EP4226494A1 - Procédé de surveillance d'un ou de plusieurs entraînements électriques d'un système électromécanique - Google Patents

Procédé de surveillance d'un ou de plusieurs entraînements électriques d'un système électromécanique

Info

Publication number
EP4226494A1
EP4226494A1 EP21783441.5A EP21783441A EP4226494A1 EP 4226494 A1 EP4226494 A1 EP 4226494A1 EP 21783441 A EP21783441 A EP 21783441A EP 4226494 A1 EP4226494 A1 EP 4226494A1
Authority
EP
European Patent Office
Prior art keywords
drives
values
measured
characteristic values
series
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.)
Pending
Application number
EP21783441.5A
Other languages
German (de)
English (en)
Inventor
Ivo BALZER
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.)
Prokon Regenerative Energien Eg
Original Assignee
Prokon Regenerative Energien Eg
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 Prokon Regenerative Energien Eg filed Critical Prokon Regenerative Energien Eg
Publication of EP4226494A1 publication Critical patent/EP4226494A1/fr
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors
    • H02P29/02—Providing protection against overload without automatic interruption of supply
    • H02P29/024—Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load
    • 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
    • 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
    • F03D15/00—Transmission of mechanical power
    • 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
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/0204—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor for orientation in relation to wind direction
    • 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
    • F03D80/70—Bearing or lubricating arrangements
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
    • H02P23/14—Estimation or adaptation of motor parameters, e.g. rotor time constant, flux, speed, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P5/00—Arrangements specially adapted for regulating or controlling the speed or torque of two or more electric motors
    • H02P5/74—Arrangements specially adapted for regulating or controlling the speed or torque of two or more electric motors controlling two or more ac dynamo-electric motors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P9/00—Arrangements for controlling electric generators for the purpose of obtaining a desired output
    • H02P9/006—Means for protecting the generator by using control
    • 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
    • F05B2260/00—Function
    • F05B2260/80—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
    • F05B2270/60—Control system actuates through
    • F05B2270/602—Control system actuates through electrical actuators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P2101/00—Special adaptation of control arrangements for generators
    • H02P2101/15—Special adaptation of control arrangements for generators for wind-driven turbines
    • 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 and a system for monitoring or analyzing one or more electric drives of an electromechanical system, e.g. B. a wind direction tracking of a wind turbine, wherein the drive or drives z. B. work as servomotors on a movable machine element of the system, z. B. work on a storage of an azimuth bearing.
  • an electromechanical system e.g. B. a wind direction tracking of a wind turbine
  • the drive or drives z. B. work as servomotors on a movable machine element of the system
  • z. B. work on a storage of an azimuth bearing.
  • the electromechanical system is z. B. a wind direction tracking of a wind turbine, with which the nacelle of the wind turbine is held or adjusted in the direction of the prevailing wind direction.
  • the nacelle of the wind turbine is rotatably mounted on a tower or tower head.
  • the wind direction tracking is carried out actively using one or more drives, which are preferably designed as electric drives.
  • These drives which are also referred to as azimuth drives, work as servomotors, e.g. B. on the bearing ring of the azimuth bearing or tower head bearing, which is z. B. can be a slewing bearing with external teeth or internal teeth.
  • the drives can B.
  • a standstill brake is integrated in the motor.
  • e.g. B. realized one or more azimuth brakes.
  • Various variants are implemented, e.g. B. with internal gearing of the azimuth bearing with internal azimuth brake or with internal gearing of the azimuth bearing with external
  • the electric drives are z. B. designed as single-phase or multi-phase AC drives or three-phase drives, that is, they are operated with single-phase or multi-phase alternating current (three-phase current).
  • the invention also includes systems with one or more DC drives.
  • Wind turbines and in particular their wind direction tracking are exposed to high loads in practice, so that they are subject to wear and damage can occur.
  • the reliable detection of damage to the yaw system and in particular to the drives of the yaw system is of great importance in practice, since failures lead to downtimes and thus high costs or damage to the operator.
