A highway optical fiber point positioning method based on distributed acoustic wave sensing signals

Abstract

The application discloses a highway optical fiber point location calibration method based on distributed acoustic wave sensing signals, and comprises the following steps: converting a facility stake number on a highway into an optical fiber point location, then extracting an optical fiber signal feature set, so that the feature set is matched with the facility, and finally linearly calibrating any optical fiber point location stake number. The highway optical fiber point location calibration method based on distributed acoustic wave sensing signals calibrates all optical fiber point locations to highway stake numbers, so that information such as accidents, road conditions and early warnings calculated based on the optical fiber can be positioned to specific stake numbers, and the precision is improved.

Description

Technical Field

[0001] This invention relates to the field of traffic information technology, specifically to a method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals. Background Technology

[0002] Optical fiber distributed acoustic sensing (DAS) technology is a sensing technology that emits laser beams and uses the principles of optical reflection, scattering, and interference to detect sound and vibration signals in the environment. DAS technology can utilize existing communication optical fibers to achieve long-distance, high-capacity continuous detection of roads and vehicles over a range of 20–50 kilometers.

[0003] For example, among the currently disclosed patent technologies, publication number CN114566040B, entitled "A High-Speed ​​Accident Location System and Method Based on a Telecommunication Company's Buried Optical Cable," includes a high-speed accident location system composed of a buried communication optical cable, a distributed optical fiber vibration detector, and a data processing unit, as well as an accident location method based on this system. This method monitors the driving status of vehicles along the highway in real time. Once an abnormal event is detected, it immediately determines the nature of the event and provides the time and location information of the event, allowing relevant departments to initiate relevant feedback measures and broadcast warnings to vehicles in the affected section of the road, greatly improving the efficiency of accident feedback on highways. This system focuses on the location of accidents on highways through distributed optical fiber sensing technology.

[0004] Secondly, there is also the patent with publication number CN118629213A, entitled "An Integrated System for Highway Traffic Condition Evaluation and Early Warning Based on Distributed Optical Fiber." This system includes a sensing optical fiber laid along the highway lanes to capture sound waves or vibration signals; a distributed optical fiber signal receiving component and a data processing module that receive the sound waves or vibration signals from the sensing optical fiber and process them into practical information; a highway traffic condition evaluation module that receives the practical information from the distributed optical fiber signal receiving component and the data processing module at its input end, and outputs the traffic condition evaluation results for each section of the highway; and a highway traffic early warning response module that receives the evaluation results from the highway traffic condition evaluation module. This system uses distributed optical fiber sensing technology to perform multi-level, fine-grained evaluations of the traffic conditions on each section of the highway, and controls the warning lights on the highway to display different colors and flashing frequencies or simultaneously emit alarm sounds based on the evaluation results.

[0005] The above technologies all rely on the absolute distance of optical fibers to output accident, road condition, and warning locations. However, they overlook the fact that optical fibers on highways can be bent, spliced, or coiled, resulting in actual geographical distances that are shorter than the fiber optic distance. For example, due to construction and laying reasons, the absolute length of the optical fiber does not represent the geographical distance; during highway operation, event and road condition information needs to be converted into road markers; highway markers are not absolutely accurate, therefore the fiber optic distance is not proportionally scaled when calibrated on the markers. Therefore, it is necessary to improve this technology. Summary of the Invention

[0006] This invention addresses the shortcomings of existing technologies by providing a method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals. This method calibrates all fiber optic points to highway station numbers, enabling information such as accidents, road conditions, and early warnings calculated based on fiber optics to be located at specific station numbers.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] A method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals includes the following steps:

[0009] Step 1: Convert the facility station numbers on the highway to fiber optic locations;

[0010] Step 2: Extraction of fiber optic signal feature set;

[0011] Step 3: Identify and match the feature set with the facilities;

[0012] Step 4: Linear calibration of any fiber optic point station number.

