AUTOMATED OPERATIONAL MODAL ANALYSIS ON AN OFFSHORE WIND TURBINE: CHALLENGES, RESULTS AND OPPORTUNITIES

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1 AUTOMATED OPERATIONAL MODAL ANALYSIS ON AN OFFSHORE WIND TURBINE: CHALLENGES, RESULTS AND OPPORTUNITIES W. Weijtjen 1, G. De itter 2, C. Devriendt 3 and P. Guillaume 3 1 dr.ir., Vrije Univeriteit Bruel / OWI-lab, wweijtje@vub.ac.be 2 dr.ir., Vrije Univeriteit Bruel / OWI-lab, gdeitte@vub.ac.be 3 pro.dr.ir., Vrije Univeriteit Bruel / OWI-lab / BruWind, cdevrien@vub.ac.be 4 pro.dr.ir., Vrije Univeriteit Bruel / BruWind, paguilla@vub.ac.be ABSTRACT Thi contribution ummarize over two year o applied automated operational modal analyi on an operational ohore wind turbine. It dicue the applied automated Operational Modal Analyi (OMA) algorithm and the challenge o applying OMA to operational ohore wind turbine, ranging rom the trong preence o rotor-harmonic to the enitivity o modal parameter to environmental and operational condition. The paper how the mot intereting reult o over two year o monitoring, including an indutry-irt in-depth analyi o the behavior o the damping over the entire operational window. Moreover, a hort dicuion on the potential or OMA a a monitoring tool or ohore wind turbine i given. Keyword: Ohore wind turbine, Structural Health Monitoring, Automated OMA, Harmonic, Damping 1. INTRODUCTION Thi contribution will how and dicu over two year worth o operational modal analyi on an ohore wind turbine. The reearch dicued herein tarted in 211 and i currently (215) till operational Motivation Many large-cale ohore wind arm project ue monopile oundation to obtain a cot eective deign. During the deign o thee monopile tructure atigue due to combined wind and wave loading i one o the mot important problem to take into account. Coincidence o tructural reonance with wind and wave orce or the harmonic orce induced by the rotor can lead to large tree and ubequent

2 accelerated atigue [1]. Thereore, it i important to have a clear view on what parameter inluence the reonance requencie o tructure and may potentially hit them into the range o thee excitation. Damping ratio are alo crucial or lietime prediction a the amplitude o vibration at reonance i inverely proportional to thee ratio. The overall damping o the tower mode o an ohore wind turbine conit o many dierent contribution, including tructural damping, oil damping, aerodynamic damping and additionally intalled damper uch a a tuned ma damper (TMD)[2]. The dierent dynamic o each type o damping and their relative contribution to the overall damping are a challenge or imulation and there i a deire or experimental damping meaurement on wind turbine. For onhore turbine everal meaurement have been done on operational turbine, e.g. to quantiy aero-elatic eect on the damping o blade-whirling mode [3]. Other hort term meaurement erved a proo o concept or dierent identiication technique [4, 5] or to illutrate innovative meaurement technique [6]. The irt reult o a long term monitoring campaign on an operational/commercial wind turbine in Portugal were preented in [7]. For ohore wind turbine the added upport tructure a well a the unknown in the tructure-oil interaction have encouraged a urther experimental reearch into the dynamic o the oundation and the tower. In [8] the reonance requency and modal oil damping o ohore wind turbine or dierent oil condition were determined by perorming rotor-top tet at ive wind park in the period rom 26 to 211. However, uch an approach can only yield reult when a rotor-top i perormed and thu doe not allow to determine damping over the entire operational window. Operational Modal Analyi reolve thi limitation a a continuou etimate o damping and reonance requencie become poible. In [9, 1] the modal parameter (i.e. the reonance requency, damping ratio and mode hape) or a 5MW ohore wind turbine on a tripod tructure located at the German Alpha Ventu wind arm were determined through a long term meaurement campaign. Recently, the irt reult o a meaurement campaign conducted at the Burbo Bank ohore wind arm were preented in [11] and preliminary reult o meaurement conducted at the Baltic 1 ohore wind arm were given in [12] Meaurement etup The reult in the ollowing ection are part o an ongoing reearch project at the Belwind windarm outide the Belgian coat, Fig. 1.(a). The Belwind arm conit o 55 Veta V9-3.MW turbine on monopile oundation at water depth up to 3m and located 46km outide the Belgian coat. A part o the Ohore Wind Inratructure laboratory (OWI-lab) one o the turbine wa equipped with accelerometer to invetigate the vibrational and damping propertie o the a-built tructure. The conidered turbine i ituated at a water depth o 24m w.r.t. LAT at the North ide o the wind arm. The local oil conit motly out o and with a thin layer o ti clay. The monitored tructure wa originally equipped with 1 MEMS accelerometer at our level o the tructure located 19m, 27m, 41m and 69m above the lowet atronomical tide (LAT). The etup i primarily aimed at the identiication o tower bending mode in both Fore-At (FA) and Side-Side (SS) direction, Fig. 1.(b). A the enor are ixed w.r.t. the tower tructure the yaw angle rom the SCADA i ued to tranorm meaured acceleration into the FA-SS coordinate ytem and thu decouple the FA and SS motion. Two additional enor are intalled at the top level to identiy torional vibration in the tower. During the monitoring campaign the enor at the lowet level and torional enor were removed and will not be dicued in thi contribution. The accelerometer were choen baed on their high enitivity (1V/g) and their requency range o - 25Hz. The lower requency bound wa crucial to capture the irt tructural mode which wa expected at.35hz. Beide the accelerometer, the turbine i alo equipped with both reitive and optical train gauge, load cell, diplacement enor and a corroion enor. All enor are connected to a NI CompactRIO ytem in the tower. Data i gathered continuouly and tranmitted at 1min interval to an onhore erver through a dedicated iber connection. A more detailed overview o the enor layout and the propertie o the data-acquiition ytem i held in [13]. All acceleration meaurement and conequently the reult o any OMA analyi will be greatly inlu-

