Online detection of wind turbine generators
Convolutional neural network framework for wind turbine
Deep neural network (NN) applications for wind turbine fault detection can benefit from the more fine-grained view of data that is provided by a higher temporal resolution. 13 AI models have been applied to high-frequency vibration data in a few works; however, these have usually first applied classical signal processing approaches to generate
Simplified automatic fault detection in wind turbine induction generators
BRIGHAM ET AL. machine terminal quantity analysis, for detecting induction machine faults.10-12 Stator current is commonly used in MCSA since it is sensitive to the rotor faults, and it is a suitable method to obtain a diagnostic index allowing the discrimination between faulty and healthy conditions. 13 Rotor asymmetry has been shown to induce a change in the generator
(PDF) An Early Fault Detection Method for Wind Turbine Main
An Early Fault Detection Method for Wind Turbine Main Bearings Based on Self-Attention GRU Network and Binary Segmentation Changepoint Detection Algorithm. May 2023; Energies 16(10):4123;
Cost-Sensitive LightGBM-Based Online Fault Detection Method for Wind
Introduction. With the increase in the capacity of wind turbine assembly machines, wind power generation brings economic benefits and also raised important crucial challenges related to reliability (Qiao and Lu, 2015; Wang et al., 2019).On the one hand, wind power generation technology has been developed rapidly, but wind turbine (WT) fault detection and condition
Fault detection of wind turbine system based on data-driven
Some wind turbines can produce power up to 4.8 MW . However, wind turbines can be subjected to several faults whether they are sensor faults, actuator faults, and system faults. For a wind turbine, the sensor faults include pitch position sensor faults, rotor speed sensor faults, and generator speed sensor faults.
Predictive maintenance for offshore wind turbines through deep
Tang et al. employ an improved lightGBM algorithm for online fault detection in gearboxes of wind turbines. Farrar et al. give an To achieve this goal, we use the following normalized inputs: wind turbine status, measured wind speed, actual generator power, absolute yaw position, rotor speed, and yaw motor status, as detailed in 2.1.2. We
Online health assessment and fault prediction for wind turbine generator
A health assessment and fault prediction method for wind turbine generators is proposed in this article. In health assessment module, considering generator status transferring along with environment and wind turbine–self operating, variables under wind turbine normal working are divided into two parameter spaces and recognized, namely operating conditions
A Wind Turbine Bearing Fault Detection Method Based on
Purpose This research tackles the complexities of detecting bearing faults in wind turbines, which involves non-Gaussian, non-stationary signals submerged in diverse noise sources. The study aims to present an effective algorithm to address these challenges. Methods The proposed algorithm integrates ICEEMDAN decomposition for signal analysis under
Online Wind Turbine Fault Detection Article through Automated
WIND ENERGY Wind Energ. 2009; 12:574–593 Published online 20 January 2009 in Wiley Interscience () DOI: 10.1002/we.319 Research Article * Correspondence to: A. Zaher, Electronic & Electrical Engineering Department, University of Strathclyde, 204 George St, Royal College Building, Glasgow G1 1XW, UK.
Cost-Sensitive LightGBM-Based Online Fault Detection Method for Wind
In practice, faulty samples of wind turbine (WT) gearboxes are far smaller than normal samples during operation, and most of the existing fault diagnosis methods for WT gearboxes only focus on the
Online nonintrusive condition monitoring and fault detection for wind
The goal of this dissertation research is to develop online nonintrusive condition monitoring and fault detection methods for wind turbine generators (WTGs). The proposed methods use only the
The detection of generator bearing failures on wind turbines
Research into the detection of anomalies in SCAD A data of wind turbines is currently a hot topic. This strong interest is driven b y the fact that more and more sensor data from wind
Detection and classification of faults in pitch-regulated wind turbine
The fast growing wind industry requires a more sophisticated fault detection approach in pitch-regulated wind turbine generators (WTG), particularly in the pitch system that has led to the highest failure frequency and downtime.
Wind turbines anomaly detection based on
operational mode information at wind turbine level, which is significant for anomaly detection. SCADA solution can be applied as a cheaper way to prevent energy losses or wind turbine faults detection, contrasting with the CBM approach [4–9]. Kim et al. [4] used wind turbines measurements to developed anomaly detection
Condition monitoring in wind turbines: a review
Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks. Appl. Energy, 305 (2022), p. 117925. View PDF A threshold self-setting condition monitoring scheme for wind turbine generator bearings based on deep convolutional generative adversarial networks. Measurement, 167 (2021), p
Cost-Sensitive LightGBM-Based Online Fault Detection
Zhang et al. (2018) proposed a wind turbine fault diagnosis method combining Random Forest (RF) and extreme gradient boosting (XGBoost) that were used to establish the data-driven WT fault detection framework. RF is used to rank the
Enhanced Fault Detection of Wind Turbine Using eXtreme
Wind turbines serve a vital role in renewable energy generation but operate in harsh environments and endure variable loading. Monitoring wind turbine blade conditions is therefore critical to prevent unscheduled downtime and revenue losses. This research investigates the application of machine learning techniques for detection, monitoring, and
Wind turbines anomaly detection based on power curves and
However, the output power of a wind turbine significantly depends on the amplitude of turbulence, wind speed and direction, and hence every wind turbine model has a unique power curve. The IEC procedure also ignores the fast wind fluctuations through the results of 10 min averaging, obtaining the behaviour of the machine-independent of wind fluctuations [
Vibration Signature of Generator-Side Converter Faults for Wind Turbines
2.1 Models of Generator and Converter. Direct-drive wind turbine is one of the mainstream topologies by eliminating gearboxes and adopting full power converters to improve system efficiency and reliability [] gure 1 shows a typical direct-drive wind turbine topology, including blades, main shaft, permanent magnet synchronous generator (PMSG), full power
Fault detection of wind turbine based on SCADA data analysis
The wind turbine was repaired on 4th June 2014 due to the fault of alternator stator insulation and low rotor phase. The data are firstly preprocessed, the abnormal data points such as stopping and bad points are removed. Meanwhile, the operation states wind turbine such as wind turbine startup and generator failure are saved.
