Acceleration sensor sampling rate determination method and device for power transmission line modal test, terminal equipment and storage medium

Abstract

The invention discloses an acceleration sensor sampling rate determination method and device for a power transmission line modal test, terminal equipment and a storage medium, and belongs to the field of power systems. The method comprises the following steps: calculating to obtain conductor sag, overhead line horizontal tension and conductor fixed port tension according to obtained conductor physical attributes, span and line point cloud data; constructing a power transmission line modal vibration model according to conductor physical attributes, conductor sag, overhead line horizontal tension and conductor fixed port tension, and solving to obtain conductor inherent frequency; performing a test according to the inherent frequency of the wire and a preset test frequency, and determining the highest modal order and the highest effective frequency; the lower limit of the sampling frequency of the sensor is determined according to the highest effective frequency and the preset safety coefficient, the upper limit of the sampling frequency of the sensor is determined according to the preset number of sampling points and the highest effective frequency, and then the sampling frequency range of the sensor is determined.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, apparatus, terminal equipment, and storage medium for determining the sampling rate of an acceleration sensor in a transmission line modal test. Background Technology

[0002] As the core backbone of the power system, overhead transmission lines bear the heavy responsibility of transmitting high-voltage and ultra-high-voltage power. During long-term operation, fatigue wear easily occurs at the connection points between the conductors and fittings due to the influence of light wind vibration. Light wind vibration has a unique frequency-locking effect; within a specific wind speed range, the conductor vibration frequency remains constant. When this frequency coincides with the conductor's natural frequency, resonance occurs, significantly increasing the risk of conductor loss. Therefore, accurately obtaining the conductor's natural vibration frequency is of crucial guiding significance for vibration-damping design.

[0003] Modal testing, as a core technique in vibration analysis, can effectively identify structural modal characteristics, including parameters such as natural frequencies, damping ratios, and mode shapes. For overhead transmission lines, their natural frequencies are key indicators for assessing line vibration characteristics and preventing fatigue fracture. Currently, the natural frequencies of lines are mainly obtained through accelerometers in conjunction with data acquisition systems. However, regardless of whether the sensor is contact-based or non-contact-based, the choice of sampling frequency directly affects data quality. A sampling rate that is too low will lead to the loss of critical data, while a rate that is too high will reduce frequency resolution. Existing accelerometer sampling rates are often set to fixed, high values ​​based on experience, making it impossible to adjust the sampling frequency according to the characteristics of the structure being tested, thus hindering the rapid determination of the sampling frequency. Summary of the Invention

[0004] This invention provides a method, apparatus, terminal device, and storage medium for determining the sampling rate of an accelerometer in modal testing of transmission lines. It can effectively solve the problem that the sampling rate of existing accelerometers is set to a fixed high value based on experience, and the sampling frequency cannot be adjusted according to the characteristics of the structure under test, making it impossible to quickly determine the sampling frequency.

[0005] An embodiment of the present invention provides a method for determining the sampling rate of an accelerometer in a modal test of a transmission line, comprising: Acquire the physical properties of the conductors, span, and point cloud data of the transmission line under test; the physical properties of the conductors include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. Three-dimensional reconstruction is performed based on the physical properties of the conductor, the span, and the line point cloud data to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. Based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, a modal vibration model of the transmission line is constructed, and the natural frequency of the conductor is obtained by solving the model. The highest modal order is determined by conducting tests based on the conductor's natural frequency and a preset test frequency, and the highest effective frequency is determined based on the highest modal order. The lower limit of the sensor sampling frequency is determined based on the highest effective frequency and the preset safety factor, and the upper limit of the sensor sampling frequency is determined based on the preset number of sampling points and the highest effective frequency. The sensor sampling frequency range is determined based on the upper limit and lower limit of the sensor sampling frequency.

[0006] Furthermore, based on the physical properties of the conductor, the span, and the line point cloud data, a three-dimensional reconstruction is performed to calculate the conductor sag, overhead line horizontal tension, and conductor fixed-end tension, including: For each of the aforementioned range lengths, a parabola is fitted using the least squares method to obtain the fitted curve. The centerline of the conductor is reconstructed in three-dimensional space based on the fitted curve to obtain a three-dimensional model of the conductor. Based on the three-dimensional model of the conductor, a chord is generated by connecting the suspension points of the conductor. The lowest point of the conductor on the fitted curve is located directly below the chord, and the vertical distance from the lowest point of the conductor to the chord is taken as the sag of the conductor. The horizontal tension of the overhead line is calculated based on the conductor sag, the conductor specific load, and the corresponding span. The tension at the fixed end of the conductor is calculated based on the horizontal tension of the overhead line, the mass per unit length of the conductor, and the span.

