Methods for Advanced Wind Turbine Condition Monitoring and Early Diagnosis: A Literature Review

Condition monitoring and early fault diagnosis for wind turbines have become essential industry practice as they help improve wind farm reliability, overall performance and productivity. If not detected and rectified at early stages, some faults can be catastrophic with significant loss or revenue along with interruption to the business relying mainly on wind energy. The failure of Wind turbine results in system downtime and repairing or replacement expenses that significantly reduce the annual income. Such failures call for more systematized operation and maintenance schemes to ensure the reliability of wind energy conversion systems. Condition monitoring and fault diagnosis systems of wind turbine play an important role in reducing maintenance and operational costs and increase system reliability. This paper is aimed at providing the reader with the overall feature for wind turbine condition monitoring and fault diagnosis which includes various potential fault types and locations along with the signals to be analyzed with different signal processing methods

Applying thermophysics for wind turbine drivetrain fault diagnosis using SCADA data

Cost-effective wind turbine diagnosis using SCADA data is a promising technology for future intelligent wind farm operation and management. This paper presents a thermophysics based method for wind turbine drivetrain fault diagnosis. A synthesized thermal model is formed by incorporating thermal mechanisms of the drivetrain into a wind turbine system model. Applications of the model are demonstrated in case studies of the gearbox and generator comparing simulation results and SCADA data analysis. The results show nonlinearity of the gearbox oil temperature rise with wind speed/output power that can effectively indicate gearbox efficiency degradation, which may be attributed to gear transmission problems such as gear teeth wear. Electrical generator faults, such as ventilation failure and winding voltage unbalance will cause changes to heat transfer and result in temperature changes that can be used for diagnosis purposes. This is shown by different patterns of stator winding temperature associated with power generation, while the simulation reveals the thermal mechanism. The method can be applied to diagnose some failure modes which are hard to identify from vibration analysis. The developed thermal model can play a central role for the purpose of fault diagnosis, by deriving relationships between various SCADA signals and revealing changes in the thermophysics of wind turbine operation

Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines

Electrical and electronic components are very important subcomponents in modern industrial wind turbines. Complex multimegawatt wind turbines are continuously being installed both onshore and offshore, continuously increasing the demand for sophisticated electronic and electrical components. In this work, most critical electrical and electronic components in industrial wind turbines have been identified and the applicability of appropriate condition monitoring processes simulated. A fault tree dynamic analysis has been carried out by binary decision diagrams to obtain the system failure probability over time and using different time increments to evaluate the system. This analysis allows critical electrical and electronic components of the converters to be identified in different conditions. The results can be used to develop a scheduled maintenance that improves the decision making and reduces the maintenance costs

Effective algorithms for real-time wind turbine condition monitoring and fault-detection

Reliable condition monitoring (CM) can be an effective means to significantly reduce wind turbine (WT) downtime, operations and maintenance costs and plan preventative maintenance in advance. The WT generator voltage and current output, if sampled at a sufficiently high rate (kHz range), can provide a rich source of data for CM. However, the electrical output of the WT generator is frequently shown to be complex and noisy in nature due to the varying and turbulent nature of the wind. Thus, a fully satisfactory technique that is capable to provide accurate interpretation of the WT electrical output has not been achieved to date. The objective of the research described in this thesis is to develop reliable WT CM using advanced signal processing techniques so that fast analysis of non-stationary current measurements with high diagnostic accuracy is achieved. The diagnostic accuracy and reliability of the proposed techniques have been evaluated using data from a laboratory test rig where experiments are performed under two levels of rotor electrical asymmetry faults. The experimental test rig was run under fixed and variable speed driving conditions to investigate the kind of results expected under such conditions. An effective extended Kalman filter (EKF) based method is proposed to iteratively track the characteristic fault frequencies in WT CM signals as the WT speed varies. The EKF performance was compared with some of the leading WT CM techniques to establish its pros and cons. The reported experimental findings demonstrate clear and significant gains in both the computational efficiency and the diagnostic accuracy using the proposed technique. In addition, a novel frequency tracking technique is proposed in this thesis to analyse the non-stationary current signals by improving the capability of a continuous wavelet transform (CWT). Simulations and experiments have been performed to verify the proposed method for detecting early abnormalities in WT generators. The improved CWT is finally applied for developing a new real-time CM technique dedicated to detect early abnormalities in a commercial WT. The results presented highlight the advantages of the improved CWT over the conventional CWT to identify frequency components of interest and cope with the non-linear and non-stationary fault features in the current signal, and go on to indicate its potential and suitability for WT CM.</div