3 Figure 1: (a) The Belwind windarm i located 46km outide the Belgian coat. (b) One o the turbine at Belwind i equipped with ix accelerometer in a X-Y coniguration meauring vibration in a plane parallel to the ea level (c) The intalled NI CompactRIO data acquiition ytem enced by the varying operational and environmental condition. To ae thi variability a ubet o the turbine SCADA data and meteorological data rom the nearby (approx. 3m) Ohore High Voltage Station (OHVS) i made available by the operator. Finally, the ea tate can be aeed by mean o a wave-radar intalled on the OHVS and the enor-array o Meetnet Vlaame Banken [14]. The Meetnet Vlaame Banken conit o everal wave-radar, wave-rider and meteorological tation pread acro the Belgian part o the North ea. 2. AUTOMATED OMA FOR AN OFFSHORE WIND TURBINE In thi ection the developed Automated OMA trategy will be explained. Firt, the automatic operational modal analyi algorithm, a it wa applied to a parked turbine, will be explained. Next, we will explain the ue o a harmonic tracker and a cae-by-cae tracking trategy to monitor a ully operational turbine Methodology or monitoring a parked turbine The automated OMA algorithm conit o our baic tep that are repeated or every ten minute o data. Thee our tep are: 1. Preproce: Preproce the acquired raw data 2. Sytem identiication: Apply a ytem identiication technique to the proceed data to etimate the reonance requencie, damping ratio and mode hape 3. Interpretation: Proce and condene the reult o the previou tep 4. Tracking: Link the current reult to prior reult Thee our tep are not unique to the herein preented methodology and might even be conidered a the tandard paradigm or automated operational modal analyi. The aorementioned tep are readily recognizable in everal other publication about automated OMA [9, 15, 16, 17]. In Fig. 2 illutration are given or each o the individual tep. The dierence between automated OMA trategie lie within the ollowed approach or each o the tep. In the next ection we will briely elaborate on how we illed in thee individual tep. A more detailed and elaborate dicuion can be ound in [18].

4 Autocorrelation model order dd dd.. d.. dd d.d d. d dd dd d.... d d... d. d.d d. d. d dd.d.. d.. d..... dd. d... d d......d d d d... d.d d.. dd d. Damping ratio (%) Frequency Time Frequency Natural Frequency (Hz) (a) Preproce: Calculated autocorrelation o one output (b) Sytem identiication : The p-lscf curve itter give a tabilization chart (c) Interpretation : The tabilization chart i condened into a cluter plot Time (d) Tracking: reult Figure 2: Illutration o the our tep o an automated OMA approach or a parked turbine Step 1: Preproceing Meaurement are conducted at a 5kHz rate. However, interet lie within the -5Hz requency band. To reduce the amount o data the ignal are iltered and down-ampled. The obtained time-domain data i then preproceed or OMA. The ignal at thi point, while down-ampled and iltered, are till too noiy or reliable reult rom the modal parameter etimator. An additional averaging i perormed through the calculation o auto- and cro power pectra. In OMA two technique are commonly ued to calculate the power pectra [19], called the correlogram and the periodogram approach. In eence, the periodogram calculate the power pectra by dividing ignal in everal block. Each block i windowed, e.g. Hanning, to reduce the eect o leakage. The windowed block are tranormed to the requency domain and a power pectrum i etimated by calculating the averaged pectrum over the dierent block. Alternatively, the correlogram approach conider the entire ten minute time ignal and calculate the auto- and cro-correlation o all meaured ignal. The reult i a decaying unction that i driven by the mode o the invetigated unction. When the ytem i excited by white noie then the ound decaying unction are related to the impule repone unction o the conidered ytem. Next, only a limited number o point o the decay are conidered, an operation with the ame eect a averaging. The obtained ignal i tranormed to the requency domain and the ound power pectrum i ready or OMA. A ull length dicuion on the choen etting or the preproceing and their impact on the ytem identiication i held in [2] Step 2: Sytem identiication In eence all OMA method are uitable to perorm the modal parameter etimation. However, method like peak-picking and FDD that do not provide a damping etimate are typically not conidered. In [16] it wa even hown that due to the act that FDD can only etimate reonance requencie with an accuracy limited to the requency reolution, a igniicant amount o inormation wa overlooked. More advanced method like EFDD and FSDD [21], which reolve thee limitation, have not yet been implemented or automated OMA. Mot publication with an automated OMA preer parametric etimator either baed on the ubpace etimation method, like SSI-COV [22, 15, 1, 7, 17], or the requency domain etimator like p-lscf [23]. The main reaon to chooe parametric method i the ability to achieve a better enitivity on the etimated reonance requency and to determine a damping etimate. In [24] dierent requency domain algorithm were compared uing the meaurement data o the parked ohore turbine. And in [25] the plscf wa compared to SSI-COV. Baed on both reult it wa decided that the plscf compared well to other technique and i thereore ued in the current automated operational modal analyi trategy.