[0007] Furthermore, based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, a modal vibration model of the transmission line is constructed, and the natural frequencies of the conductor are obtained by solving for them, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

[0008] Furthermore, tests are conducted based on the natural frequency of the conductor and a preset test frequency to determine the highest modal order, including: The highest modal order of the current target is obtained by conducting tests based on the natural frequency of the conductor and the preset test frequency. The intersection coverage rate of the conductor's natural frequency and the preset test frequency is calculated based on the highest modal order of the target, and then compared with the intersection coverage rate and the preset coverage threshold. If the intersection coverage is greater than or equal to the coverage threshold, the highest modal order of the target will be taken as the final highest modal order. If the intersection coverage is less than the coverage threshold, reduce the test frequency and retest, and update the highest modal order of the current target.

[0009] Furthermore, the acquisition of the line point cloud data includes: Initial line point cloud data is collected using lidar equipment; Noise filtering is applied to the initial line point cloud data to obtain the final line point cloud data.

[0010] Furthermore, the determination of the preset safety factor includes: Calculate the natural frequency deviation based on the maximum and minimum natural frequencies of the conductor; Calculate the natural frequency fluctuation value based on the natural frequency deviation and the average value of the conductor's natural frequency; The final safety factor is determined based on the inherent frequency fluctuation value and the preset fluctuation threshold.

[0011] As an improvement to the above solution, another embodiment of the present invention provides a device for determining the sampling rate of an acceleration sensor in a transmission line modal test, comprising: The data acquisition module is used to acquire the physical properties of the conductors, span, and point cloud data of the transmission line under test; the physical properties of the conductors include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. The conductor tension calculation module is used to perform three-dimensional reconstruction based on the physical properties of the conductor, the span, and the line point cloud data, and to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. The natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the sag of the conductor, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor. The highest effective frequency determination module is used to conduct tests based on the natural frequency of the conductor and a preset test frequency to determine the highest modal order, and to determine the highest effective frequency based on the highest modal order. The sampling frequency upper and lower limit determination module is used to determine the lower limit of the sensor sampling frequency based on the highest effective frequency and the preset safety factor, and to determine the upper limit of the sensor sampling frequency based on the preset number of sampling points and the highest effective frequency. The sensor sampling frequency determination module is used to determine the sensor sampling frequency range based on the upper limit and lower limit of the sensor sampling frequency.

[0012] Furthermore, the natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

[0013] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a method for determining the sampling rate of an acceleration sensor for a transmission line modal test as described in the above embodiments.

[0014] Another embodiment of the present invention provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the acceleration sensor sampling rate determination method for transmission line modal testing described in the above embodiment.

[0015] By implementing this invention, at least the following beneficial effects are achieved: This invention provides a method, apparatus, terminal equipment, and storage medium for determining the sampling rate of an accelerometer in modal testing of transmission lines. The method first acquires the physical properties, span, and point cloud data of the conductor, then calculates the conductor sag through 3D reconstruction, and derives the horizontal tension of the overhead line and the tension at the fixed end of the conductor based on the physical properties. Finally, a modal model is constructed based on these structural and mechanical parameters to solve for the conductor's natural frequency. The natural frequency of the conductor is used to anchor the vibration range to be covered, ensuring that the sampling rate selection relies entirely on the actual characteristics of the conductor under test, solving the problem of empirical methods and guaranteeing that the sampling frequency matches the structural characteristics of the conductor. Simultaneously, the highest effective frequency is determined by the conductor's natural frequency, and then the upper and lower limits of the sampling frequency are calculated, avoiding excessively high or low sampling rates and effectively balancing the contradiction between data preservation and high resolution. For different conductor types or application scenarios, the sampling frequency range can be derived solely based on the conductor's physical properties, span, and point cloud data. Even if the structural characteristics of the conductor under test change, the sensor's sampling frequency range can be quickly determined. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for determining the sampling rate of an accelerometer in a modal test of a transmission line, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the stress analysis of an overhead transmission line provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an acceleration sensor sampling rate determination device for modal testing of transmission lines provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] See Figure 1 To address the problem in existing technologies where the sampling rate of accelerometers is set to a fixed, high value based on experience, making it impossible to adjust the sampling frequency according to the characteristics of the structure under test and thus hindering the rapid determination of the sampling frequency, an embodiment of the present invention provides a flowchart illustrating a method for determining the sampling rate of an accelerometer in modal testing of transmission lines, comprising: S1. Obtain the physical properties of the conductors, span, and point cloud data of the transmission line under test; the physical properties of the conductors include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. Specifically, conductor physical properties refer to the set of parameters characterizing the inherent physical properties of the conductor itself. These are the foundation for deriving the conductor's mechanical state and vibration characteristics, including conductor mass per unit length, conductor specific load, and conductor stiffness. Conductor mass per unit length is the mass of a unit length of conductor, reflecting the influence of the conductor's own weight on tension and vibration frequency. Conductor specific load is the comprehensive load borne per unit length of conductor, encompassing loads generated by the conductor's own weight, icing, and wind loads, directly affecting the calculation of conductor sag and horizontal tension. Conductor stiffness refers to the conductor's ability to resist bending deformation, determining the higher-order modal characteristics of conductor vibration. Span refers to the horizontal distance between the suspension points of conductors on two adjacent towers in an overhead transmission line, and is a core parameter for constructing the conductor's geometry and vibration model. Line point cloud data represents a set of three-dimensional coordinate points reflecting the spatial morphology of the transmission line, collected by equipment such as lidar. It can accurately reconstruct the actual geometric position of the conductor with millimeter-level accuracy, providing a data foundation for conductor sag measurement.

