Power transmission tower tilt monitoring method and system based on complementary filtering and particle filtering

Abstract

A power transmission tower tilt monitoring method, system and device based on complementary filtering and particle filtering, the monitoring method first initializes a particle set based on particle filtering, then updates the tilt angle estimation value of each particle in the set based on the measurement information provided by the gyroscope, fuses the measurement information of the accelerometer and the gyroscope through the complementary filter to update the particle weight, and then obtains the tilt angle prediction value of the power transmission tower through weighted summation, and finally iterates to gradually approach the actual tilt angle. In the application, the particle state of each time step is dynamically updated according to the particle filtering, and the particle weight of each time step is dynamically updated according to the fusion information of the complementary filtering, while considering the influence of environmental noise, thereby improving the measurement accuracy of the tilt angle of the power transmission tower.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of transmission tower tilt monitoring, and particularly relates to a transmission tower tilt monitoring method and system based on complementary filtering and particle filtering, and is suitable for improving transmission tower tilt angle measurement accuracy. BACKGROUND

[0002] With the growth of economy, the improvement of industrialization level and the development of science and technology, the demand for electric energy in China is increasing, and the electric power industry is developing continuously. As an important supporting structure for electric power transmission, the stability of the transmission tower is particularly important. In the operation process of the transmission tower, the transmission tower is often affected by extreme weather conditions such as storms, blizzards, sandstorms and typhoons, which can easily cause the transmission tower to tilt or even collapse, which will have a significant impact on the safety and stability of the power system. Therefore, it is necessary to monitor the tilt condition of the transmission tower. At present, the detection of the tilt of the transmission tower mainly includes the following methods: installing a tilt angle sensor (gyroscope, acceleration sensor, etc.) on the top of the tower, installing a laser displacement sensor on the tower body, and using an unmanned aerial vehicle laser radar. In order to improve the tilt angle measurement accuracy of the transmission tower, a high-precision attitude solution method based on the gyroscope and the acceleration sensor is urgently needed. SUMMARY

[0003] The purpose of the present application is to provide a transmission tower tilt monitoring method and system based on complementary filtering and particle filtering, which can improve the tilt angle measurement accuracy of the transmission tower, in order to solve the above problems existing in the prior art.

[0004] To achieve the above purpose, the technical scheme of the present application is as follows:

[0005] In the first aspect, the present application provides a transmission tower tilt monitoring method based on complementary filtering and particle filtering, which comprises the following steps:

[0006] S1, initializing a particle set based on particle filtering, each particle in the particle set representing an estimated value of a tilt angle;

[0007] S2, updating the estimated value of the tilt angle of each particle in the set based on the measurement information provided by the gyroscope at the t time step, and the update formula of the estimated value of the tilt angle of the particle is:

[0008]

[0009] In the above formula, represents the estimated value of the tilt angle of the i-th particle at the t time step after updating; and t-1 represents the estimated value of the tilt angle of the i-th particle at the t-1 time step before updating; and trepresents the angular velocity measurement provided by the gyroscope in the inclination monitoring device on the power transmission tower at the t time step; Δt represents the time interval between two measurements; ∈ t represents random noise;

[0010] S3, calculate the weight of each particle based on the measurement information provided by the gyroscope and the accelerometer at the t time step, and the calculation formula of the particle weight is:

[0011]

[0012] θ fusion = a · (pitch acc + roll acc ) + (1-a) · (pitch gyro + Δθ gyro ) ;

[0013]

[0014] roll acc = atan2 (-a y , -a z ) ;

[0015] In the above formula, w (i) represents the updated weight of the i th particle; σ scnsor represents the standard deviation of measurement error; θ fusion represents the t time step fusion inclination angle estimation value obtained by using the complementary filter; θ sensor represents the t time step inclination angle measurement value obtained by the accelerometer in the inclination monitoring device on the power transmission tower; pitch acc , roll acc respectively represent the pitch angle and roll angle obtained by the accelerometer; a x , a y , a z respectively represent the acceleration components of the power transmission tower in the X, Y, Z coordinate axis directions provided by the accelerometer; pitch gyro represents the pitch angle obtained by the gyroscope; Δθ gyro represents the angle change obtained by integrating the gyroscope; a represents the weight of the accelerometer;

[0016] S4, based on the updated inclination angle estimation value and the weight, calculate the inclination angle prediction value of the power transmission tower at the t time step by weighted summation;

[0017] S5, loop and repeat S2 to S4 to calculate the inclination angle prediction value at the next time step until the maximum iteration number is reached, and output the inclination angle prediction value obtained by the last iteration.

