A wind turbine tower overturning operation method, device and system

Abstract

The application discloses a wind turbine tower overturning operation and maintenance method, device and system, and the method comprises the following steps: collecting key parameters and conventional parameters of tower overturning; acquiring key parameter characteristic values of the key parameters; when the key parameter characteristic values exceed a preset safety threshold, comprehensively deciding, according to the key parameter characteristic values and the conventional parameters, to acquire diagnosis conclusion information and wind turbine control suggestions; and according to the key parameter characteristic values, the conventional parameters, the diagnosis conclusion information and the wind turbine control suggestions, performing health degree evaluation on the wind turbine tower and giving operation and maintenance suggestions. The method has clear logic, is safe, effective, reliable and easy to operate, can evaluate the health degree of the tower and give operation and maintenance suggestions to avoid the risk of wind turbine tower overturning. The device and the system have the same beneficial effects.

Description

Technical Field

[0001] This invention relates to the field of wind turbine tower safety technology, and in particular to a method, device and system for the operation and maintenance of wind turbine tower overturning. Background Technology

[0002] Currently, the tower height of most wind turbines is between 50 and 160 meters, and they are designed with either rigid steel cylinders or flexible towers. The tower itself bears complex and variable loads (thrust, bending moment, torque), and is also affected by weather and other conditions, causing the tower to undergo a certain degree of swaying and torsion. Collapse is easily caused by resonance due to blade stall, vortex-induced stress, or blade sweeping. In addition, under the action of external forces, if there are sudden stress changes at the tower weld points, failure of bolt connections, foundation settlement, etc., the tower may also tilt or even collapse.

[0003] In recent years, wind turbine collapses and blade-to-tower sweeps have frequently come into our view. Wind turbine collapses are major accidents. Industry insiders estimate that the direct economic losses from a wind turbine collapse, including the main unit, tower, foundation, and construction costs, are around 25-30 million yuan, while the electricity costs due to downtime or power limitation caused by the investigation of the wind farm accident are expected to reach 30 million yuan. These accidents not only cause huge economic losses but also bring serious safety hazards and liabilities, creating a significant impact on society.

[0004] Currently, with the increase in wind turbine height and tower flexibility, the challenge of monitoring the operational safety of wind turbine structures has become more prominent. The wind power industry focuses more on the tower's own condition during tower monitoring than on how to mitigate risks, prevent accidents, and curb the spread of fatigue damage. Current online tower monitoring systems still rely on traditional edge-based data acquisition, with ground-based data processing, presentation, and manual diagnostic analysis to provide maintenance recommendations. This approach suffers from high equipment costs, low accuracy of monitoring information, inability to form a real-time monitoring loop, poor timeliness, and limited diagnostic effectiveness. It fails to address the core concerns of users regarding wind turbine collapse prevention and tower condition-based maintenance.

[0005] Therefore, providing a wind turbine tower overturning operation and maintenance method, device, and system for assessing the health of the tower and providing operation and maintenance suggestions to avoid the risk of wind turbine tower overturning is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method, device, and system for the operation and maintenance of wind turbine tower overturning. This method is logically clear, safe, effective, reliable, and easy to operate. It can assess the health of the tower and provide operation and maintenance suggestions to avoid the risk of wind turbine tower overturning.

[0007] Based on the above objectives, the technical solution provided by the present invention is as follows:

[0008] A method for the operation and maintenance of wind turbine tower overturning includes the following steps:

[0009] Key and routine parameters of tower overturning were collected;

[0010] Real-time acquisition of the key parameter feature values;

[0011] When the key parameter characteristic value exceeds the preset safety threshold, a comprehensive decision is made based on the key parameter characteristic value and the conventional parameter to obtain diagnostic conclusion information and wind turbine control suggestions;

[0012] Based on the key parameter characteristic values, the conventional parameters, the diagnostic conclusion information, and the wind turbine control recommendations, a health assessment of the wind turbine tower is conducted, and operation and maintenance recommendations are provided.

[0013] Preferably, the key parameters for tower overturning include: tower acceleration characteristic value, tower tilt angle characteristic value, tower displacement characteristic value, tower modal frequency variation and amplitude characteristic value, as well as tower astronomical direction and tower tilt azimuth characteristic value.

[0014] Preferably, before obtaining the key parameter feature values, the method further includes: preprocessing the key parameters;

[0015] The preprocessing methods specifically include:

[0016] Error adjustment, quadratic fitting temperature drift coefficient compensation, and replacement of one or more conventional gravitational accelerations with the local gravitational acceleration of the tower:

[0017] The key parameters are preprocessed in the manner described above to obtain the corrected key parameters.