[0019] Preferably, the acquisition of the line point cloud data includes: Initial line point cloud data is collected using lidar equipment; Noise filtering is applied to the initial line point cloud data to obtain the final line point cloud data.

[0020] S2. Perform three-dimensional reconstruction based on the physical properties of the conductor, the span, and the line point cloud data to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. Preferably, a three-dimensional reconstruction is performed based on the physical properties of the conductor, the span, and the line point cloud data to calculate the conductor sag, overhead line horizontal tension, and conductor fixed-end tension, including: For each of the aforementioned range lengths, a parabola is fitted using the least squares method to obtain the fitted curve. The centerline of the conductor is reconstructed in three-dimensional space based on the fitted curve to obtain a three-dimensional model of the conductor. Based on the three-dimensional model of the conductor, a chord is generated by connecting the suspension points of the conductor. The lowest point of the conductor on the fitted curve is located directly below the chord, and the vertical distance from the lowest point of the conductor to the chord is taken as the sag of the conductor. The horizontal tension of the overhead line is calculated based on the conductor sag, the conductor specific load, and the corresponding span. The tension at the fixed end of the conductor is calculated based on the horizontal tension of the overhead line, the mass per unit length of the conductor, and the span.

[0021] Specifically, the conductor suspension point refers to the hardware connection point on the tower used to fix the conductor, which is the reference point for calculating sag; the chord refers to the straight line connecting the conductor suspension points of two towers, which is the reference baseline for measuring conductor sag; the lowest point of the conductor refers to the point on the fitted parabola with the largest vertical distance from the chord, corresponding to the position of the maximum sag within the conductor span.

[0022] Schematic illustration: For point cloud data of a single span traverse, the x-axis along the span direction and the z-axis perpendicular to the ground are taken. The equation of the parabola is given as z = ax² + bx + c. The coefficients a, b, and c are solved using the least squares method to obtain the fitted curve. Based on the xz coordinates of the fitted parabola, combined with the y-axis (track direction) coordinates of the point cloud, a continuous traverse centerline is generated in three-dimensional space. Two suspension points A and B are marked in the three-dimensional model, generating a chord AB. Substituting the midpoint of the span into the parabola equation, the z-coordinate of the lowest point is obtained. The vertical distance from the lowest point to AB is calculated, which is the sag of the traverse.

[0023] In a preferred embodiment of the present invention, point cloud data of the transmission line is collected by a drone equipped with a lidar, achieving millimeter-level accuracy. The collected point cloud data is processed, and for each span of conductor point cloud, a parabola is fitted using the least squares method. Based on the fitted curve equation, the three-dimensional centerline of the conductor span is reconstructed with high precision in a three-dimensional model, thus obtaining the corresponding conductor point cloud data. In the three-dimensional model, the conductor suspension points A and B on the tower are connected to form a chord AB. The lowest point O on the fitted three-dimensional curve of the conductor is found directly below the chord AB. The vertical distance f from the lowest point O to the chord AB is calculated, which is the maximum sag value for that span, thus obtaining the conductor sag.

[0024] In a preferred embodiment of the present invention, the geometry of an overhead transmission line can be equivalent to an oblique parabola, and its sag can be calculated using the state equation of the oblique parabola.

[0025] In the formula, f is the sag, γ is the conductor specific load under this condition, L is the span of the conductor, and H is the horizontal tension of the overhead line. The horizontal tension of the overhead conductor can be calculated from this formula. The sag has been obtained through laser point cloud measurements, and thus, the value of the horizontal tension H of the overhead conductor can be calculated. Since the towers are of equal height, the lowest point of the sag at the center of the span is exactly at the center of the span. Therefore, the tension T at the fixed end of the conductor is: ,in, Mass per unit length, unit is L is the span of the conductor.

