Tower positioning method and system based on coherent detection type Φ-otdr

Abstract

The application provides a tower positioning method and system based on a coherent detection type Phi-OTDR. The method comprises: acquiring optical cable route calibration data of a line to be monitored; collecting dynamic phase curve data of an optical fiber along the line by using a coherent detection type Phi-OTDR, generating a spatial spectrum image through Fourier transform; identifying the position of a junction box in the image, and dividing an independent monitoring unit; extracting the wind vibration frequency characteristics of the spatial spectrum image in each unit, determining the distance boundary of each optical cable section according to the continuous bright line and vacancy characteristics corresponding to the wind vibration fundamental frequency and its harmonics, and inverting the measured distance position of each tower; and finally mapping the measured distance and the route calibration data to establish the corresponding relationship between the distance and the tower number. The application can realize accurate positioning of towers, and can assist in identifying tower types. The application overcomes the defects of traditional OTDRs, such as being affected by redundant optical cables and relying on manual comparison of account books, and is suitable for intelligent operation and maintenance of overhead transmission lines.

Description

Technical Field

[0001] This invention belongs to the field of power infrastructure monitoring technology, and particularly relates to a tower positioning method and system based on coherent detection Φ-OTDR. Background Technology

[0002] With the continuous expansion of the power grid, the safe operation and maintenance of overhead transmission lines is becoming increasingly important. Optical cables such as Fiber Optic Composite Overhead Ground Wire (OPGW) are widely laid on transmission towers, serving both communication functions and as sensing media. Currently, line fault location mainly relies on Optical Time Domain Reflectometers (OTDRs), which identify splice or break points by detecting abrupt changes in attenuation of backscattered or reflected light in the optical fiber. Maintenance personnel manually compare the distance of these abrupt changes measured by the OTDR with the design spans of adjacent towers recorded in the tower inventory to estimate the tower section where the fault occurs.

[0003] However, this traditional method has inherent drawbacks: fusion splices are typically located inside junction boxes, which contain redundant optical cables of unrecorded lengths. OTDRs measure the physical length of the fiber including the redundant portion, leading to discrepancies between the calculated tower location and the actual location, resulting in positioning errors. Furthermore, each detection requires checking records and accumulating calculations, making the operation cumbersome, slow, and unsuitable for rapid repair needs. More importantly, OTDRs can only identify abnormal points in the fiber's geometry (such as splices or fiber breaks), but cannot detect the tower's anchor points themselves, nor can they distinguish between tension towers and straight-line towers. This limited information acquisition dimension prevents automated and intelligent tower positioning and line status monitoring. Summary of the Invention

[0004] The tower positioning method based on coherent detection Φ-OTDR provided in this application can achieve accurate tower positioning and assist in tower type identification. It overcomes the shortcomings of traditional OTDRs, which are affected by redundant optical cables and rely on manual comparison of ledgers. It is suitable for intelligent operation and maintenance of overhead transmission lines.

[0005] Firstly, this application provides a tower positioning method based on a coherent detection type Φ-OTDR, including: S1. Obtain the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers. S2. Using a coherent detection type Φ-OTDR device, dynamic phase curve data caused by external disturbance events along the optical cable are collected, and Fourier transform processing is performed on multiple sets of continuously collected dynamic phase curve data to generate spatial spectrum images of the corresponding spatial locations. S3. Identify the location of the optical cable junction box based on the spatial spectrum image, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box; S4. For each independent monitoring unit, extract the wind vibration frequency characteristics from the spatial spectrum image, determine the boundary position of each optical cable segment in the optical fiber distance dimension based on the wind vibration frequency characteristics, and invert the measured distance position of each tower in the independent monitoring unit based on each boundary position; wherein, each optical cable segment corresponds to the optical cable segment between two adjacent towers. S5. Match and map the measured distance and location of each tower with the optical cable route calibration data to establish the correspondence between optical fiber distance and tower number.

[0006] In one optional implementation, in step S2, acquiring dynamic phase curve data along the optical cable caused by external disturbance events includes: Using a coherent detection Φ-OTDR device, the signal of the phase change of backscattered Rayleigh light at each spatial location along the optical fiber is continuously acquired over time at a set sampling frequency and preset acquisition duration, resulting in a dynamic phase curve data set; each frame of data in the dynamic phase curve data set records the phase value at each spatial location of the optical fiber.

