A method for monitoring the vibration displacement of blade root bolts of large wind turbines

Abstract

The present invention discloses a method for monitoring the vibration displacement of blade root bolts of large wind turbines, comprising: converting the vibration of the bolts into flange gap displacement identification through overall monitoring of the blade root bolt connection, and obtaining flange gap displacement values; extracting peak-to-peak displacement data; processing the flange gap displacement values ​​according to the unit speed information, and eliminating data where the wind turbine is stopped and the speed is less than 5r / min; drawing a speed-displacement peak-to-peak scatter plot in combination with the unit speed information; eliminating abnormal values ​​from the speed-displacement peak-to-peak scatter plot through the quartile method, and setting an effective early warning line; and immediately triggering an alarm when the peak-to-peak value of the flange gap displacement remains above the early warning line within a preset time range. The present invention can simplify blade root bolt vibration monitoring, convert it into flange gap displacement monitoring of the entire connection, realize intelligent identification of the healthy service status of blade root bolts of large wind turbines, and reduce the cost of manual inspections.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method for monitoring the vibration displacement of blade root bolts of large wind turbine blades. Background Art

[0002] The root bolts of large wind turbine blades are prone to loosening or even fatigue fracture under the long-term effects of alternating loads such as slurry, gusts, and wind shear, causing the blades to fly out and become damaged, resulting in serious economic losses. Currently, the wind power industry's common strategy is regular manual inspections. Every six months or a year, the blades are manually climbed to the connection between the hub and the blades. The bolt torque is measured using equipment such as torque wrenches to determine the axial stress of the bolts. Based on the test results, the bolts are judged to be abnormal in their working condition and then maintained or replaced. However, for modern large wind turbines, the blade length exceeds 100 meters. Regular inspection and maintenance of the root bolts of these wind turbines using manual methods would incur considerable labor costs.

[0003] To this end, the industry has proposed a series of online monitoring methods for blade root bolt vibration. Bolt monitoring technologies have been developed, depending on the number of monitoring targets, including single-bolt monitoring methods, overall bolt connection monitoring methods, and video monitoring methods based on vision technology. Consequently, a number of intelligent sensors have been developed.

[0004] Single-bolt measurement methods monitor each bolt individually. However, because they only measure individual bolts, they may require polishing before installation, which affects mechanical properties, or have strict requirements for installation location and tooling. These factors limit their widespread use in engineering projects. Vision-based video monitoring methods utilize digital image processing technology to analyze video images to monitor and evaluate the status of bolted connections. Compared to other methods, video monitoring generates larger amounts of data, resulting in increased storage resources and installation and maintenance costs.

[0005] The invention with publication number CN111852791B discloses a method for locating and warning of broken flange connection bolts of wind turbine generator sets. First, the method divides the flange connection bolts into bins according to wind speed and yaw position, and stores the displacement data collected by the split displacement sensor in the corresponding storage bins according to wind speed and yaw position. Within each preset calculation cycle, the sliding average and peak value of the bolt displacement under the current wind speed and yaw position are calculated to issue bolt loosening alarms, bolt excessive external load alarms, and flange gap monitoring alarms. This invention can use the split displacement sensor, combined with wind speed signals and yaw signals, to issue bolt loosening alarms, bolt excessive external load alarms, and flange gap monitoring alarms. The calculation is comprehensive, efficient, and reliable. It also monitors the fracture of the flange connection bolts in real time online to avoid equipment damage caused by flange connection bolt failure. The invention with publication number CN117646707B discloses a wind turbine hub monitoring method, device, equipment and storage medium, including: synchronously collecting wind turbine hub data; wherein the wind turbine hub data includes: blade data, pitch bearing vibration data and blade root flange data; calculating component indicators based on the wind turbine hub data; comparing the component indicators with preset alarm thresholds, and outputting alarm signals according to the working conditions based on the comparison results.