[0013] In the above technical solution, step 2, the extraction of the fiber optic signal feature set, includes:

[0014] a. Send pulses to the communication optical fibers that have been pre-laid along the main line of the highway;

[0015] b. The data acquisition system (DAS) collects and obtains the original vibration signal when the vehicle passes through the sensing fiber optic cable. c. 10 minutes of vibration data are collected, and the maximum vibration phase at each point is recorded.

[0016]

[0017] d. Calculate the vibration threshold T = quantum(M, 1-Q)

[0018] e. Select consecutive point segments greater than T to generate feature set A.

[0019] f. If the number of feature sets is greater than the number of facilities, T = T + 1, and repeat step e.

[0020] In the above technical solution, step 1 involves extracting the structure of the highway. The highway has communication optical fibers laid along the main line. When encountering toll collection units or tunnel units, the fiber needs to leave the main line and be jump-connected in the corresponding equipment room, resulting in huge optical attenuation. Therefore, the optical fiber can be segmented into units by changing the optical attenuation.

[0021] In the above technical solution, the process of segmenting the optical fiber into units in step 1 includes the following steps:

[0022] S11, continuous optical fiber is measured as optical fiber length F, with the front and rear jumpers being the first toll station and the second toll station, respectively;

[0023] S12. Calculate the actual road distance D using highway structure information: D = chainage of the second toll station - chainage of the first toll station;

[0024] S13. Using highway structure information, extract all facilities from the first toll station to the second toll station. (B) i For the i-th facility, P i L is the chainage of the starting point of facility i - the chainage of the first toll station. i For facility B i length;

[0025] S14, Total length of computing facility

[0026] S15, Calculation of facility length percentage

[0027] S16, Facility i starting point

[0028] S17, Facility i endpoint

[0029] In the above technical solution, during the identification and matching process of the feature set and facilities in step 3:

[0030] First, establish the distance matrix O;

[0031] The horizontal axis represents facility B. i B i0 As the starting point of the facility, B i1 The end point of the facility;

[0032] The vertical axis represents the feature set A. j A j0 As the starting point of the set, A j1 The endpoint of the set;

[0033] O ij Indicates facility B i With set A j F1 score distance,

[0034] The formula is:

[0035] Then, a dynamic programming algorithm is used to calculate the deviation matrix P, where the formula is:

[0036]

[0037] In the above technical solution, when the fiber optic discrete points are calibrated by station number in step 4, linear normalization is used to divide the intermediate points, where the formula is:

[0038]

[0039] In the above technical solution, the signal frequency of the original vibration signal when the data acquisition system DAS acquires the sensing fiber in step 2 is 2000 Hz, that is, 2000 frames of vibration data are generated per second per point. nm This represents the vibration phase value of the m-th frame at the n-th fiber optic point.

[0040] Beneficial effects: Compared with the prior art, the present invention has the following beneficial effects:

[0041] This invention relates to a method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals. This method calibrates all fiber optic points onto highway station numbers, enabling information such as accidents, road conditions, and early warnings calculated based on fiber optics to be located at specific station numbers. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 This is a flowchart of the highway fiber optic point calibration method based on distributed acoustic wave sensing signals according to the present invention.

[0044] Figure 2 This is a map showing the location of a highway fiber optic point before calibration based on distributed acoustic wave sensing signals, as described in this invention.

[0045] Figure 3 This is a map showing the location of fiber optic points on highways after calibration based on distributed acoustic wave sensing signals, according to the present invention.

[0046] Figure 4 This is a diagram showing the fiber optic point location of the high-speed communication fiber optic cable of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention.

[0048] Please refer to the following: Figures 1 to 3 As shown, the present invention discloses a method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals. First, the station numbers of facilities on the highway are converted into fiber optic points. In this process, feature points (such as jumper points, bridges, tunnels, etc.) in the fiber optic signal are extracted to match the station numbers of the highway, thereby calibrating the correspondence between the fiber optic points and the highway station numbers. Therefore, it is necessary to extract the highway structure.