  • damage to the drives of the wind tracking can only be detected unreliably.
  • other components e.g. B. other gears and electric motors or sprockets or bearings can be damaged or destroyed.
  • Such error propagation can only be prevented inadequately by known, passive protective measures. This is due to the fact that the currents of the electric motors, which can basically be used to monitor the drive, are subject to high dynamics and there are constant variances in the current consumption, which can also occur permanently. Such fluctuations in the power consumption arise z. B. by the wind
  • defective drives mostly deliver standard values in the current consumption, so that the usual protective devices (motor protection switch, circuit breaker) do not trip.
  • the nacelle is usually further aligned to the wind, even with a defective drive or several defective drives, in that the remaining, functional drives take over the work. These are overburdened.
  • even such an excessive load on the remaining drives does not trigger the protective device, since the yaw system does not move permanently, but on average only for a few seconds, which cannot trigger the thermal protective device with an average increased current flow. Due to the resulting additional load on the remaining drives, further drive damage follows.
  • the conventional protective device often only triggers when, for example, three of four drives are defective and the last remaining drive is so heavily loaded that thermal protective devices trigger or the system control stops due to the lack of yaw tracking.
  • a condition monitoring system for an engine is e.g. B. from WO 2011/069545, wherein the condition monitoring function of the motor
  • the motor end shield includes a sensor unit for detecting a measured variable of the motor, a communication means and a supply unit for supplying the sensor unit with energy.
  • the sensor unit can e.g. B. means for bearing current measurement or for measuring the temperature of the motor or the imbalance of the motor or acoustic vibrations.
  • US 2008/0183428 A1 describes a method for monitoring the operation of a tape drive that is used as a storage medium.
  • motor currents of the drives of such a tape drive are measured and compared with previously stored, theoretical values.
  • Statistical values can be determined for both the measured currents and the theoretical currents and compared with one another. The analysis is always based on previously calculated theoretical current values.
  • US 2016/0371958 A1 discloses a fitness device, namely a treadmill, in which the operation and wear of the treadmill is to be monitored.
  • the motor current is recorded at different speeds of the treadmill, so that measured values are recorded at different speeds and weighted differently, depending on the speed.
  • US 2006/0250102 A1 deals with a method for controlling or monitoring an engine, with operating parameters such as B. the current of a motor can be measured. This is compared with threshold and limit values that can be determined from statistically recorded values.
  • the invention is based on the object of creating a method with which one or more electric drives of an electromechanical system can be analyzed and/or monitored in a simple and reliable manner, in particular for damage and/or signs of wear on individual drives early and reliably recognized or avoided in advance.
  • the invention teaches, in a generic method for monitoring one or more electrical drives of an electromechanical system, that during operation of the drive or drives, one or more motor currents of one or more drives are measured at a specified sampling rate and as the respective current (or the phase) of the respective drive are stored, each with a predetermined number of measured values, that statistical characteristic values are calculated from one or more measured value series (and temporarily stored if necessary) and that by analyzing the development of the characteristic values and /or by analyzing a relationship between the characteristic values of different motor currents
  • one or more status information and/or status forecasts for one or more drives is/are generated.
  • the current or currents e.g.
  • the individual phase currents of one or more phases and preferably one or more electrical drives are recorded, stored and statistically evaluated at a high sampling rate, so that statistical parameters can be determined from a large number of measured values, from which conclusions and, if necessary, forecasts about the system status or The status of the drives can be obtained.
  • high sampling rate means a sampling rate of more than 0.2 Hz, e.g. B. at least 0.5 Hz, preferably at least 1 Hz.
  • a sampling rate of less than 10 Hz, z. B. less than 5 Hz sufficient to avoid large amounts of data. Consequently, at least one measured value per second is particularly preferably measured.
