CN115829411A - Method and system for evaluating operation state of offshore wind turbine generator - Google Patents
Method and system for evaluating operation state of offshore wind turbine generator Download PDFInfo
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- CN115829411A CN115829411A CN202211642360.2A CN202211642360A CN115829411A CN 115829411 A CN115829411 A CN 115829411A CN 202211642360 A CN202211642360 A CN 202211642360A CN 115829411 A CN115829411 A CN 115829411A
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Abstract
The method comprises the steps of obtaining SCADA system monitoring data and CMS system monitoring data of the operation state of the offshore wind turbine; selecting index data to be evaluated to obtain an index database; selecting data in a time range set by an index database and carrying out time synchronization processing on the data to obtain a synchronous database; obtaining a sample database of a continuous time series; selecting corresponding index data in a sampling database to generate a corresponding index data image, and comparing the index data image with a reference image; and if the range of the index data image deviating from the reference image is within the set range, evaluating the operation state of the offshore wind turbine generator corresponding to the index data as normal. The method has the advantages that the test equipment does not need to be additionally installed, the evaluation cost is low, the main problems generated in the operation process of the unit can be solved in time, the overall operation condition of the unit can be conveniently and comprehensively mastered, accurate guidance is provided for the operation and maintenance of the unit, and the operation and maintenance cost of the unit is reduced.
Description
Technical Field
The disclosure relates to the technical field of wind turbine generators, in particular to an evaluation method and an evaluation system for an operation state of an offshore wind turbine generator.
Background
The offshore wind power generation system has the advantages of abundant wind power resources, high operation efficiency, stable power generation, convenience for consumption close to a load center, suitability for large-scale construction and the like. The offshore wind power occupation ratio is rapidly improved, the offshore wind power installation machine amount occupation ratio is prominent year by year and is far higher than the onshore wind power installation machine amount acceleration. Under the background of low-carbon energy conversion, the cost of an offshore wind power industrial chain is reduced, a fan is large-sized, the amount of driving an offshore wind power device is continuously increased, and the high growth of sea wind comes.
Compared with onshore wind power, offshore wind power is high in operation and maintenance cost. Particularly, with the development and construction of offshore wind power plants in open sea, deep sea and ultra-large scale, the offshore wind power operation and maintenance problem is more prominent. The expenditure of the operation and maintenance cost part of the offshore wind turbine is related to the offshore maintenance and repair times, is greatly influenced by the product reliability and the operation and maintenance strategy, and belongs to the non-fixed part of the operation and maintenance cost. In the whole life cycle cost of the offshore wind power project, the wind turbine generator is the part with the highest proportion of the cost in the current offshore wind power project, and the operation and maintenance cost of the offshore wind power plant is only second to the wind turbine generator, and accounts for 18% -23% of the cost of the whole offshore wind power project and is far higher than the proportion of 12% of the operation and maintenance cost of onshore wind power. Under the condition, the evaluation on the running state of the unit is very important, the running condition of the unit can be known timely, operation and maintenance personnel can maintain the unit in a planned way, the running safety of the unit is ensured, and the operation and maintenance cost of the unit is reduced.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide an evaluation method and an evaluation system for an operation state of an offshore wind turbine, so as to solve the problem in the prior art that the maintenance cost of an offshore wind turbine is relatively high due to uncertainty of the operation state.
The embodiment of the disclosure adopts the following technical scheme: an offshore wind turbine operating condition assessment method, the method comprising:
acquiring SCADA system monitoring data and CMS system monitoring data of the operation state of the offshore wind turbine;
selecting index data to be evaluated from the SCADA system monitoring data and the CMS system monitoring data to obtain an index database;
selecting data in a time range set by an index database and carrying out time synchronization processing on the data to obtain a synchronous database;
continuously sampling data in the synchronous database by taking the first time as a sampling frequency to obtain a sampling database of a continuous time sequence;
selecting corresponding index data in a sampling database to generate a corresponding index data image, and comparing the index data image with a reference image; and if the range of the index data image deviating from the reference image is within the set range, evaluating the operation state of the offshore wind turbine generator corresponding to the index data as normal.
In some embodiments, a method of obtaining SCADA system monitoring data and CMS system monitoring data of an operating state of an offshore wind turbine includes: obtaining the time range of [ T, T + delta T ], wherein delta T is a time interval; index data in the SCADA system monitoring data at least comprises one of the following data: wind speed, wind direction, impeller rotating speed, generator torque, power, pitch angle of a blade, cabin vibration acceleration and yaw position; the index data in the CMS system monitoring data at least comprises one of the following data: the inclination angle of the tower barrel, the vibration acceleration of the tower top, the vibration of the blade and the vibration of the main shaft.
