Method, device and equipment for suppressing wind-induced vibration of steel tube tower and storage medium

Abstract

The invention provides a steel tube tower wind-induced vibration suppression method, device and equipment and a storage medium. The method is applied to an intelligent suppression system comprising an acceleration sensor, a fiber grating strain sensor, a processing unit and a damper. The method comprises the following steps that: a processing unit analyzes parameters such as energy concentration ratio of an acceleration signal, and calculates a vibration characterization factor according to a first factor, a second factor and a third factor in combination with a preset reference value and a characteristic influence factor; meanwhile, by comparing credible data of the acceleration sensor with detection data of the fiber bragg grating strain sensor, a sensor drift value is obtained, and a drift compensation value is extracted; and according to the drift compensation value correction data, determining the number of current gradient decomposition times, and adjusting the damper current to generate the damping force. Data reliability and system stability are ensured, and wind-induced vibration of the steel tube tower is effectively suppressed.

Description

Technical Field

[0001] This application belongs to the field of steel pipe towers, and particularly relates to a method, apparatus, equipment and storage medium for suppressing wind-induced vibration of steel pipe towers. Background Technology

[0002] In power transmission and distribution systems, steel pipe towers serve as crucial structures supporting high-voltage transmission lines, and their stability and safety are paramount to ensuring power supply. However, during long-term operation, steel pipe towers are inevitably affected by wind-induced vibrations. These vibrations not only lead to structural fatigue and reduced service life, but can also cause structural failure in extreme cases, resulting in serious safety accidents and economic losses. Therefore, effectively suppressing wind-induced vibrations in steel pipe towers has become a pressing technical challenge for the power industry.

[0003] Traditionally, wind-induced vibration suppression of steel pipe towers has primarily relied on structural design optimization and the application of passive damping devices. Structural design optimization increases the structure's natural frequency by increasing stiffness and adjusting mass distribution, thereby reducing resonance with wind-induced vibration frequencies. However, this method is costly to retrofit existing steel pipe towers and has limited effectiveness. Passive damping devices, such as tuned mass dampers (TMDs) and aerodynamic dampers, achieve vibration reduction by absorbing or dissipating vibrational energy. However, these devices are typically designed for specific frequencies, and their vibration reduction effect decreases significantly or even fails when the wind-induced vibration frequency changes.

[0004] With the development of intelligent control technology, intelligent suppression systems are gradually becoming a new direction for suppressing wind-induced vibration of steel pipe towers. These systems integrate advanced sensors such as accelerometers and fiber optic strain sensors to capture the vibration parameters of the steel pipe tower in real time. They then use intelligent algorithms to analyze and process the vibration data, thereby driving actuators (such as dampers) to make precise adjustments, so as to effectively suppress wind-induced vibration.

[0005] However, existing intelligent damping systems still face many challenges in practical applications. Sudden changes in wind speed can cause the vibration frequency of steel pipe towers to jump rapidly within a short period. To respond quickly to this frequency jump, the intelligent damper frequently adjusts the current of the magnetorheological spring. However, the strong alternating electromagnetic field generated during this process may couple into the sensor's signal transmission line through electromagnetic induction, producing interference signals. These interference signals superimpose with the actual vibration signal, causing a continuous and slow shift in sensor data, i.e., sensor drift. Sensor drift not only fails to keep up with the rhythm of frequency jumps but may also cause deviations in the adjustment direction due to data distortion, severely affecting the vibration damping effect. Summary of the Invention

[0006] The purpose of this application is to overcome the deficiencies in the prior art and provide a method, apparatus, equipment and storage medium for suppressing wind-induced vibration of steel pipe towers.

[0007] This application provides a method for suppressing wind-induced vibration of steel pipe towers, applied to an intelligent suppression system for wind-induced vibration of steel pipe towers. The intelligent suppression system for wind-induced vibration of steel pipe towers includes an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper. The method includes:

[0008] Generating vibration characterization factors includes: acquiring acceleration signals from the accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database by the processing unit; determining a second factor based on the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors by the processing unit, based on a first factor determined by the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors; and determining a second factor based on the frequency-time continuity, frequency-time continuity reference values, and frequency-time continuity characteristic influence factors; and calculating the vibration characterization factors based on the first factor, the second factor, and the third factor.

[0009] Generating drift compensation values ​​includes: acquiring reliable data from the acceleration sensor, acquiring detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, and extracting drift compensation values ​​by the processing unit based on the sensor drift value through a preset mapping rule.

[0010] The processing unit corrects the acceleration signal based on the drift compensation value to obtain a corrected acceleration signal, determines the number of current gradient decompositions based on the vibration characterization factor, adjusts the damper current based on the number of current gradient decompositions and the corrected acceleration signal, and the damper generates a damping force based on the adjusted current.

