Wind power tower inclination monitoring system and method based on Beidou III attitude measurement

Abstract

The invention discloses a wind power tower inclination monitoring system based on Beidou III attitude measurement. The wind power tower inclination monitoring system comprises a Beidou III satellite antenna, a Beidou III receiver and a remote server, a wind power tower inclination monitoring method based on Beidou III attitude measurement comprises the following steps that firstly, a Beidou III receiver receives a radio frequency carrier signal of a satellite, analyzes data such as a carrier phase value and the like, and sends the data to a remote network server; then constructing a wind power tower attitude angle mathematical model on the server side based on the data; an improved chaos game algorithm is designed to solve attitude angles (an elevating angle and an azimuth angle) in the mathematical model; and finally, converting the gradient of the wind power tower drum through the elevation angle. The method has the advantages of being convenient to deploy, free of system errors and the like, and has wide application prospects.

Description

Technical Field

[0001] The present invention relates to the field of Beidou navigation technology, and in particular to a wind power tower inclination monitoring system and method based on Beidou III attitude measurement. Background Art

[0002] Factors such as geological activities, extreme weather and improper human operation often cause wind turbine tower structures to tilt or even collapse. These events may not only pose a threat to personnel safety, but also bring huge economic losses. In serious cases, they may affect the stable operation of the entire power grid. In order to ensure the reliability of the wind power system, it is crucial to accurately control the inclination of the wind turbine tower. If it exceeds the specified safe inclination parameter range, not only timely alarms are required, but also corresponding maintenance measures must be taken as soon as possible. Therefore, establishing an accurate, automated and intelligent wind turbine tower inclination monitoring system is an urgent need in the industry.

[0003] The current methods for monitoring wind turbine tower tilt are mainly divided into the following categories:

[0004] 1. Manual visual inspection: This is the most traditional method, relying on inspectors to regularly check the tilt status of the tower. This method is not only time-consuming and labor-intensive, but also unable to achieve real-time monitoring and early warning.

[0005] 2. Tilt sensor detection: This method measures the tilt angle of the tower through a tilt sensor installed on the tower. Although this method can be automated, it usually only provides partial information and is limited by the accuracy and stability of the sensor.

[0006] 3. Monitoring based on the Global Positioning System (GPS): By installing a GPS receiver on the tower, the change in its spatial position can be calculated, thereby inferring the inclination of the tower. Although this method is more accurate, it has high construction and maintenance costs, especially when a complex reference station network needs to be built or used.

[0007] In view of the limitations of the above methods, it is crucial for the long-term development of the wind energy industry to develop a comprehensive, low-cost and efficient tilt monitoring system that can continuously monitor the real-time tilt status of wind turbine towers and accurately warn of potential risks in the first time. Summary of the invention

[0008] The purpose of the present invention is to solve the shortcomings of the prior art and propose a wind turbine tower inclination monitoring system and method based on Beidou III attitude measurement. Its advantage is that it can conveniently, accurately and automatically monitor the inclination of the wind turbine tower, thereby solving the shortcomings of the existing methods and improving the technical level in this field.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] The wind turbine tower inclination monitoring system based on BeiDou III attitude measurement includes two BeiDou III satellite antennas, BeiDou III receivers and a remote network server;

[0011] The two BeiDou III satellite antennas include antenna A and antenna B, which are respectively placed at the top of the wind turbine tower, and a straight line segment connecting the two antennas is defined as a baseline J; antenna A and antenna B receive radio frequency carrier signals and send them to a BeiDou III receiver;

[0012] The BeiDou III receiver is composed of BeiDou board A', BeiDou board B' and a wireless communication module; board A' and board B' are connected to antenna A and antenna B respectively, and analyze the RF carrier signal received by antenna A and antenna B to obtain the carrier phase The satellite altitude angle H and satellite azimuth angle P are finally sent to the remote network server through the wireless communication module;

[0013] The remote network server receives the carrier phase The satellite elevation angle H and the satellite azimuth angle P are substituted into the mathematical model of the attitude angle of the tower baseline J, and the improved chaotic game algorithm is used to solve it, so as to obtain the attitude angle of the baseline J, and then obtain the inclination of the wind turbine tower.

