CN-122014538-A - Dynamic monitoring and overload early warning method for in-service wind power blade load

CN122014538ACN 122014538 ACN122014538 ACN 122014538ACN-122014538-A

Abstract

The invention discloses a dynamic monitoring and overload early warning method for in-service wind power blade loads, which comprises the steps of analyzing blade section stresses under different wind conditions, taking a maximum equivalent stress criterion as a failure judgment basis to identify a maximum dangerous section as an optimal monitoring position of a strain sensor, determining the optimal mounting quantity of the strain sensor according to a finite element circumferential strain deformation result at the maximum dangerous section and a sensitive grid effective monitoring range of the strain sensor, establishing a measuring model of resistance or voltage and load to realize in-service blade dynamic load monitoring, and comparing obtained load data with design loads of a blade factory by monitoring to realize blade overload judgment and early warning. According to the invention, the stress sensor is arranged at the maximum dangerous section, so that dynamic monitoring and overload early warning of the in-service wind power blade load can be accurately realized, the wind power output is further optimally controlled by synchronously increasing monitoring of wind parameters with larger influence such as wind shearing and turbulence, and the fatigue resistance performance of the in-service wind turbine blade is improved.

Inventors

CHANG LI
ZHOU BO
WANG YINA
TIAN GUIYUN
He Binze
TONG TONG

Assignees

沈阳工业大学

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (7)

