Large wind turbine generator blade root bolt vibration displacement monitoring method

Abstract

The invention discloses a large-scale wind turbine generator blade root bolt vibration displacement monitoring method, which comprises the following steps: through blade root bolt connection integral monitoring, converting a bolt vibration condition into flange gap displacement identification, and obtaining a flange gap displacement value; extracting displacement peak-to-peak value data; processing a flange gap displacement value according to the rotating speed information of the generator set, and removing data when the wind turbine generator set stops rotating and the rotating speed is less than 5r / min; drawing a rotating speed-displacement peak-to-peak value scatter diagram in combination with the rotating speed information of the unit; removing abnormal values for the rotation speed-displacement peak-to-peak value scatter diagram through a quartile method, and setting an effective early warning line; and when the flange gap displacement peak-to-peak value is continuously above the early warning line within the preset time range, an alarm is triggered immediately. According to the invention, blade root bolt vibration monitoring can be simplified and converted into flange gap displacement monitoring of the whole connection, intelligent identification of the healthy service state of the blade root bolt of the large-scale wind turbine generator is realized, and the manual inspection cost is reduced.

Description

Technical Field

[0001] The 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 a large wind turbine blade. Background Art

[0002] The root bolts of large wind turbine blades are prone to loosening or even fatigue fracture under the long-term action of alternating loads such as slurry, gusts, and wind shear, causing the blades to fly out and be damaged, resulting in serious economic losses. At present, the commonly used strategy in the wind power industry is manual regular inspection. Every six months or a year, the tower is manually climbed to enter the connection section between the hub and the blade, and the torque of the bolts is measured using equipment such as torque wrenches to obtain the magnitude of the axial stress of the bolts. Based on the test results, it is determined whether the working state of the bolts is abnormal, and maintenance or replacement is performed. However, for modern large wind turbines, the length of the blades has exceeded 100 meters. If manual inspection and maintenance of the root bolts of these wind turbines are still carried out regularly, it will cost a very high labor cost.

[0003] To this end, the industry has proposed a series of online monitoring methods for blade root bolt vibration. In terms of bolt monitoring technology, according to the number of monitored objects, single bolt monitoring methods, bolt connection overall monitoring methods, and video monitoring methods based on visual technology have been developed, and many intelligent sensors have been developed accordingly.

[0004] The single bolt measurement method monitors each bolt, but because it only measures a single bolt, or needs to be polished before installation, affecting mechanical properties, or has high requirements for installation location and tooling, it limits the further widespread use of this method in engineering. The video monitoring method based on visual technology refers to the use of digital image processing technology to analyze video images to monitor and evaluate the state of bolt connections. Compared with other methods, video monitoring has a larger amount of data, resulting in consumption of storage resources and higher installation and maintenance costs.

[0005] The invention with the publication number CN111852791B discloses a method for positioning and warning of the fracture of flange connection bolts of wind turbine generator sets. First, the wind speed and flange flight are divided into bins, and the displacement data collected by the split displacement sensor is stored in the corresponding storage bins according to the wind speed and yaw position. In each preset calculation cycle, the bolt displacement sliding average and the bolt displacement peak value under the current wind speed and yaw position are calculated to perform bolt loosening alarm, bolt external load excessive alarm and flange gap monitoring alarm. The invention can realize bolt loosening alarm, bolt external load excessive alarm and flange gap monitoring alarm through the split displacement sensor, combined with the wind speed signal and the yaw signal, with comprehensive calculation, high calculation efficiency and strong reliability; real-time online monitoring of the fracture of the connecting bolts between flanges to avoid equipment damage caused by the failure of the flange connection bolts. 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 of bolted connection has more practical engineering significance. The strain gauge can monitor the working state of the bolt by measuring the axial strain of the bolt. It has high measurement accuracy and sensitivity, simple structure and easy installation. The only drawback is that the strain gauge pasted on the surface is easily damaged. In order to solve the problem that the strain gauge of the strain gauge is easily damaged, some researchers have designed and produced a surface strain gauge by using the stress characteristics of elastic elements, special processing technology, and patch moisture-proof sealing technology. The surface strain gauge is developed based on strain measurement technology and can have 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 gauge of the traditional strain gauge. However, there is no effective method for applying the 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 turbines. By monitoring the overall blade root bolt connection (flange gap), the bolt vibration condition is converted into flange gap displacement identification, the blade root bolt vibration monitoring is simplified, the healthy service status of the blade root bolts of large wind turbines can be intelligently identified, and the cost of manual inspection can be reduced.