In some embodiments, the method for selecting data in the set time range of the index database and performing time synchronization processing on the data to obtain the synchronous database comprises the following steps of; and stamping timestamps for the SCADA system monitoring data and the CMS system monitoring data respectively corresponding to the index database, and performing data synchronization by using the timestamps between the SCADA system monitoring data and the CMS system monitoring data.
In some embodiments, before the step of selecting the corresponding index data in the sampling database to generate the corresponding index data image, the data in the sampling database is subjected to rejection processing, and the rejection processing includes rejecting data with active power less than zero from the sampling database, and rejecting data with active power less than rated power-50 and pitch angle greater than optimal pitch angle +0.5 from the sampling database.
In some embodiments, before selecting the corresponding index data in the sampling database to generate the corresponding index data image, filtering the SCADA system monitoring data and the CMS system monitoring data corresponding to each other in the sampling database to obtain the filtering data within the frequency band range of 0.1Hz to 10 Hz.
In some embodiments, the step of selecting the corresponding index data in the sample database to generate the corresponding index data image comprises: generating a scatter diagram by using wind speed-power, wind speed-pitch angle, impeller rotating speed-power and wind speed-cabin vibration acceleration; and comparing the scatter diagram with a reference image set by the offshore wind turbine generator, and if the range of the scatter diagram deviating from the reference image is within a set range, evaluating that the basic operation state of the offshore wind turbine generator is normal.
In some embodiments, the step of selecting the corresponding index data in the sample database to generate the corresponding index data image comprises: generating a principal component frequency curve graph of a tower cylinder inclination angle and a principal component frequency curve graph of tower top vibration acceleration of the offshore wind turbine generator set at different impeller rotating speeds, wherein the principal component frequency of the tower cylinder inclination angle comprises a principal component frequency of a pitch angle and a principal component frequency of a roll angle, and the principal component frequency of the tower top vibration acceleration comprises a principal component frequency of an axial acceleration and a principal component frequency of a horizontal acceleration; when the principal component frequency of the inclination angle of the tower drum is consistent with the principal component frequency of the vibration acceleration of the tower top but deviates from the first-order frequency of the tower, the operation state of the offshore wind turbine generator is changed; when the principal component frequency of the tower inclination angle is not consistent with the principal component frequency of the tower top vibration acceleration but approaches the tower first-order frequency, the signal deviating from the tower first-order frequency is possibly abnormal; when the principal component frequency of the tower inclination angle is inconsistent with the principal component frequency of the tower top vibration acceleration and deviates from the tower first-order frequency, the corresponding signals of the tower inclination angle and the tower top acceleration may be abnormal.
In some embodiments, the step of selecting the corresponding index data in the sample database to generate the corresponding index data image comprises: fitting and generating an impeller rotating speed-blade vibration RMS curve according to a first scatter diagram of the blade running state of the offshore wind turbine generator, wherein the first scatter diagram is a scatter curve corresponding to the impeller rotating speed-blade vibration RMS when the offshore wind turbine generator runs normally, and when the impeller rotating speed-blade vibration RMS curve generated by fitting is out of the sigma range of the first scatter diagram 3, evaluating that the blade is abnormal;
fitting and generating an impeller rotating speed-blade vibration principal component frequency curve according to a second scatter diagram of the offshore wind turbine generator, wherein the second scatter diagram is the impeller rotating speed-blade vibration principal component frequency curve when the offshore wind turbine generator operates normally; and when the impeller rotating speed-blade vibration principal component frequency curve generated by fitting is out of the sigma range of the second scatter diagram 3, evaluating that the blade is abnormal.
In some embodiments, the step of selecting the corresponding index data in the sample database to generate the corresponding index data image comprises: and generating a fitting curve of impeller rotating speed and main shaft vibration RMS value when the marine generator set normally operates, adding 3sigma to the main shaft vibration RMS value at different generator rotating speeds to serve as a main shaft vibration attention threshold, and evaluating the main shaft vibration abnormality when the main shaft vibration attention threshold is exceeded.
The present disclosure also provides an evaluation system configured to evaluate an operation state of an offshore wind turbine generator system by using the above evaluation method.