[0006] Relatively speaking, the overall monitoring method for bolted connections has more practical engineering significance. Strain gauges can monitor the working condition of bolts by measuring the axial strain of the bolts. They have high measurement accuracy and sensitivity, and are simple in structure and easy to install. The only drawback is that the strain gauges attached to the surface are easily damaged. To address the problem of strain gauge strain gauges being easily damaged, researchers have designed and produced a surface strain gauge using the stress characteristics of elastic elements, special processing techniques, and patch moisture-proof sealing technology. This surface strain gauge is developed based on strain measurement technology and can achieve extremely high resolution and excellent stability at different time scales. At the same time, it has a simple structure, is easy to install and use, and is not as easily damaged as the strain gauges of traditional strain gauges. However, no effective method has yet been proposed for applying this surface strain gauge to the vibration displacement monitoring of the root bolts of large wind turbine blades. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for monitoring the vibration displacement of blade root bolts of large wind turbine blades. By monitoring the entire blade root bolt connection (flange gap), the bolt vibration condition is converted into flange gap displacement identification, which simplifies the blade root bolt vibration monitoring, realizes the intelligent identification of the healthy service status of the blade root bolts of large wind turbine blades, and reduces the cost of manual inspection.

[0008] In order to achieve the above technical objectives, the technical solution adopted by the present invention is:

[0009] A method for monitoring the vibration displacement of blade root bolts of a large wind turbine blade comprises the following steps:

[0010] S1, through the overall monitoring of the blade root bolt connection, the bolt vibration is converted into the flange gap displacement identification to obtain the flange gap displacement value;

[0011] S2, processing the flange clearance displacement value obtained in step S1, extracting the peak-to-peak value data of the displacement, and extracting a peak-to-peak value of the displacement for each package of original displacement blocks;

[0012] S3, processing the flange clearance displacement values ​​obtained in step S1 according to the wind turbine speed information, and eliminating data where the wind turbine is stopped and the speed is less than 5 r / min;

[0013] S4, drawing a speed-displacement peak-to-peak scatter plot for the flange clearance displacement value obtained in step S1 in combination with the unit speed information;

[0014] S5, using the quartile method to remove outliers from the speed-displacement peak-to-peak scatter plot obtained in step S4, and setting an effective warning line;

[0015] S6, when the peak-to-peak value of the flange gap displacement continues to be above the warning line set in step S5 within the preset time range, an alarm is immediately triggered.

[0016] Step S1 further comprises:

[0017] Determine the blade root load conditions by combining the turbine blade design with wind field information;

[0018] The number and locations of surface strain gauges are determined based on the blade root load conditions and engineering costs;

[0019] The surface strain gauge is installed and its two ends are fixed on the upper flange and lower flange at the blade root of the wind turbine to obtain the displacement value of the flange connection gap of the turbine.

[0020] Step S3 further comprises:

[0021] Get the unit speed information.

[0022] Considering the situation of no wind load or small wind load, the blade root bolts are more likely to be in healthy service, and the flange clearance displacement data obtained when the wind turbine is stopped and the speed is less than 5r / min needs to be eliminated.

[0023] Furthermore, in step S3, the unit speed information is directly read in through the PLC master control.

[0024] Furthermore, in step S3, the process of obtaining the unit speed information includes:

[0025] Install an inclination sensor in the wheel hub collection cabinet to measure and obtain inclination data;

[0026] Use digital filtering technology to filter the collected inclination data to remove noise and smooth the data

[0027] The number of identified spike data is converted into wheel hub speed.

[0028] Furthermore, in step S5, the warning line is set to the second largest value of the peak-to-peak value of the flange gap displacement under normal conditions that is less than the maximum estimated value.

[0029] Furthermore, in step S5, based on the speed-displacement peak-to-peak scatter plot, the flange clearance displacement values ​​obtained under different speed conditions are subjected to an outlier elimination operation in combination with the quartile method, which specifically includes the following steps:

[0030] Arrange the flange clearance displacement values ​​obtained at the same speed from small to large, and divide them into four equal parts using three split points Q1, Q2, and Q3, with each part containing 25% of the data. The three split points Q1, Q2, and Q3 represent the lower quartile, median, and upper quartile, respectively, and their positions are determined by the following formula:

[0031]

[0032] Where n represents the number of items of flange clearance displacement peak-to-peak data;

[0033] Based on the three split points Q1, Q2 and Q3, the minimum and maximum estimated values ​​are defined as follows:

[0034] Minimum estimate = Q1-k(Q3-Q1)

[0035] Maximum estimated value = Q3 + k(Q3 - Q1)

[0036] Where k is a parameter representing the degree of data abnormality;

[0037] When the value is greater than the maximum estimated value or the value is less than the minimum estimated value, it is recorded as an outlier;

[0038] Read the second largest value of the flange clearance displacement peak-to-peak value that is less than the maximum estimated value under normal conditions, set it as the warning value, and draw an effective warning line for the speed-displacement peak-to-peak scatter plot. The piecewise function expression is:

[0039] f(x)=k i x+b i

[0040] Where x is the rotor speed, f(x) is the warning value, i is an integer greater than or equal to 1, and i is an index value used to distinguish different situations or stages, which is associated with the range of the rotor speed.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] First, the present invention's method for monitoring the vibration displacement of blade root bolts in large wind turbines monitors the entire blade root bolt connection (flange gap) and converts bolt vibration into flange gap displacement, simplifying blade root bolt vibration monitoring. Compared to existing technologies, this method eliminates the need for individual bolt measurements and does not consume the large storage resources required by video monitoring. Instead, it provides a more practical, engineering-savvy method for monitoring the entire bolt connection.

[0043] Second, the vibration displacement monitoring method of the root bolts of large wind turbine blades of the present invention adopts a surface strain gauge with a simple structure and easy installation and use. Through special packaging technology, it can avoid the problem that the strain gauges of traditional strain-type displacement gauges are easily damaged, and can have extremely high resolution and excellent stability at different time scales.

[0044] Third, the vibration displacement monitoring method of the blade root bolts of large wind turbines of the present invention is combined with the rotation speed of the unit to set an effective early warning line, which can realize the intelligent identification of the healthy service status of the blade root bolts of large wind turbines and greatly reduce the cost of manual regular inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is the general layout diagram of the installation method of the surface strain gauge DH1207 and the overall monitoring method;

[0046] Figure 2 It is a data analysis flow chart;

[0047] Figure 3 This is a schematic diagram of the DH1207 layout;

[0048] Figure 4 It is the on-site installation construction drawing;

[0049] Figure 5 is a schematic diagram of the gap peak-to-peak value;

[0050] Figure 6a It is a schematic diagram of the inclination data filtering;

[0051] Figure 6b This is a partial diagram of the inclination data filtering;

[0052] Figure 7a This is the "speed-displacement peak-to-peak" scatter plot of the displacement meter No. 7-3 on blade B from March 5 to April 9, 2024;

[0053] Figure 7bThis is the "speed-displacement peak-to-peak" scatter plot of the displacement meter No. 7-3 on blade B from April 9 to May 14, 2024;

[0054] Figure 7c This is the "speed-displacement peak-to-peak" scatter plot of the displacement meter No. 7-3 on blade B from May 14 to June 18, 2024;

[0055] Figure 7d This is the "speed-displacement peak-to-peak" scatter plot of the displacement meter No. 7-3 on blade B from June 18 to July 19, 2024;

[0056] Figure 7e This is a comparison chart of the warning lines of the displacement meter No. 7-3 of blade B in different time periods;

[0057] Figure 8 This is a three-dimensional curve graph (time-speed-peak-peak value) of the displacement meter No. 7-3 of blade B from March 5 to July 19, 2024. DETAILED DESCRIPTION

[0058] The embodiments of the present invention are described in further detail below with reference to the accompanying drawings.

[0059] The present invention discloses a method for monitoring the vibration displacement of blade root bolts of a large wind turbine blade, the method comprising the following steps:

[0060] S1, using the surface strain gauge DH1207, monitors the entire blade root bolt connection (flange gap), converts the bolt vibration into flange gap displacement identification, and obtains the displacement value;

[0061] S2, processing the flange clearance displacement value obtained in step S1, extracting the peak-to-peak value data of the displacement, and extracting a peak-to-peak value of the displacement for each package of original displacement blocks.