[0007] In an optional implementation, in step S3, identifying the location of the optical cable junction box based on the spatial spectrum image includes: In the spatial spectrum image, the region where the vibration intensity is lower than the background vibration intensity across the entire frequency range and is continuously distributed longitudinally along the distance direction is identified as the junction box location.

[0008] In one optional implementation, in step S3, the entire optical cable under test is divided into several independent monitoring units according to the location of the junction box, including: Using the locations of two adjacent junction boxes identified as the start and end points of the independent monitoring unit in the distance dimension, the entire optical cable under test is sequentially divided into multiple independent monitoring units connected end to end.

[0009] In an optional implementation, in step S4, wind vibration frequency features are extracted from the spatial spectrum image, and the boundary positions of each optical cable segment in the fiber distance dimension are determined based on the wind vibration frequency features, including: Wind vibration frequency features are extracted from the spatial spectrum image. These wind vibration frequency features include the fundamental frequency of the wind vibration and its integer multiples of harmonics. Within the independent monitoring unit, the search proceeds segment by segment from the starting point to the ending point. If a continuous distance range exists within the current search area, and this distance range exhibits continuous bright fringes on the wind-induced fundamental frequency and its integer multiple harmonics, and the number of bright fringes gaps on each integer multiple harmonic is consistent with the corresponding harmonic order, then the continuous distance range is determined to correspond to an optical cable segment. The starting point and ending point of this continuous distance range are then determined as the measured distance positions of the two adjacent towers at both ends of the optical cable segment.

[0010] In one optional implementation, if the location of the wind-induced fundamental frequency cannot be confirmed within the current search area, but the locations of multiple integer multiples of the wind-induced fundamental frequency can be confirmed, then the frequency value of the wind-induced fundamental frequency is estimated based on the frequency interval between two adjacent integer multiples of the harmonics, and the estimated wind-induced fundamental frequency is used as the search benchmark to re-execute the bright fringe search and distance range determination to determine the boundary location of the optical cable segment.

[0011] In an alternative implementation, after S4, the method further includes determining the tower type using the natural frequency characteristics in the spatial spectrum image: For each tower, based on the measured distance location, determine whether the spectral component corresponding to the natural frequency is continuous when crossing the tower location. If it is continuous, the tower is determined to be a straight tower; if the spectral component corresponding to the natural frequency shows a discontinuity at the tower location, the tower is determined to be a tension tower.

[0012] In one optional implementation, when the wind vibration frequency characteristics within the independent monitoring unit are missing, the measured distance position of the tension tower is determined by utilizing the fault distribution of the spectral components corresponding to the natural frequency at each tower location. The identified tension towers are then matched one-to-one with the tower number sequence in the optical cable route calibration data according to the measured distance order, and the measured distance position of the straight tower within the independent monitoring unit is calculated accordingly.

[0013] In one optional implementation, in step S5, the measured distance and location of each tower are matched and mapped with the optical cable route calibration data, including: The measured distance position sequence of each tower obtained by inversion within each independent monitoring unit is fitted and aligned with the cumulative sequence of design spans corresponding to each tower number in the optical cable route calibration data to establish a one-to-one correspondence between the measured distance position and the tower number.

[0014] Secondly, this application provides a tower positioning system based on a coherent detection type Φ-OTDR, the system comprising: The data acquisition module is used to acquire the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers. The spatial spectrum image generation module is used to acquire dynamic phase curve data caused by external disturbance events along the optical cable using a coherent detection Φ-OTDR device, and to perform Fourier transform processing on multiple sets of continuously acquired dynamic phase curve data to generate spatial spectrum images of the corresponding spatial locations. The monitoring unit division module is used to identify the location of the optical cable junction box based on the spatial spectrum image, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box; The location inversion module is used to extract wind vibration frequency characteristics from the spatial spectrum image for each independent monitoring unit, determine the boundary position of each optical cable segment in the fiber distance dimension based on the wind vibration frequency characteristics, and invert the measured distance position of each tower in the independent monitoring unit based on each boundary position. The mapping output module is used to match and map the measured distance and location of each tower with the optical cable route calibration data, and establish the correspondence between the optical fiber distance and the tower number.

[0015] Thirdly, this application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method provided in this application.

[0016] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method provided in this application.