[0018] The calculation formula of the weighted summation in S4 is:

[0019]

[0020]

[0021] In the above formula, represents the predicted value of the tilt angle of the power transmission tower at the t time step; represents the normalized weight of the i-th particle, and N represents the total number of particles in the particle set.

[0022] When the particle weight distribution is uneven, a new particle set is constructed by resampling, and the tilt angle estimate value of each particle in the updated set in S2 is based on the new particle set; the resampling is specifically:

[0023] A random number is randomly selected from the uniform distribution [0, 1), and a particle that meets the following conditions is found from the particle set, and is added to the new particle set as a new particle; the selection and addition operation is repeated until the total number of particles in the new particle set reaches the total number of particles in the initial particle set:

[0024] CDF i CDF i+1 ;

[0025]

[0026]

[0027] In the above formula, u represents the randomly selected random number; CDF i , and CDF i+1 respectively represent the cumulative weights of the i-th and i+1-th particles in the particle set before resampling.

[0028] In a second aspect, the present application provides a power transmission tower tilt monitoring system based on complementary filtering and particle filtering, the monitoring system comprising an initialization module, a particle value updating module, a particle weight updating module, a tilt angle prediction value calculation module, and an output module.

[0029] The initialization module is configured to initialize a particle set based on particle filtering, and each particle in the particle set represents a tilt angle estimate value.

[0030] The particle value updating module is configured to update the tilt angle estimate value of each particle in the set based on the measurement information provided by the gyroscope at the current time step, and the update formula of the tilt angle estimate value of the particle is:

[0031]

[0032] In the above formula, represents the updated tilt angle estimation value of the i-th particle at the t time step; θ t-1 represents the tilt angle estimation value of the i-th particle at the t-1 time step before updating; ω t represents the angular velocity measurement value provided by the gyroscope in the tilt monitoring device on the power transmission tower at the t time step; Δt represents the time interval between two measurements; ∈ t represents random noise;

[0033] The particle weight updating module is configured to calculate the weight of each particle based on the measurement information provided by the gyroscope and the accelerometer at the current time step, and the calculation formula of the particle weight is:

[0034]

[0035] θ fusion = α · (pitch acc + roll acc ) + (1-α) · (pitch gyro + Δθ gyro ) ;

[0036]

[0037] roll acc = atan2 (-a y , -a z ) ;

[0038] In the above formula, w (i) represents the updated weight of the i-th particle; σ scnsor represents the measurement error standard deviation; θ fusion represents the fusion tilt angle estimation value at the t time step obtained using the complementary filter; θ sensor represents the tilt angle measurement value at the t time step obtained by the accelerometer in the tilt monitoring device on the power transmission tower; pitch acc , roll acc respectively represent the pitch angle and roll angle obtained by the accelerometer; a x , a y , a z respectively represent the acceleration components of the power transmission tower in the X, Y, and Z coordinate axis directions provided by the accelerometer; pitch gyro represents the pitch angle obtained by the gyroscope; Δθ gyro represents the angle change obtained by integrating the gyroscope; and α represents the weight of the accelerometer.

[0039] The tilt angle prediction value calculation module is configured to calculate the tilt angle prediction value of the current power transmission tower by weighted summation based on the updated tilt angle estimation value and the weight.

[0040] The output module is configured to output the predicted value of the tilt angle obtained in the last iteration.

[0041] The calculation formula of the weighted sum is:

[0042]

[0043]

[0044] In the above formula, represents the predicted value of the tilt angle of the power transmission tower at the t time step; represents the normalized weight of the i-th particle, and N represents the total number of particles in the particle set.