The beneficial effects of this disclosed embodiment lie in:
the method for evaluating the operation state of the marine direct-drive unit based on the monitoring data of the SCADA system and the CMS system is adopted, no additional test equipment is needed, the evaluation cost is low, the main problems generated in the operation process of the unit can be solved in time, the overall operation condition of the unit can be conveniently and comprehensively mastered, accurate guidance is provided for the operation and maintenance of the unit, the safe operation of the unit is ensured, and the operation and maintenance cost of the unit is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present disclosure, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an evaluation method of the present disclosure;
FIG. 2 is a flow chart of data preprocessing according to the present disclosure;
FIG. 3 is a scatter plot of wind speed versus power for the present disclosure;
FIG. 4 is a scatter plot of wind speed versus pitch angle for the present disclosure;
FIG. 5 is a scatter plot of impeller speed versus power for the present disclosure;
FIG. 6 is a scatter plot of wind speed versus fore and aft nacelle vibration acceleration for the present disclosure;
FIG. 7 is a scatter plot of the present disclosure velocity division versus left and right nacelle vibration acceleration;
FIG. 8 is a graph of principal component frequency (pitch angle versus axial acceleration) for the present disclosure;
FIG. 9 is a graph of principal component frequency (roll angle versus horizontal acceleration) for the present disclosure;
FIG. 10 is a plot of impeller speed versus blade shimmy RMS of the present disclosure;
FIG. 11 is a plot of impeller speed versus blade flapping RMS of the present disclosure;
FIG. 12 is a graph of impeller speed versus blade shimmy FRE for the present disclosure;
FIG. 13 is a graph of impeller speed versus blade flap FRE for the present disclosure;
FIG. 14 is a plot of impeller speed versus spindle vibration RMS of the present disclosure.
Detailed Description
Various aspects and features of the disclosure are described herein with reference to the drawings.
It will be understood that various modifications may be made to the embodiments of the present application. Accordingly, the foregoing description should not be construed as limiting, but merely as exemplifications of embodiments. Other modifications will occur to those skilled in the art within the scope and spirit of the disclosure.
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and, together with a general description of the disclosure given above, and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.
These and other characteristics of the present disclosure will become apparent from the following description of preferred forms of embodiment, given as non-limiting examples, with reference to the attached drawings.
It should also be understood that, although the present disclosure has been described with reference to some specific examples, a person of skill in the art shall certainly be able to achieve many other equivalent forms of the disclosure, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present disclosure will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present disclosure are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various forms. Well-known and/or repeated functions and structures have not been described in detail so as not to obscure the present disclosure with unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriately detailed structure.
The specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the disclosure.
In order to solve the problems that in the background art, the maintenance cost of an offshore wind turbine is high, the running state cannot be accurately controlled, and therefore the maintenance cost cannot be reduced due to accurate point aligning, the disclosure provides an evaluation method for the running state of the offshore wind turbine. As shown in fig. 1, the evaluation method includes: and acquiring SCADA system monitoring data and CMS system monitoring data of the operation state of the offshore wind turbine. Wherein, the SCADA system (Supervisory control and DataAcquisition) is a data acquisition and state monitoring control system; the CMS system (conditionmonitoring system) is a state monitoring system. The SCADA system is installed in an offshore wind turbine, and includes a control unit, a database storing operation data and/or operation parameters, and a network communication interface for exchanging data and/or operation commands with an external unit through an external network. The offshore wind turbine generator set is provided with a state detection system, namely a CMS system; the CMS system is mainly used for monitoring wind turbine components in real time by additionally arranging a vibration sensor and a rotating speed sensor on a bearing, a gear box, a generator and other components of the wind turbine.
After the SCADA system monitoring data and the CMS system monitoring data are obtained, as shown in fig. 2, the data are preprocessed, and first, index data to be evaluated is selected from the SCADA system monitoring data and the CMS system monitoring data to obtain an index database. And selecting data in the time range set by the index database and carrying out time synchronization processing on the data to obtain a synchronous database.
Then, continuously sampling the data in the synchronous database by taking the first time as a sampling frequency to obtain a sampling database of a continuous time sequence; for example, if the first time is set to 10 minutes, the sampling is performed every 10 minutes, and the sampling is performed continuously to form a continuous time-series sample database.
Selecting corresponding index data in the sampling database to generate a corresponding index data image, and comparing the index data image with the reference image; and if the range of the index data image deviating from the reference image is within the set range, evaluating the operation state of the offshore wind turbine generator corresponding to the index data as normal.