[0049] Fiber optic cables are laid along the main highway. When encountering toll booths or tunnels, they need to leave the main highway and be patched in corresponding equipment rooms, resulting in significant optical attenuation. Therefore, the optical fiber can be segmented into units based on changes in optical attenuation. In the embodiments of this invention, subsequent implementations are all within a 0-16km unit. Each point in the original fiber optic data represents 10m, therefore 16km contains 1600 points. Please refer to the relevant documentation. Figure 4 As shown.

[0050] The implementation process includes the following steps:

[0051] 1. The fiber length F is calculated as 0-16km. The jump points are the first toll station and the second toll station, respectively.

[0052] 2. Calculate the actual road distance D using highway structure information: D = (chainage of the second toll station - chainage of the first toll station);

[0053] 3. Using highway structure information, extract all facilities from the first toll station to the second toll station, B. i For the i-th facility, P i L is the chainage of the starting point of facility i - the chainage of the first toll station. i For facility B i length;

[0054] 4. Calculate the total length of the facility.

[0055] 5. Calculate the proportion of facility length

[0056] 6. Facility i Starting Point

[0057] 7. Facility i endpoint location

[0058] Table 1 below lists the start and end station numbers and fiber optic start and end points of the 23 facilities between the first and second toll stations:

[0059] Table 1

[0060]

[0061]

[0062] Secondly, the fiber optic signal feature set is extracted, which includes the following steps:

[0063] 1. Send pulses to the communication optical fibers that have been pre-laid along the main line of the highway;

[0064] 2. The DAS system collects and obtains the original vibration signal when the vehicle passes through the sensing fiber optic cable. The signal frequency is 2000 Hz, meaning 2000 frames of vibration data are generated per second per point. nm The vibration phase value of the m-th frame at the n-th fiber optic point;

[0065] 3. Collect 10 minutes of vibration data and take the maximum vibration phase at each point.

[0066]

[0067] 4. Calculate the vibration threshold T = quantum(M, 1-Q)

[0068] 5. Select consecutive point segments greater than T to generate feature set A.

[0069] 6. If the number of feature sets is greater than the number of facilities, T = T + 1, and repeat step 5.

[0070] Table 2 below shows the 23 fiber optic signal feature sets detected:

[0071] Table 2

[0072]

[0073]

[0074] The feature set and facilities are then identified and matched. In this embodiment, the identification and matching process includes the following steps:

[0075] 1. Construct a 23x23 distance matrix O;

[0076] 2. The horizontal axis represents facility B. i B i0 As the starting point of the facility, B i1 This is the end point of the facility.

[0077] 3. The vertical axis represents the feature set A. j A j0 As the starting point of the set, A j1 The endpoint of the set.

[0078] 4. O ij Indicates facility B i With set A j The F1 score distance is calculated using the following formula:

[0079]

[0080]

[0081]

[0082] 5. Use dynamic programming to find the deviation matrix P. Dynamic programming (DP) is typically used to solve problems with optimal properties. In such problems, there may be many feasible solutions, each corresponding to a value. Similar to the divide-and-conquer method, the basic idea of ​​dynamic programming is to decompose the problem to be solved into several subproblems, solve the subproblems first, and then obtain the solution to the original problem from the solutions of these subproblems.

[0083] The formula for calculating the deviation matrix P using the dynamic programming algorithm is:

[0084]