5 Height (m) 4 Height (m) 4 Height (m) 4 Height (m) 4 Height (m) Figure 3: Reerence mode hape a ued by the tracking algorithm or parked condition (.l.t.r. : FA1, SS1, B1, SS2, FA2) Step 3: Interpretation The reult o a parametric modal parameter etimator i a tabilization chart a hown in Fig. 2.(b), rom which the etimated modal parameter are picked. People novel in modal analyi oten ak which pole are the correct olution within a tabilization chart. While there are ome general rule-o-thumb they are till not concluive. A human actor alway remain part o the modal parameter election uing a tabilization chart. The bigget dierence between modal analyi and automated modal analyi lie in the act that the human actor ha to be eliminated. The mot common trategy i to condene the tabilization chart. While the exact trategy varie over dierent publication, [17, 1, 22], the core idea i imilar. While in regular modal analyi a ingle pole, or each mode, i picked rom the tabilization chart, mot automation algorithm try to conider all etimated pole and condene thee reult. In eence rather than looking at a ingle table pole in the tabilization chart, thee algorithm look at table line and combine all reult within the table line into a ingle etimate. In [22] thi wa implemented uing a hierarchical clutering algorithm. In a econd tep thee obtained cluter can be evaluated, i.e. are they phyical or mathematical, uing a Fuzzy C-mean clutering approach [26]. In later publication the econd tep wa omitted a a proper tracking alo reject improbable pole Step 4: Tracking The main purpoe o the tracking tep i to link the newly obtained reult with earlier reult in order to track mode over long period o time. Typically, tracking algorithm will work very imilar to clutering algorithm. They will oten calculate a ditance unction or the ound pole compared to a reerence et o tracked mode. The ound mode i thu linked to the reerence mode to which it ha the mallet ditance. Etimated pole that exceed a threhold ditance rom all o the reerence value are rejected. The ditance unction will typically rely on the reonance requencie and mode hape, e.g. through the MAC-value. Ditance unction that rely on damping have ome potential, a two cloely paced mode might have dierent damping value, but are typically le reliable due to the greater pread on damping reult. Moreover, many cloely paced mode are alo reolved by the mode hape. E.g. in (near) ymmetric ytem, bending mode typically come in cloely-paced pair o orward and ideway mode. While they are very cloe w.r.t their reonance requencie, they have near orthogonal mode hape. A good et o reerence modal parameter i crucial or a proper unctioning o thee tracking algorithm. The tracking reerence were determined by manually proceing the reult over a given period o time, e.g. everal week. A an illutration Fig. 3 how the ive irt reerence mode hape a are ued or the current turbine in parked condition. A econd important element in etting tracking parameter i to conider the natural variability o the etimated modal parameter. With natural variation occurring, e.g. due to the tidal level, the threhold ditance cannot be et too mall. Eectively, one want to track