The method for evaluating the operation state of the marine direct-drive unit based on the monitoring data of the SCADA system and the CMS system is adopted, no additional test equipment is needed, the evaluation cost is low, the main problems generated in the operation process of the unit can be solved in time, the overall operation condition of the unit can be conveniently and comprehensively mastered, accurate guidance is provided for the operation and maintenance of the unit, the safe operation of the unit is ensured, and the operation and maintenance cost of the unit is reduced.
The method for acquiring the SCADA system monitoring data and the CMS system monitoring data of the operation state of the offshore wind turbine generator comprises the following steps: obtaining the time range [ T, T + delta T ], wherein delta T is a time interval; for example, the time range is 1 month from 2022 to 11 months from 2022, and the time interval is 30 minutes or one hour, which can be set according to the requirement.
Index data in the SCADA system monitoring data at least comprises one of the following data: wind speed, wind direction, impeller speed, generator torque, active power, pitch angle (all blades), nacelle vibration acceleration (left and right, front and back), yaw position, and the like. The index data in the CMS system monitoring data includes at least one of: the inclination angle (pitch and roll) of the tower, the vibration acceleration (left and right, front and back) of the tower top, the vibration (shimmy and waving) of the blade, the vibration (vertical, horizontal and axial) of the main shaft and the like. And for a certain index, selecting data of the index in a time range of a plurality of time periods from the obtained monitoring data, wherein the time range is smaller than the time range when the SCADA system monitoring data and the CMS system monitoring data of the operation state of the offshore wind turbine generator are obtained. For example, with ten days as a time range, data corresponding to the index in every ten days is selected, and 11 segments of data are continuously acquired.
The method for selecting data in the time range set by the index database and carrying out time synchronization processing on the data to obtain a synchronous database comprises the following steps of; and stamping timestamps for the SCADA system monitoring data and the CMS system monitoring data respectively corresponding to the index database, and performing data synchronization by using the timestamps between the SCADA system monitoring data and the CMS system monitoring data.
Before the step of selecting the corresponding index data in the sampling database to generate the corresponding index data image, the data in the sampling database is removed, and the removal processing comprises the steps of removing the data with the active power less than zero from the sampling database, and removing the data with the active power less than rated power-50 and the pitch angle greater than the optimal pitch angle +0.5 from the sampling database.
Before selecting the corresponding index data in the sampling database to generate the corresponding index data image, filtering the corresponding SCADA system monitoring data and CMS system monitoring data in the sampling database to obtain filtering data in a set frequency band range, for example, filtering data in a frequency band range of 0.1Hz-10 Hz. And filtering data from different sources (an SCADA system and a CMS system) to remove interference data. Filtered data in the frequency band range of 0.1Hz-10Hz is obtained.
As shown in fig. 3 to 7, the step of selecting the corresponding index data in the sampling database to generate the corresponding index data image includes generating a scatter diagram from the wind speed-power, the wind speed-pitch angle, the impeller rotation speed-power, and the wind speed-nacelle vibration acceleration. The method is used as the basis for analyzing and evaluating the basic operation state of the offshore wind turbine. Comparing the scatter diagram with a reference image set by the offshore wind turbine generator, and if the range of the scatter diagram deviating from the reference image is within a set range, evaluating that the basic operation state of the offshore wind turbine generator is normal; otherwise, the alarm is given when the abnormity occurs.
The analytical evaluation of tower frequency includes: as shown in fig. 8 and 9, the tower operation monitoring data is counted, including the principal component frequency of the tower inclination angle and the principal component frequency of the tower top vibration acceleration at different rotation speeds, and the principal component frequency is extracted and fourier transform is adopted. The step of selecting corresponding index data in the sampling database to generate a corresponding index data image comprises a principal component frequency curve graph of a tower inclination angle and a principal component frequency curve graph of tower top vibration acceleration, wherein the principal component frequency of the tower inclination angle comprises a principal component frequency of a pitch angle and a principal component frequency of a roll angle, and the principal component frequency of the tower top vibration acceleration comprises a principal component frequency of an axial acceleration and a principal component frequency of a horizontal acceleration. When the principal component frequency of the tower inclination angle is consistent with the principal component frequency of the tower top vibration acceleration but deviates from the tower first-order frequency, the operation state of the offshore wind turbine generator is changed. When the principal component frequency of the tower inclination angle is not consistent with the principal component frequency of the tower top vibration acceleration, but one of the principal component frequencies is close to the tower first-order frequency, the signal deviating from the tower first-order frequency may be abnormal. And when the principal component frequency of the tower inclination angle is inconsistent with the principal component frequency of the tower top vibration acceleration and deviates from the tower first-order frequency, the corresponding signals of the tower inclination angle and the tower top acceleration are abnormal possibly, and an alarm is given.
