scholarly journals Alternative fault detection and diagnostic using information theory quantifiers based on vibration time-waveforms from condition monitoring systems: Application to operational wind turbines

2021 ◽  
Vol 164 ◽  
pp. 1183-1194
Author(s):  
Gustavo de Novaes Pires Leite ◽  
Guilherme Tenório Maciel da Cunha ◽  
José Guilhermino dos Santos Junior ◽  
Alex Maurício Araújo ◽  
Pedro André Carvalho Rosas ◽  
...  
Keyword(s):  
Information Theory ◽  
Fault Detection ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Monitoring Systems ◽  
Condition Monitoring Systems ◽  
Vibration Time

scholarly journals Remote data acquisition for condition monitoring of wind turbines

2015 ◽  
Vol 6 (2) ◽  
pp. 10
Author(s):  
Bavo De Maré ◽  
Jacob Sukumaran ◽  
Mia Loccufier ◽  
Patrick De Baets
Keyword(s):  
Data Acquisition ◽  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Good Condition ◽  
Offshore Wind ◽  
Monitoring Systems ◽  
Offshore Wind Turbines ◽  
Condition Monitoring Systems ◽  
Remote Data

While the number of offshore wind turbines is growing and turbines getting bigger and more expensive, the need for good condition monitoring systems is rising. From the research it is clear that failures of the gearbox, and in particular the gearwheels and bearings of the gearbox, have been responsible for the most downtime of a wind turbine. Gearwheels and bearings are being simulated in a multi-sensor environment to observe the wear on the surface.

scholarly journals The specification and testing of a Horizontal Axis Tidal Turbine Rotor Monitoring approach

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Matthew Allmark ◽  
Paul Prickett ◽  
Roger Grosvenor ◽  
Carwyn Frost
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Fault Detection ◽  
Condition Monitoring ◽  
Turbulence Intensity ◽  
Turbine Rotor ◽  
Horizontal Axis ◽  
Monitoring Systems ◽  
Tidal Turbine ◽  
Condition Monitoring Systems

The sustainable deployment of Horizontal Axis Tidal Turbines will require effective management and maintenance functions. In part, these can be supported by the engineering of suitable condition monitoring systems. The development of such a system is inevitably challenging, particularly given the present limited level of operational data associated with installed turbines during fault onset. To mitigate this limitation, a computational fluid dynamics model is used to simulate the operational response of a turbine under a known set of fault conditions. Turbine rotor imbalance faults were simulated by the introduction of increasing levels of pitch angle offset for a single turbine blade. The effects of these fault cases upon cyclic variations in the torque developed by the turbine rotor were then used to aid creation of a condition monitoring approach. A parametric tidal turbine rotor model was developed based on the outputs of the computational fluid dynamics models. The model was used to facilitate testing of the condition monitoring approach under a variety of more realistic conditions. The condition monitoring approach showed good performance in fault detection and diagnosis for simulations relating to turbulence intensities of up to 2 %. Finally, the condition monitoring approach was applied to simulations of 10 % turbulence intensity. Under the 10 % turbulence intensity case the rotor monitoring approach was successfully demonstrated in its use for fault detection. The paper closes with discussion of the effectiveness of using computational fluid dynamics simulations extended by parametric models to develop condition monitoring systems for horizontal axis tidal turbine applications.

Quantifying the Economic Benefits of Wind Turbine Condition Monitoring

2014 ◽  
Author(s):  
Richard Williams ◽  
Christopher Crabtree ◽  
Simon Hogg
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Economic Benefits ◽  
Offshore Wind ◽  
Monitoring Systems ◽  
Financial Benefit ◽  
Condition Monitoring Systems ◽  
Detection Ratio

This paper presents a cost benefit analysis for wind turbine condition monitoring systems. It is widely acknowledged that performing proactive maintenance actions can reduce the number and severity of wind turbine failures. However, the use of condition monitoring systems to determine the health of the system is often viewed as costly and of little financial benefit. In this analysis the increased costs associated with condition monitoring were offset by the positive effect of early fault detection, with faults being detected before they reach a critical stage. The continual growth in turbine output and the emergence of far-offshore wind farm sites make the economic case for cost of energy reduction from timely and accurate fault detection ever stronger. An assessment of the capability of the monitoring system was undertaken through allowance for the true to false condition monitoring detection ratio and the ability of the system to detect the severity of a fault. The analysis also compared onshore and offshore assets where the access availability can severely influence the downtime. The results show a clear financial justification for wind turbine condition monitoring and indicate the successful detection ratio required before a condition monitoring system can offer a financial benefit.

Cointegration Modelling for Health and Condition Monitoring of Wind Turbines - An Overview

2022 ◽  
Author(s):  
P.B. Dao
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Control Charts ◽  
Failure Detection ◽  
Short Review ◽  
Early Failure ◽  
Promising Tool ◽  
Condition Monitoring Systems ◽  
Scientists And Engineers

Abstract. The cointegration method has recently attracted a growing interest from scientists and engineers as a promising tool for the development of wind turbine condition monitoring systems. This paper presents a short review of cointegration-based techniques developed for condition monitoring and fault detection of wind turbines. In all reported applications, cointegration residuals are used in control charts for condition monitoring and early failure detection. This is known as the residual-based control chart approach. Vibration signals and SCADA data are typically used with cointegration in these applications. This is due to the fact that vibration-based condition monitoring is one of the most common and effective techniques (used for wind turbines); and the use of SCADA data for condition monitoring and fault detection of wind turbines has become more and more popular in recent years.

Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data

2018 ◽  
Vol 116 ◽  
pp. 107-122 ◽  
Author(s):  
Phong B. Dao ◽  
Wieslaw J. Staszewski ◽  
Tomasz Barszcz ◽  
Tadeusz Uhl
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Cointegration Analysis

A Survey of Condition Monitoring Systems Operation in Romanian Transmission Substations

2021 ◽  
Author(s):  
Bogdan Leu ◽  
Bogdan-Adrian Enache ◽  
Florin-Ciprian Argatu ◽  
Marilena Stanculescu
Keyword(s):  
Condition Monitoring ◽  
Monitoring Systems ◽  
Condition Monitoring Systems
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