[0085] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 1 2 27 49 66 88 108 129 149 171 191 212 233 264 293 321 354 385 421 457 493 528 562 595 2 29 3 12 21 38 55 73 90 110 129 149 168 198 226 253 284 315 350 384 420 454 488 520 3 33 13 3 5 16 28 43 57 75 91 110 127 155 181 207 237 266 300 333 367 400 433 464 4 30 24 6 3 10 19 31 43 58 73 90 107 133 157 182 210 238 271 303 336 368 400 430 5 37 41 18 11 3 5 12 20 31 42 56 69 92 114 136 163 188 219 249 281 311 342 371 6 36 54 31 20 6 3 6 11 20 29 41 53 74 94 114 139 163 192 221 251 280 309 337 7 37 57 45 32 12 6 3 5 11 17 26 36 55 72 91 114 136 163 190 219 247 275 302 8 36 58 60 45 20 11 5 2 6 11 18 26 43 59 76 97 118 143 169 196 222 249 275 9 39 62 75 60 32 20 10 6 2 4 8 13 27 40 54 73 91 115 138 163 188 213 237 10 37 63 80 75 43 29 17 10 4 2 5 9 21 33 46 63 80 102 125 148 172 196 219 11 39 65 83 91 56 41 26 17 7 5 2 4 13 23 34 49 64 84 104 127 148 171 192 12 38 65 86 100 70 52 35 25 12 8 3 3 11 19 28 42 56 74 93 114 135 156 176 13 49 77 97 113 93 73 53 41 25 20 12 10 3 4 7 14 22 35 49 65 81 97 114 14 51 89 110 126 117 95 73 59 40 33 23 19 5 4 4 9 15 25 36 50 64 79 93 15 56 96 127 144 145 121 97 81 60 51 39 33 12 10 8 5 6 13 20 30 41 52 64 16 54 99 134 160 171 147 120 103 79 69 54 47 20 17 13 5 5 10 16 25 34 45 55 17 61 106 144 173 194 178 149 130 104 92 75 66 33 29 23 11 10 5 6 10 15 21 27 18 59 109 150 182 206 207 177 156 127 114 95 85 46 41 33 18 15 5 5 9 13 18 24 19 58 107 150 187 214 234 204 181 150 136 115 104 59 53 43 25 20 7 5 8 11 15 20 20 60 109 152 190 222 245 232 207 175 159 137 124 74 67 56 34 28 10 8 5 6 8 11 21 58 108 152 192 224 252 259 233 199 182 158 144 89 81 69 43 36 15 11 6 5 7 9 22 58 109 153 193 226 255 279 259 223 206 179 164 105 96 82 54 46 20 15 8 6 5 6 23 57 107 151 191 226 257 283 285 247 228 201 185 121 112 96 65 55 26 20 10 8 6 5

[0086] The route with the minimum deviation loss is shown in red in the table above, where

[0087] One feature for multiple facilities: Feature set 14 corresponds to facilities 14 and 15, take the longer feature set 15. Multiple features for one facility: Feature sets 18 and 19 correspond to facility 19, take the longer feature set 18.

[0088] facility Facility starting point Facility End Feature set Feature origin Characteristic endpoint 1 189.8 196.5 1 195 198 2 245 251.7 2 249 255 3 288.1 292.1 3 293 294 4 310.2 313.3 4 314 316 5 372 375.8 5 377 378 6 405.4 408.4 6 408 410 7 449 452.4 7 449 452 8 481.7 485.4 8 481 482 9 539.8 544.8 9 538 544 10 566.9 569.7 10 565 567 11 620.6 623.1 11 616 618 12 651 652.9 12 646 647 13 837 840.1 13 829 831 14 860.7 861.4 / / / 15 912.4 914.9 14 900 901 16 1037.8 1040.4 15 1025 1027 17 1077.3 1084 16 1061 1067 18 1235.3 1245.6 17 1233 1243 / / / 18 1261 1261 19 1284.7 1291.4 19 1287 1296 20 1379.7 1388.4 20 1380 1389 21 1410.3 1433.7 21 1401 1425 22 1474.6 1485.8 22 1469 1480 23 1502.9 1505.9 23 1502 1504

[0089] Finally, the station number of any fiber optic point is linearly calibrated. Based on the bridge serial number, the correspondence between the starting and ending station numbers of the bridge and the fiber optic points is obtained. The points are evenly distributed in the middle section between two bridges. For example, if the distance between two bridges is 1 kilometer and there are 90 points, the station distance between points in this interval is not 10 meters but 11.1 meters.

[0090] During this process, the station numbers of the discrete fiber optic points were marked. For example, fiber optic point 1502 was marked as station number 1480875, the starting point of facility 23, and fiber optic point 1504 was marked as station number 1480904, the ending point of facility 23. The intermediate points were divided using linear normalization.

