Implementation of a Dynamic Monitoring System on a Wind Turbine

Transcription

1 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 Porto, Portugal, June - July 4 A. Cunha, E. Caetano, P. Ribeiro, G. Müller (eds.) ISSN: -9; ISBN: Implementation of a Dynamic Monitoring System on a Wind Turbine Gustavo Oliveira, Filipe Magalhães, Álvaro Cunha, Elsa Caetano ViBest, Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4-46 Porto, Portugal gustavo.oliveira@fe.up.pt, filipema@fe.up.pt, acunha@fe.up.pt, ecaetano@fe.up.pt ABSTRACT: Wind is one of the most important and reliable renewable energy sources in the world. Currently, the implementation of new wind turbines is supported by large multi-mw systems, with flexible support structures at onshore and offshore locations. Although high technological maturity and availability is already presented by modern wind turbines, the continuous increase in dimension and flexibility of the turbines support structures leads to some concern about their structural integrity throughout their period of operation. Thus, in the present paper, the first steps of the implementation of a dynamic monitoring system for damage detection on a wind turbine, developed by the Laboratory of Vibrations and Structural Monitoring (ViBest), are introduced. The preparation, implementation and initial results of the monitoring system installed on a. MW onshore wind turbine tower are presented. KEY WORDS: wind turbine; monitoring; ambient vibration test; operational modal analyses. INTRODUCTION Wind energy is considered one of most reliable and feasible options for renewable and clean energy. Year after year, wind energy market has presented a consistent growth both for onshore [, ] and, more recently, offshore locations []. However, as a financial investment, wind turbines need to present high availability rates and, consequently, low downtime failures. This fact justifies the development and implementation of monitoring systems based on the continuous tracking of the modal parameters of the structure as indicators of early damage. For this purpose, tools for extraction of these parameters based only on the dynamic response of the structure must be implemented and used. This experimental modal analysis approach, also named as Operational Modal Analysis (OMA), is a well-studied field of investigation and several successfully works on civil engineering structures have already been published. For example, Magalhães et al. [4] and Hu et al. [] developed dynamic monitoring systems for a roadway arch bridge and for a footbridge, respectively. Considering the wind energy field, some previous works presented interesting results concerning modal identification of wind turbine structures. Pelayo et al. [6] were able to identify two onshore wind turbines with foundation damages through the comparison of their natural frequencies against the ones from a healthy turbine. Hu et al. [7] presented the variation of the modal parameters from a. MW wind turbine during a period of two years. Lastly, Devriendt et al. [8] presented the evolution of the natural frequencies and modal damping ratios of modes of an offshore wind turbine. This paper describes the first steps of the implementation of a dynamic monitoring system by the Laboratory of Vibrations and Structural Monitoring (ViBest, This system aims to detect early damage on the support structure of wind turbines. The paper is divided into two main parts. Initially, the ambient vibration test performed prior to the installation of the monitoring system is presented. The main results obtained with the application of two state of the art output-only algorithms are shown. These results are then correlated with the results provided by a finite-element (FE) model. In the second part, the implemented continuous dynamic monitoring system is introduced and the first results are described. DESCRIPTION OF THE STRUCTURE The wind turbine under analysis is a. MW system with a variable-speed generator located at the north of Portugal. It has a height of 8 m and a blade length of roughly 4 m. Its support structure is composed by a concrete slab foundation and a steel tower. As usual, the tower is constituted by individual cylindrical segments which are connected to each other by flanged bolted connections. AMBIENT VIBRATION TEST. Test procedure The ambient vibration test was conducted during a maintenance period (wind turbine parked with sporadic rotation of the nacelle and with blades pitched out of the wind), with low wind speed conditions. A more detailed description of this test and the results obtained can be found in [9]. In order to measure the vibrations of the tower, 4 tri-axial 4-bit strong motion accelerometers (S to ) were used. These devices were located at three different levels along the tower (see Figure ). These positions were kept during the entire test and 7 setups of 96 seconds were recorded. 68