6 Stabilization Chart model order d d d p 12p.. 15p. 3p d. 6p SS1,FA1 FA2,SS2 FA3 SS3 requency (Hz) Figure 4: Stabilization chart or a dataet during which the turbine wa contantly rotating at 16rpm which yield harmonic at.8, 1.6, 2.4, 3.2 and 4Hz. mode through their natural variation rather than loing them every time a high tide come in. Fig. 2.(d) how the reult o a well deined tracking algorithm, that i able to capture the natural variation o the individual mode Challenge in monitoring an ohore wind turbine The algorithm preented in Sec wa initially developed or parked condition. Once the turbine tart operating three major new challenge pop up: Harmonic caued by the rotor poe a eriou challenge to any automated OMA The changing geometry o the turbine can igniicantly alter the overall dynamic o the tower Interpreting the vat amount o reult againt the environmental condition Challenge 1: Dealing with Harmonic The main ource or harmonic excitation or ohore wind turbine originate rom both wave-excitation and the rotor harmonic. Rotor harmonic are typically identiied a a multiple o the rotor peed p. For a three bladed turbine the multiple o 3-p are o particular relevance. Fig. 4 how how thee multiple o the 3p harmonic pop up in a tabilization chart. Wind turbine are deigned to avoid thee harmonic a much a poible. But deign mot oten ocue on the irt FA and SS mode. For the conidered turbine the FA1 and SS1 mode are poitioned nicely in between the 1p and 3p harmonic. While the FA1 and SS1 are well ditanced rom any harmonic, or the operational rotor peed 1-16 rpm, other mode regularly interact with a harmonic. Higher order mode are oten within the range o multiple harmonic. The FA1 and SS1 mode might be unaected by the rotor harmonic, they do interact with the wave period which roughly range rom.2hz to.4hz. Or otherwie put, all mode o an OWT are at ome point aected by a harmonic excitation. In [27, 28] everal trategie to reolve the rotor harmonic in the wind turbine were teted. Overall, they how ome improvement but inuicient to ully remove the eect o the harmonic. The (p)toma amily o algorithm [29, 3] might olve thi iue in the near uture, but ha till ome challenge to overcome [18]. So, a o now we will rely on the property that OMA till yield reliable reult when both harmonic and mode are well identiied. Through the SCADA data the average ten minute turbine RPM i known. It i thu poible to evaluate each reult againt thi ten minute average. Fig. 5.(a), inpired by Campbell diagram, how the number o detected mode within a given 2D bin. It thu how the reult o all identiied mode. The dahed line indicate where the harmonic requencie are to be ound. Epecially the 3p,.5-.8Hz, and the 6p, 1-1.6Hz, rotor harmonic how up in the diagram. Other higher order harmonic are ometime detected

7 (a) All identiied mode (b) Reult with harmonic tracking Figure 5: Campbell diagram inpired 2D hitogram. Color vary rom purple to red according to the number o time the mode wa identiied. In the dahed line indicate the 1,3,6,...,21p harmonic requencie. but are ar le dominant a the 3 and 6p. The current olution to harmonic will lag all etimated pole within a ive percent range o the harmonic aociated with the current rotational peed. We reer to thi approach a harmonic tracking. The analyt can then chooe to reject all lagged etimate. In Fig. 5.(b) the Campbell diagram i repeated but with the harmonic tracker activated and all aected etimate rejected. The ive percent range i choen baed upon experience and the known enitivity o the automated operational modal analyi technique. The ive percent bound i alo neceary to addre the variation o the RPM within the ten minute dataet. The ive percent boundary i currently conidered a rather ae boundary but i contantly challenged nonethele. For each obtained reult the quetion i aked, what about the harmonic? The reult hared in the continuation o thi thei hould illutrate that the harmonic tracking i a pragmatic, yet eicient method to reolve the iue o harmonic in the automated OMA o an OWT. The major diadvantage o the harmonic tracker are the gap o rejected reult that occur or ome operational cae a many valuable reult have to be rejected, Fig. 5.(b). Thee gap can only be illed in by applying OMA technique that are le enitive to the eect o input coloration. However, work on data rom the intrumented Belwind turbine have hown that at thi point there i no o-the-hel olution to reolve the eect o thee harmonic[27, 28]. Meanwhile promiing input inenitive etimation approache, like ptoma [29], are till at a lab-tet level. Another alternative approach to ill up the gap, made by the harmonic tracker, i uing order baed operational modal analyi[31]. Order-baed modal analyi i typically ued in motor run-up tet, in which the motor harmonic are conidered a a weeping periodical input that run through all ytem dynamic. Applied to the wind turbine thi would imply to look at the rotor harmonic a an input with a varying requency. The data that i now rejected by the harmonic tracker could thu erve a an input to an order baed model analyi algorithm. A uch it i complementary to the current approach and can erve to ill in the gap. However, the perormance o the algorithm need to be veriied when applied to an operational windturbine. Epecially the peciic behavior o the broad-band windturbine rotor harmonic, the time-varying behavior o the turbine and the abence o a continuou run up might aect the perormance o an order baed approach Challenge 2: The eect operational condition have on the modal parameter o the turbine The ohore wind turbine i ubjected to wide variety o dierent operational cae. Thee dierent operational cae reult in trong variation in the modal parameter. To illutrate thi behavior conider

