A method for dynamic diameter measurement of live conductors in high-voltage overhead lines based on quantum lidar

Abstract

This invention relates to the field of quantum lidar technology, and in particular provides a method for dynamic diameter measurement of live conductors in high-voltage overhead power lines based on quantum lidar. The method includes generating frequency-entangled-squeezed composite photon pairs using a quantum entangled light source and applying FMCW phase modulation; extracting the instantaneous radial velocity of the conductor using the frequency offset of interference fringes to obtain raw time-of-flight data with timestamps and an instantaneous velocity sequence; using the instantaneous velocity sequence as a dynamic time reference, performing non-uniform resampling correction on the time-of-flight histogram to obtain a motion-compensated distance-angle sparse measurement dataset; inputting the motion-compensated sparse measurement dataset into a compressed sensing reconstruction program, reconstructing the three-dimensional cross-sectional profile of the conductor through L1 norm optimization iteration, and extracting the maximum diameter, minimum diameter, and roundness deviation parameters from the profile to form a continuous diameter variation curve along the entire span of the line. This invention meets the stringent requirements for live-line detection of high-voltage overhead power lines.

Description

Technical Field

[0001] This invention relates to the field of quantum lidar technology, and in particular to a method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar. Background Technology

[0002] High-voltage overhead transmission lines form the backbone of the power system. During long-term operation, their conductors are subjected to the combined effects of multiple factors, including corona discharge, wind vibration, icing, lightning strikes, and corrosive weather, leading to geometric deformations such as localized wear, broken single-strand aluminum wires, necking of crimped pipes, and bulging. These deformations directly alter the conductor's resistance distribution, current-carrying capacity, and mechanical strength, posing a significant risk of serious accidents such as line breaks and tower collapses. Therefore, high-precision, dynamic, and continuous diameter measurement of conductors in energized operation is crucial for assessing line health, predicting remaining lifespan, and guiding differentiated operation and maintenance.

[0003] Currently, the power industry primarily relies on manual tower climbing for overhead line conductor inspection, drone-mounted visible light or infrared camera patrols, and traditional lidar scanning technology. Manual tower climbing requires power outages, is extremely inefficient, and carries high-altitude operational risks. Drone-based visual inspections are limited by lighting conditions, angle, and image resolution, making it difficult to obtain precise three-dimensional dimensions of the conductors. Traditional lidar, such as time-of-flight or frequency-modulated continuous wave radar, can acquire distance information, but in high-voltage environments, safety distance requirements typically necessitate a distance of at least three meters from the conductor, resulting in extremely weak echo signals. Furthermore, the conductors in operation are subject to wind deflection (horizontal sway), torsion (rotation around their own axis), and vibrations from the measurement platform itself, leading to severe motion distortion in the collected point cloud data. In addition, surface contaminants such as dust, bird droppings, and icing further reduce optical reflectivity, making it difficult for current technologies to achieve sub-millimeter diameter measurement accuracy in dynamic scenarios without cooperative targets, and even more difficult to simultaneously extract the conductor's instantaneous velocity to correct motion errors.

[0004] Therefore, there is an urgent need for a dynamic diameter measurement method that can be performed without contact with, away from, and unaffected by strong electromagnetic interference and conductor surface conditions, in order to resolve the contradictions between safe distance, motion compensation, and weak signal extraction capabilities in traditional measurement methods. Addressing the shortcomings of existing technologies, the main objective technical problem to be solved is: how to overcome interference from strong ambient light, corona discharge noise, and weak echo signals caused by conductor surface contamination, while maintaining a safe distance of more than three meters from high-voltage live conductors; and simultaneously eliminate point cloud displacement distortion caused by conductor wind deflection, torsion, and the movement of the measurement platform. This would enable high-precision, continuous dynamic diameter measurement of the cross-sectional profile of overhead line conductors under high-speed dynamic conditions, i.e., when the radial velocity change rate of the conductor is unknown. High precision refers to sub-millimeter level, continuity refers to the entire range, and the ability to accurately identify geometric defects longer than five centimeters, such as local wear, necking, and bulges. Summary of the Invention

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] One aspect of the present invention provides a method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar, comprising the following steps:

[0007] A quantum entangled light source generates frequency entangled-squeezed composite photon pairs and applies FMCW phase modulation; the signal beam is irradiated onto the surface of the target conductor, while the idler beam is retained in the local reference arm; the receiver obtains the flight time histogram of the echo photons through quantum correlation coincidence detection, and extracts the instantaneous radial velocity of the conductor using the frequency offset of the interference fringes, thus obtaining the original flight time data with timestamps and the instantaneous velocity sequence.

[0008] Using the instantaneous velocity sequence as a dynamic time reference, non-uniform resampling correction is performed on the flight time histogram to eliminate point cloud displacement distortion caused by wind deflection, torsion and measurement platform motion, and obtain motion-compensated distance-angle sparse measurement dataset.

[0009] The motion-compensated sparse measurement dataset is input into the compressed sensing reconstruction program. The three-dimensional cross-sectional profile of the conductor is reconstructed through L1 norm optimization iteration. The maximum diameter, minimum diameter, and roundness deviation parameters are extracted from the profile to form a continuous diameter variation curve along the entire span of the line.

[0010] This invention presents a method for dynamic diameter measurement of energized overhead power line conductors based on quantum lidar. Through the synergistic application of various techniques, it achieves accurate and interference-resistant dynamic conductor parameter measurement. The frequency entangled-squeezed composite photon pairs generated by the quantum entangled light source are modulated by FMCW to enhance detection sensitivity and the dynamic velocity measurement range. The quantum correlation characteristics of the signal light and idler light effectively suppress noise, significantly improving the signal-to-noise ratio of the echo signal while providing high-precision instantaneous velocity measurement, thus providing a benchmark for motion compensation. The non-uniform resampling correction process combines time-of-flight data and velocity sequences to construct a dynamic compensation model, eliminating point cloud distortion caused by conductor wind deflection, torsion, and measurement platform motion, ensuring the geometric accuracy of the sparse measurement dataset and enhancing the reliability of 3D reconstruction. The compressed sensing reconstruction algorithm reconstructs the conductor cross-sectional profile using sparse measurement data, extracting precise diameter variation parameters to ensure omnidirectional dynamic diameter measurement capability along the line span. Measurements are completed while the conductor remains energized, avoiding the influence of the high-voltage environment and improving engineering inspection efficiency. Attached Figure Description

[0011] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0012] Figure 1 This is a flowchart of the live dynamic diameter measurement method for high-voltage overhead line conductors based on quantum lidar provided in Embodiment 1 of the present invention;