[0045] The monitoring system further comprises a resampling module configured to construct a new particle set by resampling when the particle weight distribution is uneven, and a particle value updating module configured to update the tilt angle estimate value of each particle in the new particle set; the resampling is specifically:

[0046] A random number is randomly drawn from a uniform distribution [0, 1), and a particle satisfying the following condition is found from the particle set and added to the new particle set as a new particle; the drawing and adding operations are repeated until the total number of particles in the new particle set reaches the total number of particles in the initial particle set:

[0047] CDF i CDF i+1 ;

[0048]

[0049]

[0050] In the above formula, u represents the randomly drawn random number; CDF i , and CDF i+1 respectively represent the cumulative weights of the i-th and i+1-th particles in the particle set before resampling.

[0051] In a third aspect, the present application provides a power transmission tower tilt monitoring device based on complementary filtering and particle filtering, the monitoring device comprising a memory and a processor;

[0052] The memory is configured to store computer program code and transmit the computer program code to the processor;

[0053] The processor is configured to execute the foregoing method according to instructions in the computer program code.

[0054] In a fourth aspect, the present application provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to implement the method described above.

[0055] Compared with the prior art, the present application has the following advantages:

[0056] 1. The power transmission tower tilt monitoring method based on complementary filtering and particle filtering initializes a particle set based on particle filtering, then updates the tilt angle estimation value of each particle in the set based on the measurement information provided by the current gyroscope, and fuses the measurement information of the accelerometer and the gyroscope through a complementary filter to update the particle weight, and then obtains the tilt angle prediction value of the power transmission tower through weighted summation, and finally iterates to gradually approach the actual tilt angle. The design dynamically updates the particle state of each time step according to particle filtering, dynamically updates the particle weight of each time step according to complementary filtering, and considers the influence of environmental noise, thereby improving the measurement accuracy of the tilt angle of the power transmission tower. Therefore, the present application can improve the measurement accuracy of the tilt angle of the power transmission tower.

[0057] 2. The power transmission tower tilt monitoring method based on complementary filtering and particle filtering constructs a new particle set through resampling, the weight of each particle in the new particle set is equal, and the weight of each particle in the new particle set is updated based on the measurement information provided by the current time step gyroscope. In the above design, resampling is based on cumulative weight, particles with high weight may be repeatedly drawn and particles with low weight may be discarded, which can maintain the diversity of the new particle set and amplify the influence of particles with high weight, thereby improving the accuracy of the prediction result. Therefore, the present application can improve the accuracy of the prediction result. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 The flowchart of the method of the present application.

[0059] Figure 2 The structural block diagram of the system of the present application.

[0060] Figure 3 The structural block diagram of the device of the present application. DETAILED DESCRIPTION

[0061] The present application will be further described in detail below in conjunction with the specific embodiments and the accompanying drawings.

[0062] Example 1:

[0063] Referring to Figure 1 A power transmission tower tilt monitoring method based on complementary filtering and particle filtering is specifically performed according to the following steps:

[0064] S1, initialize a particle set based on particle filter, each particle in the particle set represents an estimated value of the tilt angle, and each particle has the same initial weight;

[0065] S2, update the estimated value of the tilt angle of each particle in the particle set based on the measurement information provided by the gyroscope at time step t, and the update formula of the estimated value of the tilt angle of the particle is:

[0066]

[0067] In the above formula, represents the estimated value of the tilt angle of the i-th particle at time step t after updating; θ t-1 represents the estimated value of the tilt angle of the i-th particle at time step t-1 before updating; ω t represents the angular velocity measurement value provided by the gyroscope in the tilt monitoring device on the power transmission tower at time step t; Δt represents the time interval between two measurements; ∈ t represents the random noise caused by factors such as wind in the real environment;

[0068] S3, calculate the weight of each particle based on the measurement information provided by the gyroscope and the accelerometer at time step t, and the calculation formula of the particle weight is:

[0069]

[0070] θ fusion = α · (pitch acc + roll acc ) + (1-α) · (pitch gyro + Δθ gyro ) ;

[0071]

[0072] roll acc = atan2 (-a y , -a z ) ;

[0073] In the above formula, w (i) represents the updated weight of the i-th particle; σ scnsor represents the standard deviation of the measurement error; θ fusion represents the fused tilt angle estimation value at time step t obtained using the complementary filter; θ sensor represents the tilt angle measurement value at time step t obtained by the accelerometer in the tilt monitoring device on the power transmission tower; pitch acc , roll acc respectively represent the pitch angle and roll angle obtained by the accelerometer; a x, a y , a z respectively represent the acceleration components of the power transmission tower in the X, Y, Z coordinate axis directions provided by the accelerometer; pitch gyro represents the pitch angle obtained by the gyroscope; Δθ gyro represents the angle change amount obtained by the gyroscope integration; a represents the weight of the accelerometer;

