Wind Turbine Gearbox Fault Diagnosis Using Adaptive Morlet Wavelet Spectrum

Yao, Xingjia; Guo, Changchun; Zhong, Mingfang; Li, Yan; Shan, Guangkun; Zhang, Yanan

doi:10.1109/icicta.2009.375

Cited by 20 publications

(5 citation statements)

References 8 publications

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“…Feng et al [88] described the novel iterative atomic decomposition thresholding (IADT) for planetary gearbox diagnostics by extracting the target gear frequencies from the vibration spectrum. Yao et al [89] also presented use of adaptive Morlet-wavelets for detection of tooth cracks in wind turbine gearboxes.…”

Section: Frequency and Time-frequency Methodsmentioning

confidence: 97%

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Kandukuri

Klausen

Karimi

et al. 2016

Renewable and Sustainable Energy Reviews

171

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Section: Frequency and Time-frequency Methodsmentioning

confidence: 97%

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Kandukuri

Klausen

Karimi

et al. 2016

Renewable and Sustainable Energy Reviews

171

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“…In [2], [3] the authors used the rotor modulating signals spectra for the stator and rotor fault diagnosing. H. Douglas et al [4] utilized wavelet analysis for detection of the stator faults and [28], [29] have used wavelet analysis for distinguishing of fault signals and the background noise in wind turbine. Mohanty and Kar [5] represent fault detection of a multistage gearbox by applying discrete wavelet transformation to demodulate the current signal.…”

Section: -2 Condition Monitoringmentioning

confidence: 99%

Acoustic Emission Condition Monitoring: An Application for Wind Turbine Fault Detection

Purarjomandlangrudi

Nourbakhsh

2013

IJRET

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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE)technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

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“…However, due to the large amount of noise, it is usually difficult to detect a potential failure in a gearbox using vibration signals. Based on adaptive Morlet wavelet filter, Yao Xing-jia et al presents a novel method for crack tooth of wind turbine gearbox [14]. Based on adaptive Morlet wavelet and singular value decomposition, Jiang Yong-hua et al presents a new de-noising method which is applied to feature extraction for wind turbine vibration signals [15].…”

Section: Condition Monitoring and Fault Diagnosis Of Gearboxmentioning

confidence: 99%

A Review of Condition Monitoring and Fault Diagnosis of Wind Turbine Gearbox Using Signal Processing

Zhang

et al. 2012

AMR

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Due to gearbox is one of the high failure rate component in the wind turbine, the research of it has been paid wide attention in recent years. This paper reviewed the two aspects about the wind turbine gearbox. First, some signal process methods including how to determine the threshold were summarized. Then, the condition monitoring and fault diagnosis of gearbox were reviewed using the measured signals. These researches are benefited for reducing economic losses which is caused by the gearbox failure. Based on the above reviews, this paper gives some developmental direction.

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Wind Turbine Gearbox Fault Diagnosis Using Adaptive Morlet Wavelet Spectrum

Cited by 20 publications

References 8 publications

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Acoustic Emission Condition Monitoring: An Application for Wind Turbine Fault Detection

A Review of Condition Monitoring and Fault Diagnosis of Wind Turbine Gearbox Using Signal Processing

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