[0014] The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement includes the following steps:

[0015] Step 1: Let the projection of baseline J on the horizontal plane be J', define the angle between projection J' and the true north direction as the heading angle α of baseline J, and the value range of heading angle α is 0 to 360 degrees; define the angle between baseline J and projection J' as the pitch angle β of baseline J, and the value range of pitch angle β is -90 to +90 degrees; receive and analyze the RF carrier signal of Beidou III satellite; antenna A and antenna B respectively receive the RF carrier signals of m epochs of n Beidou III satellites, n≥4, m≥4, and send them to Beidou receiver;

[0016] BeiDou board A' and BeiDou board B' analyze the RF carrier signals received by antenna A and antenna B respectively, and obtain the carrier phase, satellite altitude angle and satellite azimuth angle of m epochs of n BeiDou III satellites, which are recorded as in, and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board A';

[0017] and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board B';

[0018] Step 2: Establish a mathematical model of the attitude angle of the baseline J on the tower;

[0019] Obtain the carrier phase single difference equation; calculate the carrier phase difference between antenna A and antenna B at the i-th satellite at the k-th epoch Calculate the carrier phase difference between antenna A and antenna B at the jth satellite at the kth epoch Calculate the double difference of carrier phase; establish the mathematical model of attitude angle of baseline J;

[0020] Step 3: Propose an improved chaotic game algorithm to solve the mathematical model and obtain the attitude angle of the baseline J;

[0021] The search space of the improved chaotic game algorithm is set to d (d = 1, 2) dimensions, and the upper and lower bounds of the dth dimension are (x min,d ,x max,d ), where the first dimension is the heading angle α, and the second dimension is the pitch angle β; let the maximum number of iterations of the algorithm be t max , the number of iterations for the algorithm to find the global optimal solution is t, 1≤t≤t max ; Initialize the number of iterations t = 1;

[0022] Randomly generate z qualified seeds in the t-th generation search space to form the candidate solution set X in the t-th generation search space z (t);

[0023] X z (t) = [X pq (t)]

[0024] X pq (t) = x min,q +rand()×(x max,q -x min,q )

[0025] Where, X pq (t) represents the position of each dimension q of the pth qualified seed (1 <p<z),

[0026] In the formula, x max,q and x min,q are the maximum and minimum values ​​of the solution space in the qth dimension, respectively. rand() is a function that generates a uniformly distributed random number between 0 and 1.

[0027] Calculate z candidate solutions based on the baseline J attitude angle mathematical model Finess of the initial qualified seeds p,t (α,β)=F p,t (X pq(t)); and determine the optimal candidate solution position X in the t-th generation search space o (t);

[0028] X o (t) = [x o,d (t)]

[0029] In the formula, x o,d (t) expresses the individual optimal value in the d-th dimension search space of the optimal candidate solution;

[0030] Calculate the average group of candidate solutions MG(t) in the t-th generation search space;

[0031]

[0032] According to the optimal candidate solution position X in the t-th generation search space o (t), the candidate solution average group MG(t) and each qualified seed establish the Sierpinski triangle; weighting is performed inside the triangle according to formula (10), so as to obtain z qualified seeds X in the t+1 generation search space z (t+1);

[0033] X z (t+1)=X z (t)+θ i +ψ i ×(X o (t)-Φ i ×MG(t)

[0034] In the formula, θ i , ψ i , Φ i They represent random numbers for controlling movement limits and selecting directions respectively;

[0035] Recalculate the baseline J attitude angle mathematical model Finess of the z candidate solutions at the t+1th generation qualified seeds p,t+1 (α,β)=F p,t+1 (X pq (t)); and Fitness p,t (α, β) is compared. If the fitness value of the new candidate solution is greater than that of the original candidate solution, it is replaced by the new candidate solution. Otherwise, the original candidate solution is retained.

[0036] Assign t+1 to t and judge t <t max Is it true? If so, execute the above steps; otherwise, the iteration is completed and the optimal position X of the group is obtained. o (t max )=[x o,d (t max )] is the optimal solution of the mathematical model of the baseline J attitude angle; xo,1 (t max ) and x o,2 (t max ) are the heading angle α and pitch angle β of the baseline J obtained by the algorithm;

[0037] Step 4: Calculate the inclination of the wind turbine tower;

[0038] The heading angle α(0) and pitch angle β(0) of the baseline J when it was initially installed are known, as well as the current heading angle α and pitch angle β of the baseline J obtained in step 3, and the horizontal torsion angle Δα and tilt angle Δβ of the tower are obtained respectively; further calculation can be used to obtain the inclination η of the wind turbine tower.