[0091]

[0092] In this embodiment, an example is given below. For instance, fiber optic point 1503 belongs to the interval between points 1502 and 1504, that is, it is located at station numbers 1480875-1480904, and its calibrated station number is...

[0093] Fiber optic point 1490 falls within the range of points 1480-1502, specifically between chainages 1480712 and 1480875. Its calibrated chainage is...

[0094] In summary, the present invention provides a method for calibrating fiber optic locations on highways based on distributed acoustic wave sensing signals. This method converts facility station numbers on highways into fiber optic locations, extracts fiber optic signal feature sets, and identifies and matches these feature sets with the facilities. By calibrating all fiber optic locations onto highway station numbers, information such as accidents, road conditions, and early warnings calculated based on fiber optics can be located at specific station numbers, thereby improving accuracy.

[0095] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the inventive concept should fall within the protection scope of the present invention. All technical contents for which protection is sought in this invention are fully described in the claims.

Claims

1. A method for calibrating fiber optic points on highways based on distributed acoustic wave sensing signals, characterized in that, Includes the following steps: S1. Based on the optical attenuation changes of the highway communication optical fiber, the optical fiber is segmented into units, and the facility station numbers on the highway are converted into optical fiber locations. S2. Extraction of fiber optic signal feature sets; specifically including the following steps: a. Send pulses to the communication optical fibers that have been pre-laid along the main line of the highway; b. The original vibration signal of the vehicle passing through the sensing fiber is collected and obtained by the data acquisition system DAS; c. Collect 10 minutes of vibration data and take the maximum vibration phase at each point. ,in The vibration phase value of the m-th frame at the n-th fiber optic point; d. Calculate the vibration threshold T = quantile(Mn, 1-Q). Where Q represents the proportion of facility length. , D represents the total length of the facility, and D represents the actual road distance. e. Take a continuous range of points greater than T and generate a feature set A; f. If the number of feature sets is greater than the number of facilities, T = T + 1, and repeat step e; S3. Establish a distance matrix based on the facilities and the extracted fiber optic signal feature set, calculate the deviation matrix using a dynamic programming algorithm, and identify and match the feature set with the facilities based on the deviation matrix; S4. Based on the identification and matching results, perform linear calibration of the station number for any fiber optic point.

2. The method for highway fiber optic point calibration based on distributed acoustic wave sensing signals as described in claim 1, characterized in that, The process of segmenting the optical fiber into units in S1 includes the following steps: S11, continuous optical fiber is measured as optical fiber length F, with the front and rear jumpers being the first toll station and the second toll station, respectively; S12. Calculate the actual road distance D using highway structure information: D = chainage of the second toll station - chainage of the first toll station; S13. Using information on highway structures, extract all facilities from the first toll station to the second toll station. For the i-th facility, The starting point of facility i is the chainage number of the first toll station. For facilities length; S14, Total length of computing facility ; S15, Calculation of facility length percentage ; S16, Facility i starting point ; S17, Facility i endpoint .

3. The method for highway fiber optic point calibration based on distributed acoustic wave sensing signals as described in claim 1, characterized in that, During the identification and matching process between the feature set and the facility in S3: First, establish the distance matrix O; The horizontal axis represents facilities. ,in As the starting point of the facility, The end point of the facility; The vertical axis represents the feature set. ,in As the starting point of the set, The endpoint of the set; Indication facilities With sets F1 score distance, The formula is: ; Then, a dynamic programming algorithm is used to calculate the deviation matrix P, where the formula is: ； To pass through the deviation matrix This enables the feature set to be identified, matched, and aligned with the facility.

4. The method for highway fiber optic point calibration based on distributed acoustic wave sensing signals as described in claim 1, characterized in that, The data acquisition system DAS in S2 acquires the original vibration signal frequency of the sensing fiber at 2000 Hz, which means that 2000 frames of vibration data are generated per second per point.

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