8 Reonance Frequency (Hz) Reonance Frequency (Hz) Time Time Figure 6: Tracking reult o the third order FA and SS mode during parked (let) and rotating (right) condition. Baed on the mode hape ( Red: FA motion, Green: SS motion) it can be concluded that reonance requencie can igniicantly hit between operational condition. Wind peed rpm Pitch angle (m/) (deg) Min. Max. Min. Max. Min. Max. 1:Pitch : >8 n/a n/a n/a n/a 8 1 2:Pitch : ±8 2 n/a n/a 7 8 3:Pitch : ±2 n/a n/a n/a n/a :RPM : <1 n/a n/a n/a n/a 5:RPM : ±1 n/a n/a n/a n/a 6:RPM : <16 n/a n/a n/a n/a 7:RPM: ±16 n/a n/a n/a n/a 8:Cut-Out 2 n/a n/a n/a 7 8 Table 1: Deinition o the conidered cae in the algorithm Fig. 6. Thi igure how how the FA and SS mode that have been identiied a the third order tower bending mode, witch poition once the turbine tart rotating. A poible explanation lie with the changed geometry o the turbine over the two operational cae. A major dierence between a rotating and parked turbine i the blade pitch angle. In parked condition the turbine blade are pitched out with a blade pitch angle o approximately 8 deg. Once rotating the blade are pitched into maller angle with a minimum at approx. -3 deg. It i known rom imulation that higher order tower mode alo have a igniicant blade motion and are thu more aected by variation in the blade geometry. The key idea to reolve thi variability i to ue the available SCADA inormation to link each tenminute dataet to a recurring operational condition reerred to a a cae. Each cae i deined by the boundary condition et by the analyt and thee are eaily modiied or new turbine, control trategie or deinition o operational cae originating rom norm. Table 1 give the boundarie ued or the monitored turbine. Thee cae were deined by looking at the SCADA data o the turbine during 212 and by recognizing the dierent operational tate o the turbine. Fig. 7 erve to illutrate the phyical meaning o the et boundary condition By uing a cae-by-cae tracking approach it i poible to ue multiple reerence et or tracking during dierent operational cae rather than jut a ingle et to track over all dierent cae. I a ingle reerence et wa ued to capture all variability due to the dierent operational condition it would require a very broad etting. However, thi problem i olved by allowing multiple reerence et or tracking with tighter acceptance criteria. Within each cae the tracking etting are optimized a to achieve a good ratio between the ucce rate and etimate quality within thi cae. So or each cae the expected reonance requencie and mode hape are deined and any reult within range o thee expected value will be accepted or rejected. Thi ultimately reult in a ar maller pread on the obtained reult. The inal reult can then be preented cae by cae, which i intereting or both analyi and deign. I or example a deigner wihe to perorm a atigue-lie analyi or a turbine at rated power, then a cae deinition : Power 3MW will provide the tatitic or damping and reonance requency etimate or that particular cae. In [1] the reult are alo preented in a imilar cae by

9 RPM Wind Speed (m/) Figure 7: RPM v. Windpeed with color indicating the dierent cae a deined in Table 1 cae ahion on a wind turbine in the Alpha Ventu wind arm Challenge 3: Data interpretation In order to quickly acce, analyze and interpret the reult o the automated OMA a ramework or data analyi wa built. The ramework collect and combine data obtained rom dierent ource, e.g. SCADA, Meteorological and the Meetnet Vlaame Banken. Modal parameter reult can then eaily be analyzed a a unction o mode, wind peed or any o the vat array o available parameter. Around thi ramework a graphical uer interace (GUI) wa built to provide a at and reliable tool to perorm any analyi. The initial eort o programming a GUI, paid o a a ingle analyi can be perormed in a matter o minute without having to look at the ource code. The reult hown in the next ection are all achieved through thi GUI and can be repeated quickly or dierent period o time, dierent tracker etting and ultimately dierent turbine 3. RESULTS In thi ection the reult o the OMA driven analyi are hown. Thi contribution will be dicuing the identiied tower mode, but the method wa alo able to detect and track blade and whirling mode [18]. Finally, the damping etimate or the irt tower bending mode, FA1 and SS1, are dicued in more detail Reonance requencie o the tower mode Six tower mode are tracked over time, i.e. the three pair o tower bending mode (FA1-SS1, FA2-SS2, FA3-SS3). Thee tower mode hould be detectable within each operational cae The reonance requencie during dierent operational cae Fig. 8 how the reult o all data obtained in 212 with the cae deined in Table 1. All ix mode were conitently tracked in the majority o cae. Only the FA2 and SS2 were not alway tracked a the 6p and 9p oten interact with thee mode and reult were rejected by the harmonic tracker. Higher order harmonic do alo interact with the third order mode but ater rejection by the harmonic tracker uicient data remain to draw reult, with exception or SS3 at 16rpm. Low ucce rate or FA3 at Pitch:±2 and Cut-Out do not allow or a deinitive reult at thi time. The plotted reonance requencie are the trimmed (25%) mean o the etimated reonance requencie or each cae. The reonance requency or the irt order mode i not igniicantly inluenced by the operational cae. On the other hand, both the econd and third order mode reonance requencie change igniicantly once the turbine tart producing (Cae 3 to Cae 7). Epecially trongly aected are the third order mode which have witched reonance requencie, a wa mentioned earlier. The reult all point to an important obervation: The reonance requencie o a wind turbine vary igniicantly or dierent operational cae.