[0011] Optionally, acquiring reliable data from the acceleration sensor includes:

[0012] The raw acceleration signal is acquired from the acceleration sensor;

[0013] The processing unit extracts the original acceleration signal within a fixed time window;

[0014] The processing unit calculates the cross-correlation coefficient between the captured signal and the reference signal;

[0015] When the cross-correlation coefficient is greater than or equal to a preset cross-correlation coefficient threshold, the intercepted signal is recorded as reliable data.

[0016] Optionally, the step of obtaining the corrected acceleration signal by the processing unit based on the drift compensation value includes:

[0017] The drift compensation value is invoked by the processing unit;

[0018] The processing unit performs an addition operation on the acceleration signal, where the addend is the drift compensation value, to generate a corrected acceleration signal.

[0019] Optionally, determining the number of current gradient decompositions based on the vibration characterization factor includes:

[0020] The processing unit extracts a preset interval mapping table, which stores the correspondence between vibration characterization factor intervals and gradient decomposition times.

[0021] The processing unit matches the vibration characterization factor to the target interval in the interval mapping table;

[0022] The processing unit extracts the gradient decomposition number corresponding to the target interval.

[0023] Optionally, the processing unit extracts a drift compensation value based on the sensor drift value using a preset mapping rule, including:

[0024] The processing unit extracts a preset interval mapping table, which stores the correspondence between sensor drift value intervals and drift compensation values.

[0025] The processing unit matches the sensor drift value to the target interval in the interval mapping table;

[0026] The processing unit extracts the drift compensation value corresponding to the target interval.

[0027] Optionally, adjusting the damper current based on the number of current gradient decompositions and the corrected acceleration signal includes:

[0028] The processing unit calculates the current change value;

[0029] The processing unit divides the current change value into multiple current increments based on the number of gradient decompositions.

[0030] The processing unit sequentially adds the multiple current increments to the current value of the damper to generate the adjusted damper current.

[0031] Optionally, after the damper generates the damping force according to the adjusted current, the method further includes:

[0032] The processing unit obtains transient characteristic indicators of the vibration frequency;

[0033] When the transient characteristic index is greater than or equal to the transient characteristic index threshold, the processing unit triggers the adjustment of the damper parameters.

[0034] This application also provides a wind-induced vibration suppression device for steel pipe towers, applied to an intelligent wind-induced vibration suppression system for steel pipe towers. The intelligent wind-induced vibration suppression system for steel pipe towers includes an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper. The method includes:

[0035] The first generation module generates vibration characterization factors, including: acquiring acceleration signals from the accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database by the processing unit; determining a second factor based on the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors by the processing unit, based on a first factor determined by the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors; and determining a second factor based on the frequency-time continuity, frequency-time continuity reference values, and frequency-time continuity characteristic influence factors; and calculating the vibration characterization factors based on the first factor, the second factor, and the third factor.

[0036] The second generation module generates drift compensation values, including: acquiring reliable data from the acceleration sensor, acquiring detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, and extracting the drift compensation value by the processing unit according to the sensor drift value through a preset mapping rule.

[0037] The execution module, through the processing unit, corrects the acceleration signal based on the drift compensation value to obtain the corrected acceleration signal, determines the number of current gradient decompositions based on the vibration characterization factor, adjusts the damper current based on the number of current gradient decompositions and the corrected acceleration signal, and the damper generates damping force based on the adjusted current.

[0038] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0039] This application provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the above-described method.

[0040] The beneficial effects of this application are:

[0041] This application provides a method for suppressing wind-induced vibration of steel pipe towers, applied to an intelligent suppression system for wind-induced vibration of steel pipe towers. The intelligent suppression system includes an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper. The method includes: generating vibration characterization factors, including: acquiring acceleration signals from the acceleration sensor; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset reference values ​​for energy concentration, frequency bandwidth, and frequency-time continuity from a database by the processing unit; and determining a first factor based on the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors by the processing unit using the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors. The second factor; and the second factor determined by the frequency-time continuity, frequency-time continuity reference value, and frequency-time continuity characteristic influence factor; calculate the vibration characterization factor based on the first factor, the second factor, and the third factor; generate drift compensation value, including: obtaining reliable data from the acceleration sensor, obtaining detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, extracting the drift compensation value by the processing unit according to the sensor drift value through a preset mapping rule; correcting the acceleration signal by the processing unit according to the drift compensation value to obtain the corrected acceleration signal, determining the number of current gradient decompositions according to the vibration characterization factor, adjusting the damper current according to the number of current gradient decompositions and the corrected acceleration signal, and generating damping force by the damper according to the adjusted current. This application ensures data reliability and system stability by accurately identifying vibration, dynamically adjusting damper parameters, and correcting sensor drift, achieving rapid response and effective suppression of wind-induced vibration of steel pipe towers, and comprehensively ensuring the safe and stable operation of steel pipe towers under various vibration scenarios. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the process for suppressing wind-induced vibration of steel pipe towers in this application;

[0043] Figure 2 This is a schematic diagram of the wind-induced vibration suppression device for steel pipe towers in this application. Detailed Implementation