[0074] S4, based on the updated pitch angle estimation value and the weight, calculating the pitch angle prediction value of the power transmission tower at the t time step by weighted summation; the calculation formula of the weighted summation is:

[0075]

[0076]

[0077] In the above formula, represents the pitch angle prediction value of the power transmission tower at the t time step; represents the normalized weight of the i-th particle, and N represents the total number of particles in the particle set;

[0078] When the particle weight distribution in the particle set is uneven, a new particle set is constructed by resampling, and S2 updates the pitch angle estimation value of each particle in the new particle set; the distribution of the particle weight can be judged according to the calculation result by calculating the standard deviation or variance of the particle weight, if the standard deviation or variance is large, it indicates that the particle weight distribution is uneven, and resampling is needed, and the resampling is specifically:

[0079] A random number is randomly selected from the uniform distribution [0, 1), and a particle satisfying the selection condition is found from the particle set, and is added to the new particle set as a new particle; the selection and addition operation is repeated until the total number of particles in the new particle set reaches the total number of particles in the initial particle set; the result of the resampling is to obtain a new particle set, the particles with high weight may be repeatedly selected and the particles with low weight may be discarded, and the weight of each particle in the new particle set is equal, so that the diversity of the new particle set can be maintained, the influence of the particles with high weight can be amplified, and the estimation accuracy can be improved. The selection condition is:

[0080] CDF i <u<CDF i+1 ;

[0081]

[0082]

[0083] In the above formula, u represents the randomly selected random number; CDF i , CDFi+1 respectively represent the cumulative weights of the i-th and i+1-th particles in the particle set before resampling.

[0084] Two inclination monitoring devices are arranged in the embodiment, which are respectively installed on both sides of the waist of the transmission tower at 2 / 3 of the height from the ground. Each inclination monitoring device is composed of an acceleration sensor and a gyroscope sensor. The final output inclination angle of the transmission tower is the average of the inclination angle estimates obtained by the two inclination monitoring devices.

[0085] S5, the calculation of the inclination angle prediction value of the next time step is repeated from S2 to S4 until the maximum number of iterations is reached, and the inclination angle prediction value obtained in the last iteration is output.

[0086] Embodiment 2:

[0087] Referring to Figure 2 A transmission tower inclination monitoring system based on complementary filtering and particle filtering includes an initialization module, a particle value updating module, a particle weight updating module, an inclination angle prediction value calculation module, a resampling module, and an output module. The initialization module is used to initialize a particle set based on particle filtering. Each particle in the particle set represents an inclination angle estimate. The particle value updating module is used to update the inclination angle estimate of each particle in the set based on the measurement information provided by the gyroscope at the current time step. The update formula of the inclination angle estimate of the particle is:

[0088]

[0089] In the above formula, represents the inclination angle estimate of the i-th particle at time step t after updating; θ t-1 represents the inclination angle estimate of the i-th particle at time step t-1 before updating; ω t represents the angular velocity measurement value provided by the gyroscope in the inclination monitoring device of the transmission tower at time step t; Δt represents the time interval between two measurements; ∈ t represents the random noise caused by factors such as wind in the real environment;

[0090] The particle weight updating module is used to calculate the weight of each particle based on the measurement information provided by the gyroscope and accelerometer at the current time step. The calculation formula of the particle weight is:

[0091]

[0092] θ fusion = α · (pitch acc + roll acc) + (1-α) · (pitch gyro + Δθgyro );

[0093]

[0094] roll acc =atan2(-a y ,-a z );

[0095] In the above formula, w (i) represents the updated weight of the i-th particle; σ scnsor represents the measurement error standard deviation; θ fusion represents the t-time step fusion tilt angle estimation value obtained using the complementary filter; θ sensor represents the t-time step tilt angle measurement value obtained by the accelerometer in the tilt monitoring device on the power transmission tower; pitch acc , roll acc respectively represent the pitch angle and roll angle obtained by the accelerometer; a x , a y , a z respectively represent the acceleration components of the power transmission tower provided by the accelerometer in the X, Y, Z coordinate axis directions; pitch gyro represents the pitch angle obtained by the gyroscope; Δθ gyro represents the angle change amount obtained by integrating the gyroscope; a represents the weight of the accelerometer.