[0017] The technical solution provided in this application uses a coherent detection Φ-OTDR instead of a traditional OTDR. It continuously acquires dynamic phase changes caused by external disturbances (such as wind vibration) at various locations along the optical fiber, and converts the time-domain signal into a two-dimensional spatial-spectral image using Fourier transform. This image clearly shows the wind vibration frequency components unique to different optical cable sections. The wind vibration fundamental frequency and its integer multiples of harmonics form continuous bright fringes along the distance direction, and frequency gaps corresponding to the order appear at the harmonic locations. This characteristic has a strict correspondence with the length of the optical cable section and the tower boundary. Based on this physical law, this invention can directly invert the boundaries of each optical cable section by searching for bright fringes segment by segment in the spectral image. The fiber optic distance between the towers at both ends of a section can be determined without relying on the span values ​​in the ledger, thus fundamentally eliminating errors caused by the unknown length of redundant optical cables in the junction box. Simultaneously, the spatial spectrum image also contains low-frequency natural frequency components, whose continuity or interruption characteristics when crossing towers accurately reflect the tower type (straight-line tower or tension tower), providing additional information for line structure assessment. Furthermore, since the positioning process automatically completes image recognition and boundary extraction, there is no need for manual review of ledgers and span-by-span calculations, significantly improving the immediacy of fault response. In summary, this invention achieves high-precision, high-efficiency, and multi-information fusion tower positioning, significantly enhancing the intelligent operation and maintenance capabilities of overhead lines. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the tower positioning method based on coherent detection Φ-OTDR provided in this application; Figure 2 This is the original spatial spectrum diagram provided in this application; Figure 3 This is a schematic diagram of the division of wind-induced vibration and natural vibration frequency ranges provided in this application; Figure 4 This is a schematic diagram of the tower positioning system based on coherent detection type Φ-OTDR provided in this application. Detailed Implementation

[0019] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Figure 1 This is a flowchart illustrating the tower positioning method based on coherent detection Φ-OTDR provided in this application, as shown below. Figure 1 As shown, the technical solution provided in this application includes the following steps: S1. Obtain the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers.

[0021] In some embodiments, the optical cable route calibration of the overhead transmission line to be monitored is first completed. Through on-site surveys or historical data, the tower numbers and the designed span between adjacent towers (i.e., the theoretical length of the optical cable between two towers, in meters) are obtained. Simultaneously, this information is entered into a database to establish a basic "tower number - approximate location" correspondence list, so that the analyzed feature points can be matched one-to-one with the actual towers in subsequent steps. It should be noted that the "theoretical length of the optical cable" here is only an initial reference value and will be precisely corrected through subsequent signal analysis.

[0022] S2. Using a coherent detection type Φ-OTDR device, dynamic phase curve data caused by external disturbance events along the optical cable are collected, and Fourier transform processing is performed on multiple sets of continuously collected dynamic phase curve data to generate spatial spectrum images of the corresponding spatial locations.

[0023] In some embodiments, a Φ-OTDR device is used to acquire vibration signals along the optical fiber and convert them into a spatial spectrum image to reveal the distribution of vibration frequency components at each location.

[0024] Connect the coherent detection Φ-OTDR device to one end of the optical cable to which the overhead transmission line to be monitored is attached via an optical cable jumper. Set the pulse width (determines spatial resolution), repetition frequency (determines maximum detection distance), and sampling rate of the probe light pulse (satisfying the Nyquist sampling theorem to cover the highest vibration frequency of interest, e.g., ≥100Hz). Ensure that the center wavelength of the light source is stable (e.g., 1550nm) and has high coherence (coherence length greater than the total length of the optical cable).

[0025] The Φ-OTDR device is activated, injecting coherent probe light pulses into the optical fiber. The receiver employs coherent detection, heterodyne interferometry between the backscattered Rayleigh light and the local oscillator light, and extracts the phase change information of the scattered light using a balanced detector. For each spatial location point on the fiber (distance resolution depends on the pulse width, typically 5-20m), the phase change of the scattered light over time is recorded, forming a dynamic phase curve, denoted as . ,in, The distance along the fiber optic cable. The acquisition time is represented by this curve. This curve fully records the phase disturbance caused by the propagation of sound / vibration waves along the optical fiber, reflecting the spatial and temporal distribution of external vibration events (such as wind vibration, mechanical vibration, etc.).