[0018] Preferably, obtaining the tower acceleration characteristic value includes the following steps:

[0019] The corrected key parameters are converted into acceleration data;

[0020] The acceleration data is filtered and anisotropically processed within a preset frequency range;

[0021] Based on the filtered acceleration data and the first preset formula, the acceleration characteristic value of the tower is obtained.

[0022] Preferably, obtaining the characteristic value of the tower tilt angle includes the following steps:

[0023] The corrected key parameters are converted into acceleration data;

[0024] Calculate the gravitational acceleration values ​​for the X-axis, Y-axis, and Z-axis data respectively;

[0025] Obtain the mean gravitational acceleration along the X-axis, Y-axis, and Z-axis;

[0026] The characteristic value of the tower tilt angle is obtained based on the average gravitational acceleration along the X-axis, the average gravitational acceleration along the Y-axis, the average gravitational acceleration along the Z-axis, and the second preset formula.

[0027] The corrected key parameters include: the X-axis data, the Y-axis data, and the Z-axis data.

[0028] Preferably, obtaining the tower displacement characteristic value includes the following steps:

[0029] The corrected key parameters are converted into acceleration data;

[0030] The average acceleration value is obtained based on the acceleration data;

[0031] The static displacement value is obtained based on the tower height, the preset deflection coefficient, the average acceleration value, and the third preset formula.

[0032] The dynamic displacement value is obtained from the multiple integral of the acceleration data;

[0033] The tower displacement characteristic value is obtained based on the static displacement value, the dynamic displacement value, and the fourth preset formula;

[0034] The conventional parameters include: the tower height;

[0035] The corrected key parameters include: the X-axis data, the Y-axis data, and the Z-axis data.

[0036] Preferably, obtaining the tower modal frequency variation and amplitude characteristic values ​​includes the following steps:

[0037] The corrected key parameters are converted into acceleration data;

[0038] After bandpass filtering the X-axis and Z-axis data, FFT processing is performed to obtain the actual modal frequency values;

[0039] The tower modal frequency change is obtained based on the actual modal frequency value and the preset theoretical modal frequency value;

[0040] Obtain the spectral amplitude based on the actual modal frequency spectral lines;

[0041] Based on the spectral line amplitude, the acceleration amplitude characteristic value is obtained;

[0042] The corrected key parameters include: the X-axis data, the Y-axis data, and the Z-axis data;

[0043] The actual modal spectral lines are obtained from the actual modal frequency values.

[0044] Preferably, obtaining the astronomical orientation and tilt azimuth characteristic values ​​of the tower includes the following steps:

[0045] The corrected key parameters are converted into astronomical orientation information corresponding to the sensor installation location;

[0046] Based on the X-axis data, the Y-axis data, and the Z-axis data, and the tower tilt angle feature value, obtain the tower tilt azimuth feature value;

[0047] The corrected key parameters include: X-axis data of the three-dimensional magnetoresistive data, Y-axis data of the three-dimensional magnetoresistive data, and Z-axis data of the three-dimensional magnetoresistive data.

[0048] The standard parameters include: the sensor installation location.

[0049] Preferably, when the key parameter characteristic value exceeds a preset safety threshold, the wind turbine tower is in an abnormal state;

[0050] When the key parameter characteristic value exceeds a preset safety threshold, the process of making a comprehensive decision based on the key parameter characteristic value and the conventional parameters to obtain diagnostic conclusion information and wind turbine control suggestions includes the following steps:

[0051] Based on the abnormal state of the wind turbine tower, extract the key parameter feature values ​​and the conventional parameters corresponding to the abnormal state;

[0052] Based on the key parameter feature values ​​and the conventional parameters, comprehensive decision-making information is obtained;

[0053] The corresponding wind turbine control recommendations are invoked based on the comprehensive decision information.

[0054] A wind turbine tower overturning maintenance device includes:

[0055] The data acquisition module is used to collect key and routine parameters of the tower overturning.

[0056] The feature extraction module is used to obtain the key parameter feature values ​​of the key parameters;

[0057] The decision and suggestion module is used to obtain comprehensive decision information and wind turbine control suggestions based on the key parameter feature value and the regular parameter when the key parameter feature value exceeds the preset safety threshold.

[0058] The health assessment and operation and maintenance module is used to assess the health of the wind turbine tower and provide operation and maintenance recommendations based on the key parameters, the routine parameters, the comprehensive decision information and the wind turbine control recommendations.

[0059] A wind turbine tower overturning operation and maintenance system includes: a tower overturning monitoring device, a wind turbine main control PLC, and a health assessment and operation and maintenance device;

[0060] The wind turbine main control PLC is connected to the tower overturning monitoring device;

[0061] The health assessment and maintenance equipment includes: a ground server and a PoE switch;

[0062] The PoE switch is connected to both the wind turbine main control PLC and the ground server.