[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, the method comprising the following steps:

[0010] S1, through the overall monitoring of the blade root bolt connection, the bolt vibration is converted into 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 displacement peak-to-peak value data, and extracting a displacement peak-to-peak value for each package of original displacement blocks;

[0012] S3, processing the flange clearance displacement values ​​obtained in step S1 according to the unit speed information, and eliminating the data when the wind turbine unit 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, removing abnormal values ​​from the speed-displacement peak-to-peak scatter plot obtained in step S4 by using the quartile method, 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 a preset time range, an alarm is immediately triggered.

[0016] Step S1 further comprises:

[0017] Combine the unit blade design with wind field information to determine the blade root load condition;

[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 main control.

[0024] Furthermore, in step S3, the process of acquiring 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 peak data is converted into wheel hub speed.

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

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

[0030] Arrange the flange clearance displacement values ​​obtained under the same speed state from small to large, and divide them into four equal parts using three split points Q1, Q2 and Q3, each part contains 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 in the normal state, 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] Wherein x is the wind 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 wind rotor speed.

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

[0042] First, the vibration displacement monitoring method of the blade root bolts of a large wind turbine of the present invention converts the vibration of the bolts into the identification of the displacement of the flange gap by monitoring the overall blade root bolt connection (flange gap), thereby simplifying the vibration monitoring of the blade root bolts. Compared with the prior art, the present invention does not need to measure a single bolt, nor does it consume a large amount of storage resources like video monitoring, but is a more practical engineering-significant overall monitoring method for bolt connections.

[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, which has a simple structure and is easy to install and use. Through special packaging techniques, 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, combined with the rotation speed of the unit, sets 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 It 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 inclination data filtering;

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

[0052] Figure 7a It is the scatter plot of “speed-displacement peak-to-peak value” of displacement meter No. 7-3 of blade B during the period from March 5 to April 9, 2024;

[0053] Figure 7bIt is the scatter plot of “speed-displacement peak-to-peak value” of displacement meter No. 7-3 of blade B during the period from April 9 to May 14, 2024;

[0054] Figure 7c It is the scatter plot of “speed-displacement peak-to-peak value” of displacement meter No. 7-3 of blade B during the period from May 14 to June 18, 2024;

[0055] Figure 7d It is the scatter plot of “speed-displacement peak-to-peak value” of displacement meter No. 7-3 of blade B during the period 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 It 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 further described in detail below in conjunction with 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 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 displacement peak-to-peak value data, and extracting a displacement peak-to-peak value for each package of original displacement blocks.

[0062] S3, according to the unit speed information, the flange clearance displacement values ​​obtained in step S1 are processed, and the data when the wind turbine unit is stopped and the speed is less than 5r / min are eliminated (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 value obtained in step S1 in combination with the unit speed information;

[0064] S5, removing abnormal values ​​from the "speed-displacement peak-to-peak" scatter plot obtained in step S4 by the quartile method, 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 a 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 surface strain gauge DH1207 to monitor the blade root bolt connection as a whole (flange gap), convert the bolt vibration into flange gap displacement identification, and obtain the displacement value. The specific steps include:

[0068] Combine the unit blade design with wind field information to determine the blade root load condition;

[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, both ends of the sensor need to be fixed on the upper flange and lower flange positions at the blade root of the wind turbine 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 displacement peak-to-peak value data, and extract a displacement peak-to-peak value from each package of original displacement blocks.

[0073] Step 3: Based on the unit speed information, process the flange clearance displacement values ​​obtained in step 1, and remove the data when the wind turbine unit is stopped and the speed is less than 5r / 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). Specifically, the following steps are included:

[0074] The unit speed information can be directly read in through the PLC main control, or it can be obtained 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, and the flange clearance displacement data obtained in step 1 when the wind turbine is stopped and the speed is less than 5r / min needs to be eliminated.

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

[0077] Step 5: Use the quartile method to remove abnormal values ​​from the "speed-displacement peak-to-peak" scatter plot obtained in step 3, so as to set 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 under the same speed state from small to large, and divide them into four equal parts using three division 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 abnormality. 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 in the normal state, 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 verification is located in a wind power plant. The unit model is United Power UP121-2000, and the unit number is #196. In order to monitor the position change of the unit blade root bolts, as well as possible loosening or deformation, the blade root bolt vibration displacement monitoring method implemented in this example includes the following steps:

[0093] Step 1: Use the surface strain gauge DH1207 to monitor the blade root bolt connection as a whole (flange gap), convert the bolt vibration into flange gap displacement identification, 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 based on the blade root load and engineering cost. Figure 3 : 8 DH1207 sensors are arranged at the root of each blade, with 2 sensors densely distributed about 5° above and below the 0° and 180° diagonals, and 1 sensor each at the 45°, 90°, 225° and 270° angles. To facilitate subsequent data analysis and processing, each blade and the corresponding bolt measurement point are numbered and named, see Table 1.