The analysis and evaluation of the operating state of the blade comprises the following steps: as shown in fig. 10 to 13, the step of selecting the corresponding index data in the sampling database to generate the corresponding index data image includes fitting and generating an impeller rotation speed-blade vibration (shimmy, flap) RMS curve according to a first scatter diagram of the blade running state of the offshore wind turbine, where the first scatter diagram is a corresponding scatter curve of impeller rotation speed-blade vibration (shimmy, flap) RMS when the offshore wind turbine runs normally, and when the impeller rotation speed-blade vibration RMS curve generated by fitting is outside the 3sigma range of the first scatter diagram, evaluating that the blade is abnormal, and giving an alarm.
Fitting and generating an impeller rotating speed-blade vibration (shimmy and flapping) principal component frequency curve according to a second scatter diagram of the offshore wind turbine generator, wherein the second scatter diagram is the impeller rotating speed-blade vibration (shimmy and flapping) principal component frequency curve when the offshore wind turbine generator operates normally; and when the impeller rotating speed-blade vibration principal component frequency curve generated by fitting is out of the sigma range of the second scatter diagram 3, evaluating whether the blade is abnormal, and giving an alarm.
The analytical evaluation of the running state of the main shaft comprises the following steps: as shown in fig. 14, the step of selecting the corresponding index data in the sampling database to generate the corresponding index data image includes generating an RMS value fitting curve of the impeller rotation speed and the main shaft vibration (vertical, horizontal, and axial) when the marine generator set normally operates, taking the RMS value of the main shaft vibration at different generator rotation speeds plus 3sigma as a main shaft vibration attention-required threshold, and when the threshold is exceeded, evaluating the main shaft vibration abnormality and giving an alarm.
The present disclosure also provides an evaluation system configured to evaluate an operation state of an offshore wind turbine generator system by using the above evaluation method.
While the present disclosure has been described in detail with reference to the embodiments, the present disclosure is not limited to the specific embodiments, and those skilled in the art can make various modifications and alterations based on the concept of the present disclosure, and the modifications and alterations should fall within the scope of the present disclosure as claimed.
Claims (10)
1. An offshore wind turbine operating state evaluation method, comprising:
acquiring SCADA system monitoring data and CMS system monitoring data of the operation state of the offshore wind turbine;
selecting index data to be evaluated from the SCADA system monitoring data and the CMS system monitoring data to obtain an index database;
selecting data in a time range set by an index database and carrying out time synchronization processing on the data to obtain a synchronous database;
continuously sampling data in the synchronous database by taking the first time as a sampling frequency to obtain a sampling database of a continuous time sequence;
selecting corresponding index data in a sampling database to generate a corresponding index data image, and comparing the index data image with a reference image; and if the range of the index data image deviating from the reference image is within the set range, evaluating the operation state of the offshore wind turbine generator corresponding to the index data as normal.
2. The evaluation method of claim 1, wherein the method of obtaining SCADA system monitoring data and CMS system monitoring data of the operating status of the offshore wind turbine comprises: obtaining the time range [ T, T + delta T ], wherein delta T is a time interval; index data in the SCADA system monitoring data at least comprises one of the following data: wind speed, wind direction, impeller rotating speed, generator torque, power, pitch angle of a blade, vibration acceleration of an engine room and yaw position; the index data in the CMS system monitoring data at least comprises one of the following data: the inclination angle of the tower barrel, the vibration acceleration of the tower top, the vibration of the blade and the vibration of the main shaft.
3. The evaluation method according to claim 2, wherein the method of selecting data in the time range set by the index database and performing time synchronization processing on the data to obtain the synchronized database comprises; and stamping timestamps for the SCADA system monitoring data and the CMS system monitoring data respectively corresponding to the index database, and performing data synchronization by using the timestamps between the SCADA system monitoring data and the CMS system monitoring data.
