Bearing Corrosion Failure Diagnosis of Doubly Fed Induction Generator in Wind Turbines Based on Stator Current Analysis

Chen, Xi; Xu, Wei; Islam, Md. Rabiul

doi:10.1109/tie.2019.2917418

Cited by 45 publications

(20 citation statements)

References 50 publications

(66 reference statements)

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“…The interactions between the generator and power electronics can bring issues including bearing currents, additional stress in insulation because of overvoltage in transients and high-voltage slew rates (Chen et al, 2020); therefore, these interactions should be studied and modeled not only for the design but also for O&M. Proper filters and control methods should be integrated according to the generator types and power electronics topologies. For the upscaling of wind generators, various modular and multilevel power converter topologies feeding multiphase windings will be a promising solution.…”

Section: Generatormentioning

confidence: 99%

Wind turbine drivetrains: state-of-the-art technologies and future development trends

et al. 2022

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Abstract. This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the system that converts kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. Offshore development and digitalization are also a focal point in this study. Drivetrain in this context includes the whole power conversion system: main bearing, shafts, gearbox, generator and power converter. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps. The main challenges in drivetrain research identified in this paper include drivetrain dynamic responses in large or floating turbines, aerodynamic and farm control effects, use of rare-earth material in generators, improving reliability through prognostics, and use of advances in digitalization. These challenges illustrate the multidisciplinary aspect of wind turbine drivetrains, which emphasizes the need for more interdisciplinary research and collaboration.

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Section: Generatormentioning

confidence: 99%

Wind turbine drivetrains: state-of-the-art technologies and future development trends

et al. 2022

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“…Moreover, several techniques are described in the literature for monitoring the condition of wind turbine bearings based on electrical signals [95,96], acoustic emissions [97] and vibration measurements [98]. For fluid bearings, eddy current sensors can be used to monitor the oil film thickness [99].…”

Section: Structure and Drivetrain Mechanicsmentioning

confidence: 99%

“…-Non-linear bearing friction [93,94] -Bearing monitoring [95][96][97][98] -Fluid bearing monitoring [99] Rotating reference frame model [105][106][107][108] (Figure 5)…”

Section: Extensionsmentioning

confidence: 99%

Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load

et al. 2021

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The Industry 4.0 concept of a Digital Twin will bring many advantages for wind energy conversion systems, e.g., in condition monitoring, predictive maintenance and the optimisation of control or design parameters. A virtual replica is at the heart of a digital twin. To construct a virtual replica, appropriate modelling techniques must be selected for the turbine components. These models must be chosen with the intended use case of the digital twin in mind, finding a proper balance between the model fidelity and computational load. This review article presents an overview of the recent literature on modelling techniques for turbine aerodynamics, structure and drivetrain mechanics, the permanent magnet synchronous generator, the power electronic converter and the pitch and yaw systems. For each component, a balanced overview is given of models with varying model fidelity and computational load, ranging from simplified lumped parameter models to advanced numerical Finite Element Method (FEM)-based models. The results of the literature review are presented graphically to aid the reader in the model selection process. Based on this review, a high-level structure of a digital twin is proposed together with a virtual replica with a minimum computational load. The concept of a multi-level hierarchical virtual replica is presented.

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“…The fault diagnosis of rolling bearings is closely related to the safe operation of rotating machinery. However, in practical application, the fault data of rolling bearings is often difficult to obtain, as when the new equipment is often in normal operation, there are few failures in a short time, thus normal data are easy to collect, while fault data such as fault location, generation mode, and damage degree are difficult to collect [2]. Secondly, it is necessary to label and sort the collected fault data, but this is a huge workload, time-consuming, and requires a lot of manpower, material, and financial resources.…”

Section: Introductionmentioning

confidence: 99%

A Fault Diagnosis Method for Rolling Bearings Based on Parameter Transfer Learning under Imbalance Data Sets

et al. 2021

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Fault diagnosis under the condition of data sets or samples with only a few fault labels has become a hot spot in the field of machinery fault diagnosis. To solve this problem, a fault diagnosis method based on deep transfer learning is proposed. Firstly, the discriminator of the generative adversarial network (GAN) is improved by enhancing its sparsity, and then adopts the adversarial mechanism to continuously optimize the recognition ability of the discriminator; finally, the parameter transfer learning (PTL) method is applied to transfer the trained discriminator to target domain to solve the fault diagnosis problem with only a small number of label samples. Experimental results show that this method has good fault diagnosis performance.

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Bearing Corrosion Failure Diagnosis of Doubly Fed Induction Generator in Wind Turbines Based on Stator Current Analysis

Cited by 45 publications

References 50 publications

Wind turbine drivetrains: state-of-the-art technologies and future development trends

Wind turbine drivetrains: state-of-the-art technologies and future development trends

Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load

A Fault Diagnosis Method for Rolling Bearings Based on Parameter Transfer Learning under Imbalance Data Sets

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