10 The preented reult are the mean value over a year o meaurement. While the average value Reonance Frequency (Hz) Reonance Frequency (Hz) Reonance requency (Hz) (a) Firt order FA (Blue) and SS (Green) mode (b) Second order FA (Purple) and SS (Cyan) mode (c) Third order FA (Gold) and SS (Gray) mode Figure 8: Obtained reult or the irt three order FA and SS mode in 212. With (let) Mode hape o FA and SS mode (right) Reonance requencie or the dierent cae. The number on the X-axi repreent the cae a deined in Table 1. give an indication to what extent the reonance requencie can hit over dierent operational cae, all inormation about the environmental variability i lot The eect o environmental eect on the reonance requencie Fig. 9 demontrate the eect the environmental condition can have on the reonance requencie o an ohore wind turbine. Thee reult how the etimated reonance requencie o the SS2 mode during a period o parked condition. From Fig. 9.(a) a trong variation o the reonance requency can be oberved. Driving orce o thee variation are the tidal level and the wave-height, hown in Fig. 9.(c). The eect o the tidal level can be eaily explained. With higher tidal level the amount o water being diplaced by the turbine increae. The amount o diplaced water act a a ma-loading on the turbine, ultimately reducing it reonance requency. The relation between the tidal level and the reonance requency i negatively correlated, when tide rie the reonance requencie go down. Removing thee eect through linear regreion [32] reveal an underlying dependency with the yawangle, Fig. 9.(b). Under ome yaw-angle the wind turbine ha an increaed reonance requency. The 18 degree period o thi tiening indicate that the upport tructure i mot likely not axiymmetric and i tiened in a particular direction. Thi direction can be conidered a the tiet angle o the machine and wa linked to an auxiliary tructure called a J-Tube. The J-Tube i a teel tructure to protect the high voltage cable rom boat impact and rough ea. Thi local tiening i oberved in all tracked tower mode, Fig. 9.(d) and the tiet angle are alway cloe to the location o the J-Tube. Note that thi i remarkable a dierent mode hape imply a dierent eect o the J-Tube. Thee obervation demontrate the achieved enitivity o the propoed algorithm and the reliability o the etimate over a long period o time.

11 Reonance requency Reonance requency Time (a) Linear Model Yaw Φ (b) Normalized data Tidal Level (cm) Wave Height (cm) Time Time (c) Environmental condition during the training period (d) Top view with indication o the tiet angle or all 6 mode Figure 9: Reult or the reonance requency o the SS2 mode in parked condition. (a) Even a linear model (-) can partially ollow the variability in the data. (b) Looking at the normalized data reveal that the monopile i not axiymmetric.(c) Overview o tidal level and wave height and turbine yaw angle during the conidered period. (d) All 12 tiet angle plotted on top o a top view chematic o the tructure tranition piece. Mot etimate identiy the tiet tructural direction in the vicinity o the J-tube (two yellow circle) Damping o the irt tower mode One o the initial goal o the intalled accelerometer at Belwind wa to veriy the aumed damping value during deign o the wind arm. In particular the damping value o the irt FA and SS tower mode are o interet. A vibrational level are inverely related to damping, they play an important role in the atigue-lie calculation o the turbine. In thi ection we will thoroughly invetigate the behavior o the damping value o the irt tower mode. A detailed dicuion on the damping o higher order mode can be ound in [18]. We tart rom the original overpeed tet and build our way up to a detailed analyi Initial reult The irt experiment to etimate the damping value wa perormed by conducting an overpeed tet o the wind turbine. During the overpeed tet the rotational peed i brought to a maximum, ater which the blade are quickly pitched out. With the lo o aerodynamical load the tower pring back and a tep-repone like vibration i oberved, Fig. 1. From the impule repone the Fore-At damping ratio can readily be determined. Reult o thi etimation were irt preented in [33]. Note that a imilar approach, uing regular rotor top, i uggeted in [8] to determine the damping value over a longer period o time m 37m.1 23m Acceleration (g) Time () Figure 1: Acceleration meaured during an overpeed top. The highlighted area can be conidered a an impule repone o the OWT.

