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MEMS for structural health monitoring of wind turbine blades
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Structural health monitoring is becoming more valuable for wind energy producers as wind farms become larger and more remote. Increasing numbers of wind turbines are being installed offshore in order to take advantage of the higher wind speeds and more consistent wind resource available over the water. High winds and waves make access to offshore wind farms more limited than at onshore sites, making early identification and monitoring of developing repair and maintenance needs much more important. As structural health monitoring becomes a priority for offshore turbines, there is a need for appropriate sensors for this task. The rotor blades are a key location to monitor, as they are responsible for all of the energy capture of the turbine. Rotor blades are also among the top contributors to unplanned downtime, alongside the gearbox and generator. Improved structural health monitoring of the blades therefore has the potential to provide significant benefits. The proposed sensor system for wind turbine rotor blades is based on micro-electromechanical systems (MEMS) incorporating tri-axial gyroscopes, accelerometers and magnetometers. The MEMS, distributed along the blade, enable precise determination of the orientation of each blade segment. Orientation information from each MEMS is used to find the deformation shape of the blade, which is the input to a finite element model for calculation of the strains and stresses over the entire blade. As an initial test of the system, the MEMS are affixed to a beam under a static bending load. The output from each accelerometer, gyroscope and magnetometer is combined and filtered to produce an estimate of the local deflection angles. Information from several sensors is used to determine the beam deformation. Finite element analysis of the deformation will produce a strain distribution for the entire beam, which can be compared with strain measured at various points on the beam using conventional strain gauges.
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... Unlike the global SHM, the local SHM for WT's structural members has been received the early attention during the last few decades. Accordingly, many nondestructive evaluation methods, such as acoustic emission method, thermal imaging method, ultrasonic method, electrical resistance-based damage detection method, vision-based method, X-ray method, electromechanical impedance-based method have recently been investigated for the local SHM on WT structures (Joosse et al. 2002, Lading et al. 2002, Dutton 2004, Matsuzaki and Todoroki 2006, Park et al. 2015). However, these local SHM techniques were mostly developed to focus on detecting structural damage in the blades of wind turbines, and their applications to the critical joints of WT towers are still limited. ...
... Unlike the global SHM, the local SHM for WT's structural members has been received the early attention during the last few decades. Accordingly, many nondestructive evaluation methods, such as acoustic emission method, thermal imaging method, ultrasonic method, electrical resistance-based damage detection method, vision-based method, X-ray method, electromechanical impedance-based method have recently been investigated for the local SHM on WT structures ( Joosse et al. 2002, Lading et al. 2002, Dutton 2004, Matsuzaki and Todoroki 2006, Park et al. 2015). However, these local SHM techniques were mostly developed to focus on detecting structural damage in the blades of wind turbines, and their applications to the critical joints of WT towers are still limited. ...
In recent years, the wind energy has played an increasingly important role in national energy sector of many countries. To harvest more electric power, the wind turbine (WT) tower structure becomes physically larger, which may cause more risks during long-term operation. Associated with the great development of WT projects, the number of accidents related to large-scaled WT has also been increased. Therefore, a structural health monitoring (SHM) system for WT structures is needed to ensure their safety and serviceability during operational time. The objective of this study is to develop a hybrid damage detection method for WT tower structures by measuring vibration and impedance responses. To achieve the objective, the following approaches are implemented. Firstly, a hybrid damage detection scheme which combines vibration-based and impedance-based methods is proposed as a sequential process in three stages. Secondly, a series of vibration and impedance tests are conducted on a lab-scaled model of the WT structure in which a set of bolt-loosening cases is simulated for the segmental joints. Finally, the feasibility of the proposed hybrid damage detection method is experimentally evaluated via its performance during the damage detection process in the tested model.