[0026] Continuous collection for a period of time ,For example The time is set to ensure that low-frequency components (such as those below 1 Hz) are sufficiently observed, resulting in a continuous set of dynamic phase curve data. Subsequently, for each spatial location... Phase timing signal at the point Perform a Discrete Fourier Transform (DFT) to transform it from the time domain to the frequency domain, obtaining the vibration spectrum amplitude at that location. Apply this to all locations. The spectral amplitudes are arranged by distance to obtain a two-dimensional spatial spectral image, with the horizontal axis representing the fiber distance. The vertical axis represents frequency. The pixel grayscale represents the vibration intensity. This image can clearly distinguish the vibration frequency characteristics of different fiber optic cable segments.

[0027] In some embodiments, wavelet transform or Hilbert-Huang transform (HHT) can also be used to generate time-frequency diagrams, which can also extract wind vibration and natural frequency features, and are suitable for non-stationary vibration signals.

[0028] S3. Identify the location of the optical cable junction box based on the spatial spectrum image, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box.

[0029] In some embodiments, Figure 2 This is the original spatial spectrum diagram provided in this application. Figure 3 This is a schematic diagram illustrating the division of wind-induced vibration and natural frequency ranges provided in this application. See [link / reference]. Figure 2 and Figure 3In the spatial spectrum image, the location of the junction box is significantly lower than the adjacent area at all frequencies because the optical cable is fixed inside the box and the excess cable is coiled, making it difficult for external vibrations to be effectively transmitted. This appears as a dark band across all frequencies on the spectrum. Using these dark areas corresponding to the junction boxes as natural dividing boundaries, the entire sensing optical cable can be divided into several independent monitoring units. Each monitoring unit corresponds to the line segment between two tension towers. Through image edge detection or threshold segmentation algorithms, the location of these dark bands, i.e., the fiber optic distance corresponding to the junction box, is automatically identified. ( , (Total number of junction boxes).

[0030] In some embodiments, threshold segmentation employs an adaptive threshold, using the average vibration intensity of all pixels in the entire spatial spectrum image multiplied by a preset coefficient (e.g., 0.3~0.5) as the segmentation threshold. A region identified as a junction box must simultaneously meet the following conditions: (a) the vibration intensity of the region is below the segmentation threshold across all frequency ranges; (b) the continuous length of the region along the distance direction is greater than a preset length threshold (e.g., 10 meters) to exclude isolated low-brightness pixels caused by random noise or localized weak vibrations. If the fiber optic distance between identified adjacent junction box locations is less than a preset distance threshold (e.g., 100 meters), they are merged or marked as suspected junction boxes for manual verification.

[0031] In some embodiments, in addition to image dark area threshold segmentation, the characteristic of extremely small phase variance at the optical cable fixing point can be utilized to directly calculate the time variance of the phase at each position. The point with the lowest variance is the junction box, without relying on the image.

[0032] S4. For each independent monitoring unit, extract the wind vibration frequency characteristics from the spatial spectrum image, determine the boundary position of each optical cable segment in the optical fiber distance dimension based on the wind vibration frequency characteristics, and invert the measured distance position of each tower in the independent monitoring unit based on each boundary position.

[0033] Each optical cable section corresponds to the optical cable section between two adjacent towers.

[0034] In some embodiments, the optical cable segment between two adjacent junction boxes is used as an independent monitoring unit. Each unit covers a distance range: ; This unit contains several towers, let the number of which be... Then, a gap will form between adjacent towers. Independent optical cable section. The first and last towers of the unit (i.e., the towers where the junction boxes are located) are fixed as tension towers.

[0035] Each segment of optical cable generates a unique wind-induced vibration frequency (or simply wind vibration frequency) under the excitation of an external wind field, typically above 1 Hz. Due to differences in cable length, tension, and other parameters among different cable segments, their dominant wind vibration frequencies also differ. In a spectral image, these wind vibration frequencies clearly show the range of their propagation along the cable. The boundary of each wind vibration frequency range is the location of the tower. This is because the hardware on the tower (such as suspension clamps) partially hinders the transmission of wind vibration energy, causing abrupt changes or attenuation in the vibration frequency of different cable segments at the tower. In a spatial spectral image, the wind vibration frequency of the same cable segment appears as a horizontal bright stripe of a certain width (covering the length of the cable segment) in the distance direction, with frequency gaps appearing at harmonics (i.e., lower energy at the center frequency, appearing as a "gap").

[0036] The specific location process is as follows: The dark stripe at the beginning of the unit (the side with the smaller distance) corresponds to tower number 1 (the connection tower), and the dark stripe at the end (the side with the larger distance) corresponds to... Tower number [number] is marked with its distance [distance]. and .