12 Overpeed Firt ambient Two week [33] [33] [13] ξ ξ ξ σ ξ ξ σ ξ ξ σ ξ FA SS1 n/a No Table 2: Damping value or a parked turbine in % along with tandard deviation σ ξ over the conidered period. Value highlighted in orange are obtained when the tuned ma damper i turned o. The lat row i the number o dataet that have been conidered Damping in parked condition Rotor top require a particular action o the turbine in order to determine damping. However, [33] wa the irt to ugget an automated OMA trategy baed on vibration induced by ambient orce to determine damping over longer period o time. Thi lead to the analyi o a two week period o parked condition o which the irt reult were preented in [13]. By uing automated OMA it became poible to acquire vat amount o damping etimate and more importantly damping etimate during dierent environmental condition. Ultimately allowing to analyze the behavior o damping over dierent wind condition. Table 2 um up the reult ound rom the aorementioned publication. The mot recent reult rom the ongoing campaign are alo provided. Earliet reult were obtained when the intalled tuned ma damper (TMD) wa turned o. The eect o the TMD can be quantiied by looking at the damping ratio during parked condition at low wind peed. In the abence o aerodynamical damping the total tructural damping, including the eect o the TMD, reult in approximate % o total damping. It i important to notice the tability o the overall etimate over time o both damping etimate. The change in σ ξ over the earlier reult in [13] and the more recent reult are due to updated etting within the entire trategy. Important to note i that the conidered tandard deviation i motly linked to the environmental variability o the damping value. Eectively, one can undertand that dierent environmental condition will have an inluence upon the damping. The tandard deviation hould thu not be conidered a an uncertainty upon the etimate, but more a an indication o the range o poible damping value. An increaed tandard deviation thu thereore not inherently mean that the etimate have become poorer. In the next ection we will broaden the analyi beyond parked condition and include all operational condition Damping during operational condition In Fig. 11 the cae-by-cae damping reult are preented or the irt order tower mode. Thee value are the reult o proceing dataet over a period o two year. The cae deinition are thoe preented in Table 1. Both reult or 212 and 213 are preented a box plot. In Fig. 11.(c) the median value o the damping etimate are hown, thee correpond with the red horizontal line in the box plot. Several intereting obervation can be made. At a irt glance, one notice the tability o the damping etimate over two year. Only during Cut-out there i a dierence between both year. Thi can be attributed to the rare occurrence o Cut-out, which reult in a mall number o damping etimate. During parked condition, Pitch:>8deg and Pitch:±8deg., the SS damping exceed the FA damping. With the blade pitched out, i.e. acing away rom the wind, mot blade urace i acing the SS direction. Thi larger blade urace will induce air low and thu diipate energy. Or otherwie put, the SS mode ha a larger contribution o aerodynamic damping. Note, that thi eect i even viible when the blade are pitched above 8deg or at 8deg. The FA damping lightly increae, due to a larger blade urace, while the SS damping decreae lightly. Thi trend continue over dierent cae. Over the next cae the blade will pitch in and the turbine tart rotating. At Pitch:±2 both direction are approximately equally damped. With increaing rotational

13 15 FA1 15 FA1 Damping ratio (%) 1 5 Damping ratio (%) 1 5 Damping ratio (%) Pitch>8 Pitch±8 Pitch±2 RPM<1 RPM±1 RPM<16 RPM:16 Cut out SS1 Pitch>8 Pitch±8 Pitch±2 RPM<1 RPM±1 RPM<16 RPM:16 Cut out Damping ratio (%) Pitch>8 Pitch±8 Pitch±2 RPM<1 RPM±1 RPM<16 RPM:16 Cut out SS Pitch>8 Pitch±8 Pitch±2 RPM<1 RPM±1 RPM<16 RPM:16 Cut out Damping ratio (%) (a) 212 FA SS (b) 213 Pitch>8 Pitch±8 Pitch±2 RPM<1 RPM±1 RPM<16 RPM:16 Cut out (c) Comparion o damping value or 212 ( ) and 213 (- -). The plotted reult are the median value o (a) and (b). Figure 11: Cae by Cae damping reult or the irt order tower mode. (a-b) how the box plot o the obtained damping value or the dierent operational cae. On each box, the horizontal line repreent the median, the edge o the box are the 25th and 75th percentile, the whiker extend to the mot extreme data point not conidered outlier, and outlier are plotted individually a + peed, and maller pitch angle, the damping o the FA mode increae and ar exceed the SS damping. At the maximum rotational peed, RPM:±16, the damping o the FA mode reache 6%. Above the maximum wind peed the turbine i pitched out, with pitch angle imilar to thoe in Pitch±8. Again there i more blade urace in the SS direction which reult in a larger damping in thi direction. Given that the geometry in Cut-Out i imilar to the geometry in Pitch:±8, it i worth pointing out that the damping i larger in Cut-Out than in Pitch:±8. The caue lie within the larger wind peed which will reult in a larger aerodynamic damping contribution. For both 212 and 213 the relative increae in damping i larger or the SS mode than or the FA mode. The analyi o damping can be alo be done w.r.t. the available environmental parameter. In particular the behavior w.r.t the wind peed i o interet The inluence o environmental parameter In Fig. 12 the damping etimate during production, not conidering parked condition and cut-out, or 212 are hown. With increaing wind peed the damping o the FA mode increae rom 1.8% to 6.5-7%. The damping alo increae or the SS direction but only rom 1.8% to 3%. The rapid increae in FA damping can readily be attributed to the turbine rotation. The induced airlow increae aerodynamic damping. Eventually the FA damping tagnate around 6.5-7%. Thi tagnation o the damping value wa alo predicted by theory or imilar turbine [34]. However, more dedicated imulation model uggeted that the damping would again drop ater a given wind peed [34]. The current reult do not indicate uch a drop. In [8] an decreaed damping ratio wa ound at higher vibration level o the nacelle. Such an eect i not viible rom the conidered dataet, but thi can attributed to