... In the last years, several damage detection techniques and algorithms have been developed. Among the most promising ones there are the AE method [3], [4], the impedance-based method [5], the wave propagation-based method and the vibration-based (VB) methods [6]. The AE approach can be considered a standard practice for damage detection purposes during blade tests, but it requires the availability of a lot of AE sensors in order to cover the interested regions [3], [4]. ...
Rotating machines have always been used in a wide variety of industrial applications. Nowadays it is very difficult to find machines or mechanical systems which do not have any rotating component such as gears, bearings, shafts, wheels and so on. Wind turbines, gearboxes, combustion and electrical engines, generators and gas turbines are just few examples of objects with several rotating substructures. These machines face very complex and non-linear conditions during their operating cycles. they are often subjected to the fatigue problem and it is fundamental to detect faults or damages well in advance in order to reschedule the maintenance cycles. This is especially true for big machines (i.e. wind turbines) where the maintenance costs are a huge part of the total costs. Structural Health Monitoring (SHM) is a technology which is able to provide a continuous indication of the health and the reliability of the structure along its lifecycle. A damage detection technique is an essential part of any SHM system. Its scope consists in the identification of some structural and environmental parameters which have to be monitored regularly during the operation of the machine. This technique should be able to distinguish if the damage is present or not in the structure, but it should also locate and quantify the same damage. A damage can be seen as a change in material and/or geometric properties of a structure, including variation of boundary conditions and structural connections. Several studies have been performed and two different SHM strategies have been defined. The first one is based upon the whirling phenomenon. The whirling modes are the most identifiable modes in operating conditions and they appear to be very sensitive to changes of stiffness. Their amplitude and phase can be used as damage indicators because they allow to identify the loss of isotropy in the rotor. A second parameter which is quite sensitive even to small changes of stiffness is the curvature of the mode shapes. For beam-like structure it has been demonstrated being a very good damage indicator. Several simulations have been run together with some experimental validation on a wind turbine blade.
... Then, strain gauges have been applied for in-situ monitoring with measuring the local strain of the wind turbine blades. However, they are often vulnerable to the long term use [5,6], and insensitive to internal damage. Although optical fiber sensors have been used as an alternative thanks to their long-term durability [7], the internal damage is still difficult to be detected. ...
This paper proposes a continuous line laser thermography technique for damage visualization of wind turbine blades under rotating condition. Although a number of non-destructive testing techniques have been proposed for damage inspection of wind turbine blades under stationary condition, a few prior studies on the operating blade monitoring have been reported due to technical challenges associated with actual implementation issues. The proposed continuous line laser thermography technique is able to inspect wind turbine blades with fully noncontact mechanism, no couplant requirement, data acquisition without spatial scanning mechanism and intuitive data interpretation. First, thermal waves are generated by a continuous line laser beam targeted onto the rotating wind turbine blades, and the corresponding thermal responses are simultaneously measured by an infrared camera. Then, a new pixel tracking and statistical pattern recognition algorithms are developed and applied to the measured thermal images in the time domain so that only damage features can be extracted even under the rotating condition of wind turbine blades. The performance of the proposed continuous line laser thermography technique is verified through scaled wind turbine model tests under varying rotating speed.
... Then, strain gauges have been applied for in-situ monitoring with measuring the local strain of the wind turbine blades. However, they are often vulnerable to the long term use [5,6], and insensitive to internal damage. Although optical fiber sensors have been used as an alternative thanks to their long-term durability [7], the internal damage is still difficult to be detected. ...
In this study, a multi-spot laser scanning thermography (MLST) system is developed for automated, rapid and long-range inspection of delamination in composite structures. First, thermal waves are generated by scanning a multi-spot laser beam over a target composite structure, and the corresponding thermal waves are measured by using an infrared (IR) camera. Then a thermal image processing algorithm is developed to detect a hidden delamination based on the premise that abnormal temperature variation will be observed near the hidden delamination due to the differences of diffusion rates between the intact and damage regions. The proposed system provides following advantages for composite structure inspection: (1) complete non-contact, non-destructive, and non-intrusive inspection, (2) long-range inspection, making it possible to inspect a large area, and (3) baseline-free delamination inspection using only current-state infrared data, minimizing false alarms caused by environmental and operational variations. The effectiveness of the proposed MLST system is successfully verified using both a CFRP composite plate and a GFRP wind turbine blade specimen.