[0044] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is to be understood that various forms of implementation of the present disclosure are intended and should not be limited to the embodiments set forth herein. Rather, the embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0045] Please refer to Figure 1 As shown, this application provides a method for suppressing wind-induced vibration of steel pipe towers, applied to an intelligent suppression system for wind-induced vibration of steel pipe towers, to solve the problem of suppressing wind-induced vibration of steel pipe towers. The system includes an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper. The method includes:

[0046] S101. Generating vibration characterization factors includes: acquiring acceleration signals from an accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by a processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from a database by the processing unit; and calculating the vibration characterization factors based on the ratio of energy concentration to energy concentration reference value multiplied by the energy concentration characteristic influence factor, the ratio of frequency bandwidth reference value to frequency bandwidth plus one multiplied by the frequency bandwidth characteristic influence factor, and the ratio of frequency-time continuity to frequency-time continuity reference value multiplied by the frequency-time continuity characteristic influence factor, according to the first factor, the second factor, and the third factor.

[0047] Obtaining acceleration signals from accelerometers refers to acquiring time-domain acceleration data generated by vibration through accelerometers installed on the steel pipe tower. This signal contains the raw information of the steel pipe tower's vibration.

[0048] The analysis of the energy concentration, frequency bandwidth, and frequency-time continuity of an acceleration signal by the processing unit refers to the signal processing and analysis performed by the processing unit on the acceleration signal.

[0049] Energy concentration indicates the degree to which vibration energy is concentrated in the dominant frequency component. The time-domain vibration signal is converted into a spectrum through Fourier transform, the dominant frequency component is identified by the peak value of the spectrum, and then the ratio of the sum of the energy of these dominant frequency components to the total energy of the signal is calculated.

[0050] Frequency bandwidth represents the effective width of the main frequency component. It is determined by the energy peak point through spectrum analysis, and then the upper and lower frequency points corresponding to the peak energy decaying to half are taken. The interval between the two points is the effective bandwidth.

[0051] Frequency-time continuity represents the stability of frequency changes over time. The time-frequency matrix is ​​obtained through continuous wavelet transform, and the instantaneous frequency corresponding to each moment is extracted to form an instantaneous frequency curve. Then, the frequency change rate of the curve is calculated, and the variance of all change rates is calculated to obtain the frequency-time continuity.

[0052] The processing unit extracts preset reference values ​​for energy concentration, frequency bandwidth, and frequency time continuity from the database. This means obtaining pre-stored benchmark values ​​from the system database. These reference values ​​are set based on historical data or theoretical calculations and are used to compare with real-time data. The energy concentration reference value is the ideal or average value of energy concentration, the frequency bandwidth reference value is the typical value of frequency bandwidth, and the frequency time continuity reference value is the standard value of frequency time continuity.

[0053] The processing unit extracts preset energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database. These influence factors are used to weight the contribution of different parameters to the vibration characterization factor, and their values ​​range from 0 to 1. Furthermore, the sum of the energy concentration characteristic influence factor, frequency bandwidth characteristic influence factor, and frequency-time continuity characteristic influence factor is 1.

[0054] The vibration characterization factor calculated by the processing unit refers to the quantitative calculation using a formula. The formula is: F equals energy concentration divided by the energy concentration reference value multiplied by the energy concentration characteristic influence factor, plus the frequency bandwidth reference value divided by the frequency bandwidth plus one multiplied by the frequency bandwidth characteristic influence factor, plus the frequency time continuity divided by the frequency time continuity reference value multiplied by the frequency time continuity characteristic influence factor.

[0055] The formula is expressed as:

[0056]

[0057] in, Indicates the first factor. Indicates the second factor. This indicates the third factor.

[0058] F represents the vibration characterization factor of the principal vibration frequency, and Q represents the energy concentration. The value represents the energy concentration reference value, m represents the energy concentration characteristic influencing factor, and W represents the frequency bandwidth. Here, j represents the frequency bandwidth reference value, j represents the frequency bandwidth characteristic influencing factor, and R represents the frequency time continuity. This represents the reference value for frequency-time continuity, and u represents the influence factor of frequency-time continuity characteristics.

[0059] The comprehensive calculation using the above formulas ensures that the vibration characterization factor accurately reflects the significance of steel pipe tower vibration, which is then used for subsequent adjustment strategy decisions. For example, when the energy concentration is high, it indicates that the vibration energy is concentrated near a single dominant frequency, the vibration signal exhibits a stable sine wave with pure frequency components, and the vibration characterization factor increases; when the frequency bandwidth is narrow, there are few frequency components in the signal, the characteristic frequency is single and clear, and the vibration characterization factor increases; when the frequency-time continuity is good, the characteristic frequency is stable over time, facilitating long-term monitoring, and the vibration characterization factor increases.