[0013] Figure 2 This is a schematic diagram of the live dynamic diameter measurement method for high-voltage overhead line conductors based on quantum lidar provided in Embodiment 1 of the present invention;

[0014] Figure 3 This is a process diagram of obtaining the original flight time data and instantaneous velocity sequence with timestamps provided in Embodiment 2 of the present invention;

[0015] Figure 4 This is a process diagram of non-uniform resampling correction of the flight time histogram provided in Embodiment 4 of the present invention;

[0016] Figure 5 This is a process diagram of reconstructing the three-dimensional cross-sectional profile of a conductor through L1 norm optimization iteration provided in Embodiment 6 of the present invention;

[0017] Figure 6 A block diagram of the electronic device provided by the present invention;

[0018] Figure 7 A block diagram of a computer-readable storage medium provided for this invention. Detailed Implementation

[0019] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0021] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0022] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0023] This invention utilizes a quantum entangled light source to generate frequency-entangled squeezed-state composite photon pairs, combined with quantum correlation coincidence detection to filter out non-correlated background noise at the physical level, thus resolving the contradiction between safe distance and signal-to-noise ratio. It uses the instantaneous velocity sequence of the conductor extracted from interference fringes as a dynamic time reference to perform non-uniform resampling correction on the time-of-flight histogram, eliminating motion distortion. Then, the motion-compensated sparse dataset is input into an L1-norm optimized compressed sensing reconstruction program to recover the three-dimensional cross-sectional profile of the conductor from the undersampled data with high fidelity. Finally, the maximum diameter, minimum diameter, and roundness deviation parameters are extracted to form a continuous diameter variation curve along the entire span of the line.

[0024] Example 1: As Figure 1 As shown, this embodiment of the invention provides a method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar, comprising the following steps:

[0025] Step S100: The quantum entangled light source generates frequency entangled-squeezed state composite photon pairs and applies FMCW phase modulation; the signal beam is irradiated onto the surface of the target conductor, while the idler beam is retained in the local reference arm; the receiver obtains the flight time histogram of the echo photons through quantum correlation coincidence detection, and extracts the instantaneous radial velocity of the conductor using the frequency offset of the interference fringes, to obtain the original flight time data and instantaneous velocity sequence with timestamps;

[0026] Step S200: Using the instantaneous velocity sequence as a dynamic time reference, perform non-uniform resampling correction on the flight time histogram to eliminate point cloud displacement distortion caused by wind deflection, torsion and measurement platform motion, and obtain motion-compensated distance-angle sparse measurement dataset.

[0027] Step S300: Input the motion-compensated sparse measurement dataset into the compressed sensing reconstruction program, reconstruct the three-dimensional cross-sectional profile of the conductor through L1 norm optimization iteration, extract the maximum diameter, minimum diameter and roundness deviation parameters from the profile, and form a continuous diameter variation curve along the entire span of the line.

[0028] Quantum entanglement light sources are emitters that generate photon pairs with quantum correlation characteristics, typically based on spontaneous parametric down-conversion or periodically polarized crystals. Entangled photon pairs are used to construct measurement optical paths resistant to ambient light interference, enabling the system to obtain high signal-to-noise ratio echo signals from distances exceeding three meters from the conductor under high-voltage conditions, thus resolving the contradiction between close-range measurement and safe distance in traditional lidar. Frequency entanglement-squeezed-state composite photon pairs possess both frequency entanglement and squeezed-state characteristics. Frequency entanglement refers to the strong correlation between the signal light and idler light frequencies, while squeezed-state refers to the active suppression of quantum noise in a certain dimension. Frequency entanglement is used to calculate the instantaneous velocity of the conductor from the interference fringes, while squeezed-state is used to reduce phase noise, enabling sub-millimeter-level diameter measurement accuracy even under conditions of strong electromagnetic fields and weak echoes caused by conductor surface contamination. FMCW phase modulation applies linear phase modulation in the form of a continuous wave to the optical signal output from the quantum entanglement light source. This modulation makes the flight time of the echo photons linearly related to the interference frequency shift. Combined with quantum correlation detection, distance and velocity information can be obtained simultaneously, providing a high-temporal-resolution velocity reference for motion compensation. The target conductor is the live conductor in a high-voltage overhead line whose diameter needs to be measured, such as steel-cored aluminum stranded wire or aluminum alloy conductor. Direct illumination of the conductor in operation allows for the acquisition of its true cross-sectional profile under dynamic conditions such as wind deflection, torsion, and vibration, used to assess wear, corrosion, and defects in the crimped pipe. The idler beam is a path of light that is not emitted to the target but retained in the local reference arm amidst entangled photon pairs. It has quantum frequency entanglement with the signal beam and serves as a local reference at the receiver. Background light noise is eliminated through quantum correlation detection with the echo photons, and the instantaneous velocity of the conductor is calculated using its frequency offset. The local reference arm is the optical path inside the quantum lidar that retains the idler beam and performs delay or interference processing on it. This optical path does not contact the target conductor and provides the receiver with a reference signal that has quantum correlation with the emitted signal. It is the core structure for achieving correlation detection and velocity extraction. The receiver is an optical and detection component that collects echo photons reflected from the target conductor, including quantum pulse gates and superconducting nanowire single-photon detector arrays. Its function is to identify only echo photons entangled with idler photons in strong background light, including sunlight and corona discharge light, and output a time-of-flight histogram and interference fringe frequency shift. Quantum correlation refers to the non-classical statistical correlation between the signal light and the idler light due to entanglement. The receiver counts only photon pairs that conform to this correlation, thereby physically filtering out all non-correlated background light, resulting in a measurement signal-to-noise ratio far exceeding that of classical lidar, thus allowing measurement of low-reflectivity, dirty conductors at a safe distance. The time-of-flight histogram of the echo photons is a statistical graph of the arrival times of the echo photons recorded by the receiver. The arrival time of each echo photon corresponds to the total flight time of the signal light from emission to reflection back from the conductor. After motion compensation and compressed sensing reconstruction, this can be converted into distance and ultimately used to reconstruct the three-dimensional profile of the conductor.Compressed sensing reconstruction is a computational algorithm that reconstructs a complete 3D profile using sparse measurement data. The distance-angle dataset after motion compensation is sparsely sampled. Through L1 norm optimization iteration, it can recover conductor cross-sectional details, such as single-strand aluminum wire grooves and local bulges, without increasing the number of scan points. This meets the spatial resolution requirement of identifying defects longer than five centimeters even at high-speed movements exceeding one meter per second. The maximum diameter, minimum diameter, and roundness deviation parameters are three feature quantities extracted from the reconstructed 3D conductor cross-sectional profile. The maximum diameter reflects the overall size of the conductor; the minimum diameter is used to locate local wear or necking (i.e., the thinnest point); and the roundness deviation, the ratio of the difference between the maximum and minimum diameters to the nominal diameter, is used to determine whether the conductor has lost its roundness due to stress or local defects, and is a key indicator for assessing remaining life. The continuous diameter variation curve for the entire span is a curve formed by continuously arranging the diameter parameters of all measurement points along the entire span (i.e., between two adjacent towers) according to mileage coordinates. This curve can intuitively locate defects such as local bulges (sudden diameter increase), necking at the inlet of the crimped pipe (sudden diameter decrease), and uniform wear (slow diameter decrease), providing a complete online status map for operation and maintenance decisions.