[0063] The ground server is connected to both the PoE switch and the tower overturning monitoring device.

[0064] Preferably, the health assessment and maintenance device includes: a SCADA server;

[0065] The SCADA server is connected to the tower overturning monitoring device and the wind turbine main control PLC, respectively.

[0066] This invention provides a method for the operation and maintenance of wind turbine tower overturning. Specifically, it involves collecting key and conventional parameters of tower overturning; extracting features from the key parameters to obtain their feature values; when the feature values ​​of the key parameters exceed a preset safety threshold, obtaining comprehensive decision-making information and wind turbine control suggestions based on the key parameter feature values ​​and conventional parameters; and conducting a health assessment of the tower by integrating the key parameters, conventional parameters, comprehensive decision-making information, and wind turbine control suggestions, and providing operation and maintenance recommendations to the staff.

[0067] This invention addresses the issue of wind turbine tower overturning risks when key parameter characteristic values ​​exceed preset safety thresholds, indicating a dangerous abnormal state. It integrates key parameter characteristic values ​​and conventional parameters to obtain comprehensive decision-making information and provide wind turbine control recommendations. At this point, staff control the wind turbine based on the comprehensive decision-making information and wind turbine control recommendations, thereby avoiding the risk of wind turbine overturning. After avoiding the risk of wind turbine overturning, a health assessment of the wind turbine tower is conducted based on key parameters, conventional parameters, comprehensive decision-making information, and wind turbine control recommendations, and operation and maintenance recommendations are provided. Staff then perform adaptive operation and maintenance on the wind turbine tower based on the health assessment results to prevent the same overturning risk from recurring. Compared to existing technologies, this invention provides corresponding recommendations and solutions both when the wind turbine is in a dangerous abnormal state and after the risk of wind turbine overturning has been avoided. This allows staff to address the pain point of tower overturning based on the recommendations and solutions, effectively avoiding the risk of tower overturning.

[0068] The present invention also discloses a wind turbine tower overturning operation and maintenance device and system. Since the device and system and the method solve the same technical problems and belong to the same technical concept, they should have the same beneficial effects, and will not be described in detail here. Attached Figure Description

[0069] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0070] Figure 1 A flowchart of a wind turbine tower overturning operation and maintenance method provided by the present invention;

[0071] Figure 2 This is a flowchart illustrating the process of obtaining the tower acceleration characteristic value in step S2 of an embodiment of the present invention;

[0072] Figure 3 This is a flowchart illustrating the process of obtaining the tower tilt angle feature value in step S2 of this embodiment of the invention.

[0073] Figure 4 This is a flowchart of step S2 for obtaining the tower displacement characteristic value provided in an embodiment of the present invention;

[0074] Figure 5 This is a flowchart of step S2 for obtaining the tower modal frequency change and amplitude characteristic value provided in an embodiment of the present invention;

[0075] Figure 6 This is a flowchart of step S2 of the present invention for obtaining the astronomical direction and tilt azimuth feature values ​​of the tower.

[0076] Figure 7 A flowchart of step S3 provided in an embodiment of the present invention;

[0077] Figure 8 This is a structural schematic diagram of a wind turbine tower overturning maintenance device provided by the present invention;

[0078] Figure 9 This is a structural schematic diagram of a wind turbine tower overturning maintenance system provided by the present invention. Detailed Implementation

[0079] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0080] The embodiments of this invention are written in a progressive manner.

[0081] This invention provides a method, apparatus, and system for the operation and maintenance of wind turbine tower overturning. It primarily addresses the technical problems of poor overturning prevention and tower condition-based operation and maintenance in existing technologies.

[0082] like Figure 1 As shown, a method for the operation and maintenance of wind turbine tower overturning includes the following steps:

[0083] S1. Collect key and routine parameters of tower overturning;

[0084] S2. Real-time acquisition of key parameter feature values;

[0085] S3. When the key parameter characteristic value exceeds the preset safety threshold, make a comprehensive decision based on the key parameter characteristic value and the regular parameters to obtain diagnostic conclusion information and fan control suggestions;

[0086] S4. Based on the key parameter characteristic values, routine parameters, diagnostic conclusions and wind turbine control recommendations, conduct a health assessment of the wind turbine tower and provide operation and maintenance recommendations.

