Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

With increasing turbine size, monitoring of blades becomes increasingly im-portant, in order to prevent catastrophic damages and unnecessary mainte-nance, minimize the downtime and labor cost and improving the safety is-sues and reliability. The present work provides a review and classification of various structural health monitoring (SHM) methods as strain measurement utilizing optical fiber sensors and Fiber Bragg Gratings (FBG’s), active/ pas-sive acoustic emission method, vibration‒based method, thermal imaging method and ultrasonic methods, based on the recent investigations and prom-ising novel techniques. Since accuracy, comprehensiveness and cost-effectiveness are the fundamental parameters in selecting the SHM method, a systematically summarized investigation encompassing methods capabilities/ limitations and sensors types, is needed. Furthermore, the damages which are included in the present work are fiber breakage, matrix cracking, delamina-tion, fiber debonding, crack opening at leading/ trailing edge and ice accre-tion. Taking into account the types of the sensors relevant to different SHM methods, the advantages/ capabilities and disadvantages/ limitations of repre-sented methods are nominated and analyzed

Algorithm for damage detection in wind turbine blades using a hybrid dense sensor network with feature level data fusion

Damage detection in wind turbine blades requires the ability to distinguish local faults over a global area. The implementation of dense sensor networks provides a solution to this local-global monitoring challenge. Here the authors propose a hybrid dense sensor network consisting of capacitive-based thin-film sensors for monitoring the additive strain over large areas and fiber Bragg grating sensors for enforcing boundary conditions. This hybrid dense sensor network is leveraged to derive a data-driven damage detection and localization method for wind turbine blades. In the proposed method, the blade\u27s complex geometry is divided into less geometrically complex sections. Orthogonal strain maps are reconstructed from the sectioned hybrid dense sensor network by assuming different bidirectional shape functions and are solved using the least squares estimator. The error between the estimated strain maps and measured strains is extracted to define damage detection features that are dependent on the selected shape functions. This technique fuses sensor data into a single damage detection feature, providing a simple and robust method for inspecting large numbers of sensors without the need for complex model driven approaches. Numerical simulations demonstrate the proposed method\u27s capability to distinguish healthy sections from possibly damaged sections on simplified 2D geometries

Optical Fiber Sensors for Aircraft Structural Health Monitoring

Aircraft structures require periodic and scheduled inspection and maintenance operations due to their special operating conditions and the principles of design employed to develop them. Therefore, structural health monitoring has a great potential to reduce the costs related to these operations. Optical fiber sensors applied to the monitoring of aircraft structures provide some advantages over traditional sensors. Several practical applications for structures and engines we have been working on are reported in this article. Fiber Bragg gratings have been analyzed in detail, because they have proved to constitute the most promising technology in this field, and two different alternatives for strain measurements are also described. With regard to engine condition evaluation, we present some results obtained with a reflected intensity-modulated optical fiber sensor for tip clearance and tip timing measurements in a turbine assembled in a wind tunnelThe authors would like to thank Professor A. Guemes for the permission to use the FBG responses shown in Figure 2. This work has been sponsored by the Ministerio de Economia y Competitividad (Spain) and FEDER funds under project TEC2012-37983-C03-01, the Gobierno Vasco/Eusko Jaurlaritza under projects IT664-13, ETORTEK14/13 and by the University of the Basque Country (UPV/EHU) through programs UFI11/16, US13/09 and EUSKAMPUS

Review on Strain Monitoring of Aircraft Using Optical Fibre Sensor

Structural health monitoring of aircraft assures safety, integrity and reduces cost-related concerns by reducing the number of times maintenance is required. Under aerodynamic loading, aircraft is subjected to strain, in turn causing damage and breakdown. This paper presents a review of experimental works, which focuses on monitoring strain of various parts of aircraft using optical fibre sensors. In addition, this paper presents a discussion and review on different types of optical fibre sensors used for structural health monitoring (SHM) of aircraft. However, the focus of this paper is on fibre bragg gratings (FBGs) for strain monitoring.  Here, FBGs are discussed in detail because they have proved to be most viable and assuring technology in this field. In most cases of strain monitoring, load conditioning and management employs finite element method (FEM). However, more effort is still required in finding the accurate positions in real time where the sensors can be placed in the structure and responds under complex deformation

MARE-WINT: New Materials and Reliability in Offshore Wind Turbine Technology

renewable; green; energy; environment; law; polic