Fault Detection and Condition Monitoring of
Research on fault detection (FD) and condition monitoring (CM) of rotating electrical generators for modern wind turbines has addressed a wide variety of technologies. Among these, permanent magnet synchronous
An NN-Based Fault Diagnosis Method for Offshore
2 天之前· The generator of the wind turbine plays an important role in converting mechanical energy into electrical energy. According to statistics, the failure rate of wind turbine generators that have been operating in complex working
Intelligent Incipient Fault Detection in Wind Turbines based on
state of health and possible flaws that the wind turbine may have to succeed in the diagnosis is necessary [34]. Research uses data specific to wind turbine, for example, short circuit current [53], axial flow [13], and Vibration [35, 60, 41], used in this work. Others analyze the wind turbine dataset to detect failures [11,70].
Fault Detection Method for Wind Turbine Generators Based on
Aiming at the problem that existing wind turbine gearbox fault prediction models often find it difficult to distinguish the importance of different data frames and are easily interfered with by non-important and irrelevant signals, thus causing a reduction in fault diagnosis accuracy, a wind turbine gearbox fault prediction model based on the attention-weighted long short-term
Adaptive fault detection in wind turbine via RF and
1 Introduction. Recently, wind energy has been considered as one of the most promising renewable energy resources. For the great competitive advantages of mature technique, low cost and little influence on environment,
Cost-Sensitive Extremely Randomized Trees Algorithm
To solve the problem of imbalanced classification in wind turbine generator fault detection, a cost-sensitive extremely randomized trees (CS-ERT) algorithm is proposed in this paper, in which the cost-sensitive learning method is
Fault detection of a wind turbine generator bearing
Wind Speed—In a wind turbine, wind turns its rotor which in-turn rotates the shaft of the generator. Thus, wind speed determines the rotational speed of the generator shaft and bearing. Additionally, since the nacelle is not
Convolutional neural network framework for wind
This paper presents a scalable and lightweight convolutional neural network (CNN) framework using high-dimensional raw condition monitoring data for the automatic detection of multiple wind turbine electromechanical faults.
Simplified automatic fault detection in wind turbine induction generators
This paper presents a simplified automated fault detection scheme for wind turbine induction generators with rotor electrical asymmetries. Fault indicators developed in previous works have made use of the presence of significant spectral peaks in the upper sidebands of the supply frequency harmonics; however, the specific location of these peaks
Fault detection of wind turbines using SCADA data and genetic
Wind energy has become a significant competitor to traditional fossil fuel energy. The use of renewable energy (RE) in the generation of electricity and transportation has grown in popularity [1].Significant growth in wind turbines makes us more adept at extracting energy due to the increasing interest in renewable energy on earth [2], [3].With the growing interest in using
6 FAQs about [Online detection of wind turbine generators]
What is a fault detection method for a wind turbine generator?
Conventional fault detection methods for wind turbine (WT) generators often grapple with inadequate warning times and poor portability. These issues contribute to heightened safety risks and an increased false positive rate (FPR) and false negative rate (FNR).
Do wind turbines have fault detection schemes?
It is worth mentioning that the parts of wind turbines may have malfunctions that should be detected using fault detection schemes. As mentioned in the introduction section, there are two sources of the wind turbine systems data including the SCADA and simulated data.
Can vibration analysis detect wind turbine drivetrain faults?
Teng W et al (2021) Vibration analysis for fault detection of wind turbine drivetrains—a comprehensive investigation. Sensors 21:1686 Wen X, Xu Z (2021) Wind turbine fault diagnosis based on Relieff-PCA and DNN.
Does SCADA data provide a fault detection system for wind turbines?
Dao PB (2022) Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data. Renewable Energy 185:641–654 Yin S, Wang G, Karimi HR (2014) Data-driven design of robust fault detection system for wind turbines. Mechatronics 24:298–306
What are sensor faults in a wind turbine?
For a wind turbine, the sensor faults include pitch position sensor faults, rotor speed sensor faults, and generator speed sensor faults. On the other hand, the actuator faults are due to converter coupling faults and pitch system faults. Furthermore, system faults can be found in the wind turbine drive train.
Are data-driven fault detection strategies effective in process monitoring of wind turbine systems?
Although significant efforts have been made in the process monitoring of wind turbine systems, to the best knowledge of the authors, there is no systematic comparative studies of data-driven fault detection strategies are available in the literature. Therefore, this is the main motivation behind this study.
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