[0062] S3, based on the turbine speed information, processing the flange clearance displacement values ​​obtained in step S1, and eliminating data where the wind turbine is stopped or the speed is less than 5 r / min (when there is no wind load or the wind load is small, the blade root bolts are more likely to be in good service);

[0063] S4, drawing a "speed-displacement peak-to-peak" scatter plot for the flange clearance displacement values ​​obtained in step S1 in combination with the unit speed information;

[0064] S5, using the quartile method to remove outliers from the "speed-displacement peak-to-peak" scatter plot obtained in step S4, thereby setting an effective warning line (the warning line is set to the second largest value of the flange clearance displacement peak-to-peak value less than the maximum estimated value under normal conditions);

[0065] S6, when the peak-to-peak value of the flange gap displacement continues to be above the warning line set in step S5 for a period of time, an alarm is immediately triggered.

[0066] Figure 1 This is the general layout diagram of the installation method and overall monitoring method of the surface strain gauge DH1207. Figure 1 The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades of the present invention specifically includes:

[0067] Step 1: Use the DH1207 surface strain gauge to monitor the entire blade root bolt connection (flange gap), convert the bolt vibration into flange gap displacement, and obtain the displacement value. This includes the following steps:

[0068] Determine the blade root load conditions by combining the turbine blade design with wind field information;

[0069] The number and locations of surface strain gauges DH1207 are determined based on the blade root load conditions and engineering costs;

[0070] During the construction and installation of DH1207, the two ends of the sensor need to be fixed on the upper flange and lower flange positions at the root of the wind turbine blade respectively. The sensor data is connected to the collector, and together with the gateway, server, etc., a complete monitoring system is set up to obtain the displacement value of the flange connection gap of the unit.

[0071] Figure 2 is a data analysis flow chart. Figure 2 After obtaining the original data, the following steps are used to analyze and process the monitoring data:

[0072] Step 2: Process the flange clearance displacement value obtained in step 1, extract the peak-to-peak value data of the displacement, and extract a peak-to-peak value of the displacement for each package of original displacement blocks.

[0073] Step 3: Based on the turbine speed information, process the flange clearance displacement values ​​obtained in step 1 and eliminate data where the turbine is stopped or the speed is less than 5 r / min (when there is no wind load or the wind load is small, the blade root bolts are more likely to be in good service). This specifically includes the following steps:

[0074] The unit speed information can be directly read in through the PLC main control, or it can be obtained by measuring and converting it by installing an additional inclination sensor in the wheel hub acquisition cabinet. If an inclination sensor is used, the collected inclination data must first be filtered using digital filtering technology (median filtering) to remove noise and smooth the data. The number of identified peak data is then converted into wheel hub speed.

[0075] Considering the situation of no wind load or small wind load, the blade root bolts are more likely to be in healthy service. Therefore, the flange clearance displacement data obtained in step 1 when the wind turbine is stopped and the speed is less than 5 r / min needs to be eliminated.

[0076] Step 4: Combined with the unit speed information, draw a "speed-displacement peak-to-peak" scatter plot for the flange clearance displacement value obtained in step 1.

[0077] Step 5: Use the quartile method to remove outliers from the "speed-displacement peak-to-peak" scatter plot obtained in step 3, thereby setting an effective warning line (the warning line is set to the second largest value of the flange clearance displacement peak-to-peak value less than the maximum estimated value under normal conditions). Specifically, the following steps are included:

[0078] Arrange the flange clearance displacement values ​​obtained at the same speed from small to large, and divide them into four equal parts using three split points Q1, Q2, and Q3, with each part containing 25% of the data;

[0079] The three split points Q1, Q2, and Q3 represent the lower quartile, median, and upper quartile, respectively, and their positions can be determined by the following formula:

[0080]

[0081] Where: n represents the number of items of flange clearance displacement peak-to-peak data;

[0082] Based on the three split points Q1, Q2 and Q3, the minimum and maximum estimated values ​​are defined as follows:

[0083] Minimum estimate = Q1-k(Q3-Q1)

[0084] Maximum estimated value = Q3 + k(Q3 - Q1)

[0085] Where k is a parameter indicating the degree of data anomaly. Generally, when k = 1.5, it indicates that the data is moderately abnormal; when k = 3, it indicates that the data is extremely abnormal.

