2017
DOI: 10.3390/s17122928
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Wireless Concrete Strength Monitoring of Wind Turbine Foundations

Abstract: Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods… Show more

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Cited by 14 publications
(4 citation statements)
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“…The evolution of the compressive strength of the geoploymer is shown in Figure 7, with a non-linear fit obtained as outlined in [97]. The mean value of compressive strength for 28 days met standard BS EN 1504-3:2005 for a non-structural class R1 repair; however, there was a growing degree of strength variability in samples as they cured.…”
Section: Resultsmentioning
confidence: 88%
“…The evolution of the compressive strength of the geoploymer is shown in Figure 7, with a non-linear fit obtained as outlined in [97]. The mean value of compressive strength for 28 days met standard BS EN 1504-3:2005 for a non-structural class R1 repair; however, there was a growing degree of strength variability in samples as they cured.…”
Section: Resultsmentioning
confidence: 88%
“…These devices can be easily embedded in various structural members, such as beams, columns, and slabs. Perry et al [4] employed a network of 11 thermocouple sensors to determine the strength of an concrete foundation by using the maturity method. In addition to the maturity index, which is a function of the temperature and time, smart aggregates embedded with piezoceramic material are used for determining the compressive strength by adopting wireless sensors.…”
Section: Introductionmentioning
confidence: 99%
“…John et al 40 developed a cost-effective IoT-enabled system for real-time monitoring of early-age compressive concrete strength. Perry et al 44 trained an artificial neural network using wireless thermocouple measurements and cube compression tests to estimate the concrete strength of wind turbine foundations. Navabian 45 developed an SHM system containing a wireless smart network, data management and analysis platform, and vibration-based nonlinearity method for damage evaluation in large civil structures.…”
Section: Introductionmentioning
confidence: 99%