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EP4077929A1 - Procédé et dispositif de détermination d'un changement dans une répartition de masse d'une pale de rotor sur une turbine éolienne - Google Patents

Procédé et dispositif de détermination d'un changement dans une répartition de masse d'une pale de rotor sur une turbine éolienne

Info

Publication number
EP4077929A1
EP4077929A1 EP20823795.8A EP20823795A EP4077929A1 EP 4077929 A1 EP4077929 A1 EP 4077929A1 EP 20823795 A EP20823795 A EP 20823795A EP 4077929 A1 EP4077929 A1 EP 4077929A1
Authority
EP
European Patent Office
Prior art keywords
rotor blade
natural frequency
mass distribution
states
mass
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP20823795.8A
Other languages
German (de)
English (en)
Inventor
Daniel Brenner
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Weidmueller Monitoring Systems GmbH
Original Assignee
Weidmueller Monitoring Systems GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Weidmueller Monitoring Systems GmbH filed Critical Weidmueller Monitoring Systems GmbH
Publication of EP4077929A1 publication Critical patent/EP4077929A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
    • F03D80/40—Ice detection; De-icing means
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/334—Vibration measurements
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

Definitions

  • the invention relates to a method for determining a change in a mass distribution of a rotor blade of a wind turbine.
  • the invention further relates to a device for carrying out the method, the device having vibration sensors on the rotor blade and / or on components of the wind turbine connected to it, as well as an evaluation device for signals from the vibration sensors.
  • the evaluation of vibrations of a rotor blade of a wind turbine is an effective means of detecting damage to rotor blades or the accumulation of additional mass.
  • additional masses can result, for example, from the accumulation of dirt and, in particular, of ice. Ice can be deposited in large quantities on rotor blades, up to the 10 or 100 kilograms (kg) range. To avoid the dangers of falling and thrown ice, knowledge of the accumulated mass of the ice is of great interest.
  • the document DE 10 2016 124 554 A1 describes a method for recognizing an accumulation of ice on a rotor blade of a wind turbine, in which a change in a natural frequency is used to deduce ice accumulation.
  • this indirect method is combined with measurement results from sensors, with the aid of which it is possible to immediately deduce ice growth.
  • Sensors with which this is possible are, for example, conductivity sensors on the surface of the rotor blade or optically or acoustically operating sensors that can determine the layer thickness of an incremental ice.
  • the disadvantage of these sensors is that they can only detect ice locally in the immediate vicinity of the sensor.
  • a method is known from the document DE 10 2006 009 480 B1 in which a plurality of such direct sensors are provided for determining a thickness profile in order to measure the thickness of an accumulated ice. Layer to be able to detect over a larger spatial area on the rotor blade. Due to the large number of sensors, such an arrangement is complex to install and also to maintain and / or troubleshoot.
  • ice growing on the tip of the rotor blade runs the risk of being thrown far away from the location of the wind turbine. Ice accumulation in the area of the blade root is less critical insofar as it would generally not be thrown outside the rotor radius even when the wind turbine is rotating. This area is usually marked as a danger area, where, on the other hand, ice thrown further away from the location of the wind turbine can lead to property and personal danger.
  • first natural frequency states of the rotor blade of the wind energy installation are determined. This can be done using measurements or using models if a mass distribution of the rotor blade and information about the stiffness of the rotor blade are known.
  • Second natural frequency states are determined from the vibration measurements.
  • the deviation of the second natural frequency states from the first natural frequency states can be read off whether and how the second mass distribution differs from the first mass distribution, i.e. whether a dirt or ice build-up has occurred.
  • a distribution of additional masses that corresponds to the difference between the second and the first mass distribution is then derived from the measured changes in the natural frequency states.
  • the invention is based on the knowledge that by considering at least two natural frequency states, not only the presence of an additional mass on the rotor blade can be detected, but statements about the position or distribution of the additional masses can also be derived.
  • resonance frequencies and / or resonance amplitudes of oscillation states of different orders are understood as natural frequency states.
  • the first natural frequency states can be determined on the basis of measurement data in that vibrations of the rotor blade are determined during the first mass distribution and the first natural frequency states of the rotor blade are determined from the recorded vibrations.
  • the vibrations are preferably recorded using measurement signals from sensors which, for example, can be arranged in or on the rotor blades, with time-dependent vibration deflections derived from the measurement signals being recorded for a certain period of time.
  • an amplitude spectrum can then be determined by transformation into the frequency range and the natural frequency states can be determined on the basis of maxima of the amplitude spectrum.
  • Natural frequency states are characterized, for example, by a frequency and / or an oscillation amplitude.
  • the second mass distribution is determined on the basis of known dependencies of the frequencies of the eigenfrequency states of mass distributions. Knowledge gained empirically or derived from model calculations about the effects of additional masses on the natural frequency states can be used to determine the unknown second mass distribution.