[0039] The present invention is further configured that in step 2, the carrier phase difference between antenna A and antenna B at the i-th satellite at the k-th epoch is The expression is:

[0040] The present invention is further configured such that in step 2, the carrier phase difference between antenna A and antenna B at the jth satellite at the kth epoch is The expression is:

[0041] The present invention is further configured that the carrier phase double difference in step 2 The expression is: In the formula, Indicates the carrier phase double difference; l AB is the length of the baseline J; λ is the wavelength of the RF carrier signal; is the phase double difference integer ambiguity; ε is the random observation noise.

[0043] The present invention is further configured such that the attitude angle mathematical model of the baseline J in step 2 is:

[0044]

[0045] The present invention is further configured such that the calculation formula of the horizontal twist angle Δα of the tower in step 4 is: Δα=α-α(0); the expression of the inclination angle Δβ of the tower is:

[0046] Δβ=β-β(0).

[0047] The present invention is further configured such that the calculation formula for the inclination η of the wind turbine tower in step 4 is: η=tan(Δβ).

[0048] The beneficial effects of the present invention are:

[0049] 1. Easy system deployment: By utilizing the high-precision positioning capability of the BeiDou III system, a monitoring baseline can be quickly established by installing only two satellite antennas on the top of the wind turbine tower, simplifying the equipment installation and maintenance process.

[0050] 2. Comprehensively reflect the inclination of the tower: The distance between the two antennas is set so that the baseline attitude can accurately reflect the overall inclination of the tower, providing more comprehensive monitoring data.

[0051] 3. High measurement accuracy: Through Beidou III satellite signals and high-precision attitude angle mathematical models, as well as advanced calculation methods such as improved chaos game, this system can calculate the tower inclination efficiently and accurately.

[0052] 4. Realize intelligent monitoring: The monitoring system automatically completes data collection, transmission and processing, and greatly improves the risk response speed through real-time monitoring and intelligent early warning functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a structural schematic diagram of a wind turbine tower inclination monitoring system based on Beidou III attitude measurement proposed in the present invention;

[0054] Figure 2 A schematic diagram of the wind turbine tower baseline position of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement proposed by the present invention;

[0055] Figure 3 A schematic diagram of a mathematical model of the baseline attitude angle on the tower of a wind turbine tower inclination monitoring system based on Beidou III attitude measurement proposed by the present invention;

[0056] Figure 4 This is a flowchart of the steps of the improved chaotic game algorithm of the wind power tower inclination monitoring system based on Beidou III attitude measurement proposed by the present invention;

[0057] Figure 5 This is a schematic diagram of the improved chaotic game algorithm of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement proposed in the present invention. DETAILED DESCRIPTION

[0058] The technical solution of this patent is further described in detail below in conjunction with specific implementation methods.

[0059] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0060] Reference Figure 1-2, a wind turbine tower inclination monitoring system based on BeiDou III attitude measurement, including two BeiDou III satellite antennas, BeiDou III receivers and a remote network server;

[0061] The two BeiDou III satellite antennas include antenna A and antenna B, which are placed at the top of the wind turbine tower respectively. The straight line connecting the two antennas is defined as baseline J. Antenna A and antenna B receive the RF carrier signal and send it to the receiver. The deployment method of antenna A and antenna B is as follows: Figure 2 As shown;

[0062] The BeiDou III receiver consists of BeiDou board A', BeiDou board B' and wireless communication module; board A' and board B' are connected to antenna A and antenna B respectively, and analyze the RF carrier signal received by antenna A and antenna B to obtain the carrier phase The satellite altitude angle H and satellite azimuth angle P are finally sent to the remote network server through the wireless communication module;

[0063] The remote network server receives the carrier phase The satellite elevation angle H and satellite azimuth angle P are substituted into the mathematical model of the attitude angle of the tower baseline J, and the improved chaotic game algorithm is used to solve it, so as to obtain the attitude angle of the baseline J, and then the inclination of the wind turbine tower is obtained.