[0087] In step S1, key and conventional parameters that caused the tower to overturn were collected by sensors;

[0088] It should be noted that the standard parameters include: tower height, installation location of the device sensors, and operating condition information characteristics, which include, but are not limited to, the following:

[0089]

[0090]

[0091] In step S2, feature values ​​are extracted from various key parameters in different ways to obtain multiple key parameter feature values;

[0092] In step S3, when the key parameter characteristic value exceeds the preset safety threshold, a comprehensive decision is made based on the acquired key parameter characteristic values ​​and conventional parameters to obtain diagnostic conclusion information and wind turbine control suggestions; the staff refers to the acquired diagnostic conclusion information and wind turbine control suggestions to control the wind turbine, thereby avoiding the risk of wind turbine overturning;

[0093] In step S4, after the risk is eliminated, a health assessment of the wind turbine tower is conducted based on the key parameter characteristic values, routine parameters, diagnostic conclusions, and wind turbine control recommendations, and operation and maintenance recommendations are provided. Staff then refer to the health assessment and operation and maintenance recommendations to conduct adaptive operation and maintenance of the wind turbine tower to prevent the risk of wind turbine overturning from recurring.

[0094] Preferably, the key parameter characteristic values ​​for tower overturning include: tower acceleration characteristic value, tower tilt angle characteristic value, tower displacement characteristic value, tower modal frequency variation and amplitude characteristic value, as well as tower astronomical direction and tower tilt azimuth characteristic value.

[0095] In practical applications, key parameters related to tower overturning include: tower acceleration, tower tilt angle, tower displacement, tower modal frequency variation and amplitude, as well as the tower's astronomical orientation and tilt azimuth. The methods for extracting feature values ​​for each key parameter differ, and different methods are used to extract the feature values ​​of the corresponding key parameters.

[0096] Preferably, before step S2, the method further includes: preprocessing key parameters;

[0097] Preprocessing methods specifically include:

[0098] Error adjustment, quadratic fitting temperature drift coefficient compensation, and replacement of one or more conventional gravitational accelerations with the local gravitational acceleration of the tower:

[0099] The key parameters are preprocessed in the manner described above to obtain the corrected key parameters.

[0100] In practical applications, key parameters can be collected using a triaxial MEMS accelerometer, and the installation and manufacturing errors of the collected key parameters can be zeroed. Alternatively, key parameters can be compensated through conventional temperature quadratic fitting. Or, one or more of the following methods can be used to obtain the corrected key parameters by replacing the standard gravitational acceleration with the local gravitational acceleration obtained from the latitude and longitude data table of the location where the wind turbine tower is installed.

[0101] like Figure 2 As shown, preferably, obtaining the tower acceleration characteristic value in step S2 includes the following steps:

[0102] A1. Convert the corrected key parameters into acceleration data;

[0103] A2. Filter and perform outlier processing on the acceleration data within a preset frequency range;

[0104] A3. Based on the filtered acceleration data and the first preset formula, obtain the tower acceleration characteristic value.

[0105] In step A1, the voltage data after error removal, compensation, and correction are converted into acceleration data;

[0106] In step A2, after setting the frequency range, the acceleration data is filtered and anomaly processing is performed within the frequency range;

[0107] It should be noted that outlier handling refers to the use of algorithms to identify and process acceleration data that exceeds the theoretical range or shows significant jumps, in order to avoid misjudgment.

[0108] In step A3, data samples are extracted from the filtered acceleration data, and the tower acceleration characteristic value X is calculated according to the first preset formula. rms ;

[0109] The first preset formula is as follows:

[0110]

[0111] Where i is the number of sampling points, Xi is the amplitude of the i-th sampling point, and N is the number of data points.

[0112] like Figure 3 As shown, preferably, obtaining the tower tilt angle characteristic value in step S2 includes the following steps:

[0113] B1. Convert the corrected key parameters into acceleration data;

[0114] B2. Calculate the gravitational acceleration values ​​for the X-axis, Y-axis, and Z-axis data respectively;

[0115] B3. Obtain the mean gravitational acceleration along the X-axis, Y-axis, and Z-axis;

[0116] B4. Based on the average gravitational acceleration along the X-axis, the average gravitational acceleration along the Y-axis, and the average gravitational acceleration along the Z-axis, and the second preset formula, obtain the characteristic value of the tower tilt angle;

[0117] The key parameters after correction include: X-axis data, Y-axis data, and Z-axis data.

[0118] In step B1, the X-axis, Y-axis, and Z-axis data in the corrected voltage data are converted into acceleration data;

[0119] In step B2, the gravitational acceleration values ​​are calculated for the X-axis acceleration data, Y-axis acceleration data, and Z-axis acceleration data, respectively.

[0120] In steps B3 and B4, the tilt angle characteristic value is calculated by combining the average values ​​in the X-axis, Y-axis and Z-axis directions with the second preset formula (i.e., the formula for trigonometric functions and deflection coefficients).