[0086] When the value is greater than the maximum estimated value or less than the minimum estimated value, it is recorded as an anomaly and needs to be eliminated.

[0087] Finally, read the second largest value of the flange clearance displacement peak-to-peak value that is less than the maximum estimated value under normal conditions, set it as the warning value, and draw an effective warning line for the "speed-displacement peak-to-peak" scatter plot. The piecewise function expression is:

[0088] f(x)=k i x+b i , (i∈[1,18], i is an integer)

[0089] Where x is the wind wheel speed and f(x) is the warning value.

[0090] Step 5: When the peak-to-peak value of the flange gap displacement continues to be above the warning line set in step 4 for a period of time, an alarm is triggered immediately.

[0091] Examples

[0092] The test prototype used for method validation is located at a wind turbine plant. The turbine model is a United Power UP121-2000, with unit number #196. To monitor the position changes and possible loosening or deformation of the turbine blade root bolts, the blade root bolt vibration displacement monitoring method implemented in this example includes the following steps:

[0093] Step 1: Use the DH1207 surface strain gauge to monitor the entire blade root bolt connection (flange gap), convert the bolt vibration into flange gap displacement, and obtain the displacement value. Specifically, it can be divided into the following steps:

[0094] Combine the unit blade design with wind field information to determine the blade root load condition.

[0095] The layout of the surface strain gauge DH1207 is determined by considering the blade root load conditions and engineering costs. Figure 3 Eight DH1207 sensors were placed at the root of each blade, with two sensors densely spaced approximately 5° above and below the 0° and 180° diagonals. One sensor was placed at each of the four angles: 45°, 90°, 225°, and 270°. To facilitate subsequent data analysis and processing, each blade and corresponding bolt measurement point has been numbered and named (see Table 1).

[0096] Table 1 DH1207 installation position

[0097]

[0098]

[0099] Install DH1207 according to the plan. The two ends of the sensor need to be fixed on the upper flange and lower flange at the root of the wind turbine blade. The on-site installation construction drawing is as follows: Figure 4 As shown, Figure 4 The text in the text is meaningless to the technical solution of the present invention. Figure 4 It is only used to show the on-site installation and construction scene. Figure 1The sensor data is connected to the collector, which, together with the gateway and server, forms a complete monitoring system to obtain the displacement value of the unit flange connection gap. The data intervals for this data are March 5 to April 9, 2024, April 9 to May 14, 2024, May 14 to June 18, 2024, and June 18 to July 19, 2024.

[0100] Step 2: Process the flange clearance displacement value obtained in step 1 and extract the peak-to-peak displacement data. One peak-to-peak displacement is extracted from each package of original displacement blocks. The specific formula is as follows:

[0101] V PP =V max -V min

[0102] Where: V pp Indicates peak-to-peak value; V max Indicates the maximum value in the signal, V min Indicates the minimum value in the signal.

[0103] Considering the large amount of data, the present invention only takes a small part of the displacement data of the No. 7-3 displacement meter at the No. 8 bolt position in blade B as an example to demonstrate data analysis. Figure 5 is a schematic diagram of the gap peak-to-peak value.

[0104] Step 3: Based on the turbine speed information, process the flange clearance displacement values ​​obtained in step 1 and eliminate data where the wind turbine is stopped or the speed is less than 5 r / min (when there is no wind load or the wind load is small, the blade root bolts are more likely to be in good service). This specifically includes the following steps:

[0105] Obtaining unit speed information: Considering the prototype PLC data is not open, this construction project installed an additional inclination sensor in the hub data collection cabinet. The collected inclination data was filtered using digital filtering technology (median filtering) to remove noise and smooth the data. The number of identified peak data was then converted into hub speed using the following processing formula:

[0106] Median filter part formula:

[0107]

[0108] Where: x(n) is a one-dimensional discrete signal; M is the filter window length, which is generally an odd number to ensure that the window has a clear center position; the med function represents the median of the sequence in the brackets; y(n) is the output signal after one-dimensional median filtering; n = 0, 1, …, N-1.

[0109] Formulas for peak data identification and speed conversion:

[0110] y={y(1),y(2),…,y(N)}

[0111]

[0112] Where: y is the filtered data sequence; σ y are the mean and standard deviation of the filtered data respectively.