Studies in Electrical Machines & Wind Turbines associated with developing Reliable Power Generation

The publications listed in date order in this document are offered for the Degree of Doctor of Science in Durham University and have been selected from the author’s full publication list. The papers in this thesis constitute a continuum of original work in fundamental and applied electrical science, spanning 30 years, deployed on real industrial problems, making a significant contribution to conventional and renewable energy power generation. This is the basis of a claim of high distinction, constituting an original and substantial contribution to engineering science

Integrated condition monitoring of industrial wind turbines

The continuous growth in wind turbine power ratings and numbers has led to increased demands in inspection and maintenance due to the more significant financial and operational consequences of unexpected wind turbine failure. The fact that wind farms are commonly located at remote sites with potentially poor accessibility means it is necessary to reduce the need for corrective maintenance through evolution to preventive and prognostic maintenance activities. Prognostic repair schedules can be employed in order to optimise maintenance and contribute to the minimisation of the overall operational costs of wind farms. The present study presents the development and qualitative evaluation of remote condition monitoring methodologies for the evaluation of the wind turbine power electronics and gearboxes. The failures of power converter and gearbox components result in significant wind turbine downtime and associated repair costs. Effective condition monitoring can enable the timely diagnosis of faults in order to prevent unexpected failures and loss of electricity production, contributing towards a noteworthy increase the reliability, availability, maintainability and safety (RAMS) of wind farms. Within this study two customised test rigs have been employed to simulate various of faults and assess the capability of RCM in diagnosing this fault effectively. In addition, field measurements have been carried out and correlated to the findings of the test rig experiments. In this study, it has been possible to identify these variables qualitatively, but the quantitative investigation is still pending and will be most likely the subject of several future studies in this field. The present thesis provides a compact summary of the analysis of the key findings of the experimental work performed within the context of the OPTIMUS FP7 European collaborative project

Wind Turbine Tribology

Wind power is of increasing interest in society due to its prospects as an environmentally friendly source of renewable energy. The use of wind turbines to extract electrical energy from wind can be dated back to the late-1800s, with the 12 kW windmill generator by Charles Brush, as well as the mid-1900s, with the 1250 kW Smith-Putnam wind turbine. Developments in the wind industry were encouraged by the oil crisis in 1973

Wind Turbine Generator Condition Monitoring via the Generator Control Loop

This thesis focuses on the development of condition monitoring techniques for application in wind turbines, particularly for offshore wind turbine driven doubly fed induction generators. The work describes the significant development of a physical condition monitoring Test Rig and its MATLAB Simulink model to represent modern variable speed wind turbine and the innovation and application of the rotor side control signals for the generator fault detection. Work has been carried out to develop a physical condition monitoring Test Rig from open loop control, with a wound rotor induction generator, into closed loop control with a doubly fed induction generator. This included designing and building the rotor side converter, installing the back-to-back converter and other new instrumentation. Moreover, the MATLAB Simulink model of the Test Rig has been developed to represent the closed loop control, with more detailed information on the Rig components and instrumentation and has been validated against the physical system in the time and frequency domains. A fault detection technique has been proposed by the author based on frequency analysis of the rotor-side control signals, namely; d-rotor current error, q-rotor current error and q-rotor current, for wind turbine generator fault detection. This technique has been investigated for rotor electrical asymmetry on the physical Test Rig and its MATLAB Simulink model at different fixed and variable speed conditions. The sensitivity of the each proposed signal has been studied under different operating conditions. Measured and simulated results are presented, a comparison with the results from using stator current and total power has been addressed and the improvement in condition monitoring detection performance has been demonstrated in comparison with previous methods, looking at current, power and vibration analysis