4. The method of claim 2, wherein the step of selecting corresponding index data in the sampled database to generate an image of the corresponding index data is preceded by a culling process of data in the sampled database, the culling process comprising culling data from the sampled database having an active power of less than zero, culling data from the sampled database having an active power of < nominal power-50 and a pitch angle of > optimal pitch angle + 0.5.
5. The assessment method according to claim 4, wherein before selecting the corresponding index data in the sampling database to generate the corresponding index data image, filtering the corresponding SCADA system monitoring data and CMS system monitoring data in the sampling database to obtain the filtered data within the frequency band range of 0.1Hz-10 Hz.
6. The assessment method according to claim 2, wherein the step of selecting corresponding metric data within the sample database to generate a corresponding metric data image comprises: generating a scatter diagram by using wind speed-power, wind speed-pitch angle, impeller rotating speed-power and wind speed-cabin vibration acceleration; and comparing the scatter diagram with a reference image set by the offshore wind turbine generator, and if the range of the scatter diagram deviating from the reference image is within a set range, evaluating that the basic operation state of the offshore wind turbine generator is normal.
7. The assessment method according to claim 2, wherein the step of selecting corresponding metric data within the sample database to generate a corresponding metric data image comprises: generating a principal component frequency curve graph of a tower cylinder inclination angle and a principal component frequency curve graph of tower top vibration acceleration of the offshore wind turbine generator set at different impeller rotating speeds, wherein the principal component frequency of the tower cylinder inclination angle comprises a principal component frequency of a pitch angle and a principal component frequency of a roll angle, and the principal component frequency of the tower top vibration acceleration comprises a principal component frequency of an axial acceleration and a principal component frequency of a horizontal acceleration; when the principal component frequency of the inclination angle of the tower drum is consistent with the principal component frequency of the vibration acceleration of the tower top and deviates from the first-order frequency of the tower, the operation state of the offshore wind turbine generator is changed; when the principal component frequency of the tower inclination angle is not consistent with the principal component frequency of the tower top vibration acceleration but approaches the tower first-order frequency, the signal deviating from the tower first-order frequency is possibly abnormal; when the principal component frequency of the tower inclination angle is inconsistent with the principal component frequency of the tower top vibration acceleration and deviates from the tower first-order frequency, the corresponding signals of the tower inclination angle and the tower top acceleration may be abnormal.
8. The assessment method according to claim 2, wherein the step of selecting corresponding metric data within the sample database to generate a corresponding metric data image comprises: fitting and generating an impeller rotating speed-blade vibration RMS curve according to a first scatter diagram of the blade running state of the offshore wind turbine, wherein the first scatter diagram is a scatter curve corresponding to the impeller rotating speed-blade vibration RMS when the offshore wind turbine runs normally, and when the impeller rotating speed-blade vibration RMS curve generated by fitting is out of a 3sigma range of the first scatter diagram, evaluating that the blade is abnormal;
fitting and generating an impeller rotating speed-blade vibration principal component frequency curve according to a second scatter diagram of the offshore wind turbine generator, wherein the second scatter diagram is the impeller rotating speed-blade vibration principal component frequency curve when the offshore wind turbine generator operates normally; and when the impeller rotating speed-blade vibration principal component frequency curve generated by fitting is out of the sigma range of the second scatter diagram 3, evaluating that the blade is abnormal.
9. The method of claim 2, wherein the step of selecting the corresponding metric data within the sample database to generate the corresponding metric data image comprises: and generating a fitting curve of impeller rotating speed and RMS (root mean square) value of main shaft vibration when the offshore generator set normally operates, taking the RMS value of the main shaft vibration at different generator rotating speeds plus 3sigma as a main shaft vibration attention threshold value, and evaluating the main shaft vibration abnormality when the main shaft vibration attention threshold value is exceeded.
10. An evaluation system, characterized in that the system is configured to evaluate the operational state of an offshore wind turbine installation using the evaluation method of any of claims 1 to 9.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116718598A (en) * | 2023-06-01 | 2023-09-08 | 鹰普罗斯叶轮（宜兴）有限公司 | Aluminum alloy impeller defect monitoring system based on visual inspection |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116718598A (en) * | 2023-06-01 | 2023-09-08 | 鹰普罗斯叶轮（宜兴）有限公司 | Aluminum alloy impeller defect monitoring system based on visual inspection |
| CN116718598B (en) * | 2023-06-01 | 2023-12-29 | 鹰普罗斯叶轮（宜兴）有限公司 | Aluminum alloy impeller defect monitoring system based on visual inspection |
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