[0060] Before generating vibration characterization factors, the processing unit performs vibration frequency set generation and main vibration frequency determination processes. The processing unit acquires acceleration signals from accelerometers, collects time-frequency domain parameters of the steel pipe tower's acceleration signals, and obtains the vibration frequency set. Time-domain analysis calculates parameters such as peak value and root mean square value using a sliding window to preliminarily determine the time-domain characteristics of the vibration. Frequency-domain analysis converts the time-domain signal into a frequency-domain spectrum using a fast Fourier transform, obtaining the amplitude corresponding to different frequencies and identifying all frequency components contained in the signal. For non-stationary signals such as wind-induced vibration, wavelet transform is combined to locate the occurrence time and duration of each frequency component on the time-frequency two-dimensional plane, forming a vibration frequency set containing multiple frequency values.

[0061] The processing unit extracts preset vibration frequency thresholds from the database. These thresholds are used to filter out secondary frequencies. Vibration frequencies within the set that are greater than the threshold are designated as primary vibration frequencies, thus focusing on the core frequencies that truly dominate the structural vibration. The processing unit iterates through the vibration frequency set to obtain each primary vibration frequency.

[0062] Next, the processing unit collects parameters for each principal vibration frequency and analyzes the vibration characterization factor for each principal vibration frequency. After sorting the vibration characterization factors of each principal vibration frequency from largest to smallest, the processing unit records the principal vibration frequency corresponding to the maximum value of the vibration characterization factor as the vibration frequency of the steel pipe tower. For example, by sorting and selecting the maximum value, it ensures that subsequent adjustment strategies are based on the most significant vibration frequency, avoiding interference from secondary frequencies.

[0063] S102. Generating drift compensation values ​​includes: acquiring reliable data from an accelerometer, acquiring detection data from a fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by a processing unit to obtain sensor drift values, and extracting drift compensation values ​​by a processing unit based on sensor drift values ​​through a preset mapping rule.

[0064] Obtaining reliable data from an accelerometer refers to the processing unit acquiring raw acceleration signals from the accelerometer and processing them to determine data reliability. Specifically, this includes the processing unit extracting raw acceleration signals within a fixed time window. The fixed time window is a sampling period set based on the vibration cycle to ensure data synchronization.

[0065] The processing unit calculates the cross-correlation coefficient between the extracted signal and the reference signal. The cross-correlation coefficient is used to evaluate the signal similarity, and the calculation formula is as follows:

[0066]

[0067] Where r represents the cross-correlation coefficient, x(i) represents the acceleration signal value collected by the sensor signal at the i-th sampling point, y(i) represents the acceleration signal value collected by the reference signal at the i-th sampling point, x and y are the mean values ​​of the two signals respectively, i=1,2,3,...,N, and N represents the number of sampling points.

[0068] When the cross-correlation coefficient is greater than or equal to the preset cross-correlation coefficient threshold, the intercepted signal is recorded as reliable data. The preset cross-correlation coefficient threshold is a preset value extracted from the database and is used to determine whether the signal is reliable.

[0069] The reference signal is the sensor signal with the smallest zero drift in static and dynamic tests preset in the database. Obtaining detection data from the fiber optic strain sensor refers to the processing unit reading strain-related data from the fiber optic strain sensor. This data is the raw or pre-processed strain value detected, converted, and stored in the database by the sensor, reflecting the deformation of the steel pipe tower.

[0070] The absolute difference between the reliable data and the detected data calculated by the processing unit refers to subtracting the absolute value of the detected data of the fiber optic strain sensor from the reliable data of the accelerometer to obtain the sensor drift value. The sensor drift value represents the degree of deviation between the sensor output and the actual physical quantity and is used to quantify the drift error.

[0071] The processing unit extracts drift compensation values ​​based on sensor drift values ​​using preset mapping rules. This means the processing unit converts sensor drift values ​​into compensation values ​​using preset mapping rules. The preset mapping rules are pre-defined correspondences between sensor drift value ranges and drift compensation values, stored in a range mapping table. The processing unit matches the sensor drift values ​​to the target range in the range mapping table and extracts the corresponding drift compensation value. The larger the sensor drift value, the further the sensor output deviates from the true physical quantity, and therefore the larger the extracted drift compensation value, to offset the drift effect. For example, a large sensor drift value indicates severe sensor data distortion, requiring a larger compensation value for correction; conversely, a small sensor drift value results in a smaller compensation value, avoiding overcompensation.

[0072] Before generating drift compensation values, the processing unit performs a signal spatiotemporal consistency alignment process: the processing unit collects the same type of miniature triaxial accelerometer at the same cross section of the steel pipe tower to form a monitoring group, and prioritizes the cross section with the most significant vibration response, such as the top of the tower, to avoid measurement errors caused by hardware differences.

[0073] The processing unit corrects the installation angle deviation through direction cosine calibration. It measures the angle between the actual installation direction of each sensor and the ideal coordinate system using a gyroscope or laser positioning device. Based on the measured angle parameters, it establishes a direction cosine matrix describing the transformation relationship between the actual coordinate system and the ideal coordinate system. It multiplies the raw acceleration data collected by the sensor with the direction cosine matrix and eliminates the cross-interference components introduced by the angle deviation through coordinate transformation.