... There have been a number of nondestructive evaluation (NDE) and Structural Health Monitoring (SHM) techniques developed to examine the health of the wind turbine blades during static and fatigue testing. Strain gages, piezoelectric actuators with force sensors, photoelastic panels, impedance-based SHM systems, acoustic emission sensors, and low-frequency accelerometers have been utilized in the past [1][2][3]. These NDE measurements correlate their signals to the decay of the structural health of the blade, but they have difficulty determining the mode of failure. ...
... Traditionally, electrical strain gauges are used for measuring the stress distribution of certain blade regions and accelerometers for measuring the dynamic responses and the modal analysis of a whole blade. Technical advances allow newly emerging sensors, for instance, optical fiber sensors [176,192], acoustic emission [193,194], and Lead zirconate titanate [195], macro-fiber composite sensor [196] to measure other inherent properties of a turbine blade for damage detection [24]. Data acquisition hardware is located within the turbine nacelle or tower or rotor hub, and the signals from the blade sensors can be monitored remotely over the turbine communication network. ...
Wind energy is one of the fastest growing renewable energy resources. It is distinctly important to increase reliability and availability of wind turbines and further to reduce the wind energy cost. Blades are considered to be one of the most critical components in wind turbine system because they convert Kinetic energy of wind into useable power. Blades are fabricated by carbon fiber reinforced polymer (CFRP) or glass fiber reinforced polymer (GFRP). Flaws and damages are inevitable during either fabrication or lifetime of a composite blade. Thus, non-destructive testing (NDT) and structural health monitoring (SHM) for wind turbine blade (WTB) are required to prevent failures and increase reliability in both manufacturing quality control and in-service inspection. In this work, a fully, in-depth and comprehensive review of NDT techniques for WTB inspection was reported based on an orderly and concise literature survey. Firstly, typical flaw and damage occurring in manufacturing progress and in service of WTB were introduced. Next, the developments of visual, sonic and ultrasonic, optical, electromagnetic, thermal and radiographic NDT for composite WTB inspection were reviewed. Thereafter, strengths and limitations of NDT techniques were concluded through comparison studies. In the end, some research trends in WTB NDT have been predicted, for example in combination with SHM. This work will provide a guide for NDT and SHM of WTB, which plays an important role in wind turbine safety control and wind energy cost savings. In addition, this work can benefit the NDT development in the field of renewable energy, such as solar energy, and energy conservation field, such as building diagnosis.
... The global stiffness of the TX-100 blade was measured with a different method because displacement data from a load application point were unavailable. Multiple sensors were mounted on this blade as the TX-100 served as a test bed for structural health monitoring sensors 19 . Among the health monitoring sensors were several accelerometers at the blade tip which were used by a team from Purdue University 20 . ...
Fatigue testing was conducted on Carbon Experimental and Twist-Bend Experimental (CX-100 and TX-100) 9-m wind turbine research blades. The CX-100 blade was designed to investigate the use of a carbon spar cap to reduce weight and increase stiffness while being incorporated using conventional manufacturing techniques. The TX-100 blade used carbon in the outboard portion of the skin to produce twist-bend coupling to passively alleviate aerodynamic loads. In the fatigue tests, the CX-100 blade was loaded by a single hydraulic cylinder while the TX-100 blade was loaded via a hydraulically-actuated resonant loading system called the Universal Resonant Exciter. The blades were outfitted with approximately 30 strain gages as well as displacement and load sensors. Both blades survived to cycle counts sufficient to demonstrate a 20-year operational life. The CX-100 blade failed at approximately 1.6 million cycles because of a buckle and crack that formed and grew just outboard of max-chord. The TX-100 blade failed because of a crack that grew from the termination point of the spar cap at the midspan of the blade. This paper covers the results of the fatigue tests.