[0029] In the above embodiments, the principle is referenced in the appendix. Figure 2 This embodiment of the high-voltage overhead line conductor dynamic diameter measurement method based on quantum lidar achieves accurate and interference-resistant dynamic conductor parameter measurement through the synergistic effect of various steps. The frequency entangled-squeezed state composite photon pairs generated by the quantum entangled light source are modulated by FMCW to improve detection sensitivity and dynamic velocity measurement range. The quantum correlation characteristics of the signal light and idler light effectively suppress noise, significantly improving the signal-to-noise ratio of the echo signal, while providing high-precision instantaneous velocity measurement, providing a benchmark for motion compensation. The non-uniform resampling correction process combines time-of-flight data and velocity sequences to construct a dynamic compensation model, eliminating point cloud distortion caused by conductor wind deflection, torsion, and measurement platform motion, ensuring the geometric accuracy of the sparse measurement dataset and enhancing the reliability of 3D reconstruction. The compressed sensing reconstruction algorithm reconstructs the conductor cross-sectional profile using sparse measurement data, extracting accurate diameter variation parameters to ensure omnidirectional dynamic diameter measurement capability along the line span; the measurement is completed while keeping the conductor energized, avoiding the influence of the high-voltage environment and improving engineering inspection efficiency.

[0030] In summary, this embodiment comprehensively utilizes technologies such as quantum detection, dynamic compensation, and sparse reconstruction to significantly improve the accuracy, stability, and applicability of dynamic conductor diameter measurement, meeting the stringent requirements of live-line testing of high-voltage overhead lines.

[0031] Example 2: Figure 3 As shown, based on Example 1, the process of obtaining the original flight time data and instantaneous velocity sequence with timestamps in step S100 of this embodiment of the invention specifically includes the following steps:

[0032] Step S101: The receiver obtains the time-domain signal sequence of interference fringes through quantum correlation coincidence detection. After windowing the time-domain signal sequence of interference fringes with a window function, it performs a fast Fourier transform and searches for the position of the spectral peak with the largest amplitude in the frequency domain. The frequency coordinates corresponding to the spectral peak are marked as the frequency offset of the interference fringes. The Fourier transform and spectral peak extraction operations are repeated for the interference fringes of each measurement period to obtain the frequency offset sequence arranged in the order of measurement time.

[0033] Step S102: Substitute each frequency offset in the frequency offset sequence into the FMCW velocity measurement equation in sequence; perform proportional relationship calculation, calculate the instantaneous radial velocity corresponding to each frequency offset, arrange all calculation results in the original order, and obtain the instantaneous radial velocity sequence.

[0034]

[0035] In the formula The center wavelength of the quantum entangled light source, and the instantaneous radial velocity. Frequency offset ;

[0036] Step S103: Match each velocity value in the instantaneous radial velocity sequence with the corresponding timestamp in the original flight time data; specifically: using the same measurement cycle number and photon arrival time as indexes, append the instantaneous radial velocity value to the metadata field of the corresponding flight time data, and merge to generate a combined data record that simultaneously contains the flight time measurement value, the corresponding timestamp, and the instantaneous radial velocity of the time conductor; arrange the combined data records generated by all measurement cycles in chronological order to form the original flight time data and instantaneous velocity sequence with timestamps.

[0037] In the above embodiments, this embodiment improves the accuracy of quantum velocity measurement by combining quantum correlation coincidence detection with fast Fourier transform analysis, significantly enhancing the detection accuracy of frequency offset and improving the measurement accuracy of instantaneous radial velocity, thus giving the velocity measurement system higher resolution. Regarding dynamic data fusion, the strict temporal alignment of flight time data, timestamps, and instantaneous velocity forms a composite data structure, ensuring the complete preservation of the spatiotemporal correlation of conductor dynamic measurement parameters, providing accurate input for analyzing conductor galloping trajectories and motion states. In terms of live-line work safety monitoring, the combined data recording supports accurate analysis of conductor dynamic sag change rate and partial discharge vibration characteristics; and through joint analysis of flight time and velocity parameters, a quantitative relationship between conductor diameter change and discharge characteristics is established, providing key criteria for the safety monitoring of high-voltage lines.

[0038] In summary, this embodiment achieves high-precision real-time monitoring of the dynamic diameter change, spatial offset, and vibration characteristics of high-voltage overhead line conductors under strong electromagnetic environment. The measurement results are not affected by corona discharge light noise, providing a reliable technical means for monitoring the energized state and safety assessment of high-voltage transmission lines.

[0039] Example 3: Based on Example 2, the process of performing windowing processing on the interference fringe time-domain signal sequence and then performing Fast Fourier Transform in step S101 of this embodiment of the invention specifically includes the following steps:

[0040] Step S1011: Perform quantum phase recovery windowing truncation on the time-domain signal sequence of the interference fringes to obtain the windowed correlated interference signal sequence;

[0041] Specifically, based on the time-domain signal sequence of interference fringes obtained by quantum correlation coincidence detection, a quantum phase recovery window function is constructed using the coherent time window of entangled photon pairs output by the quantum entangled source as the window function width. The time-domain expression of the quantum phase recovery window function is multiplied point-by-point on the time axis with the time-domain signal sequence of interference fringes, so that the correlated interference signal within the coherent time window is preserved, while the non-correlated background phase noise caused by high-voltage electromagnetic field noise and corona discharge stray light outside the window is forcibly attenuated to below the background noise level, thus obtaining the windowed correlated interference signal sequence.