  • a system according to the invention is consequently equipped with suitable measuring devices for measuring the currents of the individual drives with such a sampling rate.
  • the measured values are stored as a series of measured values in a database and evaluated statistically or stochastically using an algorithm for anomaly detection.
  • the current or currents of the drive or drives are measured. It can be z. B. are the respective instantaneous values, the rectified value or the effective value.
  • the method is preferably used in a system in which several drives are provided, the z. B. are each designed as multi-phase drives, each with several phases. So it can preferably be a wind direction tracking, in which several (z. B. four) electrical multi-phase drives on a common machine element, namely
  • the method can also be used in other types of installation with one or more drives, in which case the drive or drives can be designed as single-phase or multi-phase drives and/or as direct current drives. So come z. B. also in wind turbines DC drives for emergency travel, z. B. used in connection with the blade adjustment.
  • each series of measured values are preferably recorded continuously, with each series of measured values z. B. can have 100 to 2000 readings, preferably 400 to 1000 readings.
  • measurement series with 600 measurement values each can be recorded. Consequently, preference is given to individual "clusters" of m measuring points each, e.g. B. formed 600 measuring points.
  • the series of measured values which e.g. B. summarize an engine operation of ten minutes, do not have to be recorded continuously, but can also be made up of several operating phases, z. B. in a wind direction tracking, in which the drives are only operated for a few seconds, so that a series of measured values is composed of a large number of tracking phases.
  • the evaluation and analysis is based on the series of measured values.
  • statistical parameters are calculated from the series of measured values.
  • statistical characteristic values which are each assigned to an individual phase of an individual drive
  • Statistical characteristic values can also be calculated from the values of several measurement series, e.g. B. the mean value of the entire phases of a drive.
  • statistical characteristic values are calculated from the series of measured values from a number of phases and/or a number of drives, which characterize a correlation or connection between a number of phases or a number of drives. It can be z. B. the covariance of the measured value series or measured value curves, e.g. B. the covariances of the measured values M (1 , 2, 3, 4) L1 to M (1 , 2, 3, 4) L2 or M (1 , 2, 3, 4) L2 to M (1 , 2, 3) 4) L3 or M(1,2,3,4)L3 to M(1,2,3,4)L1.
  • the correlation coefficients for these respective pairs of measured value series are calculated.
  • the calculated, statistical characteristic values are stored in an evaluation device and are preferably each provided with a time stamp.
  • the evaluation device can include a database server in which the calculated, statistical characteristic values are stored.
  • a third step the classification or analysis of the previously calculated, statistical characteristic values takes place, which - as described above - can be statistical characteristic values that are assigned to individual currents or individual phases of individual drives (e.g. mean values , variance) or statistical parameters that already have a connection
  • the evaluation involves classifying the measured values that represent a correlation between a number of phases or a number of drives, e.g. B. an evaluation of the covariances or correlation coefficients in order to generate status information for one or more drives.
  • B. in functional, new drives low covariances between the phases / drives. If, on the other hand, there is a higher covariance between individual phases or individual drives, this indicates a fault in the respective drive.
  • a prerequisite for the evaluation or analysis of the time profile of the covariance is the measurement of a plurality of motor currents or phase currents, so that anomalies relating to the relationship between these phase currents can be detected via the covariance.
  • a value of 1 for the correlation coefficient stands for a perfect, linear connection and a value of 0 for a completely missing linear connection.
  • B the ability to set a threshold for a correlation coefficient that generates a warning message and/or a fault message. So e.g. B. a
  • Correlation coefficients of 0.7 to 0.6 will generate a warning and a correlation coefficient of less than 0.6 will generate an error.
  • it can also be expedient to monitor a time profile of the correlation coefficient over a specific period of time and in this way to identify and predict faults, damage or anomalies.
  • a possible second embodiment provides for analyzing individual or several characteristic values, each of which only has one Affect drive or a phase or a current, without it being important that there is a connection between several phases or drives or that data from an (additional) reference system is required.