[0026] S3. Based on the physical properties of the conductor, the sag of the conductor, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, construct a modal vibration model of the transmission line and solve for the natural frequency of the conductor. Specifically, the natural frequency of a conductor is the frequency at which the conductor vibrates freely without the continuous action of external force. It is determined by parameters such as conductor tension, stiffness, and span, and is the core basis for determining the sensor sampling rate.

[0027] Preferably, based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, a modal vibration model of the transmission line is constructed, and the natural frequencies of the conductor are obtained by solving the model, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

[0028] Specifically, the mechanical and moment balance equations describe the force and moment balance relationship during conductor vibration, reflecting the dynamic essence of conductor vibration; the transverse vibration control equation is a simplified core equation for transverse conductor vibration, integrating the influence of mass, stiffness, and tension on vibration; the principal mode function ordinary differential equation is a differential equation describing the spatial shape (principal mode) of conductor vibration, which solves the morphological characteristics of each order of vibration of a fixed conductor; the conductor boundary conditions are the constraint states at both ends of the conductor. Overhead conductors are usually fixed at both ends, that is, the deflection and rotation angle are both zero, which is a necessary condition for solving the natural frequency.

[0029] In a preferred embodiment of the present invention, such as Figure 2 (a) and Figure 2 As shown in (b), a dynamic analysis of the overhead conductor yields the mechanical and torque balance expressions for the conductor vibration: , in, Shear force, unit: ; The bending moment is T; T is the tension at the fixed end of the conductor, in units of... .

[0030] The relationship between the bending moment and deflection of the beam is obtained by solving the modal vibration equation of the conductor using the method of separation of variables. Substituting the mechanical and torque balance expressions of conductor vibration for simplification, and then using the method of separation of variables to solve, the solution is set as... We can obtain: , in, The stiffness of the conductor; The (principal) mode shape function; This is a time-dependent function, describing the changes of each mode over time. Since the left side of the equation is only... The function, the right side of the equation is only For a function to be equal to an equation, both sides must be equal to a constant. Let this constant be... Then it can be simplified to: Substituting the boundary conditions, we determine the state equation for the vibration of the conductor-ground wire. Since the two ends of the conductor-ground wire are fixed, the boundary conditions are as follows: Substituting the values, we can obtain the expression for the natural frequency of the conductor's vibration: Thus, the natural frequencies of the conductor can be calculated.

[0031] S4. Conduct tests based on the natural frequency of the conductor and the preset test frequency to determine the highest modal order, and determine the highest effective frequency based on the highest modal order; Specifically, the highest effective frequency refers to the natural frequency corresponding to the highest-order mode that needs to be monitored in modal testing.

[0032] Preferably, a preset test frequency range is set according to the test purpose, such as wind vibration monitoring or fatigue damage assessment; the natural frequencies of each order of the conductor are compared with the preset test frequency range to screen out all modal orders that fall within the range; the maximum value of the screened order is taken as the highest modal order, and its corresponding natural frequency is the highest effective frequency.

[0033] Preferably, the highest modal order is determined by conducting tests based on the natural frequency of the conductor and a preset test frequency, including: The highest modal order of the current target is obtained by conducting tests based on the natural frequency of the conductor and the preset test frequency. The intersection coverage rate of the conductor's natural frequency and the preset test frequency is calculated based on the highest modal order of the target, and then compared with the intersection coverage rate and the preset coverage threshold. If the intersection coverage is greater than or equal to the coverage threshold, the highest modal order of the target will be taken as the final highest modal order. If the intersection coverage is less than the coverage threshold, reduce the test frequency and retest, and update the highest modal order of the current target.

[0034] Specifically, the highest modal order of the current target refers to the highest modal order that falls within the preset test frequency range after preliminary screening, and needs to be confirmed through coverage verification; the intersection coverage rate refers to the degree of overlap between the conductor's natural frequency and the preset test frequency range, and the calculation formula is the number of natural frequencies falling within the test frequency range / the number of modal orders that should theoretically be covered within the test frequency range × 100%; the coverage threshold is the critical value for judging whether the intersection coverage rate is qualified, and it is usually set to 90% to ensure that the test covers the core modes.