2 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN Stabilization diagram All poles Stable Freq. Stable Damp. MAC S / S S S Model Order Figure. Stabilization diagram obtained with the algorithm. +. Figure. Instrumented sections and accelerometers positions. The main results obtained with this test, namely frequency values (f) and damping ratios ( ) for the first three pairs of the support structure vibration modes are summarized in Table.. Identified modal parameters The identification of modal properties of the structure from the data collected was processed with two different outputonly algorithms, previously implement in Matlab []: SSI- COV, in the time domain; and the, in the frequency domain. A more detailed description of these methods is presented in [,, ]. Usually, the results obtained with these algorithms are presented in the form of stabilization diagrams. These diagrams show poles for different orders at the frequencies of possible resonance peaks. Thus, if the properties of a pole (modal parameters) are kept constant, at a specific frequency value and for consecutive orders, it is considered a stable pole and it is very likely to indicate the existence of a vibration mode at this frequency. Representative stabilization diagrams obtained from both algorithms are presented in Figure and. As can be seen, several alignments of stable poles can be identified. In both figures, the vibration modes related to the support structure are highlighted by red boxes. Two groups of two closelyspaced fore-aft (FA) and side-side (SS) modes around. Hz and.78 Hz were identified. These are associated to the first and second bending modes. Also, the third pair of bending modes was identified at around 8. Hz and 9. Hz. As for the other stable alignments, it is believed that they are related to rotor vibration modes. The instrumentation of the blades would permit to validate this hypothesis. Model Order Stabilization diagram All poles Stable Freq. Stable Damp. MAC Figure. Stabilization diagram obtained with the algorithm. Table. Main results obtained with the ambient vibration test. f [Hz] [%] f [Hz] [%] Description....6 st FA st SS nd FA nd SS th SS th FA As can be observed, the results obtained for the frequency values with both algorithms are almost coincident. Also, the values of damping ratios for the first two pairs of vibration modes extracted by the two methods are very similar. However, the damping results for the third pair are not so coherent. This might be due to the less clear alignment of stable poles for these modes.. Numerical model With the purpose of a better understanding of the experimental results, a numerical model of the wind turbine structure was performed with ANSYS software [4]. In that sense, four-node shell elements with six degrees of freedom at each node were implemented to model the steel shell components of the tower. For the nacelle and rotor components, a point element with the representative mass was employed on their center of gravity. The door opening was also modelled according to technical drawings. The connection between the tower bottom and the foundation was defined as fixed. With this model, in which a more detailed representation of the nacelle and rotor elements is despised, only the tower related vibration modes are obtained, which is the main concern of the present work. For the purpose of illustration, an overview of the FE model mesh is presented in Figure 4. In the meanwhile a new complete model, which also includes the blades, is being developed in the HAWC software []. 684

3 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 ELEMENTS MAT NUM NOV :: PLOT NO. The experimental and numerical mode shapes, alongside with the respective MAC values, are presented in Figure to 7. 8 Mode st FA 8 Mode st SS 7 7 Z Y Figure 4. Global overview of the FE model mesh.4 Correlation between experimental and numerical results For the aim of correlating experimental and numerical results, a modal analysis of the numerical model was performed. The main results obtained, as well as the respective deviation of each experimentally identified natural frequency are presented in Table. Table. Comparison between experimental and numerical results. FE model f [Hz] f [%] f [%] Description st FA st SS nd FA nd SS rd SS rd FA The numerical results present a good correlation with the numerical ones. As expected, the numerical model presents slightly higher natural frequencies mainly due to the considered fixed boundary conditions. The frequency deviation observed is low, with ratios of around 6 %. Once again, the worst result is obtained for the last identified vibration mode (the th FA bending mode). This fact may be related to the less clear alignment of stable poles for this mode, too. Concerning