontact measurements extremely appealing tool for SHM and condition monitoring of various aerospace, civil, and mechanical engineering structures 14 . Techniques such as Laser Doppler Vibrometry (LDV), 15–17 pattern interferometry, 18,19 interferometry, 20 optics, 21 and radar 22–25 made it possible to extract the dynamic response and structural behavior of WTB while not requiring sensors attached to the system being tested. Noncontact measurement techniques have been experimented for WT monitoring, and each possesses its advantages and challenges 26 .…”

Section: Introductionmentioning

confidence: 99%

Multicamera measurement system to evaluate the dynamic response of utility‐scale wind turbine blades

et al. 2020

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Wind turbine blade certification requires static and fatigue testing at a large-scale facility similar to the Wind Technology Testing Center (WTTC) located in Charlestown, Massachusetts. Usually, these tests are conducted by using wire-based sensors such as strain gages, accelerometers, and string potentiometers. These systems are expensive, require a time-consuming installation (e.g., up to 3 weeks and $35 k-$50 k for a strain gage system on a 55-m-long blade), are difficult to deploy on large-sized structures, require additional instrumentations (e.g., power amplifiers and data acquisition systems), and produce results only at a handful of a discrete number of measurement points. In this study, a multicamera measurement system is implemented and experimentally evaluated to obtain full-field displacement and strain over a~12-m-long portion of a~60-m utility-scale wind turbine blade. The proposed system has the potential to streamline the certification process by reducing the blade's preparation and sensor installation cost and time to a few hundreds of dollars (for painting equipment) and a few days for preparing the surface of the blade for the test. Furthermore, operational modal analysis was used in conjunction with the multicamera system to estimate the natural frequencies and mode shapes of the wind turbine blade. The obtained results have shown that the proposed approach can detect in-plane displacement as low as 0.2 mm, mechanical strain with an error below 3% when compared with measurement performed using strain gages, and the first five natural frequencies with an error below 2% when compared with data recorded using traditional wire-based accelerometers. This paper presents these results and provides a summary of the strengths and weaknesses of the proposed optical measurement approach in the context of streamlining the blade certification/testing process and performing vision-based structural dynamic measurements on large-scale structures. K E Y W O R D Sdigital image correlation, fatigue tests, operational modal analysis, stitched field of view, structural health monitoring, wind turbine blades

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Section: Introductionmentioning

confidence: 99%

Multicamera measurement system to evaluate the dynamic response of utility‐scale wind turbine blades

et al. 2020

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“…Radar technology has been employed in many remote sensing applications in SHM [48]. For instance, in Ochieng, Hancock & Roberts [49] the state of the art of ground-based radar applications for in-field monitoring of wind turbines was presented. Moreover, in-field experiments with ground-based radar to measure blade tip deflection was employed.…”

Section: Radar Vibration-basedmentioning

confidence: 99%

A Literature Review of Non-Contact Tools and Methods in Structural Health Monitoring

Vegas

2021

ETOAJ

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In this review paper, the methodology employed was undertaken according to the following steps. First, the literature was collected from the SCOPUS database due to it indexes the largest number of journals and is commonly used in engineering fields [12,13]. The initial search was performed on the 21st of January 2021 with the keywords "structural health monitoring" and with the aim of obtaining exclusively the non-contact literature, the specific query was: TITLE-ABS-KEY ("structural health monitoring" AND non-contact* OR noncontact* OR contactless). The boolean operators (AND, OR, *) are used to include entirely the non-contact literature and to incorporate potential literature with different spellings of non-contact. An initial 623 results were obtained, a further limit was imposed on only English language documents. The search was not limited to a time frame, resulting in 608 documents from 1994 to 2021 plotted in Figure 1. Then, the 608 articles were browsed and 92 irrelevant documents (e.g., medical fields) were excluded and subsequently were classified according to the main method/tool, Table 1 summarizes it. Figure 1: Research publications on the use of non-contact methods and tools in structural health monitoring.Table 1: Non-contact methods/tools in SHM. Methods Number of Articles Percentage Vision-based 146 28.29% Guided Waves 91 17.64% Ultrasound 49 9.50% Vibration 47 9.11% Magnetic Methods 33 6.40% Acoustic based 31 6.01% Displacement based 28 5.43% Thermal Inspection 18 3.49%

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“…is approach may be very effective for structural health monitoring purposes. A different application is presented by Ochieng et al [8]. ey used a noncontact radar observation for structural health monitoring of infield wind turbines blades.…”

Section: Introductionmentioning

confidence: 99%

Effective Processing of Radar Data for Bridge Damage Detection

Owerko

Kuraś

2019

Shock and Vibration

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This paper presents the practical results of the evaluation of the data obtained by using ground-based radar interferometer during measurements carried out on bridge structures. Due to the nature of the objects studied, the authors proposed a comprehensive method of data analysis, which identifies whether the passage of the vehicle did not damage the bridge. The effective use of vehicles as a source of bridge excitation allowed us to first develop a method for determining the damping parameters resistant to potentially occurring beating frequencies. As a result, it is possible to determine these subsets of data registered with radar, for which it is possible to assume compliance with linear systems. This type of data, often omitted in other works, forms the basis for the second important element of the research—an algorithm based on the ARMA model supporting defect detection. The optimization of the performed calculations, in particular the proposed optimal ARMA model order, the method of fault identification based on the DSF parameter, or fault identification based on a nonmetrical Cook’s distance leads to a robust and scalable method. The method’s low computational complexity allows for implementation in real-time solutions. In addition, the distribution of errors and the sensitivity of classifiers based on the DSF parameter and Cook’s distances leaving them will enable the automation of the classification process using machine learning. The proposed method is universal; in particular, it can be used for radar interferometry methods because it is resistant to potentially variable environmental conditions.

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A review of ground‐based radar as a noncontact sensor for structural health monitoring of in‐field wind turbines blades

Cited by 30 publications

References 81 publications

Multicamera measurement system to evaluate the dynamic response of utility‐scale wind turbine blades

Multicamera measurement system to evaluate the dynamic response of utility‐scale wind turbine blades

A Literature Review of Non-Contact Tools and Methods in Structural Health Monitoring

Effective Processing of Radar Data for Bridge Damage Detection

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