  • the development over time of the characteristic values of such a current or an individual phase of a drive is analyzed by e.g. B. classification takes place on the basis of previously determined and stored characteristic values or characteristic values are initially determined and stored as reference values in a learning phase. To do this, it is expedient to use the continuously recorded series of measured values
  • z. B. are the already mentioned parameters / parameters, which relate to the distribution function or the density distribution, z. B. the spread, the first, second or third sigma, the mode, the variance, the minimum, the maximum, the standard deviation and/or the median. This enables individual drives to be monitored or analyzed using a time series analysis without the need for data from a reference system. Wear can be detected via the trend in the sense of a trend value analysis, or damage can be detected or predicted.
  • the statistical characteristic values which are determined from the series of measured values recorded continuously one after the other, are correlated and correlation coefficients can be determined from them.
  • the aforementioned status information and/or status forecasts can be derived from the correlation coefficients or from their development over time.
  • phase provides status information or a code number from which a defect can be determined.
  • the determined trend values are correlated not only with characteristic values from the past, but also with characteristic values of the other drives and/or phases in the system and via the correlation with other drives and/or phases in the determination of the status information or the code integrated.
  • a defect can be recognized from the status information or code number, e.g. B. on a drive or motor, on the associated gear, on the teeth (of the bearing ring) or on a braking system.
  • creeping errors are also reliably detected. If all drives are functional without restrictions, the trend values of the calculated characteristic values behave statically. However, if there are significant deviations in the trend values, acute deviations from other drives in the system, or if abstract values are recognized, an error or defect can be identified.
  • the trend value analysis is implemented by an evaluation algorithm in the evaluation device.
  • the measured value densities can always be used for the evaluation.
  • the measured value densities or density functions are in turn recorded and stored as measured value series (e.g. clusters with e.g. 600 measured values each). From this, a trend value can be calculated over the entire runtime. A rising or falling trend value can be an indication of a drive malfunction.
  • the trend values are in turn compared and correlated.
  • individual, statistical characteristic values of individual phases can—as described—independently of a correlation or additionally provide important information. So can z. B.
  • the algorithm can also use methods of artificial intelligence or neural networks or be implemented with such, so that the system is self-learning, since all data of each individual drive is stored permanently in the database over long periods of time and is available for analysis .
  • the invention is not only the method described, but also the electromechanical system itself, that is, an electromechanical system, the z. B. can be designed as wind direction tracking of a wind turbine.
  • An electromechanical system has at least one movable machine element on which a drive or multiple drives work. The system is set up to carry out the method described, ie it is provided with or connected to a controller and an evaluation device which are set up to carry out the method described.
  • the electromechanical system is particularly preferably a wind direction tracking system for a wind power plant, in which several AC motors work on a common bearing ring or toothed ring of an azimuth bearing.
  • other electromechanical systems are also included, in which preferably several drives work on a common machine element.
  • the invention z. B. also in crane systems, z. B. use in gantry cranes. An early damage report is always in the foreground.
  • Monitor systems with individual drives The monitoring of systems with DC drives is also possible according to the invention.
  • the data is particularly preferably stored and evaluated externally or outside of the actual electromechanical system, e.g. B. outside the wind turbine.
  • the invention proposes that the system be provided with a local control device with which the measured values are recorded. If necessary, the measured values can be buffered.
  • a permanent storage of the measured values or measured value series and an evaluation of the measured values is preferably not provided in the local control device, but the measured values are preferably transmitted (e.g. by cable/fiber optic cable or mobile radio) to an externally arranged evaluation device, which is independent of the Wind turbine can be realized far away.