  • the second mass distribution is preferred on the basis of known dependencies of the ratio of the frequencies of different natural frequency states of mass sensor distributions determined. This embodiment is based on the knowledge that the frequency ratio of different natural frequencies changes very characteristically with certain changes in the mass distribution. In particular, a distinction can be made between ice or dirt deposits that are evenly distributed along the rotor blade and more localized.
  • the second mass distribution is determined in that natural frequency states of assumed mass distributions are determined using mathematical models of the rotor blade and compared with the measured second natural frequency states.
  • the mathematical models preferably take into account the first natural frequency states, e.g. to adapt free parameters of the model to the actual measurements.
  • Fig. 1 is a schematic sectional view of part of a wind power plant
  • FIG. 2 shows a diagram for the representation of natural frequency states in the case of a rotor blade of a wind turbine
  • FIG. 3 shows an illustration of an amplitude spectrum of Schwingungszu states of a rotor blade of a wind turbine
  • FIG. 5 shows a flow diagram of a method for determining a mass distribution, for example an ice accumulation on a rotor blade.
  • Fig. 1 is an example of a sectional drawing of part of a wind power plant 1 is shown, which has a device 6 for determining a change egg ner mass distribution of a rotor blade.
  • the wind energy installation 1 shown in FIG. 1 is therefore suitable and set up for carrying out a process according to the application for determining a change in a mass distribution of a rotor blade.
  • the wind energy installation 1 has a nacelle 3 which is rotatably mounted on a tower 2 and which carries a rotor 4.
  • the rotor 4 has at least one rotor blade 41 which is connected to a rotor shaft 51 at a hub 42.
  • the area of the hub 42 and the approach of the rotor blades 41 is covered by a spin ner 43.
  • Fig. 1 two rotor blades 41 shown cut to length are exemplary shows ge. This is purely by way of example; wind turbines often have three rotor blades 41.
  • Said rotor shaft 51 is part of a drive train 5. It transmits the rotational movement of the rotor 4 to a gear 52. This in turn is coupled via a gear shaft 53 and a clutch 54 to a generator 55, which converts the mechanical energy of the rotor 4 into electrical energy converts.
  • the representation of the wind energy installation 1 with gear 55 is also purely by way of example.
  • the device according to the application and the method according to the application can just as easily be implemented with a gearless wind energy installation.
  • the device 6 for determining a change in a mass distribution of a rotor blade comprises at least one vibration sensor 61, hereinafter referred to as sensor 61 for short.
  • a sensor 61 is arranged in each of the rotor blades 41 shown.
  • Each sensor 61 is connected to an evaluation unit 63 via a sensor line 62.
  • the type of connection is shown in FIG. 1, purely by way of example.
  • the sensors 61 can be coupled to energy harvesting units, see above that they draw energy, for example, from the rotation of the rotor 4 and transmit data directly from the rotor blade 41 via radio to the evaluation unit 63.
  • the sensors 61 are vibration sensors that detect a vibration of the Ro torblatts 41.
  • the sensors 61 can be acceleration, expansion or rotation rate sensors. An oscillation is then recorded as a change in a measured acceleration value, a measured speed or a measured expansion.
  • the arrangement of the sensors 61 within the rotor blade 51 can be such that vibrations in the pivoting direction (“edge”) and / or in the flapping direction (“flap”) and / or in the torsion direction of the respective rotor blade 41 are detected.
  • the two sensors 61 shown in FIG. 1 are arranged approximately in a lower third of the rotor blade 41.
  • the sensors 61 can, however, also be arranged at other positions in the rotor blade 41.
  • vibrations of the rotor blades 41 on other components of the wind energy installation 1, on which corresponding vibration sensors are then arranged.
  • sensors can be arranged in the hub 42 and / or along the drive train 5, with vibrations of the rotor blade 41, which show up in these sensors, based on, for example, their frequency range of inherent vibrations on the drive train 5, for example due to gear meshes in the transmission 42, can be distinguished.
  • Fig. 2 shows in a schematic representation initially possible oscillation states 7 of a rotor blade, for example one of the rotor blades 41 according to FIG. 1. Shown is an oscillation amplitude on the vertical axis of the diagram as a function of a position along the rotor blade on the horizontal axis.
  • Each of the curves 71-74 represents an instantaneous deflection which is characteristic of the respective oscillation state 7.
  • the position "0" on the horizontal axis corresponds to the position of the blade root and the position “max” on the horizontal axis corresponds to the position of the blade tip.
  • Fig. 2 four oscillation states 7 are shown, a basic state in curve 71, a first harmonic in curve 72, which is characterized by a vibration node along the extension of the rotor blade, a second harmonic in curve 73, which is characterized by two vibration nodes and one third harmonic in curve 74, which is characterized by three oscillation nodes along the rotor blade.
  • the fundamental oscillation according to curve 71 is referred to as the first natural frequency state and the first, second and third harmonic as the second, third and fourth natural frequency state.
  • transverse vibrations that is, vibrations in the pivoting direction or direction of impact of the rotor blade are shown.
  • torsional vibrations i.e. rotations of the rotor blade about its longitudinal axis.
  • the time-dependent oscillation deflection derived from its measurement signals is recorded for a specific period of time for each of the sensors 61.
  • An amplitude spectrum is then preferably determined from the oscillation recorded in the time domain.
  • the transformation into the frequency range that is to say the representation as a spectrum, can take place, for example, by means of a fast Fourier transformation (FFT) or a wavelet transformation.
  • FFT fast Fourier transformation