[0074] The processing unit synchronously performs phase interpolation algorithm to correct timing, confirms phase timing error by comparing timestamps, and for signals with timing deviations, inserts equivalent vibration data from other sensors within their lag time between the original sampling points to ensure that the sampling times of the two signals are strictly aligned.

[0075] The processing unit extracts preset timing error thresholds and reference signals from the database, compares the phase of each signal with the reference signal to obtain the timing error of each phase. The phase timing error is calculated through cross-correlation analysis, using the following formula:

[0076]

[0077] in, Due to time deviation, Let f be the phase difference between the signals from each sensor, and f be the current vibration frequency.

[0078] If the timing error of a certain phase is less than the timing error threshold, the processing unit generates an alignment signal. If the timing error of a certain phase is greater than or equal to the timing error threshold, the processing unit generates a warning message such as "Attention! Phase timing error exceeds the limit".

[0079] Afterwards, the processing unit executes the complete sensor drift determination process, calculates the cross-correlation coefficient of each sensor signal, extracts the preset cross-correlation coefficient threshold from the database, and if the cross-correlation coefficient of a certain sensor signal is less than the cross-correlation coefficient threshold, the sensor drift determination is recorded as a significant drift abnormal signal, and the drift adjustment strategy is recorded as being removed from the monitoring group. If the cross-correlation coefficient is greater than or equal to the threshold, it is recorded as a non-significant drift abnormal signal, and the drift adjustment strategy is recorded as being retained data.

[0080] The processing unit verifies the amplitude deviation of the remaining signals after elimination, calculates the average amplitude of all remaining signals within the same time window, and calculates the amplitude deviation of each remaining signal from the average amplitude using the following formula:

[0081]

[0082] in, Indicates the average amplitude. The value represents the signal amplitude at that point, and h represents the amplitude deviation.

[0083] The processing unit extracts the preset amplitude deviation threshold from the database. If the amplitude deviation is less than or equal to the threshold, the sensor drift determination is recorded as a drift non-abnormal signal, and the drift adjustment strategy is recorded as reserved data. If the amplitude deviation is greater than the threshold, the sensor drift determination is recorded as a drift abnormal signal, and the drift adjustment strategy is recorded as calling historical similar working condition data temporarily.

[0084] When the drift adjustment strategy is to retain data, the processing unit performs cross-validation and determines the system signal transmission mode. Specifically, this includes: extracting detection data from the fiber Bragg grating strain sensor; obtaining the sensor drift value based on reliable data from the accelerometer and the fiber Bragg grating strain sensor; when the duration of the sensor drift value is greater than or equal to the first-order vibration period, the system signal transmission mode is designated as model-driven mode, and a structural vibration theory model constructed based on the steel pipe tower design parameters is initiated. Reliable sensor data before the drift occurs is used as the initial conditions of the model, and the model parameters are fine-tuned using the vibration signal predicted by the model and a small amount of reliable sensor data; when the duration of the sensor drift value is less than the first-order vibration period, the system signal transmission mode is designated as sensor feedback mode, and the data is corrected in real time using drift compensation values. For example, after cross-validation ensures data reliability, the system selects the transmission mode based on the drift duration to avoid malfunctions.

[0085] S103. Based on the vibration characterization factor and drift compensation value, the processing unit corrects the acceleration signal according to the drift compensation value to obtain the corrected acceleration signal. Based on the vibration characterization factor, the number of current gradient decompositions is determined. Based on the number of current gradient decompositions, the damper current is adjusted, and the damper generates damping force according to the adjusted current.

[0086] The processing unit corrects the acceleration signal based on the drift compensation value to obtain the corrected acceleration signal. This means that the processing unit calls the drift compensation value, performs an addition operation on the acceleration signal, and the addend is the drift compensation value to generate the corrected acceleration signal. This cancels out the error caused by sensor drift and ensures that the data truly reflects the vibration state.

[0087] The process of determining the number of current gradient decompositions based on the vibration characterization factors by the processing unit involves extracting a preset interval mapping table. This table stores the correspondence between vibration characterization factor intervals and gradient decomposition numbers. The processing unit matches the vibration characterization factors to the target intervals in the interval mapping table and extracts the corresponding gradient decomposition numbers for those intervals. The larger the vibration characterization factor, the more significant the vibration of the steel pipe tower.

[0088] To counteract vibration, a larger change in current is required, but to prevent excessive current change from causing sensor drift, a larger number of gradient decompositions are needed to achieve gradual adjustment.

[0089] The adjustment of the damper current by the processing unit based on the number of current gradient decompositions means that the processing unit calculates the current change value, which is the difference between the target current value and the current current value of the damper. The target current value is derived by looking up the target damping coefficient based on the vibration frequency of the steel pipe tower. The processing unit divides the current change value into multiple current increments based on the number of gradient decompositions, and then sequentially adds these multiple current increments to the current current value of the damper to generate the adjusted damper current. This step-by-step adjustment avoids sudden current changes and ensures system stability.