[0064] The method for monitoring the inclination of a wind turbine tower based on Beidou III attitude measurement includes the following steps:

[0065] Step 1: Let the projection of baseline J on the horizontal plane be J', define the angle between projection J' and the true north direction as the heading angle α of baseline J, and the value range of heading angle α is 0 to 360 degrees; define the angle between baseline J and projection J' as the pitch angle β of baseline J, and the value range of pitch angle β is -90 to +90 degrees;

[0066] Receive and analyze the RF carrier signal of Beidou III satellite;

[0067] Antenna A and antenna B receive the RF carrier signals of m epochs from n BeiDou III satellites respectively, n≥4, m≥4, and send them to the BeiDou receiver;

[0068] BeiDou board A' and BeiDou board B' analyze the RF carrier signals received by antenna A and antenna B respectively, and obtain the carrier phase, satellite altitude angle and satellite azimuth angle of m epochs of n BeiDou III satellites, which are recorded as in, and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board A'; and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board B';

[0069] Step 2: Establish a mathematical model of the attitude angle of the baseline J on the tower;

[0070] Obtain carrier phase single difference equation;

[0071] According to formula (1), the carrier phase difference between antenna A and antenna B at the i-th satellite at the k-th epoch is calculated as According to formula (2), the carrier phase difference between antenna A and antenna B at the jth satellite at the kth epoch is calculated as

[0072]

[0073] Step 2.2: Calculate the carrier phase double difference according to equation (3) and equation (4):

[0074]

[0075] In formula (4), Indicates the carrier phase double difference; l AB is the length of the baseline J; λ is the wavelength of the RF carrier signal; is the phase double difference integer ambiguity; ε is the random observation noise, and is considered to be Gaussian white noise with zero mean. The schematic diagram of the carrier phase difference is shown in Figure 3 As shown;

[0076] The mathematical model of the attitude angle of the baseline J is established using formula (5):

[0077]

[0078] Formula (5) is a function of the heading angle α and the pitch angle β. Therefore, solving the attitude angle problem is transformed into a nonlinear optimization problem.

[0079] Step 3: Propose an improved chaotic game algorithm to solve the mathematical model and obtain the attitude angle of the baseline J; the operation steps of the algorithm are as follows: Figure 4 As shown;

[0080] The search space of the improved chaotic game algorithm is set to d (d = 1, 2) dimensions, and the upper and lower bounds of the dth dimension are (x min,d ,x max,d ), where the first dimension is the heading angle α, and the second dimension is the pitch angle β; let the maximum number of iterations of the algorithm be t max , the number of iterations for the algorithm to find the global optimal solution is t, 1≤t≤t max ; Initialize the number of iterations t = 1;

[0081] According to equations (6) and (7), z qualified seeds in the t-th generation search space are randomly generated to form the candidate solution set X in the t-th generation search space. z (t);

[0082] X z (t) = [X pq (t)] (6)

[0083] X pq (t) = x min,q +rand()×(x max,q -x min,q ) (7)

[0084] In formula (6), X pq (t) represents the position of each dimension q of the pth qualified seed (1 <p<z),

[0085] In formula (7), s max,q and x min,q are the maximum and minimum values ​​of the solution space in the qth dimension, respectively. rand() is a function that generates a uniformly distributed random number between 0 and 1. In this way, the initial position of each solution candidate in the search space is randomly selected, which provides a starting point for the algorithm to initially explore the search space and avoid the algorithm falling into a local optimal solution.

[0086] Calculate z candidate solutions based on the baseline J attitude angle mathematical model Fitness p,t (α,β)=F p,t (X pq (t)); and determine the optimal candidate solution position X in the t-th generation search space according to formula (8) o (t);

[0087] X o (t) = [x o,d (t)] (8)

[0088] In formula (8), x o,d (t) expresses the individual optimal value in the d-th dimension search space of the optimal candidate solution;

[0089] Step 3.4, calculate the average group of candidate solutions MG(t) in the t-th generation search space according to formula (9);

[0090]

[0091] According to the optimal candidate solution position X in the t-th generation search space o(t), the candidate solution average group MG(t) and each qualified seed establish the Sierpinski triangle; it is manifested as the self-similarity of the fractal; weighting is performed inside the triangle according to formula (10), so as to obtain z qualified seeds X in the t+1 generation search space z (t+1);

[0092] X z (t+1)=X z (t)+θ i +ψ i ×(X o (t)-Φ i ×MG(t)) (10)

[0093] In formula (10), θ i , ψ i , Φ i They represent random numbers for controlling movement limits and selecting directions respectively;

[0094] Recalculate the baseline J attitude angle mathematical model Fitness of the z candidate solutions at the t+1th generation qualified seeds p,t+1 (α,β)=F p,t+1 (X pq (t)); and Fitness p,t (α, β) is compared. If the fitness value of the new candidate solution is greater than that of the original candidate solution, it is replaced by the new candidate solution. Otherwise, the original candidate solution is retained.

