scholarly journals Fault Detection for Pitch System of Wind Turbine-Driven Doubly Fed Based on IHHO-LightGBM

2021 ◽  
Vol 11 (17) ◽  
pp. 8030
Author(s):  
Mingzhu Tang ◽  
Zhonghui Peng ◽  
Huawei Wu
Keyword(s):  
Experimental Data ◽  
Control System ◽  
Fault Detection ◽  
False Alarm ◽  
Wind Turbine ◽  
False Alarm Rate ◽  
Optimization Algorithm ◽  
Pitch Control ◽  
Detection Model ◽  
Light Gradient

To address the issue of a large calculation and difficult optimization for the traditional fault detection of a wind turbine-based pitch control system, a fault detection model, based on LightGBM by the improved Harris Hawks optimization algorithm (light gradient boosting machine by the improved Harris Hawks optimization,IHHO-LightGBM) for the wind turbine-based pitch control system, is proposed in this article. Firstly, a trigonometric function model is introduced by IHHO to update the prey escape energy, to balance the global exploration ability and local development ability of the algorithm. In this model, the fault detection false alarm rate is used as the fitness function, and the two parameters are used as the optimization objects of the improved Harris Hawks optimization algorithm, to optimize the parameters, so as to achieve the global optimal parameters to improve the performance of the fault detection model. Three different fault data of the pitch control system in actual operations of domestic wind farms are used as the experimental data, the Pearson correlation analysis method is introduced, and the wind turbine power output is taken as the main state parameter, to analyze the correlation degree of all the characteristic variables of the data and screen the important characteristic variables out, so as to achieve the effective dimensionality reduction process of the data, by using the feature selection method. Three established fault detection models are selected and compared with the proposed method, to verify its feasibility. The experimental data indicate that compared with other algorithms, the fault detecting ability of the proposed model is improved in all aspects, and the false alarm rate and false negative rate are lower.

scholarly journals Cost-Sensitive LightGBM-Based Online Fault Detection Method for Wind Turbine Gearboxes

2021 ◽  
Vol 9 ◽  
Author(s):  
Mingzhu Tang ◽  
Qi Zhao ◽  
Huawei Wu ◽  
Zimin Wang
Keyword(s):  
Fault Detection ◽  
False Alarm ◽  
Wind Turbine ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Rank Correlation ◽  
Spearman Rank Correlation ◽  
Misclassification Cost ◽  
Spearman Rank ◽  
The Cost

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 improvement of classification accuracy and ignore the decrease of missed alarms and the reduction of the average cost. To this end, a new framework is proposed through combining the Spearman rank correlation feature extraction and cost-sensitive LightGBM algorithm for WT gearbox’s fault detection. In this article, features from wind turbine supervisory control and data acquisition (SCADA) systems are firstly extracted. Then, the feature selection is employed by using the expert experience and Spearman rank correlation coefficient to analyze the correlation between the big data of WT gearboxes. Moreover, the cost-sensitive LightGBM fault detection framework is established by optimizing the misclassification cost. The false alarm rate and the missed detection rate of the WT gearbox under different working conditions are finally obtained. Experiments have verified that the proposed method can significantly improve the fault detection accuracy. Meanwhile, the proposed method can consistently outperform traditional classifiers such as AdaCost, cost-sensitive GBDT, and cost-sensitive XGBoost in terms of low false alarm rate and missed detection rate. Owing to its high Matthews correlation coefficient scores and low average misclassification cost, the cost-sensitive LightGBM (CS LightGBM) method is preferred for imbalanced WT gearbox fault detection in practice.