[0035] In a preferred embodiment of the present invention, the natural frequencies of each order of the conductor are compared with a preset test frequency range (e.g., 0.5-5Hz), and the orders falling within the range (e.g., orders 1-4) are selected. The maximum value (order 4) is taken as the current target highest modal order. Then, it is verified whether the candidate orders can effectively cover the test requirements. For example, within the preset test frequency range of 0.5-5Hz, theoretically, it should cover 4 modes (orders 1-4), and all 4 natural frequencies should fall within the range, with a coverage rate of 4 / 4 × 100% = 100%. The coverage rate is compared with a preset coverage threshold to determine whether it is qualified. If the coverage rate meets the requirements, the candidate order is directly confirmed. For example, if the coverage rate is 100% ≥ 90%, the highest modal order is determined to be order 4. If the coverage is insufficient, the overlap can be improved by narrowing the test frequency range. For example, if the preset test frequency is 0.5-6Hz, the 5th natural frequency = 6.1Hz is outside the range, and the coverage = 4 / 5 × 80% < 90%. In this case, the test frequency range is narrowed to 0.5-5.5Hz, and the order is reselected (still 1-4 orders), restoring the coverage to 100%. Through the process of coverage verification and adjustment, it is ensured that the selection of the highest modal order meets both the test requirements and matches the actual natural frequency of the conductor, avoiding the problem of insufficient coverage due to an excessively high order or omission of key modes due to an excessively low order.

[0036] In a preferred embodiment of the present invention, due to differences in span, tension, conductor type, erection environment, and hardware connection status among various overhead transmission lines, their modal frequencies also differ. To effectively conduct modal testing, the frequency range of interest must be clearly defined beforehand based on the actual operating conditions and monitoring objectives. This process can be divided into two stages: theoretical estimation and experimental setup. Based on theoretical calculations, the natural frequencies are initially determined, and the first n natural frequencies of the conductor can be calculated. The higher the modal order n, the higher the corresponding frequency. The target frequency order is then determined according to the experimental conditions. Modal testing typically does not require acquiring all modes; instead, a reasonable highest modal order n should be selected based on actual monitoring needs and experimental excitation methods, thereby determining the target highest frequency fmax = fn. The specific selection method is as follows: If the hammering method is used for excitation, using a metal hammer (with high stiffness) can effectively excite higher-order modes, and it is recommended that n>6; when using a rubber or soft plastic hammer (with low stiffness), the energy is mostly concentrated in the lower orders, and it is recommended that n≤6.

[0037] If a vibration table is used for excitation, the value of n should be reasonably selected based on the maximum output frequency range of the vibration table and the actual response of the conductor, usually not exceeding the effective frequency band of the vibration table.

[0038] If the vibration of a light breeze in the natural environment is used as the excitation source, the vibration frequency of the conductor can be calculated based on the wind speed. The commonly used calculation formula is: Where D is the conductor diameter, v is the wind speed, and St is the Strocha number, which is usually taken as 0.18 to 0.22.

[0039] When determining fmax, appropriate adjustments should be made based on the actual operating conditions of the conductor and the monitoring objectives to ensure that the target frequency range covers the main modes of interest. If the monitoring objective is to detect wind vibration fatigue, the low-frequency range should be focused on, as the main vibration modes of the conductor are usually located at low frequencies. However, if the monitoring objective is to identify damage or anomalies, a higher frequency range may be required, as the changes in high frequencies are more pronounced after damage.

[0040] S5. Determine the lower limit of the sensor sampling frequency based on the highest effective frequency and the preset safety factor, and determine the upper limit of the sensor sampling frequency based on the preset number of sampling points and the highest effective frequency. Specifically, the lower sampling frequency limit represents the minimum sampling frequency set to avoid frequency aliasing and ensure the capture of the highest effective frequency signal, which is determined based on Shannon's sampling theorem and a safety factor; the upper sampling frequency limit represents the maximum sampling frequency set to avoid excessively high sampling rates that would reduce frequency resolution, which is constrained by the number of sampling points and frequency resolution.

[0041] Preferably, the determination of the preset safety factor includes: Calculate the natural frequency deviation based on the maximum and minimum natural frequencies of the conductor; Calculate the natural frequency fluctuation value based on the natural frequency deviation and the average value of the conductor's natural frequency; The final safety factor is determined based on the inherent frequency fluctuation value and the preset fluctuation threshold.

[0042] Specifically, the natural frequency deviation represents the difference between the maximum and minimum values ​​of the natural frequencies of the conductor, denoted as , in Hz, reflecting the absolute dispersion of the natural frequency; the natural frequency fluctuation value represents the ratio of the natural frequency deviation to the average natural frequency, in %, reflecting the relative dispersion of the natural frequency; the preset fluctuation threshold represents the critical value for judging whether the natural frequency fluctuation is severe, usually set to 10%, used to determine the size of the safety factor.