[0042] Step S1012: Map the windowed correlated interference signal sequence into a frequency domain quantum beat spectrum sequence using quantum Fourier transform;

[0043] Specifically, quantum correlation spectrum analysis is performed on the windowed correlated interference signal sequence. Utilizing the frequency entanglement correlation characteristics between the signal beam and the idler beam, the joint spectral density function of the entangled photon pairs is used as the integration kernel for the Fourier transform. During the transform, the time-domain correlated interference signal is decomposed into a superposition of entangled components of different frequencies according to its correlation with the entangled frequency components. The amplitude value corresponding to each frequency component constitutes a frequency-domain quantum beat spectrum sequence. Each spectral point in the frequency-domain quantum beat spectrum sequence represents the coherent accumulation result of the echo photons on the conductor surface at a specific entanglement frequency.

[0044] Step S1013: Extract the frequency values ​​of the non-classical beat frequency peaks from the frequency domain quantum beat spectrum sequence as frequency offsets, and arrange them in the order of measurement time to form a frequency offset sequence;

[0045] The process involves scanning all frequency channels in the quantum beat spectrum sequence in the frequency domain to search for non-classical beat frequency peaks excited by the instantaneous radial motion of the conductor. The characteristics of non-classical beat frequency peaks are that their amplitudes are significantly higher than the quantum noise floor of adjacent frequency channels, and the peak positions shift with the change of the radial velocity of the conductor. The frequency values ​​corresponding to the non-classical beat frequency peaks are extracted as the interference fringe frequency offset of the current measurement cycle, and the timestamp corresponding to the frequency offset is recorded. The above search and extraction operations are repeated for each set of measurement cycles, and the frequency offsets obtained in all cycles are arranged in chronological order of measurement time to form a frequency offset sequence arranged in chronological order of measurement time.

[0046] Among them, the quantum phase recovery window function It is a real function defined in the time domain, and its expression adopts...

[0047]

[0048] In the formula, The width of the coherence time window for entangled photon pairs output by a quantum entangled light source is determined by the coherence time parameter of the light source itself. = / 4 is the Gaussian decay constant; the function of the window function is to: Within the coherent time window, the product of the Gaussian term and the cosine-raised-cosine term is used to achieve a smooth transition at the edges and suppress spectral leakage; outside the window, the value is set to zero to force attenuation of non-correlated background phase noise caused by high-voltage electromagnetic field induced noise, corona discharge stray light, etc.

[0049] Joint spectral density function Describe the frequency of the signal light With idle frequency The entanglement correlation spectrum distribution between them, for frequency-entangled states generated based on spontaneous parametric downconversion, is expressed as follows:

[0050]

[0051] In the formula: The length of the nonlinear crystal; Let be the phase mismatch, where , , These are the wavenumbers of the pump light, signal light, and idler light in the crystal, respectively. The pump light center frequency; The pump spectral bandwidth; and These are the spectral filtering functions for the signal and idler optical channels, respectively, and are either Gaussian or rectangular functions. In practical applications, the joint spectral density function is obtained through offline quantum state tomography: using a tunable narrowband filter and a single-photon detector, the coincidence count rate under different frequency combinations is scanned to obtain a discrete two-dimensional coincidence spectrum, which is then normalized and used as... The numerical table.

[0052] In the above embodiments, this embodiment achieves high-precision dynamic monitoring of the radial displacement of high-voltage transmission lines through quantum optical processing methods; the quantum phase recovery window function effectively purifies the signal through time-domain multiplication; this window function uses the coherent time window of entangled photon pairs as a reference, while preserving correlated interference signals and suppressing non-correlated background noise to below the background noise level; effectively eliminating the pollution of the signal by high-voltage electromagnetic field noise and corona discharge interference. The quantum Fourier transform utilizes the frequency correlation characteristics of entangled photons for signal analysis. The joint spectral density function used in the transform process is used as the integration kernel, which enables the time-domain signal to be accurately decomposed into the superposition of entangled components of different frequencies; improving the spectral resolution and highlighting the characteristics of weak signals; by identifying the non-classical beat frequency peaks in the frequency domain, the precise capture of the conductor motion characteristics is achieved; the peaks have significant amplitude advantages and motion correlation, and their frequency offsets can directly reflect the changes in the radial displacement of the conductor; the final frequency offset sequence completely records the dynamic motion process of the conductor.

[0053] In summary, this embodiment fully utilizes the advantages of quantum optics technology to achieve subwavelength-level displacement measurement accuracy under strong noise conditions, providing a reliable technical means for high-voltage line safety monitoring.

[0054] Example 4: Figure 4 As shown, based on Example 1, the process of performing non-uniform resampling correction on the time-of-flight histogram in step S200 of this embodiment of the invention specifically includes the following steps:

[0055] Step S201: Using the instantaneous velocity sequence as a dynamic time reference, the instantaneous radial velocity value of each measurement cycle in the sequence is accumulated over time to calculate the cumulative displacement offset between the measurement platform and the target conductor from the start of the measurement to the current time, thus obtaining the cumulative displacement offset sequence.

[0056] Step S202: Based on the cumulative displacement offset sequence, reposition the photon arrival time corresponding to each flight time value in the original flight time histogram: when the cumulative displacement offset is positive, delay the photon arrival time by the amount of time corresponding to the cumulative displacement offset; when the cumulative displacement offset is negative, advance the photon arrival time by the amount of time corresponding to the cumulative displacement offset; compensate for the flight time axis distortion caused by wind deflection, torsion, and measurement platform movement, and generate a corrected flight time sequence;

[0057] Step S203: Associate each time value in the corrected flight time series with the corresponding scanning angle encoder output value one by one, so that each distance value after flight time conversion is accompanied by its corresponding spatial angle information, forming a motion-compensated distance-angle sparse measurement dataset.

[0058] In the above embodiments, this embodiment addresses the specific needs of dynamic diameter measurement of high-voltage overhead conductors under energized conditions. It achieves time correction for conductor vibration and measurement platform motion through a non-uniform resampling method. Based on the cumulative displacement offset obtained by periodically accumulating the instantaneous velocity sequence, the dynamic changes in photon flight paths caused by conductor wind deflection, torsion, and measurement platform motion are accurately quantified. Motion parameters are converted into time-dimensional influencing factors in optical ranging, establishing a precise mapping relationship between mechanical motion and laser flight time. By dynamically adjusting the position of photon arrival time, flight time distortion caused by conductor radial motion is compensated. The correction process eliminates the influence of motion displacement on conductor diameter measurement results, ensuring that the compensated flight time value accurately reflects the true geometric position of the target conductor. This approach is particularly suitable for dynamic monitoring scenarios of high-voltage energized conductors, effectively solving the measurement error problem caused by conductor motion in traditional ranging systems. The corrected flight time is spatially registered with the scanning angle to form a measurement dataset with complete spatiotemporal characteristics. This dataset retains the three-dimensional spatial information of the conductor under vibration, providing accurate input parameters for conductor diameter inversion based on quantum lidar, meeting the requirements for dynamic measurement accuracy in high-voltage line energized detection.