[0096] Table 1 DH1207 installation position

[0097]

[0098]

[0099] According to the plan, DH1207 should be installed. Both 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 1, 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. The data intervals are March 5-April 9, 2024, April 9-May 14, 2024, May 14-June 18, 2024, and June 18-July 19, 2024.

[0100] 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. 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 It is a schematic diagram of the gap peak-to-peak value.

[0104] Step 3: According to the unit speed information, process the flange clearance displacement value obtained in step 1, and remove the data when the wind turbine unit is stopped and the speed is less than 5r / 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). Specifically, the following steps are included:

[0105] Obtaining unit speed information: Considering that the prototype PLC data is not open, an additional inclination sensor is installed in the hub collection cabinet during this construction. The collected inclination data is filtered using digital filtering technology (median filtering) to remove noise and smooth the data. The number of identified peak data is 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 brackets; y(n) is the output signal after one-dimensional median filtering; n = 0, 1,…, N-1.

[0109] Peak data identification and speed conversion formula:

[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 data packet ends the spike data and the time when the data packet starts the spike data.

[0116] Considering the large amount of data, the present invention only takes 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 5r / min are eliminated.

[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 No. 7-3 displacement meter 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, 2024 - 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 value" in these four different time periods, and the comparison chart of "speed-displacement peak value" warning lines in these four different time periods ( Figure 7e ) and the three-dimensional curve (time-speed-peak-value) in the period from March 5 to July 19, 2024.

[0119] Step 5: Use the quartile method to remove abnormal values ​​from the "speed-displacement peak-to-peak" scatter plot obtained in step 4, so as to set 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 under the same speed state from small to large, and divide them into four equal parts using three division 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 abnormality. 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 in the normal state, 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 lines can be extracted and summarized to obtain Figure 7e , that is, the comparison chart of the warning line of displacement meter No. 7-3 of blade B in different time periods. Figure 7eIt can be seen that the warning lines are basically the same in each period, and the warning value increases with the increase of the speed. The slope, intercept and wind rotor speed range of the average warning line piecewise function expression are shown in Table 2:

[0133] Table 2B Parameter table of the piecewise function expression of the warning line of the displacement meter of blade 7-3 (2024 / 3 / 5-7 / 19)

[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, an alarm is triggered immediately. Figure 7e and Figure 8 It is judged that the warning lines obtained in different time periods are basically the same, indicating that the displacement change rules of the blade root bolts are basically the same, the blade root bolts are not loose, and the working state is normal. The on-site inspection personnel of the wind farm verified that there was no abnormality in the bolt state.

[0137] The present invention has been verified through wind field investigation, and it is found that the newly proposed vibration displacement monitoring method for blade root bolts of large wind turbines has reliable data, practical physical and engineering significance, and the method 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 present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present 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 embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal 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 generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. 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 capable of directing a computer or other programmable data processing device to operate 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 A 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 instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0142] Although the preferred embodiments of the present application have been described, those skilled in the art may make other 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 falling within the scope of the present application.

[0143] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also 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 flange gap displacement identification to obtain the flange gap displacement value; S2, processing the flange clearance displacement value obtained in step S1, extracting the displacement peak-to-peak value data, and extracting a displacement peak-to-peak value for each package of original displacement blocks; S3, processing the flange clearance displacement values ​​obtained in step S1 according to the unit speed information, and eliminating the data when the wind turbine unit is stopped and the speed is less than 5 r / min; 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; S5, removing abnormal values ​​from the speed-displacement peak-to-peak scatter plot obtained in step S4 by using the quartile method, and setting an effective warning line; S6, when the peak-to-peak value of the flange gap displacement continues to be above the warning line set in step S5 within a preset time range, an alarm is immediately triggered.

2. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 1 is characterized in that: Step S1 further comprises: Combine the unit blade design with wind field information to determine the blade root load condition; 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 the 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 5r / min needs to be eliminated.

4. The method for monitoring the vibration displacement of blade root bolts of large wind turbine blades according to claim 3 is 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 is characterized in that: In step S3, the process of acquiring 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 peak 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 where the peak-to-peak value of the flange gap displacement is less than the maximum estimated value in the normal state.

7. 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, 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 operation in combination with the quartile method, which specifically includes the following steps: Arrange the flange clearance displacement values ​​obtained under the same speed state from small to large, and divide them into four equal parts using three split points Q1, Q2 and Q3, each part contains 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: Minimum estimate = Q1-k(Q3-Q1) Maximum estimated value = Q3 + k (Q3 - Q1) 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 in the normal state, 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: f(x)=k i x+b i Wherein x is the wind 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 wind rotor speed.

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