[0121] It should be noted that the principle of tilt angle feature value extraction is based on the fact that the accelerometer is subjected to gravity when placed at rest, and therefore has a gravitational acceleration of 1g. Using this property, by measuring the components of gravitational acceleration on the X / Y axes, the tilt angle in the vertical plane can be calculated.

[0122] In this embodiment, as shown in the figure, we have Ax = gsinα and Ay = gcosα. Therefore, Ax / Ay = tanα, that is, α = arctan(Ax / Ay).

[0123] Based on the above principle, the tilt angle on the XY plane can be measured using a two-axis accelerometer.

[0124] However, in practical applications, it is difficult to guarantee that the tilt only occurs in the XY plane. Therefore, the tilt angle calculation formula using a triaxial sensor is as follows:

[0125] The above formula basically solves the calculation of static tilt angle under static conditions. Now, let's consider a more complex scenario: calculating the dynamic tilt angle under moving conditions. This requires adding another constraint, as shown in the following formula:

[0126]

[0127] like Figure 4 As shown, preferably, obtaining the tower displacement characteristic value in step S2 includes the following steps:

[0128] C1. Convert the corrected key parameters into acceleration data;

[0129] C2. Obtain the mean acceleration value based on the acceleration data;

[0130] C3. Obtain the static displacement value based on the tower height, preset deflection coefficient, average acceleration, and the third preset formula;

[0131] C4. Obtain the dynamic displacement value from the multiple integral of the acceleration data;

[0132] C5. Obtain the tower displacement characteristic value based on the static displacement value, dynamic displacement value, and the fourth preset formula;

[0133] Among the standard parameters are: tower height;

[0134] The key parameters after correction include: X-axis data, Y-axis data, and Z-axis data.

[0135] In step C1, the X-axis, Y-axis, and Z-axis data of the voltage data after error removal, compensation, and correction are converted into acceleration data.

[0136] In step C2, the acceleration data are averaged to obtain the mean acceleration α. 均 ;;

[0137] In step C3, the static displacement value is calculated based on the preset known tower height, deflection coefficient, and average acceleration value, as well as the third preset formula.

[0138] In this embodiment, the third preset formula is as follows: S X =H×sin(arcsin(α) 均 () × deflection coefficient) × 1000;

[0139] Where H is the tower height, and the deflection coefficient is the specific tower deformation coefficient obtained by simulation or theoretical calculation of the installation position of the wind turbine tower overturning monitoring device.

[0140] In step C4, the mean acceleration α 均 Perform multiple integrations to extract the dynamic displacement (amplitude) value S. z ;

[0141] In step C5, based on the static displacement value S X and dynamic displacement value S Z And the fourth preset formula is used to calculate and obtain the tower displacement characteristic value S;

[0142] In this embodiment, the fourth preset formula is as follows:

[0143] like Figure 5 As shown, preferably, the step S2 of obtaining the tower modal frequency change and amplitude characteristic value includes the following steps:

[0144] D1. Convert the corrected key parameters into acceleration data;

[0145] D2. After bandpass filtering the X-axis and Z-axis data, perform FFT processing to obtain the actual modal frequency values;

[0146] D3. Obtain the tower modal frequency changes based on the actual modal frequency values ​​and the preset theoretical modal frequency values;

[0147] D4. Obtain the spectral amplitude based on the actual modal frequency spectral lines;

[0148] D5. Obtain the characteristic values ​​of acceleration amplitude based on the spectral line amplitudes;

[0149] The key parameters after correction include: X-axis data and Z-axis data;

[0150] The actual modal spectrum lines are obtained from the actual modal frequency values.

[0151] In step D1, the X-axis and Z-axis data of the voltage data after error removal, compensation, and correction are converted into acceleration data;

[0152] In step D2, the X-axis acceleration data and Z-axis acceleration data are bandpass filtered and then processed by FFT to obtain the actual modal frequency values.

[0153] It should be noted that the Fast Fourier Transform (FFT) is a general term for efficient and fast computation methods that use computers to calculate the Discrete Fourier Transform (DFT). FFT can be basically divided into two categories: time-decimation methods and frequency-decimation methods. However, general time-decimation and frequency-decimation methods can only handle lengths of N = 2M. Additionally, there is the Combinatoric Radix-4 FFT to handle FFTs of general lengths.

[0154] In step D3, the deviation value is obtained based on the actual modal frequency value and the preset theoretical modal frequency value. The deviation value represents the change in the tower modal frequency.

[0155] In step D4, the actual modal spectrum line is obtained based on the actual modal frequency value, and then the spectrum line amplitude is obtained based on the actual modal frequency spectrum line.

[0156] In step D5, the obtained spectral amplitude is converted into acceleration amplitude.

[0157] In practical applications, if further subdivision is required, the deviations and values ​​of forward / backward, pitch, torsion, and higher-order modal frequencies can be extracted.