[0096] The tilt angle prediction value calculation module is configured to calculate the tilt angle prediction value of the current power transmission tower by weighted summation based on the updated tilt angle estimation value and the weight, and the calculation result is transmitted to the receiving end through the telemetry signal transmitter and the telemetry signal receiver. The calculation formula of the weighted summation is:

[0097]

[0098]

[0099] In the above formula, represents the tilt angle prediction value of the power transmission tower at the t-time step; represents the normalized weight of the i-th particle, and N represents the total number of particles in the particle set;

[0100] The resampling module is configured to construct a new particle set by resampling when the particle weight distribution is uneven, and the particle value updating module updates the tilt angle estimation value of each particle in the new particle set. The resampling is specifically:

[0101] A random number is randomly drawn from a uniform distribution [0, 1), and a particle satisfying the following condition is found from the particle set, and is added to the new particle set as a new particle; the drawing and adding operation is repeated until the total number of particles in the new particle set reaches the total number of particles in the initial particle set:

[0102] CDF i CDF i+1 ;

[0103]

[0104]

[0105] In the above formula, u represents a randomly drawn random number; CDF i , and CDF i+1 respectively represent the cumulative weights of the i th and i+1 th particles in the particle set before resampling;

[0106] The output module is configured to output the tilt angle prediction value obtained in the last iteration.

[0107] Embodiment 3:

[0108] Referring to Figure 3 , a power transmission tower tilt monitoring device based on complementary filtering and particle filtering, comprising a memory and a processor; the memory is used to store computer program code and transmit the computer program code to the processor; the processor is used to execute the method as described in embodiment 1 according to the instructions in the computer program code.

[0109] Embodiment 4:

[0110] A computer readable storage medium, the computer readable storage medium has a computer program stored thereon, the computer program is executed by a processor to realize the method described above.

[0111] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system) and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of the flows and / or blocks in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that realizes the functions specified in the flowchart Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The functions specified in one flow or multiple flows and / or blocks

[0112] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that are executed on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0114] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the preferred embodiments by those of skill in the art once they have the benefit of the present disclosure. Therefore, the appended claims are intended to encompass within their scope all possible variations and modifications of the preferred embodiments.

[0115] It is apparent that a person skilled in the art can make a variety of changes and modifications to the application without departing from the spirit and scope of the application. Thus, if these modifications and variations of the application fall within the scope of the claims and their equivalents, it is intended to include them within the scope of the application.

Claims

1. A power transmission tower tilt monitoring method based on complementary filtering and particle filtering, characterized in that: The monitoring method comprises: S1, initializing a particle set based on particle filtering, each particle in the particle set representing a tilt angle estimate value; S2, based on The time step gyroscope provides measurement information to update the tilt angle estimate of each particle in the set, and the update formula of the tilt angle estimate of the particle is: ； In the above formulae, denotes the estimated tilt angle of the i-th particle at time step after update; denotes the estimated tilt angle of the i-th particle at time step before update; denotes the estimated tilt angle of the i-th particle at time step after update; denotes the time interval between two measurements; denotes the random noise; S3、 based on The weight of each particle is calculated based on the measurement information provided by the gyroscope and the accelerometer, and the calculation formula of the particle weight is: ； ； ； ； In the above formula, denotes the updated weight of the i-th particle; denotes the measurement error standard deviation; denotes the angle change obtained using the complementary filter time step fused tilt angle estimate value; denotes the angle change obtained by the accelerometer in the tilt monitoring device on the power transmission tower time step tilt angle measurement value; respectively denote the pitch angle and roll angle obtained by the accelerometer; , respectively denote the acceleration components of the power transmission tower provided by the accelerometer in the X, Y, Z coordinate axis directions; denotes the pitch angle obtained by the gyroscope; denotes the angle change obtained by integrating the gyroscope; denotes the weight of the accelerometer;​​ S4, based on the updated tilt angle estimation value and the weight, calculating a weighted sum a tilt angle prediction value of the power transmission tower at the time step S5, repeatedly calculating the tilt angle prediction value of the next time step by S2-S4 until the maximum number of iterations is reached, and outputting the tilt angle prediction value obtained in the last iteration; When the particle weight distribution is uneven, a new particle set is constructed by resampling, and the tilt angle estimate value of each particle in the updated set in S2 is updated based on the new particle set; The resampling is specifically: A random number is randomly selected from a uniform distribution [0, 1), and a particle that meets the following conditions is found from the particle set and added to the new particle set as a new particle; Repeat the extraction and addition operation until the total number of particles in the new particle set reaches the total number of particles in the initial particle set: ； ； ； In the above formula, represents a random number randomly extracted; , respectively represent the cumulative weights of the i-th and i+1-th particles in the particle set before resampling. The calculation formula of the weighted sum in S4 is: ； ； In the above formula, represents the inclination angle prediction value of the power transmission tower at the time step; represents the normalized weight of the i-th particle; represents the normalized weight of the i+1-th particle; represents the total number of particles in the particle set.