[0043] In a preferred embodiment of the present invention, the modal orders that require special attention are selected, such as the first 3 or 4 orders, and the difference between the maximum and minimum values ​​is calculated. The average value of the natural frequencies of the selected orders is calculated, and then the natural frequency fluctuation value is calculated based on the natural frequency deviation and the average value of the conductor's natural frequency. If the natural frequency fluctuation value is ≤10%, it indicates that the frequency is stable, and the safety factor is 2.5-3; if the natural frequency fluctuation value is >10%, it indicates that the frequency fluctuation is severe, and the safety factor is 3-4. The safety factor is adjusted according to the degree of frequency fluctuation; the more severe the fluctuation, the larger the safety factor, to avoid frequency aliasing. The safety factor is dynamically adjusted with the degree of frequency fluctuation. When the frequency is stable, the sampling rate redundancy caused by an excessively large safety factor is avoided, while data integrity is ensured when the fluctuation is severe.

[0044] S6. Determine the sensor sampling frequency range based on the upper limit and lower limit of the sensor sampling frequency.

[0045] In a preferred embodiment of the present invention, the highest vibration mode order n of interest is determined based on the actual operation of the conductor in the environment and the specific requirements for monitoring the conductor, thus obtaining the effective highest frequency fmax = fn. A lower limit is determined based on Shannon's sampling theorem. According to Shannon's sampling theorem, the sampling frequency must satisfy: To avoid frequency aliasing, a certain safety margin is usually required, introducing a safety factor k (typically 2.5 to 4). Therefore, the actual sampling frequency should satisfy the following: The upper limit is determined based on the frequency resolution and the number of sampling points. To meet the frequency resolution requirement Δf and considering the limitation of the number of sampling points N, the sampling frequency must also satisfy: Where Δf is the desired frequency resolution, and N is the number of sampling points (limited by the memory and processing power of the acquisition system). Finally, considering both the upper and lower limits, the range of values ​​for the sensor sampling frequency fs is: In practical applications, an appropriate fs value should be selected based on the performance of the acquisition equipment, while satisfying the above inequalities. That is, after determining the sensor sampling frequency range, the corresponding accelerometer sampling frequency can be selected in the transmission line modal test according to the sensor sampling frequency range, so that the test can be conducted more timely and accurately.

[0046] First, by using a drone equipped with a lidar to measure conductor sag, the difficulties and high risks associated with installing traditional tension sensors are effectively avoided, enabling safe and efficient acquisition of millimeter-level geometric parameters. Second, by combining the parabolic model with dynamic theory, sag data is accurately converted into conductor tension and various modal frequencies, establishing a complete theoretical closed loop from geometric measurement to mechanical parameter calculation, significantly improving the reliability of tension estimation and the specificity of modal identification. The target frequency range and sampling parameters can be scientifically determined according to actual monitoring needs and on-site excitation conditions, overcoming the shortcomings of traditional experiments that rely on experience and are prone to oversight. By introducing safety factors and frequency resolution constraints, sensor sampling settings are optimized, ensuring both data accuracy and sampling efficiency, providing systematic and reliable technical support for conductor vibration monitoring, fatigue assessment, and anti-galloping design. The overall solution combines theoretical rigor with engineering practicality, possessing significant potential for widespread application.

[0047] By implementing this embodiment, the physical properties, span, and point cloud data of the conductor are first acquired. Then, the conductor sag is calculated through 3D reconstruction. Combined with the physical properties, the horizontal tension of the overhead line and the tension at the fixed end of the conductor are derived. Finally, a modal model is constructed based on these structural and mechanical parameters to solve for the conductor's natural frequency. The natural frequency of the conductor is used to anchor the vibration range to be covered, ensuring that the sampling rate selection is entirely based on the actual characteristics of the conductor under test, solving the problem of empirical methods and ensuring that the sampling frequency matches the structural characteristics of the conductor. At the same time, the highest effective frequency is determined by the conductor's natural frequency, and then the upper and lower limits of the sampling frequency are calculated, avoiding excessively high or low sampling rates and effectively balancing the contradiction between data preservation and high resolution. Under different conductor types or different application scenarios, the sampling frequency range can be derived only based on the conductor's physical properties, span, and point cloud data. Even if the structural characteristics of the conductor under test change, the sampling frequency range of the sensor can be quickly determined.