[0158] like Figure 6 As shown, preferably, the step S2 of obtaining the astronomical direction and tilt azimuth characteristic values ​​of the tower includes the following steps:

[0159] E1. Convert the corrected key parameters into astronomical orientation information corresponding to the sensor installation location;

[0160] E2. Based on the X-axis data, Y-axis data, and Z-axis data and the tower tilt angle characteristic value, obtain the tower tilt azimuth characteristic value;

[0161] The key parameters after correction include: X-axis data, Y-axis data, and Z-axis data of the three-dimensional magnetoresistive data.

[0162] Common parameters include: sensor installation location.

[0163] In step E1, the key parameters after correction are obtained from the three-dimensional magnetoresistive positioning chip. The X-axis magnetoresistive data, Y-axis magnetoresistive data and Z-axis magnetoresistive data are compared with the sensor installation position to obtain the astronomical direction information corresponding to the sensor installation position.

[0164] In step E2, the X-axis magnetoresistive data, Y-axis magnetoresistive data, and Z-axis magnetoresistive data are combined with the tower tilt angle feature value obtained in the previous step to obtain the tower tilt azimuth feature value.

[0165] In this embodiment, the three-dimensional magnetoresistive positioning chip uses three mutually perpendicular magnetoresistive devices to measure the tower's tilt orientation. Each axial magnetoresistive device detects the geomagnetic field strength in that direction. A magnetoresistive device installed facing due east (or a predetermined direction, referred to as the X-direction) detects the vector value of the geomagnetic field in the X-direction; a magnetoresistive device installed facing due north (or a predetermined direction) detects the vector value of the geomagnetic field in the Y-direction; and magnetoresistive devices installed vertically detect the vector value of the geomagnetic field in the Z-direction. Because the tower will tilt at an angle when the sensors are installed on a non-horizontal plane during wind turbine operation, the tower's tilt orientation is corrected using the tilt angle calculated from the triaxial acceleration and gravitational acceleration values.

[0166] like Figure 7 As shown, preferably, when the key parameter characteristic value exceeds the preset safety threshold, the wind turbine tower is in an abnormal state;

[0167] Step S3 includes the following steps:

[0168] F1. Based on the abnormal state of the wind turbine tower, extract the key parameter feature values ​​and conventional parameters corresponding to the abnormal state;

[0169] F2. Obtain comprehensive decision-making information based on key parameter characteristic values ​​and conventional parameters;

[0170] F3. Based on the comprehensive decision-making information, call upon the corresponding wind turbine control suggestions.

[0171] In step F1, key parameter feature values ​​and conventional parameters are extracted for each abnormal state. For example, key parameter feature values ​​and conventional parameters of tower resonance are extracted through vortex-induced oscillation principal elements, key parameter feature values ​​and conventional parameters of blade stall are extracted through tower monitoring principal elements, and key parameter feature values ​​and conventional parameters of faults such as tower cracks and tower loosening are extracted through fault principal elements.

[0172] It should be noted that, except for the large acceleration caused by blade stall, vortex-induced resonance, or blade sweeping, the vibration value of the tower during normal operation is within 5mg (rms) [industry standard: 3mg (rms) for over-limit warning and 5mg (rms) for alarm]. Therefore, the triaxial MEMS accelerometer needs to have high precision, low noise, and AD conversion ≥20 bits, and the analog-to-digital conversion setting should be aliased to ensure the accuracy of the monitoring data.

[0173] In step F2, based on the corresponding key parameter feature values ​​and conventional parameters, corresponding decision information is given based on neural network and / or statistics.

[0174] In step F3, the corresponding wind turbine control suggestion information is invoked based on the decision information. That is, the wind turbine control method A should be used for tower resonance, the wind turbine control method B should be used for blade loss, and the wind turbine control method C should be used for tower failure.

[0175] like Figure 8 As shown, a wind turbine tower overturning maintenance device includes:

[0176] The data acquisition module is used to collect key and routine parameters of the tower overturning.

[0177] The feature extraction module is used to obtain the feature values ​​of key parameters.

[0178] The decision and suggestion module is used to obtain comprehensive decision information and wind turbine control suggestions based on the key parameter characteristic values ​​and regular parameters when the key parameter characteristic values ​​exceed the preset safety threshold.

[0179] The health assessment and operation and maintenance module is used to assess the health of wind turbine towers and provide operation and maintenance recommendations based on key parameters, routine parameters, comprehensive decision-making information and wind turbine control suggestions.