[0095] Assign t+1 to t and judge t <t max Is it true? If so, execute the above steps; otherwise, the iteration is completed and the optimal position X of the group is obtained. o (t max )=[x o,d (t max )] is the optimal solution of the mathematical model of the baseline J attitude angle; [x o,1 (t max ) and x o,2 (t max ) are the heading angle α and pitch angle β of the baseline J obtained by the algorithm; the steps of updating the candidate solutions and then solving the optimal solution by the improved chaotic game are as follows: Figure 5 As shown;

[0096] Step 4: Calculate the inclination of the wind turbine tower;

[0097] Given the heading angle α(0) and pitch angle β(0) of the baseline J when it was initially installed, as well as the current heading angle α and pitch angle β of the baseline J obtained in step 3, the horizontal torsion angle Δα and tilt angle Δβ of the tower can be obtained using equations (11) and (12), respectively:

[0098] Δα=α-α(0)(11)

[0099] Δβ=β-β(0)(12)

[0100] The inclination η of the wind turbine tower can be further calculated by formula (13):

[0101] η=tan(Δβ)(13).

[0102] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The wind turbine tower inclination monitoring system based on BeiDou III attitude measurement is characterized by: Includes two BeiDou III satellite antennas, BeiDou III receiver and remote network server; The two BeiDou III satellite antennas include antenna A and antenna B, which are respectively placed at the top of the wind turbine tower, and a straight line segment connecting the two antennas is defined as a baseline J; antenna A and antenna B receive radio frequency carrier signals and send them to a BeiDou III receiver; The BeiDou III receiver is composed of BeiDou board A', BeiDou board B' and a wireless communication module; board A' and board B' are connected to antenna A and antenna B respectively, and analyze the radio frequency carrier signal received by antenna A and antenna B to obtain the carrier phase The satellite altitude angle H and satellite azimuth angle P are finally sent to the remote network server through the wireless communication module; The remote network server receives the carrier phase The satellite elevation angle H and the satellite azimuth angle P are substituted into the mathematical model of the attitude angle of the tower baseline J, and the improved chaotic game algorithm is used to solve it, so as to obtain the attitude angle of the baseline J, and then obtain the inclination of the wind turbine tower.

