On the Use of a Single Piezoelectric Strain Sensor for Wind Turbine Planetary Gearbox Fault Diagnosis

Yoon, Jae; He, David; Hecke, Brandon Van

doi:10.1109/tie.2015.2442216

Cited by 66 publications

(33 citation statements)

References 32 publications

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“…The residual error between the actual and predicted power produced was then used for the condition monitoring of wind turbines. The condition monitoring, fault diagnosis and reliability of major wind turbine components and sub-systems, such as blades (Yang et al 2015), drive trains (Yang et al 2015), power converters (Zhou et al 2015), gearboxes (Yoon et al 2015;Du et al 2015) and bearings (Ming et al 2015;Gerber et al 2015), were well covered by the selected contributions. Moreover, it also uses sensors/signals for wind turbines fault diagnosis such as strain sensors (Yang et al 2015;Yoon et al 2015), vibration (Yang et al 2015a, b;Du et al 2015;Gerber et al 2015), acoustic emission (Ming et al 2015) and SCADA data (Long et al;Papatheou et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Reasons for wind turbine generator failures: a multi-criteria approach for sustainable power production

Gowdar¹,

Gowda²

2016

Renewables

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Power generation quantity from wind sector is increasing at much faster rate day by day in the scenario of power systems, which obviously needs reliable operation. Therefore, accurate monitoring and error diagnosis are almost mandatory. This paper aims to identify important errors that affect the performance and can easily detect the faults of wind turbine generators (WTGs). Wind turbines are subjected to different sort of failures; thus, before starting to identify various kinds of errors, it is necessary to identify what kind of failures can be found in the real world which causes healthy operation of WTGs. Out of different errors, error that is caused by the operation of gearbox could stop or reduce the generation of power from WTGs for a long time. Recently, several condition monitoring and fault diagnosis techniques have been introduced in order to minimize downtime and maintenance cost while increasing energy availability and life time service of the wind farms. Different types of sensors have been used for long time in wind turbine fault diagnosis or monitoring systems to collect data of the generator health. Many researchers analyzed wind turbine failures using different software. The present study uses different approaches and prepares a multicriteria decision-making framework using analytic hierarchy process (AHP). The analysis of the data under AHP frame work revealed overspeed guard/turbine out of control error got the top most impediment to the healthy operation of WTGs, and high brake temperature fits in the fifth position among the five different error groups considered.

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Section: Introductionmentioning

confidence: 99%

Reasons for wind turbine generator failures: a multi-criteria approach for sustainable power production

Gowdar¹,

Gowda²

2016

Renewables

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“…Accelerometers are some of the most frequently used sensors and are often used to measure global information, such as frequency and mode shape [85]. Strain gauges not only provide localized measurement, they are also good at capturing static or dynamic measurands at a relatively low variation rate [86]. Fiber-optic sensors measure local strain, are immune to electromagnetic interference, and are suitable for long-distance data transportation [87].…”

Section: Sensor Techniques and Signal Acquisitionmentioning

confidence: 99%

Basic research on machinery fault diagnostics: Past, present, and future trends

et al. 2017

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Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.

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“…Serious faults even lead to fatal casualties such as the LN-OJF helicopter accident at Norway in June 2016, which are caused by the main planetary gearbox fault. Therefore, mechanical fault diagnosis like fault mechanism and fault feature extraction has caused more and more attention [1][2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…Mishra et al [4] diagnosed bearing fault under slow speed operation by wavelet de-noising. Yoon et al [5] preprocessed the torsional Technical Editor: José Roberto de França Arruda. vibration signal of planet gearbox by time-domain synchronous average and extracted their characteristic parameters for fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Experimental application of stochastic resonance based on Wood–Saxon potential on fault diagnosis of bearing and planetary gearbox

Chi

Kang

Zhang

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

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Bearing and planetary gearbox are important for rotating machinery. However, their faults often cause the stop of the machinery or even fatal casualties. Vibration signal contains the status information of the rotating machinery, which is covered by the strong noise. Stochastic resonance (SR) is a noise-benefit phenomenon, which can detect the weak fault characteristic signal from the vibration signal under strong noise. To detect the fault of bearing or planetary gearbox effectively, SR based on Wood-Saxon potential which only has on potential well called WSSR is studied, and a novel fault diagnosis strategy based on WSSR is proposed. The effect of every WSSR parameter, anti-noise capability of WSSR under different noise intensities and optimal frequency response of WSSR under different driving frequency are analyzed by simulation. To verify the effectiveness of our proposed fault diagnosis strategy based on WSSR, three preset fault tests of bearing and two of planetary gearbox are carried out. Bi-stable SR is also used for comparison. The results show that our proposed fault diagnosis strategy is more effective for the fault detection of bearing and planetary gearbox than bi-stable SR.

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On the Use of a Single Piezoelectric Strain Sensor for Wind Turbine Planetary Gearbox Fault Diagnosis

Cited by 66 publications

References 32 publications

Reasons for wind turbine generator failures: a multi-criteria approach for sustainable power production

Reasons for wind turbine generator failures: a multi-criteria approach for sustainable power production

Basic research on machinery fault diagnostics: Past, present, and future trends

Experimental application of stochastic resonance based on Wood–Saxon potential on fault diagnosis of bearing and planetary gearbox

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