[0180] This invention also discloses a wind turbine tower overturning operation and maintenance device, which includes a data acquisition module, a feature extraction module, a decision-making and suggestion module, and a health assessment and operation and maintenance module. During operation, the data acquisition module collects key and routine parameters related to tower overturning and sends the key parameters to the feature extraction and health assessment and operation and maintenance modules, while sending the routine parameters to these modules. The feature extraction module extracts the key parameter feature values ​​and sends them to the decision-making and suggestion module. When the key parameter feature value exceeds a preset safety threshold, the decision-making and suggestion module obtains comprehensive decision information and corresponding wind turbine control suggestions based on the key parameter feature value and routine parameters, and sends these to the health assessment and operation and maintenance module. The health assessment and operation and maintenance module assesses the health of the wind turbine tower based on the key parameters, routine parameters, comprehensive decision information, and wind turbine control suggestions, and provides corresponding operation and maintenance suggestions.

[0181] like Figure 9 As shown, a wind turbine tower overturning operation and maintenance system includes: a tower overturning monitoring device, a wind turbine main control PLC, and a health assessment and operation and maintenance device;

[0182] The wind turbine's main control PLC is connected to the tower overturning monitoring device;

[0183] Health assessment and maintenance equipment includes: ground server and PoE switch;

[0184] The PoE switch is connected to both the wind turbine's main control PLC and the ground server.

[0185] The ground server is connected to the PoE switch and the tower overturning monitoring device, respectively.

[0186] Preferably, the health assessment and maintenance device includes: a SCADA server;

[0187] The SCADA server is connected to both the tower overturning monitoring device and the wind turbine main control PLC.

[0188] This invention also discloses a wind turbine tower overturning maintenance system, which includes a tower overturning monitoring device, a wind turbine main control PLC, and a health assessment and maintenance device. The wind turbine main control PLC is connected to the tower overturning monitoring device. The health assessment module and maintenance device have two implementation methods: The first includes a ground server and a PoE switch; the PoE switch is connected to both the wind turbine main control PLC and the ground server; the ground server is connected to both the PoE switch and the tower overturning monitoring device. The second method includes a SCADA server, which is connected to both the tower overturning monitoring device and the wind turbine main control PLC.

[0189] In the embodiments provided in this application, it should be understood that the disclosed methods, apparatus, and systems can be implemented in other ways. The apparatus and system embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, and can be electrical, mechanical, or other forms.

[0190] Furthermore, in the various embodiments of the present invention, each functional module can be fully integrated into a processor, or each module can be a separate device, or two or more modules can be integrated into a device; each functional module in the various embodiments of the present invention can be implemented in hardware or in the form of hardware plus software functional units.

[0191] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by program instructions and related hardware. The aforementioned program instructions can be stored in a computer-readable storage medium. When the program instructions are executed, they perform the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0192] It should be understood that the use of terms such as "system," "device," "unit," and / or "module" in this application is merely one method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0193] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "a," and / or "the" are not specifically singular and may include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements. An element defined by the phrase "comprising an..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes the element.

[0194] In the description of the embodiments of this application, unless otherwise stated, " / " means "or", for example, A / B can mean A or B; "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more.

[0195] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0196] If a flowchart is used in this application, it is used to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0197] The foregoing provides a detailed description of a wind turbine tower overturning maintenance method, apparatus, and system provided by the present invention. The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A wind turbine tower overturning operation method, characterized in that, The method comprises the following steps: Collecting key parameters and conventional parameters of tower overturning; Real-time acquisition of key parameter characteristic values of the key parameters; When the key parameter characteristic values exceed the preset safety threshold, according to the key parameter characteristic values and the conventional parameters, comprehensive decision is made to obtain diagnostic conclusion information and fan control suggestions; According to the key parameter characteristic values, the conventional parameters, the diagnostic conclusion information and the fan control suggestions, the health degree of the wind turbine tower is evaluated and operation and maintenance suggestions are given; The key parameter characteristic values of the tower overturning include a tower displacement characteristic value; Before the key parameter characteristic values of the key parameters are acquired, the key parameters are preprocessed; The preprocessing mode specifically includes one or more of the following: Adjusting error, secondary fitting temperature drift coefficient compensation, and replacing conventional gravity acceleration with local gravity acceleration of the tower; The key parameters are preprocessed in the above manner to obtain corrected key parameters; Acquiring the tower displacement characteristic value comprises the following steps: Converting the corrected key parameters into acceleration data; Acquiring acceleration mean values according to the acceleration data; Acquiring static displacement values according to the tower height, a preset deflection coefficient, the acceleration mean values and a third preset formula; From the double integration of the acceleration data, dynamic displacement values are acquired; According to the static displacement values, the dynamic displacement values and a fourth preset formula, the tower displacement characteristic value is acquired; The conventional parameters include the tower height; The corrected key parameters include X-axis data, Y-axis data and Z-axis data; The third preset formula is as follows: ; wherein H is the height of the tower, is the average acceleration, is the static displacement value.