1. The in-service wind power blade load dynamic monitoring and overload early warning method is characterized by comprising the following steps of: the method comprises the steps of S1, monitoring layout of strain sensors, establishing a Fluent finite element simulation calculation model according to a three-dimensional model of a blade in service and wind environment load parameters, analyzing the section stress of the blade under different wind conditions, and identifying the maximum dangerous section by taking the maximum equivalent stress criterion as a failure judgment basis as an optimal monitoring position of the strain sensors; Step S2, monitoring fatigue load of a blade in service, namely sticking a strain sensor at an optimal position on the surface of the blade, acquiring strain resistance or voltage data at a measuring point of the blade in the running process, acquiring load data of different section positions of the wind power blade through calculation of equivalent fatigue load of the wind power blade, establishing a stress-load relation according to mechanical properties of materials, and further establishing a measuring model of resistance or voltage and load, so as to realize dynamic load monitoring of the blade in service; The method comprises the steps of S3, analyzing and evaluating load monitoring data, firstly judging data change and acquisition time of data acquired by a strain sensor, an SCADA system and a laser radar system, determining the azimuth of a measured blade, or judging the azimuth change and pitch angle change of the blade in the slow rotation process of the blade according to time sequence, then extracting response frequency spectrum characteristics according to the strain measurement result, calculating natural frequency and modal characteristics of the blade by combining finite element simulation, determining the load trend of the blade in a waving and swaying state, and finally comparing the obtained load data with the design load of the delivery of the blade to realize overload judgment and early warning of the blade.
2. The method for dynamically monitoring and pre-warning overload of in-service wind power blade load according to claim 1, wherein in step S1, the method for determining the optimal monitoring positions and the optimal installation number of the strain sensors comprises the following steps: s11, constructing a high-precision three-dimensional finite element model of the blade according to the actual size, material properties and internal structure of the in-service blade by utilizing professional finite element analysis software; S12, after the three-dimensional finite element model of the blade is constructed, parameters under different working conditions are obtained from a database of the actual operation of the wind turbine, and are input into the three-dimensional finite element model of the blade to simulate the stress condition of the blade under various working conditions; S13, analyzing the simulation result, and finding out the area with the most serious stress concentration and the largest stress value on the blade by looking up the integral stress cloud image result of the blade, and determining the area as the area with the largest dangerous section; and S14, determining the optimal monitoring positions and the optimal installation number of the strain sensors according to the maximum dangerous cross section area and the effective monitoring range of the sensitivity of the strain sensors according to the finite element circumferential strain deformation result at the maximum dangerous cross section.
3. The method for dynamically monitoring and pre-warning the load of a wind power blade in service according to claim 2, wherein in step S12, parameters under different working conditions comprise a wind speed ranging from 3m/S to 25m/S, a wind direction changing from 0 ° to 360 °, a blade pitch angle adjusting from 0 ° to 90 °, and different rotational speeds.
4. The method for dynamically monitoring and pre-warning the load of the in-service wind power blade according to claim 1 is characterized in that in the step S2, after the dynamic load of the in-service blade is monitored, the accuracy of the calculated result of the equivalent fatigue load is verified by comparing the monitored loads of the same blade and the adjacent blade with the calculated equivalent fatigue load, and the load of the blade is calibrated by utilizing bending moment caused by gravity.
5. The method for dynamically monitoring and pre-warning the load of an in-service wind power blade according to claim 4, wherein in step S2, the method for dynamically monitoring the load of the in-service wind power blade comprises the following steps: Step S21, starting a mode analysis function on the established three-dimensional finite element model of the blade, and obtaining the natural frequency and the corresponding vibration mode of the blade through software calculation; Step S22, verifying the natural frequency data obtained by calculation by actually measuring the natural frequency of the in-service blade through vibration test equipment, and correcting the finite element model if the calculated value has larger deviation from the theoretical value or the actual measured value until the model calculation result accords with the actual condition; step S23, calculating a slope m of a material S-N curve according to GL2010 wind power blade authentication standard guidelines, and calculating an equivalent fatigue load according to the slope value; step S24, calculating an equivalent design fatigue load of the blade under 1Hz corresponding to the factory design fatigue load parameter, wherein the formula is as follows: (1) Wherein R eq is an equivalent design fatigue load under 1Hz, R df is a design fatigue load, N is the cycle number, and m is the slope of a material S-N curve; S25, calculating the fatigue loads of different section designs of the wind power blade, and obtaining the corresponding equivalent fatigue loads of the wind power blade at 1Hz of different section positions; s26, comparing the monitored loads of the same blade and the adjacent blade with the calculated equivalent fatigue load, evaluating whether the equivalent fatigue load calculation result is affected by wind field monitoring environment interference, and verifying the accuracy of the equivalent fatigue load calculation result; step S27, determining the azimuth of the measured blade by judging the change of the acquired data and the acquisition time, or judging the change of the azimuth of the blade and the change of the pitch angle in the slow rotation process of the blade according to the time sequence; step S28, obtaining bending moment in the waving and shimmy directions at the test section according to the bending moment caused by gravity; step S29, pasting a strain gauge on the most dangerous area of the blade according to the analysis result of the optimal monitoring position of the sensor, and obtaining a strain signal when the blade is loaded; Step S210, according to the linear relation between the strain and the load at the measuring point, the strain condition of the blade in the running process is obtained by measuring the resistance change of the strain gauge, and then the stress and the load born by the blade are converted according to the mechanical property of the material, so that the dynamic load monitoring of the in-service blade is realized.
6. The method for dynamically monitoring and pre-warning the load of an in-service wind power blade according to claim 5, wherein for the comparison and analysis with the design and simulation load, the ten-clock time sequence is calculated according to the 1Hz equivalent fatigue load, and the formula is as follows: (2) Wherein, the For a ten-clock time sequence 1Hz equivalent load, R i is the ith interval of the load spectrum, N i is the number of times of corresponding range values, m is the slope of a material S-N curve, and N is the number of cycles.
7. The method for dynamically monitoring and pre-warning the load of an in-service wind power blade according to claim 1, wherein in step S3, the specific method for realizing the judgment and pre-warning of the overload of the blade comprises the following steps: step S31, selecting a time sequence with normal data in a normal range and normal wind speed measurement under the running state of the unit according to wind environment test data; Step S32, analyzing the time length of a data file for ten minutes according to the IEC61400-13 requirement, acquiring wind speed and wind direction information of a 2.5-time wind wheel diameter by using a laser radar, and dividing load data into a measurement file for ten minutes according to average wind measurement data derived by the laser radar; step S33, according to the strain result obtained by actually monitoring the blade, carrying out time sequence spectrum analysis on the corresponding data, and extracting the characteristic frequency of the blade; step S34, according to the frequency spectrum response of the characteristic frequency of the blade, comparing the modal response calculation result, determining the vibration mode characteristics of the blade under the current wind condition load, namely the waving direction and the shimmy direction; Step S35, according to the strain monitoring result and the blade vibration mode comparison result, obtaining the magnitude and trend of the load value of the blade in the corresponding vibration mode of the flapping direction and the shimmy direction in the wind environment; step S36, the strain sensor on the blade acquires data such as stress, strain, deformation and load of the blade in real time and transmits the data to the data processing center; and step S37, the data processing center compares the data acquired in real time with fatigue loads of the factory design of the blade, and if the monitored data exceeds any fatigue overload threshold value, the data processing center indicates that the current load of the blade has overload risk and needs early warning.