2. A power transmission tower tilt monitoring system based on complementary filtering and particle filtering, characterized in that: The monitoring system comprises an initialization module, a particle value updating module, a particle weight updating module, a tilt angle prediction value calculation module, and an output module; The initialization module is configured to initialize a particle set based on particle filtering, each particle in the particle set representing a tilt angle estimate value; The particle value updating module is configured to update the tilt angle estimate value of each particle in the set based on the measurement information provided by the gyroscope at the current time step, and the update formula of the tilt angle estimate value of the particle is: ； In the above formula, This indicates that after the update, the i-th particle is in The estimated tilt angle of the time step; This indicates that the i-th particle was in the position before the update. The estimated tilt angle of the time step; express The time step is determined by the angular velocity measurement provided by the gyroscope in the tilt monitoring device on the transmission tower. Indicates the time interval between two measurements; Indicates random noise; The particle weight updating module is configured to calculate the weight of each particle based on the measurement information provided by the gyroscope and the accelerometer at the current time step, and the calculation formula of the particle weight is: ； ； ； ； In the above formula, denotes the updated weight of the i-th particle; denotes the measurement error standard deviation; denotes the angle of inclination estimation value obtained using the complementary filter time step fusion angle of inclination estimation value; denotes the acceleration obtained by the accelerometer in the inclination monitoring device on the power transmission tower time step angle of inclination measurement value; , denote the pitch angle and roll angle obtained by the accelerometer, respectively; , , denote the acceleration components of the power transmission tower provided by the accelerometer in the X, Y, Z coordinate axis directions, respectively; denotes the pitch angle obtained by the gyroscope; denotes the angle change amount obtained by the gyroscope integration; denotes the weight of the accelerometer; The tilt angle prediction value calculation module is configured to calculate the tilt angle prediction value of the current power transmission tower by weighted sum based on the updated tilt angle estimate value and weight; The output module is configured to output the tilt angle prediction value obtained in the last iteration; The monitoring system further comprises a resampling module, which is configured to construct a new particle set by resampling when the particle weight distribution is uneven, and the particle value updating module is configured to update the tilt angle estimate value of each particle in the new particle set; The resampling is specifically: A random number is randomly selected from a uniform distribution [0, 1), and a particle that meets the following conditions is found from the particle set and added to the new particle set as a new particle; Repeat the extraction and addition operation until the total number of particles in the new particle set reaches the total number of particles in the initial particle set: ； ； ； In the above formula, represents a random number randomly extracted; , respectively represent the cumulative weights of the i-th and i+1-th particles in the particle set before resampling. The calculation formula of the weighted sum is: ； ； In the above formula, represents the tilt angle prediction value of the power transmission tower at the time step represents the tilt angle prediction value of the power transmission tower at the time step represents the normalized weight of the i-th particle; represents the normalized weight of the i+1-th particle; represents the total number of particles in the particle set.

3. A power transmission tower tilt monitoring device based on complementary filtering and particle filtering, characterized in that: The monitoring device comprises a memory and a processor; The memory is configured to store computer program code and transmit the computer program code to the processor; The processor is configured to execute the method according to the instructions in the computer program code.

4. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in claim 1.

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