[0059] In summary, this embodiment achieves sub-millimeter-level ranging accuracy under motion conditions, solves the technical challenge of real-time dynamic monitoring of high-voltage overhead conductors under energized operation, and provides a reliable technical means for power grid operation and maintenance.

[0060] Example 5: Based on Example 4, the process of generating the corrected flight time series in step S202 of this embodiment of the invention specifically includes the following steps:

[0061] Step S2021: Based on the cumulative displacement offset sequence, search for the original arrival time of the photon corresponding to each flight time value in the original flight time histogram, and take the offset value within the time interval where it is located as the time to be compensated for the arrival time of the photon. If the time to be compensated is positive, it is recorded as the backward shift; if it is negative, its absolute value is recorded as the forward shift, while retaining the positive and negative signs, to obtain the detailed sequence of the direction and amplitude to be compensated for each photon arrival time.

[0062] Step S2022: Perform a shift operation on the original arrival time of each photon according to the detailed sequence of the direction and amplitude to be compensated: For photons marked as shifted backward, add a positive shift amount to their original arrival time and move them by the corresponding time length in the direction of increasing value on the time axis; for photons marked as shifted forward, subtract the positive shift amount from their original arrival time and move them by the corresponding time length in the direction of decreasing value on the time axis; during the shifting process, maintain the relative order between photons to prevent crossover and misalignment. After adjusting the arrival times of all photons, generate a new sequence of arrival times that has been corrected by stretching or compressing the time axis.

[0063] Step S2023: Each arrival time in the new arrival time sequence is bound to its original corresponding flight time value as a data pair, and all data pairs are rearranged in ascending order of new arrival time from smallest to largest; during the rearrangement, if two different photons have the same new arrival time, they are arranged according to the smaller original flight time value; finally, a corrected flight time sequence is formed, in which the first element of each data pair in the flight time sequence is the corrected arrival time, and the second element is the corresponding flight time value.

[0064] In the above embodiments, this embodiment achieves dynamic temporal correction of time-of-flight data by performing photon-by-photon compensation on the original time-of-flight histogram using a cumulative displacement offset sequence. Based on a bidirectional shifting mechanism of the positive and negative signs and amplitude of the offset, the arrival times of photons are adjusted by stretching or compressing the time axis while maintaining the photon temporal topology, eliminating temporal distortions caused by cumulative system errors. By binding and reordering the new arrival times with the original time-of-flight values, a correction sequence with strict temporal relationships is constructed. This sequence retains the physical quantity information of the original time-of-flight and ensures the correct temporal correlation of photon events through temporal reconstruction. A time-of-flight priority sorting strategy is adopted for events arriving at the same time to avoid introducing new temporal conflicts during the correction process. The final generated correction sequence satisfies two key conditions: 1) the photon arrival times strictly reflect the true time axis after compensation and adjustment; 2) each time point still carries the original time-of-flight information. The time-physical quantity dual-parameter structure provides input data for subsequent signal processing that conforms to temporal causality and retains the original physical characteristics.

[0065] Example 6: As Figure 5 As shown, based on Example 1, the process of reconstructing the three-dimensional cross-sectional profile of the conductor through L1 norm optimization iteration in step S300 of this embodiment of the invention specifically includes the following steps:

[0066] Step S301: Input the motion-compensated distance-angle sparse measurement dataset into the compressed sensing reconstruction program, use the L1 norm as the sparsity regularization term, and use an iterative soft thresholding algorithm for optimization. In each iteration, first calculate the residual between the current estimated point cloud and the measurement data; then perform soft thresholding on the residual to enhance sparsity. Repeat the iteration until the residual converges to below the preset threshold, and reconstruct the three-dimensional spatial point cloud coordinate set of each scanned section on the conductor surface to obtain the three-dimensional cross-sectional contour point cloud data of the conductor.

[0067] Step S302: From the point cloud data of the 3D cross-section profile of the conductor, extract the projection point set of each cross-section position one by one along the conductor axis at a fixed step size. Project the projection point set onto a plane perpendicular to the conductor axis. Calculate the minimum circumcircle of the point set in the plane using the convex hull algorithm to obtain the maximum and minimum diameters of the cross-section. Then calculate the difference between the maximum and minimum diameters and divide it by the nominal diameter to obtain the roundness deviation parameter. After traversing all cross-sections, form a discrete sequence of maximum diameter, minimum diameter, and roundness deviation along the conductor axis.

[0068] Step S303: Sort the discrete maximum diameter sequence, minimum diameter sequence, and roundness deviation sequence according to the conductor axial mileage coordinates. Use cubic spline interpolation to supplement intermediate values ​​for unsampled positions between two adjacent measurement sections, so that the diameter value changes continuously along the mileage coordinates. Mark the roundness deviation parameter as a floating label next to the curve of the corresponding mileage coordinate, forming a continuous and smooth diameter change curve along the entire line. Each point on the curve is accompanied by the roundness deviation information.