[0090] The damping force generated by the damper based on the adjusted current refers to the damper generating a damping force through its electromagnetic or hydraulic mechanism based on the input current value. This damping force acts on the steel pipe tower to suppress vibration. For example, when the vibration characterization factor is large, the current change value is large, but through multiple incremental adjustments, the transition is smoothed; after the drift compensation value is corrected, the sensor data is more accurate, and the current adjustment is more precise. The entire process ensures the effective generation of damping force, achieving intelligent suppression.

[0091] Furthermore, the processing unit acquires the transient characteristic index of the vibration frequency; when the transient characteristic index is greater than or equal to the transient characteristic index threshold, the processing unit triggers the adjustment of the damper parameters.

[0092] After the damping force is generated, the processing unit further acquires transient characteristic indicators of the vibration frequency to determine the suppression effect. The transient characteristic indicators of the vibration frequency acquired by the processing unit refer to the transient characteristic parameters of the vibration frequency analyzed by the processing unit, including the instantaneous frequency change of the dual-frequency differential, the degree of energy transfer, and the degree of time-domain waveform change.

[0093] The dual-frequency differential instantaneous frequency change is decomposed into the vibration signal and the reference signal using the Hilbert-Huang transform to obtain their analytical signals. The instantaneous frequencies of the two signals are extracted, and the instantaneous frequency difference between the two signals is calculated.

[0094] The energy transfer degree is obtained by using short-time Fourier transform to obtain the time spectrum of the signal, dividing the steady-state interval and the transient interval before the transient occurs, and calculating the difference between the energy proportion of the main frequency band in the steady-state interval and the energy proportion of the new frequency band in the transient interval.

[0095] The time-domain waveform abrupt change is calculated by measuring the amplitude standard deviation within a sliding window of the time-domain signal. When the increment of the standard deviation at a certain moment exceeds the threshold, it is marked as a potential abrupt change point. At the abrupt change point, the absolute value of the average slope difference of the signal length before and after is calculated.

[0096] The processing unit extracts preset reference values ​​from the database for dual-frequency differential instantaneous frequency change, energy transfer degree, and time-domain waveform change degree, as well as influence factors for dual-frequency differential instantaneous frequency change, energy transfer degree, and time-domain waveform change degree. These influence factors range from 0 to 1 and their sum is 1. The processing unit calculates the transient characteristic index using the following formula:

[0097]

[0098] Where G represents the transient characteristic index of the vibration frequency, and O represents the instantaneous frequency change of the dual-frequency differential. This represents the reference value for instantaneous frequency abrupt change in dual-frequency differential frequency modulation, 'a' represents the characteristic influencing factor of instantaneous frequency abrupt change in dual-frequency differential frequency modulation, and 'P' represents the degree of energy transfer. The value represents the reference value for the degree of energy transfer, s represents the characteristic influencing factor of the degree of energy transfer, and L represents the time-domain waveform abrupt change. d represents the reference value for the time-domain waveform abrupt change, and d represents the influence factor of the time-domain waveform abrupt change characteristic.

[0099] When the transient characteristic index is greater than or equal to the transient characteristic index threshold, the processing unit triggers damper parameter adjustment. The transient characteristic index threshold is a preset value extracted from the database and used to determine whether adjustment is needed. Triggering damper parameter adjustment means that the processing unit initiates a parameter optimization process, including extracting the initial stiffness and damping coefficient of the damper, extracting environmental correction coefficients based on the transient characteristic index, adjusting the initial parameters based on the environmental correction coefficient to obtain preliminary parameters, and then using a model predictive control algorithm to perform parameter optimization, generating updated damper parameters to ensure the damping force remains effective. For example, when the transient characteristic index is large, it indicates that the vibration frequency fluctuates violently, and the damper parameters need to be adjusted to adapt to the changes; when the index is small, no adjustment is needed.

[0100] The processing unit first determines the vibration frequency adjustment strategy based on the overall system interaction logic. The processing unit then calculates the vibration frequency deviation value based on the steel pipe tower's vibration frequency and the vibration frequency verification value. The vibration frequency verification value is extracted from the program log and is the steel pipe tower's vibration frequency at the same moment in the previous cycle. The vibration frequency deviation value reflects the dynamic change amplitude of the vibration frequency.

[0101] The processing unit extracts the deviation tolerance range of the vibration frequency deviation value and the first-order vibration period of the steel pipe tower. The deviation tolerance range is a threshold range set based on the structural safety threshold of the steel pipe tower, which distinguishes between normal fluctuations, effective jumps or disturbances in the vibration frequency. The first-order vibration period of the steel pipe tower is the time it takes for the steel pipe tower to complete one complete vibration at its first natural frequency.