[0037] In the image, from the position of tower number 1 Starting from the right-hand region (i.e., the direction of increasing distance), search for a continuous bright frequency fringe with a certain width along the distance direction (corresponding to the length of the optical cable) and multiple equally spaced gaps (corresponding to harmonics) at that frequency. Specifically, assume that a candidate fundamental frequency value is observed. Observe its harmonics , Check whether bright fringes also exist at positions ..., and whether the number of gaps is equal to their respective orders. If the existence of at least two harmonics can be confirmed, then it can be determined that... The light ripple represents the fundamental frequency of wind-induced vibration in this section of the optical cable. The distance covered by the light ripple is the span of the first section of the optical cable, and the distance corresponding to its rightmost boundary is the location of tower number 2. If the fundamental frequency is not obvious and only multiple harmonics are observed, the fundamental frequency can still be estimated based on the spacing between the harmonics, thus achieving the same location.

[0038] After confirming the location of tower No. 2 Then, repeat the above operation on the right side of the area to search for the wind vibration frequency of the second optical cable section and determine the location of tower No. 3. This process continues until all towers within the unit are located, yielding the actual distance sequence.

[0039] In some embodiments, the search can employ a sliding window traversal method, scanning the spatial spectrum image segment by segment along the distance direction, and determining the bright ripple region and its boundary based on whether the pixel grayscale within the window is higher than the background grayscale. The specific window size and grayscale threshold can be set by those skilled in the art based on the device's spatial resolution and the ambient noise level.

[0040] In some embodiments, in addition to the fundamental frequency and harmonics of wind vibration, the peak value of the wind vibration frequency amplitude along the distance or the abrupt change in the phase gradient can also be used to locate the tower, not limited to the harmonic gap feature.

[0041] Furthermore, following S4, it also includes using the natural frequency characteristics in the spatial spectrum image to determine the tower type: In addition to wind-induced vibration frequency, optical cables also possess an inherent natural frequency (typically below 1 Hz). The propagation characteristics of this natural frequency can be used to distinguish between tower types, including tension towers and straight-line towers. The criteria for judgment are as follows: Characteristics of tension towers: Tension towers are equipped with tension clamps, which can firmly fix the optical cable and effectively block the transmission of tensile strain and vibration of the optical cable. Therefore, the natural frequency of the optical cable cannot propagate through the tension tower. In the spectrum image, if a natural frequency signal is suddenly interrupted at a certain tower, showing a clear "discontinuity", then the tower can be identified as a tension tower.

[0042] Characteristics of straight-line towers: Straight-line towers typically use suspension clamps, which provide weaker fixation for the optical cable, allowing for some slippage and vibration transmission. Therefore, the natural frequency of the optical cable can propagate forward through the straight-line tower. In a spectral image, if a natural frequency signal can continuously extend from one tower (e.g., tower x) to another tower (e.g., tower y), then all towers between these two towers (excluding x and y themselves) can be considered straight-line towers.

[0043] In some embodiments, the difference in vibration energy attenuation rate at different tower types can also be used for discrimination (e.g., the energy attenuation is large at tension towers), and cross-validated with the natural frequency tomography method.

[0044] In some embodiments, when weather conditions cause the wind-induced vibration frequency of a portion of the optical cable section to completely disappear within a certain period, traditional wind-based positioning will become unusable. In this case, an auxiliary positioning process is initiated: First, switch to the natural frequency (below 1Hz) channel. Since the natural frequency is minimally affected by external weather conditions and remains stable, the precise distance location (i.e., the location of the low-frequency fault) of all tension towers within the unit is identified on the spatial spectrum image using the aforementioned discrimination method of "tension tower generating spectral faults".

[0045] Then, the identified tension towers are sorted in ascending order of distance. Since the order of tension towers in the same transmission line is known, this sorting can be directly matched with the tower numbering order in the optical cable route calibration data in step one. At this point, although the lack of wind vibration makes it impossible to directly locate straight-line towers, the physical distances of all tension towers have been bound to their actual numbers, forming the "baseline anchor points" within this unit.

[0046] Finally, taking the two adjacent anchored tension towers as the interval boundary, the total fiber length of the interval on the spectrum image is read, and the total length is allocated to each straight tower according to the proportion of each designed span in the interval in step one. The position of the straight tower can be roughly calculated, thus completing the approximate positioning of the entire unit tower.