the configuration of the vibration modes, a very good agreement was also obtained between numerical and experimental results. In order to compare these two results, the Modal Assurance Criterion (MAC) was used. This parameter is defined, for two i and j mode shapes, by: X T i. j T T... MAC () i where represents the mode shape of the vibration mode and T indicates the transpose operation. i j j (MAC =.) (MAC =.) (MAC =.) (MAC =.999) Figure. Mode shapes and respective MAC values from the st pair of vibration modes Mode nd FA.. (MAC =.99) (MAC =.994) Mode 4 nd SS.. (MAC =.99) (MAC =.99) Figure 6. Mode shapes and respective MAC values from the nd pair of vibration modes Mode th SS.. (MAC =.996) (MAC =.987) Mode 6 th FA.. (MAC =.97) (MAC =.969) Figure 7. Mode shapes and respective MAC values from the rd pair of vibration modes 4 MONITORING SYSTEM 4. Description of the system The implemented monitoring system strategy is based on the continuous tracking of the modal properties of the wind turbine support structure. Considering that damage is usually associated with stiffness reductions, the natural frequencies were used as the features of study. These features, extracted from periodically sampled dynamic responses of the structure, are used to statistically analyze their time evolution. Thus, if 68

4 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 an abnormal deviation of these features is detected from their healthy behavior, damage is likely to be present. The dynamic monitoring system installed is composed by 9 uni-axial force-balanced accelerometers (Figure 8) which are linked by a common 4 bit digitizer and acquisition system. These sensors are distributed along the tower height according to Figure 9, measuring accelerations in the horizontal and vertical directions. S S Figure 8. Sensor installed on a tower flange S S S S a) b) Figure 9. Position of the accelerometers at the different levels: a) front view; b) top view at different sections The acquisition system is configured to record acceleration time series with a length of min sampled at a rate of Hz. The data obtained with this system is then processed with the same output-only identification algorithms presented in Section. Alongside with the monitoring system, the ambient and operational conditions of the wind turbine are also recorded with the help of the installed SCADA system (independent from the dynamic system). As referred in [4], the ambient conditions, mainly temperature, can introduce noticeable variations in the modal properties of a structure under normal operation, which can even mask variations due to the presence of damage. Thus, the study of the correlations of these effects with the modal properties is necessary to remove the variability introduced by them and permit to accurately detect small shifts in the natural frequencies. Since the parameters recorded by the SCADA system are min averaged values, for each time segment recorded by the dynamic monitoring system, a representative value of each SCADA parameter is assigned. In this work, the ambient and operational conditions obtained from the SCADA system are: temperature wind speed and direction nacelle position pitch angle rotor rotational speed power production. 4. Initial results The monitoring period considered in this paper is referred to the data collected during months (from /7/ to 8//). Since the results presented in this section only represent the initial approach to the data collected, they cannot be understood as final. Due to this reason, only the first two pairs of tower bending modes were studied (the first 4 modes presented in Table ). Over this period, the wind turbine operated under various environmental conditions. To attest the suitability of the modal identification algorithms to study the behavior of wind turbine systems, acceleration samples of min were individually analyzed corresponding to adopted setups of min, corresponding to different scenarios of operation, were individually analyzed: wind turbine parked under low wind speed conditions wind turbine operating below the rated output speed, maximizing the energy production wind turbine operating at rated speed, limiting the power production to its rated power. These different operating scenarios are represented in the power curve of the wind turbine (Figure ). For the analysis of the setups, only the sensors measuring the horizontal acceleration were considered, since the amplitude of the signals from sensors S and S are considerably lower than the others. Power [kw] Setup Setup Setup Wind speed [m/s] Figure. Turbine power curve and representation of the setups manually analyzed Setup represents a scenario where the wind speed is insufficient for the generator to operate. Thus, the blades are feathered and, consequently, the rotor is idling. The acceleration time history of setup is presented in Figure. 686