14 Damping Ratio (%) Damping Ratio (%) Wind Speed (m/) (a) FA Wind Speed (m/) (b) SS1 Figure 12: Boxplot or the damping value v the windpeed during production 8 6 Damping ratio (%) 5 Damping Ratio (%) y =.31*x Time (a) SS Damping over time, with a linear regreion model ( ) baed on the windpeed and wave height. d Water Temperature 2 (b) Detrended reult a a Figure 13: (a) The windpeed and wave height dependent behavior can be partially modeled uing a linear regreion model (b) With thi trend removed the SS damping v the water temperature ( C) reveal a temperature dependency the dierent nature o the conducted experiment. A [8] only conider rotor top to obtain an etimate o damping and the reonance requency. The SS damping i le aected by the wind peed o the turbine. An obervation that correpond to the reult in Fig. 11.(b). Dierent rom the FA damping, i the dependency o the SS damping w.r.t. the wave height at the ite. While wave height and wind peed are trongly correlated, the correlation o SS damping w.r.t wave height wa lightly higher than the correlation to windpeed. A continued analyi i to ubtract a linear regreion model o the damping ratio baed on wave height and windpeed, Fig. 13.(a). By ubtracting thi imple model rom the original etimate a de-trended, a.k.a. normalized, damping etimate i ound. Fig. 13.(b) reveal a limited temperature dependent behavior that wa otherwie obcured by the variability to the windpeed and wave height. 4. OPPORTUNITIES : OMA AS DECISION SUPPORT In the previou ection we dicued the challenge and olution to apply automated OMA to an operational ohore wind turbine. However, in thi inal ection it i intereting to point out the potential beneit o a continued operational modal analyi campaign. A aid in the introduction it i relevant to wind arm operator to keep an eye on their reonance requencie. Structure-rotor interaction can caue accelerated atigue lie conumption and ultimately lead

15 (a) (b) Figure 14: (a) Laboratory example o cour development around a monopile (b) Scour caue the tower reonance requency to drop [35] or both monopile a well a tripod upport tructure to an accelerated deterioration o the upport tructure. It i exactly thi mechanim that i alo the motivation to monitor cour around the monopile oundation. A cour hole, hown in Fig. 14.(a), i caued by the eroion o the eabed around the monopile. Interetingly thi eroion will aect the reonance requencie o the upport tructure, Fig. 14.(b). In cae o evere cour thi might caue a reonance requency to hit into the range o wave-excitation or rotor-harmonic. Currently mot operator perorm bathymetric meaurement to detect cour, but have no idea whether the oberved cour i aecting the reonance requencie. Moreover, bathymetric meaurement are oten equipment intenive and have a coniderable cot. Uing OMA to track the modal parameter doe not only allow to detect cour, i.e. by detecting a hit in the reonance requencie, [32] it imultaneouly allow to judge whether the hit in reonance requency i cauing any iue. In combination with a atigue monitoring trategy [36], which relie on a imilar enor array and thu bring no added cot, OMA can become a indutry-wide practice in monitoring ohore wind turbine. 5. CONCLUSIONS Thi contribution howed an overview o challenge, reult and uture opportunitie or automated OMA on an ohore wind turbine. Over two year o applied Automated Operational Modal Analyi ha learned u many thing about the dynamic o ohore wind turbine. Uing the preented methodology, which i the culmination o our year o reearch, we obtained a method that wa uiciently enitive to monitor and detect variation in the reonance requencie and damping ratio o a ully operational wind turbine. Challenge uch a harmonic and the environmental and operational eect on the turbine dynamic have been addreed in a pragmatic and reliable way. Nonethele, there i till room or improvement in both automated operational modal analyi and ytem identiication in general. ACKNOWLEDGMENTS Thi reearch ha been perormed in the rame- work o the Ohore Wind Inratructure Project ( author alo acknowl- edge the inancial upport by the Fund or Scien- tiic Reearch Flander (FWO) and the Agency or innovation by Science and Technology (IWT). The author grateully thank the people o Belwind NV or their continuou upport within thi project. REFERENCES [1] J. van der Tempel. Deign o upport tructure or ohore wind turbine. PhD thei, TU Delt, 26. [2] N.J. Tarp-Johanen, L. Anderen, E. D. Chritenen, C. Mørch, and S. Franden. Comparing ource o damping o cro-wind motion. In Proceeding o EWEA Ohore, 29.

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