[0069] The iterative soft thresholding algorithm is a numerical iterative method for solving L1 norm regularized optimization problems. Its core is to alternately execute gradient descent and soft thresholding shrinkage steps in each iteration. The algorithm is used to recover the complete 3D cross-sectional profile of a conductor from motion-compensated distance-angle sparse measurement data. It finds the optimal cloud solution that satisfies the sparse constraints through a stepwise approximation method, ensuring that the reconstructed profile preserves the surface details of the conductor while suppressing artifacts caused by noise. The residual between the point cloud and the measurement data refers to the difference vector between the theoretical distance-angle value calculated by projecting the estimated 3D point cloud coordinates of the conductor according to the forward projection of the measurement model, and the corresponding value in the actual acquired motion-compensated sparse measurement dataset. The residual reflects the degree of deviation between the currently estimated point cloud and the actual conductor surface, and is the core basis for determining the convergence direction and controlling the update step size in the iterative soft thresholding algorithm. Soft thresholding shrinkage is an operation that applies a nonlinear transformation to each component of the residual vector: components with absolute values ​​less than a certain threshold are set to zero, and components with absolute values ​​greater than the threshold are shrunk towards zero by the threshold value. Soft thresholding shrinkage is used to enhance the sparsity of the reconstructed point cloud in the transform domain, that is, to retain the strong residual components corresponding to the main geometric features of the conductor surface, and to filter out the weak residual components caused by quantum noise, residual background light, or compensation residual errors, thereby gradually converging to a sparse solution that conforms to the actual contour of the conductor during the iteration process. The preset threshold is a pre-set convergence judgment boundary of the residual norm, which is a positive scalar value; when the L2 norm of the residual between the point cloud obtained in the current iteration and the measurement data is less than the preset threshold, it is determined that the iteration has met the accuracy requirements and the iteration stops. The threshold is pre-calibrated according to the measurement noise level of the quantum lidar, the surface roughness of the conductor, and the diameter measurement accuracy requirements. The typical value range corresponds to the sub-millimeter level spatial positioning error to ensure that the reconstructed contour can distinguish single-strand aluminum wire wear or local bulges. A cross section refers to the two-dimensional point set contour obtained by intersecting a plane perpendicular to the conductor axis with the three-dimensional spatial point cloud data of the conductor at a certain mileage location along the conductor axis. A series of cross sections are extracted along the conductor axis at fixed step sizes. Each cross section represents the local cross-sectional shape of the conductor at that location and is used to calculate the maximum diameter, minimum diameter, and roundness deviation parameters at that location, thereby achieving continuous diameter measurement along the entire length of the conductor. The three-dimensional spatial point cloud coordinate set is a dataset output by the compressed sensing reconstruction program, representing the spatial position of each measurement point on the conductor surface in a three-dimensional Cartesian coordinate system. Each point contains three coordinate values: X, Y, and Z. The X-axis is along the conductor axis, and the Y and Z axes form a cross-sectional plane perpendicular to the conductor axis. The point cloud set is the basic geometric data for subsequent extraction of cross-sectional contours and calculation of diameter parameters. Its density and accuracy directly determine the reliability of the diameter measurement results.

[0070] In the above embodiments, this embodiment reconstructs the three-dimensional cross-sectional contour point cloud of the conductor from the sparse measurement data of the quantum lidar by combining compressed sensing reconstruction with L1 norm sparse optimization, solving the problem of point cloud loss caused by vibration of the energized conductor; the extreme diameter of the cross-section is extracted based on the convex hull algorithm to achieve sub-millimeter level dynamic deformation monitoring accuracy. Cubic spline interpolation is used to establish a continuous diameter variation model to quantify the dynamic roundness deviation of the conductor under electromagnetic-mechanical coupling; the axial diameter distribution and radial deformation parameters are output simultaneously to provide spatial deformation input for electromagnetic loss calculation and mechanical strength assessment of high-voltage lines. The generated diameter-roundness curve is directly related to the dynamic capacity expansion limit and wind vibration safety margin of the conductor, meeting the online monitoring requirements of the combined deformation of thermal expansion and mechanical vibration of the conductor under energized conditions; through closed-loop processing of lidar point cloud reconstruction and geometric parameter extraction, non-contact quantum measurement of the dynamic radial dimension of the conductor is realized.

[0071] Example 7: Based on Example 6, the process of calculating the minimum circumcircle of a set of points in a plane using the convex hull algorithm in step S302 of this embodiment of the invention specifically includes the following steps:

[0072] Step S3021: Using the single cross-section projection point set extracted from the 3D cross-section contour point cloud data of the conductor as input, execute the Graham scan method or the Andrew monotonic chain algorithm to calculate the convex hull of the cross-section projection point set, obtain the convex hull vertex sequence arranged in counterclockwise order, and obtain the convex hull boundary point set of the cross section.

[0073] The Graham scan algorithm is used as follows: First, find the point with the smallest y-coordinate in the point set as the base point. If the y-coordinates are the same, take the point with the smallest x-coordinate. Calculate the polar angles of the remaining points relative to the base point and sort them in ascending order of polar angle. Initialize an empty stack and push the base point and the first point with the smallest polar angle onto the stack. Then, traverse each subsequent point in turn, checking whether the direction formed by the top two points of the stack and the current point is counterclockwise. If it is clockwise or collinear, pop the top element of the stack. Repeat the check until the counterclockwise condition is met and then push the current point onto the stack. After the traversal, the points remaining in the stack form the convex hull boundary point set in counterclockwise order. Alternatively, the Andrew monotonic chain algorithm can be used: Sort the point set in ascending order of X coordinate, and if X is the same, sort in ascending order of Y. First, scan from left to right to construct the lower convex hull, then scan from right to left to construct the upper convex hull. When merging the upper and lower convex hulls, remove duplicate endpoints to obtain the convex hull vertex sequence.

[0074] Step S3022: Based on the set of boundary points of the convex hull, use the rotating caliper method to traverse all edges of the convex hull. For each edge, find the farthest vertex in the caliper direction parallel to it, and record the point-to-point distance in the direction. After the traversal is completed, take the minimum distance value in all directions as the diameter of the minimum circumcircle. The diameter is the maximum diameter of the cross section. At the same time, record the direction line corresponding to the diameter to obtain the maximum diameter of the cross section and its direction.

[0075] The process involves inputting the convex hull vertex sequence into the rotating caliper method module: initializing two pointers, one pointing to the first edge of the convex hull and the other pointing to the farthest vertex corresponding to that edge; traversing all edges of the convex hull, for each edge, calculating the distance from the current vertex to the line containing that edge, and moving the other pointer to the vertex position that maximizes the distance, recording the distance as the candidate diameter length, and simultaneously recording the direction vector of that edge; after all edges have been traversed, taking the maximum value among all candidate diameters as the maximum diameter of the cross section, and recording the direction line corresponding to the maximum diameter;

[0076] Step S3023: After obtaining the direction of the maximum diameter, rotate the direction by 90 degrees to obtain the vertical direction, search the maximum span along the vertical direction in the original cross-section projection point set, and calculate the difference between the maximum and minimum values ​​of the projection coordinates of all points in the vertical direction; the difference is the minimum diameter of the cross-section, and finally obtain the maximum and minimum diameters of the cross-section.