2. The monitoring method of the wind turbine tower inclination monitoring system based on BeiDou III attitude measurement according to claim 1, characterized in that: The following steps are involved: Step 1: Let the projection of baseline J on the horizontal plane be J′, define the angle between projection J′ and the true north direction as the heading angle α of baseline J, and the value range of heading angle α is 0 to 360 degrees; define the angle between baseline J and projection J′ as the pitch angle β of baseline J, and the value range of pitch angle β is -90 to +90 degrees; receive and analyze the RF carrier signal of BeiDou III satellite; antenna A and antenna B respectively receive the RF carrier signals of m epochs of n BeiDou III satellites, n≥4, m≥4, and send them to BeiDou receiver; BeiDou board A' and BeiDou board B' analyze the RF carrier signals received by antenna A and antenna B respectively, and obtain the carrier phase, satellite altitude angle and satellite azimuth angle of m epochs of n BeiDou III satellites, which are recorded as in, and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board A'; and They represent the carrier phase, satellite altitude angle and satellite azimuth angle of the i-th satellite at the k-th epoch respectively, which are obtained by BeiDou board B'; Step 2: Establish a mathematical model of the attitude angle of the baseline J on the tower; Obtain the carrier phase single difference equation; calculate the carrier phase difference between antenna A and antenna B at the i-th satellite at the k-th epoch Calculate the carrier phase difference between antenna A and antenna B at the jth satellite at the kth epoch Calculate the double difference of carrier phase; establish the mathematical model of attitude angle of baseline J; Step 3: Propose an improved chaotic game algorithm to solve the mathematical model and obtain the attitude angle of the baseline J; The search space of the improved chaotic game algorithm is set to d (d = 1, 2) dimensions, and the upper and lower bounds of the dth dimension are (x min,d ,x max,d ), where the first dimension is the heading angle α, and the second dimension is the pitch angle β; let the maximum number of iterations of the algorithm be t max , the number of iterations for the algorithm to find the global optimal solution is t, 1≤t≤t max ; Initialize the number of iterations t = 1; Randomly generate z qualified seeds in the t-th generation search space to form the candidate solution set X in the t-th generation search space z (t); X z (t)=[X pq (t)] X pq (t)=x min，q +rand()×(x max,q -x min，q ) Where Xpq(t) represents the position of the pth qualified seed in each dimension q (1 <p<z), In the formula, x max,q and x min，q are the maximum and minimum values ​​of the solution space in the qth dimension, respectively. rand() is a function that generates a uniformly distributed random number between 0 and 1. Calculate z candidate solutions based on the baseline J attitude angle mathematical model Fitness p,t (α, β) = F p,t (X pq (t)); and determine the optimal candidate solution position X in the t-th generation search space o (t); X o (t)=[x o,d (t)] In the formula, x o,d (t) expresses the individual optimal value in the d-th dimension search space of the optimal candidate solution; Calculate the average group of candidate solutions MG(t) in the t-th generation search space; According to the optimal candidate solution position X in the t-th generation search space o (t), the candidate solution average group MG(t) and each qualified seed establish the Sierpinski triangle; weighting is performed inside the triangle according to formula (10), so as to obtain z qualified seeds X in the t+1 generation search space z (t+1); X z (t+1)=X z (t)+θ i +ψ i ×(X o (t)-Φ i ×MG(t)) In the formula, θ i , ψ i , Φ i They represent random numbers for controlling movement limits and selecting directions respectively; Recalculate the baseline J attitude angle mathematical model Fitness of the z candidate solutions at the t+1th generation qualified seeds p，t+1 (α, β) = F p，t+1 (X pq (t)); and Fitness p，t (α, β) are compared. If the fitness value of the new candidate solution is greater than that of the original candidate solution, it is replaced by the new candidate solution. Otherwise, the original candidate solution is retained. Assign t+1 to t and judge t <t max Is it true? If so, execute the above steps; otherwise, the iteration is completed and the optimal position X of the group is obtained. o (t max )=[x o，d (t max )] is the optimal solution of the mathematical model of the baseline J attitude angle; x o，1 (t max ) and x o，2 (t max ) are the heading angle α and pitch angle β of the baseline J obtained by the algorithm; Step 4: Calculate the inclination of the wind turbine tower; The heading angle α(0) and pitch angle β(0) of the baseline J when it was initially installed are known, as well as the current heading angle α and pitch angle β of the baseline J solved in step 3, and the horizontal torsion angle Δα and tilt angle Δβ of the tower are obtained respectively; further calculation can be used to obtain the inclination ηη of the wind turbine tower.

3. The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement according to claim 2 is characterized in that: The carrier phase difference between antenna A and antenna B at the kth epoch of the i-th satellite in step 2 is The expression is:

4. The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement according to claim 3 is characterized in that: The carrier phase difference between antenna A and antenna B at the jth satellite at the kth epoch in step 2 The expression is:

5. The monitoring method of the wind turbine tower inclination monitoring system based on BeiDou III attitude measurement according to claim 4 is characterized in that: In step 2, the carrier phase double difference The expression is: In the formula, Indicates the carrier phase double difference; l AB is the length of the baseline J; λ is the wavelength of the RF carrier signal; is the phase double difference integer ambiguity; ε is the random observation noise.

6. The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement according to claim 5 is characterized in that: The mathematical model of the attitude angle of the baseline J in step 2 is:

7. The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement according to claim 2 is characterized in that: The calculation formula for the horizontal twist angle Δα of the tower in step 4 is: Δα=α-α(0); the expression for the inclination angle Δβ of the tower is: Δβ=β-β(0).

8. The monitoring method of the wind turbine tower inclination monitoring system based on Beidou III attitude measurement according to claim 7 is characterized in that: The calculation formula of the inclination η of the wind turbine tower in step 4 is: η=tan(Δβ).

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