Wireless monitoring algorithm for wind turbine blades using Piezo‐electric energy harvesters

Lim, Dong Won; Mantell, Susan C.; Seiler, Peter

doi:10.1002/we.2023

Cited by 17 publications

(10 citation statements)

References 27 publications

(42 reference statements)

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“…Piezo-electric sensors also have a drift of 60 N/h, which makes them unsuitable for measurements over a large period of time such as in real-time SHM that takes place continuously throughout the WT operation. However, Lim et al [29] proposed a monitoring algorithm using piezosensors charging capacitors on each blade that sends a pulse when full before discharging. Given that the size and stiffness of the gauges on each blade are the same, the blades will experience roughly the same strain energy over time, and the pulses will be sent at the same time.…”

Section: Strainmentioning

confidence: 99%

Real-Time Monitoring of Wind Turbine Blade Alignment Using Laser Displacement and Strain Measurement

Ovenden

Wang

Huang

et al. 2019

Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

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Wind turbine (WT) blade structural health monitoring (SHM) is important as it allows damage or misalignment to be detected before it causes catastrophic damage such as that caused by the blade striking the tower. Both of these can be very costly and justify the expense of monitoring. This paper aims to deduce whether a SICK DT-50 laser displacement sensor (LDS) installed inside the tower and a half-bridge type II strain gauge bridge installed at the blade root are capable of detecting ice loading, misalignment, and bolt loosening while the WT is running. Blade faults were detected by the virtual instrument, which conducted a z-test at 99% and 98% significance levels for the LDS and at 99.5% and 99% significance levels for the strain gauge. The significance levels chosen correspond to typical Z-values for statistical tests. A higher significance was used for the strain gauge as it used a one-tail test as opposed to a two-tail test for the LDS. The two different tests were used to test for different sensitivities of the tests. The results show that the strain gauge was capable of detecting all the mass loading cases to 99.5% significance, and the LDS was capable of detecting misalignment, bolt loosening, and 3 out of 4 mass loading cases to 99% significance. It was able to detect the least severe mass loading case of 11 g at the root to only a 98% significance.

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Section: Strainmentioning

confidence: 99%

Real-Time Monitoring of Wind Turbine Blade Alignment Using Laser Displacement and Strain Measurement

Ovenden

Wang

Huang

et al. 2019

Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

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“…More experts and scholars are investing in this field of research. The nodes of such wireless sensor networks are miniature electronic devices, [1,2] which are small in size and low in power, and are generally powered by batteries. However, the battery needs to be replaced.…”

Section: Introductionmentioning

confidence: 99%

Experiments and Analysis of a Nonlinear Sickle‐Shaped Cantilever Beam Piezoelectric Energy Harvester for Wind Energy Harvesting

Wang

et al. 2022

Physica Status Solidi (a)

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Achieving broadband energy harvesting at low frequencies is a difficult area of research today. To solve the aforementioned problems, herein, a nonlinear sickle‐shaped cantilever beam piezoelectric energy harvester (S‐PEH) for wind energy harvesting is proposed. It has a high‐voltage output in the wind speed range of 5.37–18.23 m s−1. The S‐PEH is consists of a collector and a transducer. The collector converts wind energy into rotating mechanical energy and excites the transducer by means of magnetic coupling, thus realizing the conversion of mechanical energy to electrical energy. The special structure of the transducer's sickle‐shaped cantilever beam type can effectively harvest wind energy in low‐frequency environment and broaden the range of harvesting wind speed in high voltage. The structure and principle of S‐PEH are analyzed by theory and simulation and are experimentally verified. The results show that when the magnet on the rotor is 15 mm away from the magnet of the piezoelectric sheet, the transducer angle is 90°, the load resistance is 100 kΩ, the voltage of the blower is kept at 120 V, and the system has a maximum power of 563 μW. Moreover, it can successfully make low‐power electronics work.

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“…This study presents a new self-powered wireless failure detection method using different power levels from multiple piezoelectric energy harvesters. We utilize a simple but clear fact that piezoelectric material produces a higher voltage when the vibration is stronger and the material strain is higher [23]. When the piezoelectric material is integrated with a proposed power management circuit and a wireless transmitter, one can detect the vibration level by the wireless transmission rate.…”

Section: Introductionmentioning

confidence: 99%

Structural Failure Detection Using Wireless Transmission Rate From Piezoelectric Energy Harvesters

Jung

Eshghi

Lee

2021

IEEE/ASME Trans. Mechatron.

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This paper presents a new self-powered wireless failure detection method that uses different signal transmission rates from piezoelectric energy harvesters. Reliable signal transmission from a wireless sensor network has been challenging due to the power supply issue, often covered by batteries that need regular replacement. Piezoelectric energy harvesting is an excellent option to power the sensors in a vibrational environment, but the power level is limited by input vibrational energy. In this paper, we introduce a new failure detection strategy that uses multifunctional piezoelectric material for vibration sensing and energy harvesting. That is, when the vibration is stronger and the material strain is higher, piezoelectric material produces higher voltage and power. Different power level from multiple piezoelectric sensors is used for sensing structural failure. We design a simple power management circuit that saves power proportional to the piezoelectric voltage so that the piezoelectric patch with higher strain can transmit more frequent wireless signals (higher transmission rate). To store the piezoelectric power, the circuit is composed of a full-bridge rectifier, a Single Pole Double Throw (SPDT) switch, a comparator with hysteresis, and a wireless transmitter (Zigbee). The failure detection performance is investigated in a case study that monitors screw joint failure in a vibrating plate. Reliabilitybased design optimization is conducted to determine the piezoelectric sensor network in terms of the number and sizes of multiple piezoelectric (PZT) patches. The test results show that the proposed system successfully powers the wireless transmitter using the ultra-low scale of power from the PZT sensors (microwatt) and detect the different combination of screw joint failure in the vibrating plate.

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Wireless monitoring algorithm for wind turbine blades using Piezo‐electric energy harvesters

Cited by 17 publications

References 27 publications

Real-Time Monitoring of Wind Turbine Blade Alignment Using Laser Displacement and Strain Measurement

Real-Time Monitoring of Wind Turbine Blade Alignment Using Laser Displacement and Strain Measurement

Experiments and Analysis of a Nonlinear Sickle‐Shaped Cantilever Beam Piezoelectric Energy Harvester for Wind Energy Harvesting

Structural Failure Detection Using Wireless Transmission Rate From Piezoelectric Energy Harvesters

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