... Considerable efforts are currently being undertaken to design SHM systems for wind turbines. Novel sensing technologies and sophisticated monitoring techniques are being developed and applied to wind turbines (Jüngert 2008, Lading et al. 2002, Sutherland et al. 1994, Rolfes et al. 2007). However, robust software platforms designed to facilitate data interrogation, data archiving and automated execution of monitoring tasks have received little attention. ...
Engineering structures such as wind turbines require continuous monitoring to ensure structural safety, to reduce the overall maintenance and repair costs and, ultimately, to achieve extended lifetimes and a greater economic viability. For that purpose, an automated SHM system for wind turbines has been developed and installed on a 500 kW wind turbine in Germany. During its operation, temporary malfunctions of the installed sensing units have been observed. These malfunctions, such as temporary sensor breakdowns which are well known from real-time SHM systems, might cause the loss of valuable monitoring data if not detected timely. A multi-agent system, which is capable of self-detecting system malfunctions and notifying the human individuals automatically, has been developed and integrated into the existing SHM system. The SHM system and its subsystem, the multi-agent system, have been in continuous operation since 2009. Since then, various malfunctions have automatically been detected and appropriate actions have been taken in a timely manner. As a result, the malfunctioning of the sensors did not lead to significant data loss, thus enhancing the quality of the SHM system.
Renewable energy plays a vital role in power industry to fulfil the growing demand of power in industrial sector and other utilities. Wind energy is an attractive power source because it is plentiful and renewable. Wind energy will play a major role in the power supply in the world. The wind turbine blades are key components in wind turbine. These blades suffer from complex loading, that can cause severe malfunctioning and even catastrophic collapse, and that initiates as small defects. The bulk of the defects in wind turbine blades occur during the manufacturing phase; the rest are due to stresses caused by the aerodynamic loads and aging. The digital infrared thermography as a nondestructive test (NDT) tool was used to detect defects and monitor the health of wind turbine blades. The main objectives in this paper are to review the current state of infrared thermography of wind turbines blades tests at manufacture and in-service.
The National Research Council Canada (NRC) has worked on the development of structural health monitoring (SHM) test platforms for assessing the performance of sensor systems for load monitoring applications. The first SHM platform consists of a 5.5 m cantilever aluminum beam that provides an optimal scenario for evaluating the ability of a load monitoring system to measure bending, torsion and shear loads. The second SHM platform contains an added level of structural complexity, by consisting of aluminum skins with bonded/riveted stringers, typical of an aircraft lower wing structure. These two load monitoring platforms are well characterized and documented, providing loading conditions similar to those encountered during service.
In this study, a micro-electro-mechanical system (MEMS) for acquiring data from triads of gyroscopes, accelerometers and magnetometers is described. The system was used to compute changes in angles at discrete stations along the platforms. The angles obtained from the MEMS were used to compute a second, third or fourth order degree polynomial surface from which displacements at every point could be computed. The use of a new Kalman filter was evaluated for angle estimation, from which displacements in the structure were computed. The outputs of the newly developed algorithms were then compared to the displacements obtained from the linear variable displacement transducers connected to the platforms. The displacement curves were subsequently post-processed either analytically, or with the help of a finite element model of the structure, to estimate strains and loads. The estimated strains were compared with baseline strain gauge instrumentation installed on the platforms. This new approach for load monitoring was able to provide accurate estimates of applied strains and shear loads.