Multiple faults detection and isolation approach applied to a kraft recovery boiler

TAPPI Journal ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 33-41
Author(s):  
YVON THARRAULT ◽  
MOULOUD AMAZOUZ
Keyword(s):  
Fault Detection ◽  
Early Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Principal Component ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Detection Scheme ◽  
Multiple Faults ◽  
Recovery Boiler

Recovery boilers play a key role in chemical pulp mills. Early detection of defects, such as water leaks, in a recovery boiler is critical to the prevention of explosions, which can occur when water reaches the molten smelt bed of the boiler. Early detection is difficult to achieve because of the complexity and the multitude of recovery boiler operating parameters. Multiple faults can occur in multiple components of the boiler simultaneously, and an efficient and robust fault isolation method is needed. In this paper, we present a new fault detection and isolation scheme for multiple faults. The proposed approach is based on principal component analysis (PCA), a popular fault detection technique. For fault detection, the Mahalanobis distance with an exponentially weighted moving average filter to reduce the false alarm rate is used. This filter is used to adapt the sensitivity of the fault detection scheme versus false alarm rate. For fault isolation, the reconstruction-based contribution is used. To avoid a combinatorial excess of faulty scenarios related to multiple faults, an iterative approach is used. This new method was validated using real data from a pulp and paper mill in Canada. The results demonstrate that the proposed method can effectively detect sensor faults and water leakage.

scholarly journals Development of Hardware-in-the-Loop-Simulation Testbed for Pitch Control System Performance Test

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 2031
Author(s):  
Jongmin Cheon ◽  
Jinwook Kim ◽  
Joohoon Lee ◽  
Kichang Lee ◽  
Youngkiu Choi
Keyword(s):  
Control System ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Shear ◽  
Performance Test ◽  
Control Function ◽  
Hardware In The Loop ◽  
Rotor Speed ◽  
Test Bed ◽  
Pitch Control

This paper deals with the development of a wind turbine pitch control system and the construction of a Hardware-in-the-Loop-Simulation (HILS) testbed for the performance test of the pitch control system. When the wind speed exceeds the rated wind speed, the wind turbine pitch controller adjusts the blade pitch angles collectively to ensure that the rotor speed maintains the rated rotor speed. The pitch controller with the individual pitch control function can add individual pitch angles into the collective pitch angles to reduce the mechanical load applied to the blade periodically due to wind shear. Large wind turbines often experience mechanical loads caused by wind shear phenomena. To verify the performance of the pitch control system before applying it to an actual wind turbine, the pitch control system is tested on the HILS testbed, which acts like an actual wind turbine system. The testbed for evaluating the developed pitch control system consists of the pitch control system, a real-time unit for simulating the wind and the operations of the wind turbine, an operational computer with a human–machine interface, a load system for simulating the actual wind load applied to each blade, and a real pitch bearing. Through the several tests based on HILS test bed, how well the pitch controller performed the given roles for each area in the entire wind speed area from cut-in to cut-out wind speed can be shown.

A Pitch Control System for the KaMeWa Wind Turbine

1985 ◽  
Vol 107 (1) ◽  
pp. 47-52 ◽  
Author(s):  
B. S. Liebst
Keyword(s):  
Energy Source ◽  
Control System ◽  
Wind Turbine ◽  
Optimal Control Theory ◽  
Vibration Reduction ◽  
Pitch Control ◽  
Power Oscillations ◽  
Full State ◽  
Tower Vibration ◽  
Gust Response

This study is the design of a pitching blade control system for the National Swedish Board for Energy Source Development KaMeWa wind turbine. Full state controllers are designed utilizing optimal control theory to reduce blade and tower vibration, power oscillations, and improve gust response. The results show that substantial vibration reduction can be obtained with the existing pitch actuators installed presently on the machine.

A Novel Markov Model and its Application to BIT System

2012 ◽  
Vol 239-240 ◽  
pp. 721-725
Author(s):  
Wen Rong Zheng ◽  
Shu Zong Wang
Keyword(s):  
Complex System ◽  
Fault Diagnosis ◽  
Fault Detection ◽  
Markov Model ◽  
False Alarm ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Intermittent Fault ◽  
System A ◽  
Main Factor

Intermittent fault is the main factor for the raise of false alarm during the process of the detection in built-in test (BIT). Two-state Markov model and three-state Markov model for test is built for system fault diagnosis with BIT. According to the application of BIT in some complex system, a comparison of the false alarm rate between two-state Markov model and three-state Markov model is present, which shows we can reduce the false alarm rate (FAR) and improve fault detection rate by using three-state Markov model in BIT.

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