  • wavelet transformation wavelet transformation
  • natural frequency states can also be determined in the time domain by appropriate filtering or by stochastic methods, for example via the so-called “Stochastic Subspace Identification” (SSI).
  • SSI Stochastic Subspace Identification
  • FIG. 3 shows a spectrum transformed, for example via FFT, from the vibration recordings in the time domain into the frequency domain in a spectral curve 75.
  • the vertical axis shows the amplitude of the vibration as a function of the frequency plotted on the horizontal axis.
  • natural frequency states can be identified in a simple manner as maxima of the spectral curve 75.
  • the assignment of the maxima to the different natural frequency states is possible through the increasing frequency.
  • the described vibration measurement and generation of a spectrum is repeated at regular time intervals. If a mass distribution on the rotor blade 41 changes, for example due to ice formation, the natural frequency states determined from the spectrum according to FIG. 3 change. These are characterized by their frequency and an assigned maximum amplitude.
  • FIG. 4 shows in a diagram on the vertical axis, the maximum amplitude de of two natural frequency states, namely the second natural frequency and the third natural frequency state, during the growth of ice (or more generally an additional mass), which is presented on the horizontal axis .
  • the units on the horizontal axis are percentages that indicate an increase of 0-100% of the additional mass.
  • the maximum amplitudes of the natural frequency states are normalized in such a way that they have the value 1 if the rotor blade is in its original state, i.e. no additional mass has yet grown (i.e. at the value 0% on the horizontal axis).
  • the first model calculation shows the development of the second and third natural frequency state when the ice accumulation occurs evenly over the entire length of the blade.
  • the correspondingly calculated ratios se of the frequency to the ice-free state are shown in the diagram by diamonds 81 for the second natural frequency state and circles 82 for the third natural frequency state.
  • the ice does not grow evenly over the entire length of the blade, but is concentrated in an outer area of the rotor blade.
  • the ratio of the frequency to the ice-free state of the second oscillation state is given by squares 83 and the Ratios of the frequency to the ice-free state of the third oscillation state represented by triangles 84 in the diagram.
  • the ratio of the frequency to the ice-free state of the second and third eigenfrequency state behaves differently in the two scenarios. If the ice layer grows evenly, the changes in the maximum amplitude for the second and third natural frequency state are essentially uniform over the entire calculated area, whereas if the additional mass is located at the tip of the blade, the amplitude of the second oscillation state decreases more significantly as the additional mass increases than that of the third natural frequency state.
  • the changes in the natural frequency states can accordingly be compared with previously made model calculations for mass distribution or with in-situ model calculations for mass distribution and a mass distribution that results from the increase in the additional mass can be derived.
  • An exemplary embodiment of a method according to the application is explained in more detail below with reference to FIG. 5 using a flow chart. The method can be carried out, for example, in connection with the wind energy installation 1 shown in FIG. 1. The method is explained by way of example with reference to the wind energy installation 1 according to FIG. 1.
  • first natural frequency states of the rotor blades 41 of the rotor 4 of the wind energy installation 1 are determined in an ice-free state of the rotor 4.
  • Natural frequency states are those oscillation states in which the rotor blades 41 oscillate after being excited to oscillate. How is explained in connection with FIG. 3, natural frequency states appear at maxima of an oscillation spectrum.
  • the first natural frequency states can accordingly be determined in step S1 by measuring and recording a time curve of vibrations, for example by one or more sensors 61. A vibration spectrum is calculated from the time curve by transforming it into the frequency range. The natural frequency states then result from the position (and possibly fleas) of the maxima in the spectrum.
  • the first natural frequency states can be determined in a comparable manner using measurements that are already carried out by the manufacturer on test stands as part of quality controls. It is also possible to calculate the first eigenfrequency states on the basis of model data of the rotor blades 41.
  • the natural frequency states of the rotor blades 41 in the ice-free state represent reference measurements with a first mass distribution of the rotor blades 41.
  • a second step S2 vibrations of the rotor blades 41 are measured at a second, unknown and possibly deviating from the first mass distribution and, as described above, second natural frequency states are determined therefrom in a step S3.
  • a subsequent step S4 the differences in the natural frequency states are determined, in particular any frequency shifts that have occurred in the natural frequency states are determined.
  • the second mass distribution is then derived from these in a step S5.
  • the amount and position of any ice accumulation can be calculated from the difference between the second and the first mass distribution.
  • Steps S2 to S5 are preferably repeated at certain time intervals in order to ensure (quasi-) continuous monitoring of the rotor blades 41 with regard to ice or dirt accumulation.
  • a model calculation can also be used in which a distribution of additional masses is varied and natural frequency states derived from the model are compared with the measured ones. The additional mass distribution is varied until a “best fit” is achieved. If the method is used over a longer period of time, within which aging of the rotor blades 41 becomes noticeable in the first natural frequency states, it makes sense to repeat step S1 and thus to keep a current reference of the natural frequency states in an ice-free state.