[0047] S5. Match and map the measured distance and location of each tower with the optical cable route calibration data to establish the correspondence between optical fiber distance and tower number.

[0048] In some embodiments, after the distance positioning of each tower within all units is completed, the actual distance sequence of each tower on the optical fiber obtained in S4 is matched one-to-one with the tower number sequence collected in S1. Specifically, since the order of towers in the same transmission line is determined, and the number sequence of each tower has been recorded in S1, the tower with the closest distance is matched with the first number in the number sequence, the second closest is matched with the second number, and so on, thus establishing a complete mapping relationship between "optical fiber physical distance and tower number".

[0049] Once this mapping relationship is established, if a fiber optic fault (such as a broken fiber or abnormal vibration) is detected, it is only necessary to read the distance value of the fault point on the fiber. The tower number or specific fiber optic cable section where the fault point is located can be directly output through this mapping relationship without the need for additional record checking or manual comparison, thereby achieving rapid and accurate fault location.

[0050] Figure 4 This is a schematic diagram of the tower positioning system based on coherent detection Φ-OTDR provided in this application, as shown below. Figure 4 As shown, the present invention also provides a tower positioning system based on a coherent detection type Φ-OTDR, the system comprising: The data acquisition module is used to acquire the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers. The spatial spectrum image generation module is used to acquire dynamic phase curve data caused by external disturbance events along the optical cable using a coherent detection Φ-OTDR device, and to perform Fourier transform processing on multiple sets of continuously acquired dynamic phase curve data to generate spatial spectrum images of the corresponding spatial locations. The monitoring unit division module is used to identify the location of the optical cable junction box based on the spatial spectrum image, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box; The location inversion module is used to extract wind vibration frequency characteristics from the spatial spectrum image for each independent monitoring unit, determine the boundary position of each optical cable segment in the fiber distance dimension based on the wind vibration frequency characteristics, and invert the measured distance position of each tower in the independent monitoring unit based on each boundary position. The mapping output module is used to match and map the measured distance and location of each tower with the optical cable route calibration data, and establish the correspondence between the optical fiber distance and the tower number.

[0051] The implementation methods of some system embodiments and some method embodiments of the present invention correspond one-to-one, and will not be described again here.

[0052] This application also provides an electronic device, including: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform any of the tower positioning methods based on coherent detection type Φ-OTDR.

[0053] This application also proposes a computer storage medium storing a computer program, which, when executed by a processor, implements any one of the tower positioning methods based on a coherent detection type Φ-OTDR.

[0054] Computer storage media may be simply referred to as media. Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Dual Data SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM). The various embodiments described in this specification are presented in a progressive manner, with reference allowed to each other for similar or identical parts. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for apparatuses, devices, and non-volatile computer storage media are described simply because they are substantially similar to the method embodiments; relevant details can be found in the descriptions of the method embodiments.

[0055] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.

Claims

1. A tower positioning method based on coherent detection type Φ-OTDR, characterized in that, include: S1. Obtain the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers. S2. Using a coherent detection type Φ-OTDR device, dynamic phase curve data caused by external disturbance events along the optical cable are collected, and Fourier transform processing is performed on multiple sets of continuously collected dynamic phase curve data to generate spatial spectrum images of corresponding spatial locations. S3. Based on the spatial spectrum image, identify the location of the optical cable junction box, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box; S4. For each independent monitoring unit, extract the wind vibration frequency features from the spatial spectrum image, determine the boundary position of each optical cable segment in the optical fiber distance dimension based on the wind vibration frequency features, and invert the measured distance position of each tower within the independent monitoring unit based on each boundary position; wherein, each optical cable segment corresponds to the optical cable segment between two adjacent towers. S5. Match and map the measured distance and location of each of the poles and towers with the optical cable route calibration data to establish the correspondence between optical fiber distance and pole / tower number.

2. The method according to claim 1, characterized in that, In step S2, dynamic phase curve data caused by external disturbance events along the optical cable are collected, including: The coherent detection Φ-OTDR device continuously acquires signals of the phase change of backscattered Rayleigh light at various spatial locations along the optical fiber over time using a set sampling frequency and preset acquisition duration, thereby obtaining a dynamic phase curve data set; each frame of data in the dynamic phase curve data set records the phase value at each spatial location of the optical fiber.