Description

Dynamic monitoring and overload early warning method for in-service wind power blade load Technical Field The invention belongs to the technical field of wind driven generator blade state monitoring, and particularly relates to an in-service wind power blade load dynamic monitoring and overload early warning method. Background Failures such as leading edge corrosion, blade tip falling, icing corrosion, cementing cracking and the like of the wind turbine generator under the comprehensive actions of complex random load and field environment can often occur, if the types and the degrees of the failures can not be found and judged early, unplanned shutdown and excessive maintenance can be caused, and fracture malignant accidents can be caused under specific operation working conditions. In addition, new blade installation and debugging and technological improvement blade secondary installation need carry out blade dynamic balance test, test whether the load of the different blades of same unit is unanimous promptly, need accurate blade load monitoring system. In addition, the in-service wind turbine generator system control system can accurately execute actions such as wind, pitch, parking, starting and the like through real-time loads of the blades, and is important basic data for improving the power generation benefits of the wind turbine generator system. Therefore, the real-time monitoring and identification of the in-service blade load are important to the safe service, cost reduction and efficiency enhancement of the wind turbine generator. At present, the blades of the large wind turbine generator set are longer than hundred meters and have hundreds of flat surface areas, and the economical and technical reliability of a monitoring system is considered, so that the commercial blade load monitoring system monitors the multi-purpose strain sensor in real time, but the following technical problems are still faced in the actual wind power plant use process: (1) The blades of the wind turbine generator set need to bear 108-109 times of cyclic loads in the 20-year design service life, the times of cyclic loads born by mechanical equipment such as vehicles, helicopters and the like are greatly exceeded, fatigue load characteristics of the blades become extremely complex under the combined action of gravity load, pneumatic load and random load, and the arrangement of sensors lacks theoretical basis; (2) The wing profile structure, the layering design, the material characteristics and the manufacturing process of the blade designed by different manufacturers are relatively large, the fatigue resistance performance of the blade has relatively large uncertainty under the condition of changeable wind conditions, and accurate overload early warning cannot be realized, so that the overload false alarm rate of in-service blade load monitoring is extremely high, and the universality of a blade load monitoring system is not strong; (3) When the same type of blade is installed in different wind fields, the terrain roughness, wind profile, wind shearing and turbulence degree of the blade are possibly larger than the original design difference, so that the wind speed distribution difference along the height near the monitored wind turbine generator is larger, the actual monitoring dynamic load and the original design load are huge in difference, and the influence degree of wind condition parameters on the safe operation of the in-service blade is difficult to judge. Disclosure of Invention In view of the defects in the prior art, the invention provides an in-service wind power blade load dynamic monitoring and overload early warning method, which can accurately realize in-service wind power blade load dynamic monitoring and overload early warning by installing a stress sensor at the maximum dangerous section, further optimally control wind power output by synchronously increasing monitoring of wind parameters with larger influence such as wind shearing and turbulence, and improve the fatigue resistance of the in-service wind turbine blade. In order to achieve the above purpose, the present invention adopts the following technical scheme: An in-service wind power blade load dynamic monitoring and overload early warning method comprises the following steps: The method comprises the steps of S1, monitoring layout of strain sensors, establishing a Fluent finite element simulation calculation model according to a three-dimensional model of a blade in service and wind environment load parameters, analyzing the section stress of the blade under different wind conditions, and identifying the maximum dangerous section by taking the maximum equivalent stress criterion (Von Mises failure criterion) as a failure judgment basis to serve as the optimal monitoring position of the strain sensors; Step S2, monitoring fatigue load of a blade in service, namely sticking a strain sensor at an optimal position on the surface of the blade, acqui