  • Such an evaluation device has z. B. a database server with an evaluation software, so that the series of measured values are stored on the database server and evaluated with an evaluation algorithm.
  • the external evaluation device can e.g. B. be assigned to several wind turbines as a central control room.
  • the evaluation device preferably has an interface via which the status information can then in turn be queried with external terminals or can be transmitted to external terminals, e.g. B. on PCs, tablets or smartphones. This makes it possible to transmit warning messages from the arranged database server to various terminals or to request status information from the database server using the terminals.
  • system according to the invention can therefore optionally be set up in such a way that a system, e.g. B. wind turbine is automatically stopped in response to certain status information and consequently shut down. In this way, serious damage to the system or consequential damage can be avoided.
  • a system e.g. B. wind turbine
  • Figure 1 shows a highly simplified schematic of an electromechanical system in the embodiment as a wind direction tracking system with status monitoring according to the invention
  • FIG. 2 shows an enlarged detail from the system according to FIG. 1,
  • FIGS. 5a, 5b simplify histograms or distribution density functions.
  • FIGS. 1 and 2 an electromechanical system in the embodiment as wind direction tracking is shown schematically and in a highly simplified manner, specifically with status monitoring according to the invention for the electrical drives of the wind direction tracking.
  • Wind direction tracking is used to adjust the nacelle of a wind turbine in the direction of the prevailing wind direction.
  • the gondola is rotatably mounted on the top of the tower and can be tracked with several electric drives.
  • FIG. 1 shows a simplified section of a tower head bearing 1 with a bearing 2 on which several electric drives M1, M2, M3, M4 work.
  • An arrangement with internal gearing of the yaw bearing and with internal drives and an external yaw brake 3 is shown as an example.
  • the electric drives are connected to a control device 4 which is arranged in the wind turbine, e.g. B. in the tower head or in the nacelle.
  • the drives are designed as three-phase AC motors or three-phase motors.
  • the drives are equipped or connected to measuring devices 5, with which the phase currents of all three phases L1, L2, L3 of each individual drive M1, M2, M3, M4 are measured.
  • measuring devices 5 usual protective devices, z. B. a motor protection switch 11 and a contactor 12 indicated, which can be provided in a conventional manner.
  • the measuring devices 5 all phase currents of the drives are measured at a high sampling rate of, for example, 0.5 Hz to 5 Hz, e.g. B.
  • the measured values are (temporarily) temporarily stored in the control device 4 .
  • the measured values are transmitted (e.g. after the end of the measurement or after the wind tracking has stopped) via an A/D converter 13 and a microcontroller MC using an interface or
  • the storage and evaluation device 7 is designed, for example, as a database server for storing large amounts of data or is equipped with a database server, and evaluation software is also stored in the evaluation device 7 .
  • the measured values are evaluated in the storage and evaluation device and status information for the drives M1, M2, M3, M4 is generated from them.
  • This status information can be accessed via various end devices, e.g. B. a PC 8, a tablet 9 or a smartphone 10 and visualize it, the terminals being able to communicate with the evaluation device 7 by wire or wirelessly.
  • all three phase currents L1, L2, L3 can be measured for all motors M1, M2, M3 and M4, with the described high sampling rate of z. B. 1 Hz.
  • series of measured values are each stored with a predetermined number m of measured values, in the exemplary embodiment 600 measured values per series of measured values, i.e. the measured values are stored in clusters of 600 measuring points, specifically for each individual phase of each motor, so that in twelve series of measured values are generated and stored in the exemplary embodiment.
  • each series of measured values reflects a period of 10 minutes, whereby this period does not result from a continuous measurement, but relates to the overall operation of the respective drive as a result of several chronologically consecutive wind tracking.
  • the control device 6 which is arranged locally in the area of the drives, it is consequently not necessary to store complete series of measured values, but only the individual measurements during the operation of the drives are buffered and transmitted to the storage and evaluation device 7. There the measured values are displayed as