3. The method according to claim 1, characterized in that, In step S3, identifying the location of the optical cable junction box based on the spatial spectrum image includes: In the spatial spectrum image, the region where the vibration intensity is lower than the background vibration intensity across the entire frequency range and is continuously distributed longitudinally along the distance direction is identified as the junction box location.

4. The method according to claim 3, characterized in that, In step S3, the entire optical cable under test is divided into several independent monitoring units according to the location of the junction box, including: Using the two adjacent junction box locations identified as the start and end points of the independent monitoring unit in the distance dimension, the entire optical cable under test is sequentially divided into multiple independent monitoring units connected end to end.

5. The method according to claim 4, characterized in that, In step S4, wind vibration frequency features are extracted from the spatial spectrum image, and the boundary positions of each optical cable segment in the fiber distance dimension are determined based on the wind vibration frequency features, including: Extract the wind vibration frequency features from the spatial spectrum image, the wind vibration frequency features including the wind vibration fundamental frequency and integer multiples of the wind vibration fundamental frequency; Within the independent monitoring unit, a segment-by-segment search is performed from the starting endpoint to the ending endpoint. If a continuous distance range exists within the current search area, and this distance range exhibits continuous bright fringes on the wind-induced fundamental frequency and its integer multiple harmonics, and the number of bright fringes gaps on each integer multiple harmonic is consistent with the corresponding harmonic order, then the continuous distance range is determined to correspond to an optical cable segment. The starting endpoint and ending endpoint positions of this continuous distance range are respectively determined as the measured distance positions of the two adjacent towers at both ends of the optical cable segment.

6. The method according to claim 5, characterized in that, If the location of the wind-induced fundamental frequency cannot be confirmed within the current search area, but the locations of multiple integer multiples of the wind-induced fundamental frequency can be confirmed, then the frequency value of the wind-induced fundamental frequency is calculated based on the frequency interval between two adjacent integer multiples of the harmonics. The calculated wind-induced fundamental frequency is used as the search benchmark, and the bright fringe search and distance range determination are re-executed to determine the boundary location of the optical cable segment.

7. The method according to claim 1, characterized in that, Following S4, the method further includes determining the tower type using the natural frequency characteristics in the spatial spectrum image: For each tower, based on the measured distance location, determine whether the spectral component corresponding to the natural frequency is continuous when crossing the tower location. If it is continuous, the tower is determined to be a straight tower; if the spectral component corresponding to the natural frequency has a discontinuity at the tower location, the tower is determined to be a tension tower.

8. The method according to claim 7, characterized in that, When the wind vibration frequency characteristics within the independent monitoring unit are missing, the measured distance position of the tension tower is determined by utilizing the fault distribution of the spectral components corresponding to the natural frequency at each tower location. The identified tension towers are then matched one-to-one with the tower number sequence in the optical cable route calibration data according to the measured distance order, and the measured distance position of the straight tower within the independent monitoring unit is calculated accordingly.

9. The method according to claim 1, characterized in that, In step S5, the measured distance and location of each of the towers are matched and mapped with the optical cable route calibration data, including: The measured distance position sequence of each tower obtained by inversion within each independent monitoring unit is fitted and aligned with the design span accumulation sequence corresponding to each tower number in the optical cable route calibration data to establish a one-to-one correspondence between the measured distance position and the tower number.

10. A tower positioning system based on coherent detection Φ-OTDR, characterized in that, The system includes: The data acquisition module is used to acquire the optical cable route calibration data of the overhead transmission line to be monitored. The optical cable route calibration data includes the number of each tower and the design span between adjacent towers. The spatial spectrum image generation module is used to acquire dynamic phase curve data caused by external disturbance events along the optical cable using a coherent detection Φ-OTDR device, and to perform Fourier transform processing on multiple sets of continuously acquired dynamic phase curve data to generate spatial spectrum images of corresponding spatial locations. The monitoring unit division module is used to identify the location of the optical cable junction box based on the spatial spectrum image, and divide the entire optical cable under test into several independent monitoring units according to the location of the junction box; The location inversion module is used to extract the wind vibration frequency features in the spatial spectrum image for each independent monitoring unit, determine the boundary position of each optical cable segment in the optical fiber distance dimension based on the wind vibration frequency features, and invert the measured distance position of each tower in the independent monitoring unit based on each boundary position. The mapping output module is used to match and map the measured distance and location of each of the poles and towers with the optical cable route calibration data, and establish the correspondence between the optical fiber distance and the pole number.

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