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Wind Motors (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

L'invention concerne un procédé de détermination d'un changement dans une répartition de masse d'une pale de rotor (41) d'une turbine éolienne (1), ledit procédé comprenant les étapes suivantes : − déterminer des premiers états de fréquence naturelle de la pale de rotor (41) sur la turbine éolienne (1) à une première répartition de masse de la pale de rotor (41) ; - capturer des vibrations de la pale de rotor (41) à une seconde répartition de masse, qui peut différer de la première répartition de masse ; - déterminer des seconds états de fréquence naturelle de la pale de rotor (41) à partir des vibrations capturées ; - déterminer des changements entre les premier et second états de fréquence naturelle ; et - dériver une répartition d'une masse supplémentaire qui correspond à la différence entre la seconde et la première répartition de masse. L'invention concerne en outre un dispositif pour déterminer un changement dans une répartition de masse d'une pale de rotor (41) sur une turbine éolienne (1), comprenant au moins un capteur (61) pour enregistrer une vibration dans la pale de rotor (41) et une unité d'évaluation (63) pour mettre en œuvre un tel procédé.
EP20823795.8A 2019-12-19 2020-12-10 Procédé et dispositif de détermination d'un changement dans une répartition de masse d'une pale de rotor sur une turbine éolienne Withdrawn EP4077929A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102019135108.1A DE102019135108A1 (de) 2019-12-19 2019-12-19 Verfahren und Vorrichtung zum Bestimmen einer Änderung einer Masseverteilung eines Rotorblatts einer Windkraftanlage
PCT/EP2020/085562 WO2021122319A1 (fr) 2019-12-19 2020-12-10 Procédé et dispositif de détermination d'un changement dans une répartition de masse d'une pale de rotor sur une turbine éolienne

Publications (1)

Publication Number Publication Date
EP4077929A1 true EP4077929A1 (fr) 2022-10-26

Family

ID=73793222

Family Applications (1)

Application Number Title Priority Date Filing Date
EP20823795.8A Withdrawn EP4077929A1 (fr) 2019-12-19 2020-12-10 Procédé et dispositif de détermination d'un changement dans une répartition de masse d'une pale de rotor sur une turbine éolienne

Country Status (3)

Country Link
EP (1) EP4077929A1 (fr)
DE (1) DE102019135108A1 (fr)
WO (1) WO2021122319A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113847212B (zh) * 2021-10-29 2023-05-02 中国华能集团清洁能源技术研究院有限公司 一种风电机组叶片固有频率监测方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102006009480B4 (de) * 2006-02-27 2008-05-29 Eads Deutschland Gmbh Aerodynamisches Profil für Luftfahrzeuge und Windkraftanlagen sowie Verfahren zur Messung der Eisdicke auf einem aerodynamischen Profil
WO2012000509A2 (fr) * 2010-06-30 2012-01-05 Vestas Wind Systems A/S Système d'éolienne pour la détection du givrage des pales
DE102013202261A1 (de) * 2013-02-12 2014-08-28 Senvion Se Verfahren zum Überprüfen des Betriebs einer Windenergieanlage und Windenergieanlage
DE102016124554A1 (de) * 2016-12-15 2018-06-21 fos4X GmbH Vorrichtung und Verfahren zum Erkennen der Anlagerung von Eis an einer Struktur eines Bauwerks

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
TCHERNIAK DMITRI ET AL: "APPLICATION OF OMA TO AN OPERATING WIND TURBINE: NOW INCLUDING VIBRATION DATA FROM THE BLADES", 15 May 2013 (2013-05-15), XP093170173, Retrieved from the Internet <URL:https://orbit.dtu.dk/files/81271299/Application_of_OMA_Tcherniak.pdf> *

Also Published As

Publication number Publication date
WO2021122319A1 (fr) 2021-06-24
DE102019135108A1 (de) 2021-06-24

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