  • a statistical/stochastic evaluation and analysis of the series of measured values is carried out, ie statistical characteristic values are generated from the series of measured values, specifically z. B. on the one hand characteristic values for a correlation between several phases or several drives and on the other hand statistical characteristic values for individual phases of the respective drive. From these statistical characteristics, status information for one drive or for all drives can be generated individually or through suitable combinations, using the evaluation software or an evaluation algorithm stored in the storage and evaluation device 7, which uses the status information that reflects the respective status of the individual drives represent, created.
  • Mean value of each individual phase mean value total L1/L2/L3, i.e. (sum L1/600 + sum L2/600 + sum L3/600)/3, mean value of the individual phase measurements (L1 + L2 + L3)/3, RMS, Measured value density, value of the highest measured value density or maximum of the measured value distribution, minimum of the measured value series, maximum of the measured value series, standard deviation, variance, first sigma, second sigma, third sigma, median.
  • properly working drive can be closed or on properly working drives.
  • FIG. B an increased slip can be closed. This is particularly noticeable with the covariance M4L1 to M4L3, ie with a covariance in which the different phases of the same drive M4 are involved.
  • FIGS. 4a and 4b Similar information can be obtained by evaluating the correlation coefficients according to FIGS. 4a and 4b. It can again be seen that the correlation coefficient is in a high range for all measurement phases (compare FIG. 3a), while it falls to low values in the case of a defective drive (compare FIG. 3b). It can be seen that these dips in the correlation coefficient always occur when the drive M4 is involved, so that a fault in the area of a drive can be determined particularly reliably via the correlation coefficient. Based on the comparison or on the basis of relationships between the individual correlation coefficients, the software can consequently verify which engine is malfunctioning, in good time before damage occurs. It is of particular importance that the temporal development of these covariances or correlation coefficients can be analyzed in the sense of a time series analysis or trend value analysis.
  • FIGS. 3a, 3b and 4a, 4b show the evaluation and analysis of certain statistical characteristic values only by way of example. Further statistical characteristic values are particularly preferably evaluated and monitored in order to be able to detect different types of defects or types of wear.
  • FIGS. 5a and 5b show examples of histograms or distribution density functions of series of measured values for a new drive (FIG. 5a) on the one hand and a defective drive (FIG. 5b) on the other. It can be seen that the measured value distribution for a new drive is approximately normally distributed, with the frequency of the phase currents indicated on the x-axis being plotted. In contrast, FIG. 5b shows such a distribution for an existing system with a defect.
  • These measurement distribution densities can be stored in statistical indicators or statistical indicators can be determined from the distribution densities, e.g. B. the spread, the first and second and third sigma, the mode, the variance, the minimum, the maximum, the standard deviation and/or the median.
  • an individual drive or an individual motor current can be analyzed or monitored and wear can be reliably detected or predicted without a reference system having to be monitored.
  • Only the drive data stored in the past is required as a reference by analyzing the development of the distribution density function or its index over time. So e.g. For example, the three sigma values are used to verify short-term measurements in order to reliably identify acute damage. if e.g. B. Measured values often outside the sigma values, this is an indication of an error and the further the measured value is from the modal value, the clearer and more acute the error case.
  • correlations of the series of measured values recorded over time or the characteristic values determined therefrom can be analyzed and correlation coefficients can be determined and evaluated.
  • the storage and evaluation device 7 is usually far away from the wind turbine, so that z. B. a variety of wind turbines can be monitored via a central monitoring device.
  • visualization software can be stored in the storage and evaluation device 7, which visually displays the collected and derived values from the database for the user and serves as a communication interface between the evaluation algorithm and the user.
  • a corresponding reaction to the error event e.g. B. an alarm mail or, if desired, a stop of the wind tracking can also be carried out.
  • the storage and evaluation device 7 is only shown in a highly simplified manner in the drawings.
  • it can contain a database server.
  • the software for data evaluation and anomaly detection as well as error reporting can be stored on the same server.
  • an additional computer/server can be provided, which implements the evaluation, anomaly detection and error reporting.