[0048] See Figure 3 This is a schematic diagram of a device for determining the sampling rate of an acceleration sensor in a modal test of a transmission line according to an embodiment of the present invention, comprising: The data acquisition module is used to acquire the physical properties of the conductors, span, and point cloud data of the transmission line under test; the physical properties of the conductors include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. The conductor tension calculation module is used to perform three-dimensional reconstruction based on the physical properties of the conductor, the span, and the line point cloud data, and to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. The natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the sag of the conductor, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor. The highest effective frequency determination module is used to conduct tests based on the natural frequency of the conductor and a preset test frequency to determine the highest modal order, and to determine the highest effective frequency based on the highest modal order. The sampling frequency upper and lower limit determination module is used to determine the lower limit of the sensor sampling frequency based on the highest effective frequency and the preset safety factor, and to determine the upper limit of the sensor sampling frequency based on the preset number of sampling points and the highest effective frequency. The sensor sampling frequency determination module is used to determine the sensor sampling frequency range based on the upper limit and lower limit of the sensor sampling frequency.

[0049] Specifically, the natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

[0050] This invention provides a device for determining the sampling rate of an accelerometer in modal testing of transmission lines. The device includes a data acquisition module that acquires the physical properties of the conductors, span length, and line point cloud data of the transmission line under test. The physical properties of the conductors include the mass per unit length of the conductor, the specific load of the conductor, and the conductor stiffness. In the conductor tension calculation module, a three-dimensional reconstruction is performed based on the physical properties of the conductors, the span length, and the line point cloud data to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. Finally, in the natural frequency calculation module, the physical properties of the conductors, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor are calculated. Tension is used to construct a modal vibration model of the transmission line and solve for the natural frequency of the conductor. In the highest effective frequency determination module, tests are conducted based on the natural frequency of the conductor and a preset test frequency to determine the highest modal order, and the highest effective frequency is determined based on the highest modal order. In the sampling frequency upper and lower limit determination module, the lower limit of the sensor sampling frequency is determined based on the highest effective frequency and a preset safety factor, and the upper limit of the sensor sampling frequency is determined based on the preset number of sampling points and the highest effective frequency. Finally, in the sensor sampling frequency determination module, the sensor sampling frequency range is determined based on the upper and lower limits of the sensor sampling frequency.

[0051] By first acquiring the physical properties, span, and point cloud data of the conductor, and then calculating the conductor sag through 3D reconstruction, the horizontal tension of the overhead line and the tension at the fixed end of the conductor are derived based on the physical properties. Finally, a modal model is constructed based on these structural and mechanical parameters to solve for the conductor's natural frequency. The natural frequency of the conductor is used to anchor the vibration range to be covered, ensuring that the sampling rate selection is entirely based on the actual characteristics of the conductor under test, solving the problem of empirical methods, and ensuring that the sampling frequency matches the structural characteristics of the conductor. At the same time, the highest effective frequency is determined by the conductor's natural frequency, and then the upper and lower limits of the sampling frequency are calculated, avoiding excessively high or low sampling rates, effectively balancing the contradiction between data preservation and high resolution. For different conductor types or different application scenarios, the sampling frequency range can be derived only based on the conductor's physical properties, span, and point cloud data. Even if the structural characteristics of the conductor under test change, the sampling frequency range of the sensor can be quickly determined.

[0052] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0053] Those skilled in the art will understand that, for convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0054] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a method for determining the sampling rate of an acceleration sensor for modal testing of a transmission line as described in the above embodiments. The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0055] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0056] The memory can be used to store the computer program. The processor implements various functions of the terminal device by running or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device or other volatile solid-state storage device.

[0057] Another embodiment of the present invention provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the acceleration sensor sampling rate determination method for transmission line modal testing described in the above embodiment.

[0058] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0059] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for determining the sampling rate of an accelerometer in modal testing of a transmission line, characterized in that, include: Acquire the physical properties of the conductors, span, and point cloud data of the transmission line under test; The physical properties of the conductor include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. Three-dimensional reconstruction is performed based on the physical properties of the conductor, the span, and the line point cloud data to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. Based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, a modal vibration model of the transmission line is constructed, and the natural frequency of the conductor is obtained by solving the model. The highest modal order is determined by conducting tests based on the conductor's natural frequency and a preset test frequency, and the highest effective frequency is determined based on the highest modal order. The lower limit of the sensor sampling frequency is determined based on the highest effective frequency and the preset safety factor, and the upper limit of the sensor sampling frequency is determined based on the preset number of sampling points and the highest effective frequency. The sensor sampling frequency range is determined based on the upper limit and lower limit of the sensor sampling frequency.