[0102] If the vibration frequency deviation is greater than or equal to the deviation tolerance range and the vibration frequency duration is greater than or equal to the first-order vibration period of the steel pipe tower, it is determined to be an effective jump. The vibration frequency adjustment strategy is recorded as damper current adjustment. The damper current change value is extracted based on the vibration frequency of the steel pipe tower. The gradient decomposition number is determined based on the vibration characterization factor of the steel pipe tower vibration frequency. The vibration frequency duration is obtained from the frequency domain analysis to obtain the duration corresponding to the vibration frequency of the steel pipe tower.

[0103] If the vibration frequency deviation is within the deviation tolerance range, the vibration frequency adjustment strategy is recorded as system adaptive adjustment. The system continuously calculates the stiffness correction and damping coefficient correction based on the real-time collected wind speed and acceleration signals using the model predictive control algorithm.

[0104] If the vibration frequency deviation is greater than or equal to the upper limit of the deviation tolerance range but the duration of the vibration frequency is less than the first vibration period, the vibration frequency adjustment strategy is recorded as non-start adjustment.

[0105] If the vibration frequency deviation is less than the lower limit of the deviation tolerance range but the duration of the vibration frequency is less than the first-order vibration period, the vibration frequency adjustment strategy is recorded as system adaptive adjustment.

[0106] If the vibration frequency deviation is less than the lower limit of the deviation tolerance range and the duration of the vibration frequency is greater than or equal to the first-order vibration period, the vibration frequency adjustment strategy is recorded as "stop adjustment".

[0107] For example, the subsequent sensor drift adjustment unit is triggered only when the strategy is damper current regulation, ensuring the correctness of the conditional logic. Afterwards, the processing unit performs a damping force suppression effect determination. Based on the damping force and vibration velocity, it obtains the damping compensation value, multiplies the damping force by the vibration velocity to obtain the damper's instantaneous power, and records it as the damping compensation value. It also extracts the energy consumed by the damper in one vibration cycle and records it as the effective energy consumption value. When the damping compensation value is less than or equal to the effective energy consumption value, the damping force suppression effect is determined to be effective suppression, and the damping force compensation mechanism is recorded as not compensating for damping force. When the damping compensation value is greater than the effective energy consumption value, the damping force suppression effect is determined to be ineffective suppression, and the damping force compensation mechanism is recorded as compensating for damping force. A limited PID algorithm is used to obtain the compensation current based on the actual output damping force and the target damping force. The resistance deviation value is calculated as the output adjustment amount, quickly responding to deviations, accumulating historical deviations, predicting deviation change trends, and setting upper and lower limit thresholds for the compensation current.

[0108] For example, when the damping offset value is greater than the effective energy dissipation value, the compensation current is calculated and limited by the inverse model to avoid overshoot.

[0109] The processing unit also improves the context for calculating transient characteristic indicators of vibration frequency. Dual-frequency differential instantaneous frequency change refers to the sudden change in the instantaneous frequency difference between two frequency components at a certain moment. The larger the dual-frequency differential instantaneous frequency change, the higher the frequency jump rate, and the more significant the frequency change in transient characteristics. Energy transfer degree refers to the rapid migration of vibration energy from one frequency / time interval to another in the time-frequency domain. The greater the energy transfer degree, the more thorough the energy transfer from the steady-state distribution region to the transient region, the higher the energy concentration in the transient interval, and the more significant the response intensity. Time-domain waveform abrupt change refers to the drastic change in the amplitude, slope, or curvature of the time-domain signal at a certain moment. The more severe the time-domain waveform abrupt change, the stronger the instantaneous impact on the system, forcing energy to transfer from the original steady-state frequency domain to the new frequency domain.

[0110] Please refer to Figure 2 As shown, this application also provides a wind-induced vibration suppression device for steel pipe towers, applied to an intelligent wind-induced vibration suppression system for steel pipe towers. The intelligent wind-induced vibration suppression system for steel pipe towers includes an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper. The method includes:

[0111] The first generation module 201 generates vibration characterization factors, including: acquiring acceleration signals from the accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database by the processing unit; determining a second factor based on a first factor determined by the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors, and then determining a second factor based on the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors; and calculating the vibration characterization factors based on the second factor determined by the frequency-time continuity, frequency-time continuity reference values, and frequency-time continuity characteristic influence factors, according to the first factor, the second factor, and the third factor.

[0112] The second generation module 202 generates drift compensation values, including: acquiring reliable data from the acceleration sensor, acquiring detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, and extracting the drift compensation value by the processing unit according to the sensor drift value through a preset mapping rule.

[0113] The execution module 203 executes the acceleration signal obtained by the processing unit based on the drift compensation value, determines the number of current gradient decompositions based on the vibration characterization factor, adjusts the damper current based on the number of current gradient decompositions and the corrected acceleration signal, and generates damping force by the damper based on the adjusted current.

[0114] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0115] This application provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the above-described method.

[0116] The above description of the embodiments is provided to enable those skilled in the art to understand and apply this application. Those skilled in the art will readily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without inventive effort. Therefore, this application is not limited to the above embodiments, and any improvements and modifications made to this application based on the disclosure thereof should be within the scope of protection of this application.