5 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 x Setup. histories of setup are presented in Figure. The acceleration amplitudes registered are considerably higher than those of the setup. S - S Setup Time [s] 4 6 Acceleration [g] Acceleration [g] Figure. Measured acceleration signals during setup -.6 The main results obtained for the setup are shown in Figure. These estimations of natural frequencies and modal damping ratios represent the poles obtained in a stabilization diagram of the method (similar to Figure and ) which met all the stabilization criteria. These criteria, already introduced in [9], were applied to the setups and were: maximum frequency variation: % maximum damping variation: % maximum damping value: % minimum MAC value: 97 % As can be seen, the 4 vibration modes were identified, even in low wind speed conditions. The results are consistent with the ones obtained with the ambient vibration test, although some deviation was found regarding the damping values. This situation may be explained by the lower wind speed present during the setup which led to a reduction of the aerodynamic damping component. Another situation in line with the results obtained with the ambient vibration test was the higher damping value of the st SS mode when compared to the st FA mode. This situation is due to the deviation of the rotor from the wind direction and to the high pitch value of the blades. Under these conditions, the air has a larger opposition in the SS direction, which justifies the higher value of damping of the st SS mode. Setup Time [s] 4 6 The results obtained for the setup are presented in Figure 4. It is observed that the frequency values of the 4 bending modes slightly increased. Also, the damping values of the modes (with exception of the st SS mode) present a considerably increase. This increase is justified by the aerodynamic component of the damping, which increases with the increase of the wind speed. This effect is more noticeable for modes with large modal amplitude where the wind force is higher and with modes whose deflection coincides with the wind direction. For these reasons, the st FA mode presents the higher value of damping and a considerable increase compared to setup. Also, a large difference between the damping values of the st pair of modes is noticed, proving the effect of the mode shape orientation to the wind flow. On the other hand, due to their small modal amplitude at the top (see Figure 6), the rd and 4th modes present a lower damping increase and a smaller difference between them. In addition, the inversion in the order of the first pair of vibration modes is noticed. Although there is not a justification for this phenomenon at this moment, the inversion of the order of the first pair of modes was noticeable during the considered period Setup 4. ffa =. Hz ξfa = 4.9 % 4..4 ffa =. Hz ξfa =. %. ffa =.77 Hz ξfa =. % Damping [%].6 fss =.86 Hz ξss =.6 %... Figure. Measured acceleration signals during setup fss =. Hz ξss =.9 %.8 Damping [%] Figure. Natural frequencies and damping ratios for the setup Setup is referred to a scenario where the turbine is already in operation but the wind speed is still below its rated value. Under these circumstances, the turbine is oriented to the main wind incidence direction, the pitch angle of the blades is set to its minimum value and, consequently, the turbine is maximizing the power production. The acceleration time ffa =.79 Hz ξfa =. % fss =.4 Hz ξss =.6 % fss =.84 Hz ξss =.4 % Figure 4. Natural frequencies and damping ratios for the setup Setup represents the optimal situation for the turbine operation. The wind speed is higher than the rated speed which means that the generator is at its maximum production level. In order to keep the power production as stable as possible, the pitch angle of the blades increases with the wind 687

6 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 speed in order to reduce the blades lift coefficient and, thus, reduce the rotor torque generated by the wind. The acceleration time histories of setup are presented in Figure. As can be observed, this setup presents the higher levels of acceleration. Setup Acceleration [g]. S. -. Figure 7. Color map of the first singular value spectrum from the FA direction -. Time [s] 4 6 Figure. Measured acceleration signals during setup The main results from this setup are shown in Figure 6. They are similar to the ones obtained for setup. However, as expected, the damping values of the st pair of vibration modes increased compared to setup. This situation is due to the higher drag effect created by the higher wind speed occurred in setup. This increase in the damping values did not affect the nd pair of modes, which demonstrate the lower influence of the aerodynamic component on