2. The wind turbine tower overturning method of claim 1, wherein, The key parameter characteristic values of the tower overturning further include a tower acceleration characteristic value, a tower inclination angle characteristic value, a tower modal frequency change and amplitude characteristic value, and a tower astronomical direction and tower inclination azimuth characteristic value.

3. The wind turbine tower method of claim 2, wherein, Acquiring the tower acceleration characteristic value comprises the following steps: Converting the corrected key parameters into acceleration data; Filtering and outlier processing the acceleration data within a preset frequency range; According to the filtered acceleration data and a first preset formula, the tower acceleration characteristic value is acquired.

4. The wind turbine tower method of claim 2, wherein, Acquiring the tower inclination angle characteristic value comprises the following steps: Converting the corrected key parameters into acceleration data; Respectively calculating gravity acceleration values of X-axis data, Y-axis data and Z-axis data; Acquiring gravity acceleration mean values of X-axis, Y-axis and Z-axis; According to the gravity acceleration mean values of X-axis, Y-axis and Z-axis and a second preset formula, the tower inclination angle characteristic value is acquired; The corrected key parameters include the X-axis data, the Y-axis data and the Z-axis data.

5. The wind turbine tower method of claim 2, wherein, Acquiring the tower modal frequency change and amplitude characteristic value comprises the following steps: Converting the corrected key parameters into acceleration data; After band-pass filtering the X-axis data and the Z-axis data, FFT processing is performed to acquire actual modal frequency values; According to the actual modal frequency values and preset theoretical modal frequency values, the tower modal frequency change is acquired; According to the actual modal frequency spectrum line, a spectrum line amplitude is acquired; According to the spectrum amplitude, an acceleration amplitude characteristic value is obtained; The corrected key parameters include the X-axis data and the Z-axis data. The actual modal frequency spectrum line is obtained from the actual modal frequency value.

6. The wind turbine tower method of claim 2, wherein, Obtaining a tower cylinder astronomical direction and a tower cylinder tilt azimuth characteristic value, including the following steps: Converting the corrected key parameters into astronomical direction information corresponding to the sensor installation position; According to the X-axis data, the Y-axis data, and the Z-axis data and the tower cylinder tilt angle characteristic value, a tower cylinder tilt azimuth characteristic value is obtained; The corrected key parameters include the X-axis data, the Y-axis data, and the Z-axis data of the three-dimensional magnetic resistance. The conventional parameters include the sensor installation position.

7. The wind turbine tower method of claim 2, wherein, When the key parameter characteristic value exceeds the preset safety threshold, the wind turbine tower cylinder is in an abnormal state; When the key parameter characteristic value exceeds the preset safety threshold, according to the key parameter characteristic value and the conventional parameters, comprehensive decision information and wind turbine control suggestions are obtained, including the following steps: According to the abnormal state of the wind turbine tower cylinder, the key parameter characteristic value and the conventional parameters corresponding to the abnormal state are extracted; According to the key parameter characteristic value and the conventional parameters, comprehensive decision information is obtained; According to the comprehensive decision information, the corresponding wind turbine control suggestions are called.

8. A wind turbine tower overturning operation device, characterized in that, Applied to the wind turbine tower cylinder overturning operation and maintenance method of claim 1, including: A collection module for collecting key parameters and conventional parameters of tower cylinder overturning; A feature extraction module for obtaining a key parameter characteristic value of the key parameters; A decision and suggestion module for obtaining comprehensive decision information and wind turbine control suggestions according to the key parameter characteristic value and the conventional parameters when the key parameter characteristic value exceeds the preset safety threshold; A health degree evaluation and operation and maintenance module for evaluating the health degree of the wind turbine tower cylinder according to the key parameters, the conventional parameters, the comprehensive decision information, and the wind turbine control suggestions and giving operation and maintenance suggestions.

9. A wind turbine tower overturning maintenance system, characterized in that, Including: The wind turbine tower cylinder overturning monitoring device, the wind turbine main control PLC, and the health degree evaluation and operation and maintenance device of claim 8; The wind turbine main control PLC is connected with the tower cylinder overturning monitoring device; The health degree evaluation and operation and maintenance device includes a ground server and a POE switch; The POE switch is connected with the wind turbine main control PLC and the ground server respectively; The ground server is connected with the POE switch and the tower cylinder overturning monitoring device respectively.

10. The wind turbine tower de-rotation system of claim 9, wherein, The health degree evaluation and operation and maintenance device includes a SCADA server; The SCADA server is connected with the tower cylinder overturning monitoring device and the wind turbine main control PLC respectively.

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