Real-time tracking of human body motion is an important technology in synthetic environments, robotics, and other human-computer interaction applications. This paper presents an extended Kalman filter designed for real-time estimation of the orientation of human limb segments. The filter processes data from small inertial/magnetic sensor modules containing triaxial angular rate sensors, accelerometers, and magnetometers. The filter represents rotation using quaternions rather than Euler angles or axis/angle pairs. Preprocessing of the acceleration and magnetometer measurements using the Quest algorithm produces a computed quaternion input for the filter. This preprocessing reduces the dimension of the state vector and makes the measurement equations linear. Real-time implementation and testing results of the quaternion-based Kalman filter are presented. Experimental results validate the filter design, and show the feasibility of using inertial/magnetic sensor modules for real-time human body motion tracking
Orientation of a static or slow-moving rigid body can be determined from the measured gravity and local magnetic field vectors. Some formulation of the QUaternion ESTimator (QUEST) algorithm is commonly used to solve this problem. Triads of accelerometers and magnetometers are used to measure gravity and local magnetic field vectors in sensor coordinates. In the QUEST algorithm, local magnetic field measurements affect not only the estimation of yaw but also that of roll and pitch. Due to the deviations in the direction of the magnetic field vector between locations, it is not desirable to use magnetic data in calculations that are related to the determination of roll and pitch. This paper presents a geometrically intuitive 3-degree-of-freedom (3-DOF) orientation estimation algorithm with physical meaning [which is called the factored quaternion algorithm (FQA)], which restricts the use of magnetic data to the determination of the rotation about the vertical axis. The algorithm produces a quaternion output to represent the orientation. Through a derivation based on half-angle formulas and due to the use of quaternions, the computational cost of evaluating trigonometric functions is avoided. Experimental results demonstrate that the proposed algorithm has an overall accuracy that is essentially identical to that of the QUEST algorithm and is computationally more efficient. Additionally, magnetic variations cause only azimuth errors in FQA attitude estimation. A singularity avoidance method is introduced, which allows the algorithm to track through all orientations.
Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals received are used to determine highly sensitive processes such as the flight path of a plane, the orbit of a space vehicle, or the control of a machine. The authors use dynamic models from mechanical and aerospace engineering to provide immediate results of estimation concepts with a minimal reliance on mathematical skills. The book documents the development of the central concepts and methods of optimal estimation theory in a manner accessible to engineering students, applied mathematicians, and practicing engineers. It includes rigorous theoretial derivations and a significant amount of qualitiative discussion and judgements. It also presents prototype algorithms, giving detail and discussion to stimulate development of efficient computer programs and intelligent use of them. This book illustrates the application of optimal estimation methods to problems with varying degrees of analytical and numercial difficulty. It compares various approaches to help develop a feel for the absolute and relative utility of different methods, and provides many applications in the fields of aerospace, mechanical, and electrical engineering.
Wind Turbines (WT) are one of the fastest growing sources of power production in the world today and there is a constant need to reduce the costs of operating and maintaining them. Condition monitoring (CM) is a tool commonly employed for the early detection of faults/failures so as to minimise downtime and maximize productivity. This paper provides a review of the state-of-the-art in the CM of wind turbines, describing the different maintenance strategies, CM techniques and methods, and highlighting in a table the various combinations of these that have been reported in the literature. Future research opportunities in fault diagnostics are identified using a qualitative fault tree analysis.
Strain-displacement mappings based on linear and quadratic curvature assumptions are derived, compared for a numerical model and applied to a 4.37 m tapered composite boom with a circular cross-section. Displacement estimations are obtained for both the vertical and horizontal directions with displacement estimation errors of less than 0.2 mm in the vertical direction and 1 mm in the horizontal direction. Limitations on strain displacement algorithms for long booms are discussed as well as strain sensor noise effects on estimation accuracy. Bibtex entry for this abstract Preferred format for this abstract (see Preferences) Find Similar Abstracts: Use: Authors Title Abstract Text Return: Query Results Return items starting with number Query Form Database: Astronomy Physics arXiv e-prints
Quaternion-Based Kalman Filter for Human Body Motion Tracking
Quaternion-Based Kalman Filter for Human Body Motion Tracking," IEEE Transactions on Robotics,
Vol. 22, No. 6, 2006, pp. 1216-1227.