[0113] will satisfy The point y(k) where k1 is a custom threshold coefficient, usually greater than 0, is marked as a peak data point, and the number of peak data points P is counted:

[0114] R=P / d t

[0115] Where: P is the number of spike data points, d t It is the difference between the time when the spike data ends and the time when the spike data starts.

[0116] Considering the large amount of data, this paper only uses a small part of the inclination data as an example to demonstrate data analysis. Figure 6a-6b As shown in Figure 2, they are the inclination data filtering diagram and the inclination data filtering local diagram respectively.

[0117] Considering the situation of no wind load or small wind load, the blade root bolts are more likely to be in healthy service. Here, the flange clearance displacement data obtained in step 1 when the wind turbine is stopped and the speed is less than 5 r / min are excluded.

[0118] Step 4: Combined with the unit speed information, draw a "speed-displacement peak-to-peak" scatter plot and a three-dimensional curve graph (time-speed-peak-to-peak) for the flange clearance displacement value obtained in step 1. Considering the large amount of data, the present invention only takes the displacement meter No. 7-3 at the No. 8 bolt position in blade B as an example to demonstrate data analysis. Figure 7a-Figure 8 As shown, they are the displacement gauge No. 7-3 on blade B from March 5 to April 9, 2024 ( Figure 7a ), April 9-May 14, 2024 ( Figure 7b ), May 14-June 18, 2024 ( Figure 7c ), June 18-July 19, 2024 ( Figure 7d ) The scatter plot of "speed-displacement peak-to-peak value" in these four different time periods, and the comparison chart of the warning line of "speed-displacement peak-to-peak value" in these four different time periods ( Figure 7e ) and the three-dimensional curve (time-speed-peak-peak value) during the period from March 5 to July 19, 2024.

[0119] Step 5: Use the quartile method to remove outliers from the "speed-displacement peak-to-peak" scatter plot obtained in step 4, thereby setting an effective warning line (the warning line is set to the second largest value of the flange clearance displacement peak-to-peak value less than the maximum estimated value under normal conditions). Specifically, the following steps are included:

[0120] Arrange the flange clearance displacement values ​​obtained at the same speed from small to large, and divide them into four equal parts using three split points Q1, Q2, and Q3, with each part containing 25% of the data;

[0121] The three split points Q1, Q2, and Q3 represent the lower quartile, median, and upper quartile, respectively, and their positions can be determined by the following formula:

[0122]

[0123] Where: n represents the number of items of flange clearance displacement peak-to-peak data;

[0124] Based on the three split points Q1, Q2 and Q3, the minimum and maximum estimated values ​​are defined as follows:

[0125] Minimum estimate = Q1-k(Q3-Q1)

[0126] Maximum estimated value = Q3 + k(Q3 - Q1)

[0127] Where k is a parameter indicating the degree of data anomaly. Generally, when k = 1.5, it indicates that the data is moderately abnormal; when k = 3, it indicates that the data is extremely abnormal.

[0128] When the value is greater than the maximum estimated value or less than the minimum estimated value, it is recorded as an anomaly and needs to be eliminated.

[0129] Finally, read the second largest value of the flange clearance displacement peak-to-peak value that is less than the maximum estimated value under normal conditions, set it as the warning value, and draw an effective warning line for the "speed-displacement peak-to-peak" scatter plot. The piecewise function expression is:

[0130] f(x)=k i x+b i , (i∈[1,18], i is an integer)

[0131] Where x is the wind rotor speed, f(x) is the warning value. In this case, i∈[1,18].

[0132] from Figure 7a-7d The warning line can be extracted and summarized to obtain Figure 7e , that is, the comparison chart of the warning lines of the displacement meter No. 7-3 of blade B in different time periods. Figure 7eIt can be seen that the warning line is basically the same in each time period. As the speed increases, the warning value also increases. The slope, intercept and wind rotor speed range of the average warning line piecewise function expression are shown in Table 2:

[0133] Table 2B Parameters of the piecewise function expression for the warning line of the displacement meter No. 7-3 on blade 7 (March 5, 2024 - July 19, 2024)

[0134]

[0135]

[0136] Step 6: When the peak-to-peak value of the flange clearance displacement continues to be above the warning line set in step 5 for a period of time, the alarm is triggered immediately. Figure 7e and Figure 8 The warning lines obtained at different time periods were essentially consistent, indicating that the displacement patterns at the blade root bolts were essentially the same, indicating that the bolts had not loosened and were operating normally. On-site inspections by wind farm personnel confirmed that the bolts were operating normally.