the damping of these modes. Setup 6 ffa =. Hz ξfa =. % Damping [%] Figure 8. Color map of the first singular value spectrum from the SS direction 4. ffa =.767 Hz ξfa =.79 % fss =. Hz ξss =.9 % fss =.8 Hz ξss =.7 %.8.9 Figure 6. Natural frequencies and damping ratios for the setup After proofing the suitability of the output-only modal identification algorithms for different scenarios of turbine operation, an initial approach to the automated analysis of the continuously collected data during months was performed. Initially, the first singular value spectrum for the Hz range for both FA and SS directions was computed. The color map of these singular value spectra are presented in Figure 7 and 8, where the hotter colors represent the higher amplitudes and the cooler colors represent the smaller amplitudes of the spectra. Thus, it is expected to detect red lines at the resonance frequencies of the structure. 688 From the analysis of Figure 7 and 8, it is clear that the pairs of bending modes are well identified across the entire period. In both figures, a red alignment is identified around the corresponding frequencies, meaning that, for the analyzed spectrum range, the support structure of the wind turbine vibrates mainly with these frequencies. It is also noted that the energy of the st pair of bending modes is well confined to a reduced frequency range. On the other hand, the energy of the nd pair of bending modes seems to be spread in a larger range, which may indicate a larger variability of the frequency values of these modes when compared to the st pair. The entire monitored period was then automatically processed with the help of the identification routine. For this purpose, the methodology presented in [6] was followed. This methodology for the automated identification of modal parameters is based on a hierarchical clustering algorithm. It consists on the analysis of the similarities of the poles computed on stabilization diagrams (as the ones present in Figure and ). Since different vibration modes can present similar values of damping values, only the frequency values and the mode shapes were used to compute the similarity between poles. The similarity criterion used to compute the distance between the pole i and j was:

7 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 fj.9 MACi j ().8 Thus, if the distance between poles, computed according to equation (), is short, they probably represent the same physical vibration mode. Consequently, they will be included in the same cluster. In the present analysis, a distance of. was used. After the first clusters are formed, there will be aggregations between different clusters with similar poles. The criterion defined for this operation was the single linkage. In the application of this methodology to the monitoring system presented in this paper, only the poles which meet all the stabilization criteria were used for the clustering algorithm. Also, since that, at this stage, this initial analysis only intended to track the first pairs of bending modes, the tuning of the automatic identification of clusters is not yet optimized. Figure 9 presents the evolution of the natural frequencies from the st and nd bending modes during the analyzed period. As can be seen, these vibration modes were clearly identified during this period, which included several operating conditions..8.7 FA SS.7 4// // Time 6// Figure. Zoom around the natural frequencies of the nd pair of bending modes for a period of days In order to understand these variations it is important to confront the extracted modal properties with the operational data acquired with the SCADA system. This task is still under development. Nevertheless, with the aim of illustrating the various operating conditions of the wind turbine during the period under analysis, some data is presented in Figure, and FA SS.. 4 Rotor speed [RPM] d i j fi f j /8/ /9/ Time // Figure 9. Evolution of the natural frequencies of the first bending modes identified during the period from /7/4 to 8//4 From the observation of Figure 9, the large variation of the frequency value of the nd pair of bending modes is also evident. This remark is in line with the results from Figure 7 and 8. A zoom in this frequency range for a period of days, evidencing this observation, is present in Figure. It is clear, from these two figures, that some additional work is needed to understand the factors behind these variations Wind speed [m/s] Figure. Relationship between rotor speed and wind speed during the period under analysis ( min averaged values) Figure presents the evolution of the rotor rotational speed with the wind speed during the analyzed period. As can be seen, the wind turbine operated in a wide range of wind speeds and, consequently, of rotor speeds. Figure presents a polar plot of the speed and direction of the wind during the same period. Although it shows a broad range of directions of wind incidence, there is a clear dominant direction around West and Southwest. 689