2. The method for determining the sampling rate of an acceleration sensor in a modal test of a transmission line as described in claim 1, characterized in that, Based on the physical properties of the conductor, the span, and the line point cloud data, a three-dimensional reconstruction is performed to calculate the conductor sag, overhead line horizontal tension, and conductor fixed-end tension, including: For each of the aforementioned range lengths, a parabola is fitted using the least squares method to obtain the fitted curve. The centerline of the conductor is reconstructed in three-dimensional space based on the fitted curve to obtain a three-dimensional model of the conductor. Based on the three-dimensional model of the conductor, a chord is generated by connecting the suspension points of the conductor. The lowest point of the conductor on the fitted curve is located directly below the chord, and the vertical distance from the lowest point of the conductor to the chord is taken as the sag of the conductor. The horizontal tension of the overhead line is calculated based on the conductor sag, the conductor specific load, and the corresponding span. The tension at the fixed end of the conductor is calculated based on the horizontal tension of the overhead line, the mass per unit length of the conductor, and the span.

3. The method for determining the sampling rate of an accelerometer in a modal test of a transmission line as described in claim 1, characterized in that, Based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, a modal vibration model of the transmission line is constructed, and the natural frequencies of the conductor are obtained by solving the model, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

4. The method for determining the sampling rate of an accelerometer in a modal test of a transmission line as described in claim 1, characterized in that, The highest modal order is determined by conducting tests based on the conductor's natural frequency and a preset test frequency, including: The highest modal order of the current target is obtained by conducting tests based on the natural frequency of the conductor and the preset test frequency. The intersection coverage rate of the conductor's natural frequency and the preset test frequency is calculated based on the highest modal order of the target, and then compared with the intersection coverage rate and the preset coverage threshold. If the intersection coverage is greater than or equal to the coverage threshold, the highest modal order of the target will be taken as the final highest modal order. If the intersection coverage is less than the coverage threshold, reduce the test frequency and retest, and update the highest modal order of the current target.

5. The method for determining the sampling rate of an acceleration sensor in a transmission line modal test as described in claim 1, characterized in that, The acquisition of the line point cloud data includes: Initial line point cloud data is collected using lidar equipment; Noise filtering is applied to the initial line point cloud data to obtain the final line point cloud data.

6. The method for determining the sampling rate of an accelerometer in a modal test of a transmission line as described in claim 1, characterized in that, The determination of the preset safety factor includes: Calculate the natural frequency deviation based on the maximum and minimum natural frequencies of the conductor; Calculate the natural frequency fluctuation value based on the natural frequency deviation and the average value of the conductor's natural frequency; The final safety factor is determined based on the inherent frequency fluctuation value and the preset fluctuation threshold.

7. A device for determining the sampling rate of an acceleration sensor in modal testing of a transmission line, characterized in that, include: The data acquisition module is used to acquire the physical properties of the conductors, span, and point cloud data of the transmission line under test. The physical properties of the conductor include the mass per unit length of the conductor, the specific load of the conductor, and the stiffness of the conductor. The conductor tension calculation module is used to perform three-dimensional reconstruction based on the physical properties of the conductor, the span, and the line point cloud data, and to calculate the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor. The natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the sag of the conductor, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor. The highest effective frequency determination module is used to conduct tests based on the natural frequency of the conductor and a preset test frequency to determine the highest modal order, and to determine the highest effective frequency based on the highest modal order. The sampling frequency upper and lower limit determination module is used to determine the lower limit of the sensor sampling frequency based on the highest effective frequency and the preset safety factor, and to determine the upper limit of the sensor sampling frequency based on the preset number of sampling points and the highest effective frequency. The sensor sampling frequency determination module is used to determine the sensor sampling frequency range based on the upper limit and lower limit of the sensor sampling frequency.

8. The device for determining the sampling rate of an acceleration sensor in modal testing of a transmission line as described in claim 7, characterized in that, The natural frequency calculation module is used to construct a modal vibration model of the transmission line based on the physical properties of the conductor, the conductor sag, the horizontal tension of the overhead line, and the tension at the fixed end of the conductor, and to solve for the natural frequency of the conductor, including: Based on the overhead line horizontal tension, conductor fixed port tension, conductor physical properties, conductor unit length mass, and conductor stiffness, a modal vibration model of the transmission line is constructed. Based on the modal vibration model of the transmission line, dynamic analysis was performed to obtain the corresponding mechanical and torque balance equations. By simplifying the mechanical and moment balance equations, the control equation for the transverse vibration of the conductor is obtained. Based on the decomposition of the control equation for the transverse vibration of the conductor, the ordinary differential equation of the principal mode function is obtained. Substituting the preset boundary conditions of the conductor into the ordinary differential equation of the principal mode function, the principal mode function equation is obtained, and the natural frequency of the conductor is derived from the principal mode function equation.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements a method for determining the sampling rate of an acceleration sensor for a transmission line modal test as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a method for determining the sampling rate of an acceleration sensor for a transmission line modal test as described in any one of claims 1 to 6.

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