[0137] The present invention has been verified through wind field investigation and found that the newly proposed method for monitoring the vibration displacement of blade root bolts of large wind turbines has reliable data, practical physical and engineering significance, and is simple and easy to operate.

[0138] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0139] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0140] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions for executing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0142] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0143] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for monitoring the vibration displacement of blade root bolts of large wind turbines, characterized in that: The method comprises the following steps: S1, through the overall monitoring of the blade root bolt connection, the bolt vibration is converted into the flange gap displacement identification to obtain the flange gap displacement value; S2, processing the flange clearance displacement value obtained in step S1, extracting the peak-to-peak value data of the displacement, and extracting a peak-to-peak value of the displacement for each package of original displacement blocks; S3, processing the flange clearance displacement values ​​obtained in step S1 according to the wind turbine speed information, and eliminating data where the wind turbine is stopped and the speed is less than 5 r / min; S4, combining the unit speed information, draw a speed-displacement peak-to-peak scatter plot; S5, using the quartile method to remove outliers from the speed-displacement peak-to-peak scatter plot obtained in step S4, and setting an effective warning line; when the peak-to-peak value of the flange clearance displacement remains above the set warning line within a preset time range, an alarm is immediately triggered; In step S5, based on the speed-displacement peak-to-peak scatter plot, the flange clearance displacement values ​​obtained under different speed conditions are subjected to outlier elimination in combination with the quartile method, specifically including the following steps: Arrange the flange clearance displacement values ​​obtained at the same speed from small to large, and divide them into four equal parts using three split points Q1, Q2, and Q3, with each part containing 25% of the data. The three split points Q1, Q2, and Q3 represent the lower quartile, median, and upper quartile, respectively, and their positions are determined by the following formula: Where n represents the number of items of flange clearance displacement peak-to-peak data; Based on the three split points Q1, Q2 and Q3, the minimum and maximum estimated values ​​are defined as follows: Where k is a parameter representing the degree of data abnormality; When the value is greater than the maximum estimated value or the value is less than the minimum estimated value, it is recorded as an outlier; Read the second largest value of the flange clearance displacement peak-to-peak value that is less than the maximum estimated value under normal conditions, set it as the warning value, and draw an effective warning line for the speed-displacement peak-to-peak scatter plot. The piecewise function expression is: Where x is the wind wheel speed, f(x) is the warning value, Take an integer greater than or equal to 1, It is an index value used to distinguish different situations or stages, which is associated with the range of wind rotor speed.

2. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 1, characterized in that: Step S1 further comprises: Determine the blade root load conditions by combining the turbine blade design with wind field information; The number and locations of surface strain gauges are determined based on the blade root load conditions and engineering costs; The surface strain gauge is installed and its two ends are fixed on the upper flange and lower flange at the blade root of the wind turbine to obtain the displacement value of the flange connection gap of the turbine.

3. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 1, characterized in that: Step S3 further comprises: Get unit speed information; Considering the situation of no wind load or small wind load, the blade root bolts are more likely to be in healthy service, and the flange clearance displacement data obtained when the wind turbine is stopped and the speed is less than 5 r / min need to be eliminated.

4. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 3, characterized in that: In step S3, the unit speed information is directly read in through the PLC master control.

5. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 3, characterized in that: In step S3, the process of obtaining the unit speed information includes: Install an inclination sensor in the wheel hub collection cabinet to measure and obtain inclination data; Use digital filtering technology to filter the collected inclination data to remove noise and smooth the data The number of identified spike data is converted into wheel hub speed.

6. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 1, characterized in that: In step S5, the warning line is set to the second largest value of the flange gap displacement peak-to-peak value less than the maximum estimated value under normal conditions.

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