Claims

1. A method for suppressing wind-induced vibration of steel pipe towers, characterized in that, An intelligent system for suppressing wind-induced vibration of steel pipe towers is applied, the system comprising an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper, the method comprising: Generating vibration characterization factors includes: acquiring acceleration signals from the accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database by the processing unit; determining a second factor based on the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors by the processing unit, based on a first factor determined by the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors; determining a third factor based on the frequency-time continuity, frequency-time continuity reference values, and frequency-time continuity characteristic influence factors; and calculating the vibration characterization factors based on the first, second, and third factors. Generating drift compensation values ​​includes: acquiring reliable data from the acceleration sensor, acquiring detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, and extracting drift compensation values ​​by the processing unit based on the sensor drift value through a preset mapping rule. The processing unit corrects the acceleration signal based on the drift compensation value to obtain a corrected acceleration signal, determines the number of current gradient decompositions based on the vibration characterization factor, adjusts the damper current based on the number of current gradient decompositions and the corrected acceleration signal, and the damper generates a damping force based on the adjusted current.

2. The method according to claim 1, characterized in that, The acquisition of reliable data from the acceleration sensor includes: The raw acceleration signal is acquired from the acceleration sensor; The processing unit extracts the original acceleration signal within a fixed time window; The processing unit calculates the cross-correlation coefficient between the captured signal and the reference signal; When the cross-correlation coefficient is greater than or equal to a preset cross-correlation coefficient threshold, the intercepted signal is recorded as reliable data.

3. The method according to claim 1, characterized in that, The process of obtaining the corrected acceleration signal by the processing unit based on the drift compensation value includes: The drift compensation value is invoked by the processing unit; The processing unit performs an addition operation on the acceleration signal, where the addend is the drift compensation value, to generate a corrected acceleration signal.

4. The method according to claim 1, characterized in that, The step of determining the number of current gradient decompositions based on the vibration characterization factor includes: The processing unit extracts a preset interval mapping table, which stores the correspondence between vibration characterization factor intervals and gradient decomposition times. The processing unit matches the vibration characterization factor to the target interval in the interval mapping table; The processing unit extracts the gradient decomposition number corresponding to the target interval.

5. The method according to claim 1, characterized in that, The processing unit extracts drift compensation values ​​based on the sensor drift values ​​using a preset mapping rule, including: The processing unit extracts a preset interval mapping table, which stores the correspondence between sensor drift value intervals and drift compensation values. The processing unit matches the sensor drift value to the target interval in the interval mapping table; The processing unit extracts the drift compensation value corresponding to the target interval.

6. The method according to claim 1, characterized in that, The step of adjusting the damper current based on the number of current gradient decompositions and the corrected acceleration signal includes: The processing unit calculates the current change value; The processing unit divides the current change value into multiple current increments based on the number of gradient decompositions. The processing unit sequentially adds the multiple current increments to the current value of the damper to generate the adjusted damper current.

7. The method according to claim 1, characterized in that, After the damper generates damping force according to the adjusted current, the process further includes: The processing unit obtains transient characteristic indicators of the vibration frequency; When the transient characteristic index is greater than or equal to the transient characteristic index threshold, the processing unit triggers the adjustment of the damper parameters.

8. A device for suppressing wind-induced vibration of steel pipe towers, characterized in that, An intelligent system for suppressing wind-induced vibration of steel pipe towers is applied, the system comprising an acceleration sensor, a fiber optic strain sensor, a processing unit, and a damper, the method comprising: The first generation module generates vibration characterization factors, including: acquiring acceleration signals from the accelerometer; analyzing the energy concentration, frequency bandwidth, and frequency-time continuity of the acceleration signals by the processing unit; extracting preset energy concentration reference values, frequency bandwidth reference values, frequency-time continuity reference values, energy concentration characteristic influence factors, frequency bandwidth characteristic influence factors, and frequency-time continuity characteristic influence factors from the database by the processing unit; determining a second factor based on the frequency bandwidth reference values, frequency bandwidth, and frequency bandwidth characteristic influence factors by the processing unit, based on a first factor determined by the energy concentration, energy concentration reference values, and energy concentration characteristic influence factors; and determining a second factor based on the frequency-time continuity, frequency-time continuity reference values, and frequency-time continuity characteristic influence factors; and calculating the vibration characterization factors based on the first factor, the second factor, and the third factor. The second generation module generates drift compensation values, including: acquiring reliable data from the acceleration sensor, acquiring detection data from the fiber optic strain sensor, calculating the absolute difference between the reliable data and the detection data by the processing unit to obtain the sensor drift value, and extracting the drift compensation value by the processing unit according to the sensor drift value through a preset mapping rule. The execution module, through the processing unit, corrects the acceleration signal based on the drift compensation value to obtain the corrected acceleration signal, determines the number of current gradient decompositions based on the vibration characterization factor, adjusts the damper current based on the number of current gradient decompositions and the corrected acceleration signal, and the damper generates damping force based on the adjusted current.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in any one of claims 1-7.

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