Landscapes

  • 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)
  • Power Engineering (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Wind Motors (AREA)
  • Control Of Electric Motors In General (AREA)

Abstract

L'invention concerne un procédé de surveillance d'un ou de plusieurs entraînements électriques (M1, M2, M3, M4) d'un système électromécanique, en particulier d'un système de suivi de direction du vent d'une éolienne, le ou les entraînements (M1, M2, M3, M4) agissant sur un composant de machine mobile de l'installation, par exemple sur une bague de palier (2) d'un palier azimutal (1). Le procédé est caractérisé en ce que : pendant le fonctionnement des entraînements, une pluralité de courants, par exemple des courants de phase de phases multiples (L1, L2, L3), et/ou de multiples entraînements (M1, M2, M3, M4), sont mesurés à une vitesse d'échantillonnage prédéfinie et stockés sous la forme d'une série de valeurs mesurées contenant chacune un nombre prédéfini m de valeurs mesurées ; des valeurs caractéristiques statistiques sont dans chaque cas calculées à partir d'une ou de plusieurs séries de valeurs mesurées ; et une ou plusieurs informations d'état et/ou prévisions d'état sont générés pour un ou plusieurs entraînements par l'analyse de la variation dans le temps des valeurs caractéristiques et/ou par l'analyse d'une corrélation des valeurs caractéristiques de différents courants de moteur.
EP21783441.5A 2020-10-09 2021-09-23 Procédé de surveillance d'un ou de plusieurs entraînements électriques d'un système électromécanique Pending EP4226494A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102020126587.5A DE102020126587A1 (de) 2020-10-09 2020-10-09 Verfahren zur Überwachung eines oder mehrerer elektrischer Antriebe einer elektromechanischen Anlage
PCT/EP2021/076254 WO2022073773A1 (fr) 2020-10-09 2021-09-23 Procédé de surveillance d'un ou de plusieurs entraînements électriques d'un système électromécanique

Publications (1)

Publication Number Publication Date
EP4226494A1 true EP4226494A1 (fr) 2023-08-16

Family

ID=78032408

Family Applications (1)

Application Number Title Priority Date Filing Date
EP21783441.5A Pending EP4226494A1 (fr) 2020-10-09 2021-09-23 Procédé de surveillance d'un ou de plusieurs entraînements électriques d'un système électromécanique

Country Status (5)

Country Link
US (1) US20230304478A1 (fr)
EP (1) EP4226494A1 (fr)
CA (1) CA3193757A1 (fr)
DE (1) DE102020126587A1 (fr)
WO (1) WO2022073773A1 (fr)

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001086141A1 (fr) * 2000-05-12 2001-11-15 Aloys Wobben Organe d'entrainement azimutal pour eoliennes
US7231317B2 (en) 2003-01-08 2007-06-12 International Business Machines Corporation Correlating power signatures with automated equipment
US7408317B2 (en) 2005-05-04 2008-08-05 Wildeck, Inc. Apparatus having a motor, controller for the motor, and method of controlling the motor
WO2011069545A1 (fr) 2009-12-10 2011-06-16 Siemens Aktiengesellschaft "condition monitoring system" (système de surveillance d'état) d'un moteur
US20140039817A1 (en) * 2012-08-06 2014-02-06 Phase3 Technologies Ltd. System and method for monitoring an electrically-connected system having a periodic behavior
US9922528B2 (en) 2014-03-12 2018-03-20 Precor Incorporation Fitness equipment unit service condition notification system
CN110442833B (zh) * 2019-06-10 2022-09-09 内蒙古工业大学 一种基于多维度scada数据评估风电机组健康状态评估方法

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WO2022073773A1 (fr) 2022-04-14
CA3193757A1 (fr) 2022-04-14
US20230304478A1 (en) 2023-09-28
DE102020126587A1 (de) 2022-04-14

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