8 Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 4 the monitored period; and the study of the influence of the ambient and operational effects on the modal properties of the wind turbine. Wind direction vs Wind speed [m/s] N ACKNOWLEDGMENTS W E S Figure. Wind direction and speed during the period under analysis Figure confronts the nacelle orientation of the wind turbine with the wind speed. As in Figure, the wind turbine is mainly oriented to the same direction of the wind, which confirms (the expected) good agreement between wind direction and nacelle orientation. REFERENCES [] [] [] [4] Nacelle orientation vs Wind speed [m/s] N The authors would like to acknowledge: () all the financial support provided by the Portuguese Foundation for Science and Technology (FCT) to ViBest/ FEUP in the framework of the Project Dynamic Behaviour Monitoring for Structural Safety Assessment / National Network of Geophysics (National Programme for Scientific Re-equipment) () the Ph.D. Scholarship (SFRH/BD/798/) provided by FCT to the first author; () the support given by INEGI, the wind turbine manufacturer Senvion and the wind turbine owner Cavalum. [] W E [6] [7] S [8] Figure. Nacelle orientation and wind speed during the period under analysis [9] CONCLUSIONS This paper presents the work developed up to now under the scope of the development of a dynamic monitoring system for a. MW wind turbine. Initially, an ambient vibration test performed prior to the installation of the monitoring system is described and the main results discussed. Alongside, a FE model of the wind turbine is developed and the results from a modal analysis are compared with the ones obtained with the experimental test. Furthermore, the suitability of the outputonly modal identification algorithms is shown with the study of different setups corresponding to the dynamic response of the structure under different operation scenarios. Lastly, the initial results from the automated identification of the wind turbine modal parameters are presented. The next steps for the implementation of the dynamic monitoring system will comprise: the identification of the source of the identified stable alignments in the ambient vibration test which do not correspond to support structure modes; a better understanding of the variability of the frequency values from the two pairs of bending modes along 69 [] [] [] [] [4] [] [6] The European Wind and Energy Association (EWEA), Wind in Power European Statistics, 4. Global Wind Energy Council (GWEC), Global Wind Statistics,. The European Wind and Energy Association (EWEA), The European Offshore Wind Industry Key Trends and Statistics, 4. F. Magalhães, Á. Cunha, E. Caetano, Vibration based structural health monitoring of an arch bridge: From automated OMA to damage detection, Mechanical Systems and Signal Processing, 8, -8,. W.-H. Hu, C. Moutinho, E. Caetano, F. Magalhães, Á. Cunha, Continuous dynamic monitoring of a lively footbridge for serviceability assessment and damage detection, Mechanical Systems and Signal Processing,, 8-,. F. Pelayo, M. López-Aenlle, A. Fernández-Canteli, R. Cantieni, Operacional modal analysis of two wind turbines with Foundation problems, 4th International Operational Modal Analysis Conference (IOMAC), Instanbul, Turkey,. H.-W. Hu, R. Rohrmann, S.Said, W.Rücker, Development of a Vibration-Based Structural Health Monitoring System for Wind Turbines, the 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Hong-Kong,. C. Devriendt, F. Magalhães, M. El Kafafy, G. de Sitter, Á. Cunha, P. Guillaume, Long-term dynamic monitoring of an offshore wind turbine, st International Modal Analysis Conference (IMAC), California, USA,. G. Oliveira, F. Magalhães, E. Caetano, Á. Cunha, Modal Identification and FE Model Correlation of a Wind Turbine Tower, th International Operational Modal Analysis Conference, Guimarães, Portugal,. MATLAB b, The Mathworks Inc, Natick, MA,. B. Peeters, G. de Roeck, Reference-based Stochastic Subspace Identification for Output-Only Modal Analysis, Mechanical Systems and Signal Processing, (6), 8-878, 999. B. Peeters, H. Van der Auweraer, Polymax: a Revolution in Operational Modal Analysis, st International Operational Modal Analysis Conference (IOMAC), Copenhagen, Denmark,. F. Magalhães, Á. Cunha, Explaining operational modal analysis with data from an arch bridge, Mechanical Systems and Signal Processing, (), 4-4,. ANSYS Mechanical, Release 4. T. J. Larsen, A. M. Hansen, How HAWC, the user s manual, Risø-R97(EN), 7 F. Magalhães, Á. Cunha, E. Caetano, Online automatic identification of the modal parameters of a long span arch bridge, Mechanical Systems and Signal Processing,, 6-9, 9