[0077] The process involves rotating the line in the direction of the maximum diameter by 90 degrees to obtain a direction line perpendicular to it. Specifically, the direction vector of the line in the direction of the maximum diameter is transformed into an orthogonal vector by swapping the coordinate components and changing the sign of one of them. Then, all points in the original cross-section projection point set are traversed in the vertical direction, and the projected coordinate value of each point on the vertical direction line is calculated. The maximum and minimum values ​​of the projected coordinates are taken, and the difference between them is calculated. The difference is the minimum diameter of the cross-section. The reason for rotating it by 90 degrees is to obtain the cross-section width perpendicular to the direction of the maximum diameter through the orthogonal direction, which represents the minimum span of the conductor on the cross-section and accurately calculates the roundness deviation parameter. Finally, the maximum and minimum diameters of the cross-section are obtained.

[0078] In the above embodiments, this embodiment uses the Graham scan method or the Andrew monotonic chain algorithm to efficiently extract the convex hull boundary point set from the original point cloud. Polar angle sorting or monotonic chain scanning ensures the order and integrity of the boundary points, establishing an accurate geometric topology for computation. The application of the rotating caliper method optimizes the traversal of the convex hull boundary. By dynamically tracking the farthest vertex, it avoids the performance loss caused by full computation, accurately locating the maximum diameter and its direction vector; reducing the complexity of the traditional O(n²) brute-force search to linear level, significantly improving computational efficiency. The orthogonal direction search mechanism generates a reference axis perpendicular to the maximum diameter through vector rotation, performing projection calculations on the original point set rather than the convex hull point set, ensuring that the measurement result of the minimum diameter is not affected by the convex hull fitting error; through mathematical methods of coordinate transformation and extreme value projection, it accurately captures the true minimum span of the cross section. The final output maximum and minimum diameter parameters provide an accurate geometric benchmark for roundness evaluation. The entire algorithm, through multi-stage processing of convex hull dimensionality reduction, rotation traversal, and orthogonal projection, optimizes computational complexity while ensuring measurement accuracy, meeting the dual requirements of real-time performance and reliability in engineering applications.

[0079] Dynamic diameter measurement of conductors on a high-voltage transmission line: Due to the constant influence of strong winds, the conductors (LGJ-400 / 35 type steel-cored aluminum stranded wire) of a certain 500kV transmission line (XX line #32-#33) exhibit abnormal vibrations. The maintenance unit requires dynamic diameter measurement of the conductors under energized conditions to assess whether there are defects such as wear or bulges.

[0080] The detection method uses a quantum lidar diameter measurement system (model: QLDS-5000), and the main process is as follows:

[0081] Dynamic scanning, 5 minutes / level, the measuring vehicle is parked 12 meters to the side of the conductor, emitting 1550nm quantum entangled light, and collecting the echo on the surface of the conductor in real time;

[0082] Simultaneous recording of flight time and interferometric frequency offset, with a data sampling rate of 1kHz;

[0083] Motion compensation, based on instantaneous velocity sequence, corrects point cloud offset caused by conductor galloping, with a compensation error of <0.2mm;

[0084] Defect analysis involves extracting conductor cross-sectional parameters through 3D reconstruction and calculating the maximum diameter, minimum diameter, and roundness deviation.

[0085] Key test data:

[0086]

[0087] Anomaly analysis (K23+105):

[0088] Localized bulge +0.7mm: Loose outer layer of aluminum strands causing abnormally large diameter.

[0089] Necking defect - 1.6mm: internal steel core corrosion, out-of-round cross section, deviation > 5% threshold.

[0090] Operation and maintenance suggestions:

[0091] 1. Emergency Control: Limit the load current of conductor segment K23+105 to 80% of its rated value to prevent localized overheating;

[0092] 2. Re-inspection plan: The temperature rise will be re-verified using UAV infrared imaging within two weeks;

[0093] 3. Maintenance Arrangement: Replace the wires in conjunction with the next power outage opportunity.

[0094] This test utilizes quantum lidar technology to achieve dynamic diameter measurement of high-voltage live conductors, accurately locating mechanical damage at K23+105. The data is authentic and valid, providing a basis for decision-making in line operation and maintenance.

[0095] Figure 6A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0096] Electronic devices may include a central processing unit / microprocessor / main control chip; and a storage medium coupled to the central processing unit / microprocessor / main control chip, wherein computer-executable instructions are stored for performing the steps of various methods of embodiments of the present invention when executed by a processor.

[0097] The central processing unit / microprocessor / main control chip may include, but is not limited to, one or more processors or microprocessors.

[0098] Storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (such as hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0099] In addition, the electronic device may include (but is not limited to) a data bus, an input / output bus / external bus / device bus, a display, and input / output devices (e.g., keyboard, mouse, speaker, etc.).

[0100] The central processing unit / microprocessor / main control chip can communicate with external devices via wired or wireless networks (not shown) through input / output buses / external buses / device buses.

[0101] The storage medium may also store at least one computer-executable instruction for performing the steps of various functions and / or methods in the embodiments described herein when the central processing unit / microprocessor / main control chip is running.

[0102] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0103] Figure 7 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0104] like Figure 7As shown, instructions, such as computer-readable instructions, are stored on a non-transitory computer-readable storage medium. When the computer-readable instructions are executed by a processor, the various methods described above can be performed. The non-transitory computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the non-transitory computer-readable storage medium, the various methods described above can be performed.

[0105] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0106] The units described as separate components may or may not be physically separate. 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0107] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0108] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0109] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dynamic diameter measurement of live conductors in high-voltage overhead lines based on quantum lidar, characterized in that, The process includes the following steps: using frequency-entangled-squeezed photon pairs generated by a quantum entangled light source for FMCW modulation, and then simultaneously detecting the conductor echo and local reference light after beam splitting; obtaining the time-of-flight histogram and instantaneous velocity sequence through quantum coincidence measurement; dynamically resampling the original data based on the velocity sequence to compensate for motion distortion caused by wind deflection or torsion, and generating a corrected sparse distance-angle dataset; and using compressed sensing L1 optimization to reconstruct the three-dimensional profile of the conductor, outputting the diameter variation curve and roundness parameters for the entire conductor section.

2. The method for dynamic diameter measurement of live high-voltage overhead line conductors based on quantum lidar as described in claim 1, characterized in that, A quantum entangled light source generates frequency entangled-squeezed composite photon pairs and applies FMCW phase modulation; the signal beam is irradiated onto the surface of the target conductor, while the idler beam is retained in the local reference arm; the receiver obtains the flight time histogram of the echo photons through quantum correlation coincidence detection, and extracts the instantaneous radial velocity of the conductor using the frequency offset of the interference fringes, thus obtaining the original flight time data and instantaneous velocity sequence with timestamps.

