The state-of-the-art advancement in wind turbine condition monitoring and fault diagnosis for the recent several years is reviewed. Since the existing surveys on wind turbine condition monitoring cover the literatures up to 2006, this review aims to report the most recent advances in the past three years, with primary focus on gearbox and bearing, rotor and blades, generator and power electronics, as well as system-wise turbine diagnosis. There are several major trends observed through the survey. Due to the variable-speed nature of wind turbine operation and the unsteady load involved, time-frequency analysis tools such as wavelets have been accepted as a key signal processing tool for such application. Acoustic emission has lately gained much more attention in order to detect incipient failures because of the low-speed operation for wind turbines. There has been an increasing trend of developing model based reasoning algorithms for fault detection and isolation as cost-effective approach for wind turbines as relatively complicated system. The impact of unsteady aerodynamic load on the robustness of diagnostic signatures has been notified. Decoupling the wind load from condition monitoring decision making will reduce the associated down-time cost.

A review of recent advances in wind turbine condition monitoring and fault diagnosis

This paper provides a comprehensive survey on the state-of-the-art condition monitoring and fault diagnostic technologies for wind turbines (WTs). The Part I of this survey briefly reviews the existing literature surveys on the subject, discusses the common failure modes in the major WT components and subsystems, briefly reviews the condition monitoring and fault diagnostic techniques for these components and subsystems, and specifically discusses the issues of condition monitoring and fault diagnosis for offshore WTs.

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A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

Deployment of larger scale wind turbine systems, particularly offshore, requires more organized operation and maintenance strategies to ensure systems are safe, profitable and cost-effective. Among existing maintenance strategies, reliability centred maintenance is regarded as best for offshore wind turbines, delivering corrective and proactive (i.e. preventive and predictive) maintenance techniques enabling wind turbines to achieve high availability and low cost of energy. Reliability centred maintenance analysis may demonstrate that an accurate and reliable condition monitoring system is one method to increase availability and decrease the cost of energy from wind. In recent years, efforts have been made to develop efficient and cost-effective condition monitoring techniques for wind turbines. A number of commercial wind turbine monitoring systems are available in the market, most based on existing techniques from other rotating machine industries. Other wind turbine condition monitoring reviews have been published but have not addressed the technical and commercial challenges, in particular, reliability and value for money. The purpose of this paper is to fill this gap and present the wind industry with a detailed analysis of the current practical challenges with existing wind turbine condition monitoring technology.

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Wind turbine condition monitoring: technical and commercial challenges

Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes a WT condition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform-based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from direct- or indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical fault like perturbations were successfully detected when applied to the test rig.

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Cost-Effective Condition Monitoring for Wind Turbines

The ever increasing size of wind turbines and the move to build them offshore have accelerated the need for optimised maintenance strategies in order to reduce operating costs. Predictive maintenance requires detailed information on the condition of turbines. Due to the high costs of dedicated condition monitoring systems based on mainly vibration measurements, the use of data from the turbine supervisory control and data acquisition (SCADA) system is appealing. This review discusses recent research using SCADA data for failure detection and condition monitoring (CM), focussing on approaches which have already proved their ability to detect anomalies in data from real turbines. Approaches are categorised as (i) trending, (ii) clustering, (iii) normal behaviour modelling, (iv) damage modelling and (v) assessment of alarms and expert systems. Potential for future research on the use of SCADA data for advanced turbine CM is discussed.

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Using SCADA data for wind turbine condition monitoring – a review

This paper discusses the results of an extensive
investigation to assess the added value of various
techniques of health monitoring to optimise the
maintenance procedures of offshore wind farms. This
investigation has been carried out within the
framework of the EU funded CONMOW project
(Condition Monitoring for Offshore Wind Farms)
which was carried out from 2002 through 2007, [5].
A small wind farm of five turbines has been
instrumented with several condition monitoring
systems and also with the “traditional” measurement
systems. Analyses of these measurements and of data
collected by the turbine's SCADA systems have been
performed to assess (1) if failures can be detected;
(2) if so, if they can be detected at an early stage and
their progress over time can be monitored; and (3) if
criteria are available to assess the component's
health. Several data analysis methods and
measurement configurations have been developed,
applied, and tested.
This paper first describes the use condition
monitoring to change from scheduled and corrective
maintenance to condition based maintenance.
Second, the paper describes the CONMOW project,
and the major results. viz. the assessment of the
usefulness and capabilities of condition monitoring
systems and algorithms for identifying early failures.
Finally, the economic consequences of applying
condition monitoring systems have been quantified
and assessed.

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Assessment of Condition Monitoring Techniques for Offshore Wind Farms

Maintenance of wind farms is of increasing importance. Especially in remote areas, where logistics and accessibility are restricted, costs of preventive as well as corrective maintenance form a substantial part of the costs of electricity. The importance of a tool that assists in feedback to the design, failure logging, configuration control and maintenance planning is evident. This paper describes the importance of such a tool, the functional specifications that should be met and the experience with implementation of such a system at a wind turbine manufacturer.

Theo Verbruggen

Papers

Assessment of Condition Monitoring Techniques for Offshore Wind Farms

Maintenance Manager to control operation and maintenance of offshore wind farms