3. The method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar as described in claim 2, characterized in that, The process of obtaining raw flight time data with timestamps and instantaneous velocity sequences includes the following steps: The receiver obtains the time-domain signal sequence of interference fringes through quantum correlation coincidence detection. After windowing the time-domain signal sequence of interference fringes with a window function, it performs a fast Fourier transform and searches for the position of the spectral peak with the maximum amplitude in the frequency domain. The frequency coordinates corresponding to the spectral peak are marked as the frequency offset of the interference fringes. The Fourier transform and spectral peak extraction operations are repeated for the interference fringes of each measurement period to obtain the frequency offset sequence arranged in the order of measurement time. Each frequency offset in the frequency offset sequence is substituted into the FMCW velocity measurement equation in turn; the proportional relationship is calculated, and the instantaneous radial velocity corresponding to each frequency offset is calculated respectively. All the calculation results are arranged in the original order to obtain the instantaneous radial velocity sequence. Each velocity value in the instantaneous radial velocity sequence is matched one-to-one with the corresponding timestamp in the original flight time data.

4. The method for dynamic diameter measurement of live high-voltage overhead line conductors based on quantum lidar as described in claim 1, characterized in that, Using the instantaneous velocity sequence as a dynamic time reference, non-uniform resampling correction is performed on the flight time histogram to eliminate point cloud displacement distortion caused by wind deflection, torsion, and measurement platform motion, resulting in a motion-compensated distance-angle sparse measurement dataset.

5. The method for dynamic diameter measurement of live high-voltage overhead line conductors based on quantum lidar as described in claim 4, characterized in that, The process of performing non-uniform resampling correction on the time-of-flight histogram includes the following steps: Using the instantaneous velocity sequence as a dynamic time reference, the instantaneous radial velocity value of each measurement cycle in the sequence is accumulated over time to calculate the cumulative displacement offset between the measurement platform and the target conductor due to relative motion from the start of the measurement to the current time, thus obtaining the cumulative displacement offset sequence. Based on the cumulative displacement offset sequence, the photon arrival time corresponding to each flight time value in the original flight time histogram is repositioned; the flight time axis distortion caused by wind deflection, torsion and measurement platform movement is compensated to generate a corrected flight time sequence; Each time value in the corrected flight time series is associated with the corresponding scan angle encoder output value, so that each distance value after flight time conversion is accompanied by its corresponding spatial angle information, forming a motion-compensated distance-angle sparse measurement dataset.

6. The method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar as described in claim 5, characterized in that, When the cumulative displacement is positive, the photon arrival time is delayed by the amount of time corresponding to the cumulative displacement; when the cumulative displacement is negative, the photon arrival time is advanced by the amount of time corresponding to the cumulative displacement.

7. The method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar as described in claim 5, characterized in that, The process of generating the corrected flight time series includes the following steps: Based on the cumulative displacement offset sequence, the original arrival time of the photon corresponding to each flight time value in the original flight time histogram is searched one by one, and the offset value within its time interval is used as the time amount to be compensated for the photon arrival time. If the time amount to be compensated is positive, it is recorded as the backward shift; if it is negative, its absolute value is recorded as the forward shift, while retaining the positive and negative signs, thus obtaining a detailed sequence of the direction and amplitude to be compensated for each photon arrival time. According to the detailed sequence of directions and amplitudes to be compensated, the original arrival time of each photon is shifted one by one; during the shifting process, the relative order between each photon is kept from crossing or misaligning. After the arrival time of all photons is adjusted, a new sequence of arrival times is generated after time axis stretching or compression correction. Each arrival time in the new arrival time sequence is bound to its original corresponding time-of-flight value as a data pair, and all data pairs are rearranged in ascending order of the new arrival time. During the rearrangement, if two different photons have the same new arrival time, they are prioritized according to the smaller original time-of-flight value. Finally, a corrected time-of-flight sequence is formed, in which the first element of each data pair in the time-of-flight sequence is the corrected arrival time, and the second element is the corresponding time-of-flight value.

8. The method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar as described in claim 7, characterized in that, For photons marked as shifted backward, add a positive shift value to their original arrival time and move them along the time axis in the direction of increasing value by the corresponding time length; for photons marked as shifted forward, subtract the positive shift value from their original arrival time and move them along the time axis in the direction of decreasing value by the corresponding time length.

9. The method for dynamic diameter measurement of live conductors of high-voltage overhead lines based on quantum lidar as described in claim 1, characterized in that, The motion-compensated sparse measurement dataset is input into the compressed sensing reconstruction program. The three-dimensional cross-sectional profile of the conductor is reconstructed through L1 norm optimization iteration. The maximum diameter, minimum diameter, and roundness deviation parameters are extracted from the profile to form a continuous diameter variation curve along the entire span of the line.

10. The method for dynamic diameter measurement of live high-voltage overhead line conductors based on quantum lidar as described in claim 9, characterized in that, The process of reconstructing the three-dimensional cross-sectional profile of a conductor through L1 norm optimization iteration includes the following steps: The motion-compensated distance-angle sparse measurement dataset is input into the compressed sensing reconstruction program. The L1 norm is used as the sparsity regularization term, and an iterative soft thresholding algorithm is used for optimization. In each iteration, the residual between the current estimated point cloud and the measurement data is calculated first. Then, the residual is shrunk by soft thresholding to enhance sparsity. The iteration is repeated until the residual converges to below the preset threshold. The three-dimensional spatial point cloud coordinate set of each scan section on the conductor surface is reconstructed, and the three-dimensional cross-sectional contour point cloud data of the conductor is obtained. From the point cloud data of the 3D cross-section profile of the conductor, the projection point set of each cross-section position is extracted one by one along the conductor axis at a fixed step size. The projection point set is projected onto a plane perpendicular to the conductor axis. The minimum circumcircle of the point set in the plane is calculated by the convex hull algorithm to obtain the maximum and minimum diameters of the cross-section. Then, the difference between the maximum and minimum diameters is calculated and divided by the nominal diameter to obtain the roundness deviation parameter. After traversing all cross-sections, the maximum diameter sequence, minimum diameter sequence and roundness deviation sequence are formed discretely arranged along the conductor axis. The discrete maximum diameter sequence, minimum diameter sequence, and roundness deviation sequence are sorted according to the conductor axial mileage coordinates. For unsampled positions between two adjacent measurement sections, the intermediate values ​​are supplemented using cubic spline interpolation, so that the diameter value changes continuously along the mileage coordinates. The roundness deviation parameter is marked as a floating label next to the curve of the corresponding mileage coordinate, forming a continuous and smooth diameter change curve along the entire span of the line, with roundness deviation information attached to each point on the curve.

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