Fault early warning method and system for tunnel communication equipment

Abstract

The present invention relates to the field of tunnel communication technology, and in particular to a fault warning method and system for tunnel communication equipment. The method comprises testing and obtaining the standing wave ratio (SWR) in a target area within a tunnel, and obtaining monitoring data in the target area through monitoring equipment within the tunnel; performing a physical morphology analysis of a leaky cable based on the monitoring data to obtain physical fault information of the leaky cable; performing reverse prediction of the physical fault of the leaky cable based on the SWR to obtain predicted physical fault information of the leaky cable, and analyzing and obtaining physical fault confidence based on the physical fault information of the leaky cable, wherein the physical fault confidence is analyzed based on reverse similarity and position deviation; configuring weights based on the physical fault confidence, and calculating and obtaining communication equipment fault parameters based on the SWR and the physical fault information of the leaky cable to perform fault warning identification, thereby improving the accuracy and reliability of fault warning of tunnel communication equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel communications, and in particular to a fault early warning method and system for tunnel communication equipment. Background Art

[0002] In tunnel communication systems, leaky cables are crucial communications equipment, and their operating status directly impacts communication quality. With the continuous advancement of tunnel construction, tunnel length and complexity have increased, and the operating environment of leaky cables has become increasingly harsh. They are susceptible to factors such as vibration, temperature fluctuations, and external impacts, leading to physical failures such as deflection and movement, as well as potential electrical performance issues. To ensure the normal operation of tunnel communications, timely warnings of tunnel communication equipment failures are necessary. However, traditional fault warning methods often rely on a single parameter and manual analysis of monitoring data, resulting in low accuracy and reliability in tunnel communication equipment fault warnings. Summary of the Invention

[0003] The present invention aims to solve the technical problem of low accuracy and reliability of fault warning of tunnel communication equipment in the prior art, and provides a fault warning method and system for tunnel communication equipment.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] In a first aspect, the present invention provides a fault warning method for tunnel communication equipment, comprising: testing and obtaining the standing wave ratio in a target area in a tunnel, and obtaining monitoring data in the target area through monitoring equipment in the tunnel; performing a physical morphology analysis of a leaky cable based on the monitoring data to obtain physical fault information of the leaky cable; performing a reverse prediction of the physical fault of the leaky cable based on the standing wave ratio to obtain predicted physical fault information of the leaky cable, and analyzing and obtaining physical fault confidence based on the physical fault information of the leaky cable, wherein the physical fault confidence is analyzed based on the reverse similarity and position deviation; configuring weights based on the physical fault confidence, and calculating and obtaining communication equipment fault parameters based on the standing wave ratio and the physical fault information of the leaky cable to perform fault warning judgment.

[0006] Optionally, the standing wave ratio in the target area in the tunnel is tested and obtained, and monitoring data in the target area is obtained through monitoring equipment in the tunnel, including: using a standing wave ratio tester to test and obtain the standing wave ratio in the target area in the tunnel; monitoring and obtaining monitoring data in the target area through monitoring equipment in the tunnel, wherein the monitoring data includes a monitoring image.

[0007] Optionally, based on the monitoring data, a physical morphology analysis of the leaky cable is performed to obtain physical fault information of the leaky cable, including: obtaining a leaky cable physical fault identifier; inputting the monitoring data into the leaky cable physical fault identifier, performing a physical morphology analysis of the leaky cable, and obtaining physical fault information of the leaky cable, wherein the physical fault information of the leaky cable includes parameters of deflection and movement of the leaky cable.

[0008] Among them, obtaining a leaky cable physical fault identifier includes: collecting a sample monitoring data set based on historical monitoring data of the leaky cable equipment, and marking the scale parameters of the leaky cable deflection and movement in each sample monitoring data to obtain a sample leaky cable physical fault information set; constructing a leaky cable physical fault identifier based on deep learning; using the sample monitoring data set and the sample leaky cable physical fault information set, supervising the leaky cable physical fault identifier until the test converges, thereby obtaining a leaky cable physical fault identifier.

[0009] Optionally, a reverse prediction of the leaky cable physical fault is performed based on the standing wave ratio to obtain the predicted leaky cable physical fault information, and the physical fault confidence is obtained by analysis in combination with the leaky cable physical fault information, including: obtaining all historical leaky cable physical fault information when the standing wave ratio appears based on the tunnel communication equipment monitoring data within a historical time, and calculating the mean to obtain the predicted leaky cable physical fault information; calculating the reverse similarity and position deviation based on the predicted leaky cable physical fault information and the leaky cable physical fault information, and analyzing to obtain the physical fault confidence.

[0010] Among them, according to the predicted leaky cable physical fault information and the leaky cable physical fault information, the reverse similarity and position deviation are calculated, and the physical fault confidence is obtained by analysis, including: calculating the similarity between the predicted leaky cable physical fault information and the leaky cable physical fault information to obtain the reverse confidence; according to the leaky cable physical fault information and the standard position of the leaky cable installation, the actual leaky cable position is calculated; the position deviation between the actual leaky cable position and the monitoring center position of the monitoring equipment is calculated, and the monitoring confidence is calculated; according to the reverse confidence and the monitoring confidence, the physical fault confidence is calculated.

[0011] Optionally, according to the physical fault confidence configuration weight, combined with the standing wave ratio and the leaky cable physical fault information, the communication equipment fault parameters are calculated to obtain the fault warning judgment, including: using the physical fault confidence to optimize the calculation of the preset physical fault weight to obtain the physical fault weight; according to the physical fault weight, the standing wave ratio weight is calculated to obtain the standing wave ratio weight; according to the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated to perform the fault warning judgment.

[0012] Among them, according to the standing wave ratio, the physical fault information of the leaky cable, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and a fault warning is judged, including: calculating the deviation amplitude of the standing wave ratio from the standard standing wave ratio to obtain the standing wave ratio fault coefficient; calculating the ratio of the physical fault information of the leaky cable to the maximum physical fault information of the leaky cable to obtain the physical fault parameters; using the physical fault weight and the standing wave ratio weight to perform weighted calculation on the physical fault parameters and the standing wave ratio fault coefficient to obtain the communication equipment fault parameters, judging whether they are greater than or equal to the fault parameter threshold, and performing a fault warning.

[0013] In a second aspect, the present invention provides a fault warning system for tunnel communication equipment, comprising:

[0014] A monitoring data acquisition module is used to test and obtain the standing wave ratio in the target area of ​​the tunnel, and to obtain monitoring data in the target area through monitoring equipment in the tunnel;

[0015] A physical fault acquisition module is used to perform a physical morphology analysis of the leaky cable based on the monitoring data to obtain physical fault information of the leaky cable;

[0016] a physical fault reverse prediction module, configured to reversely predict the leaky cable physical fault based on the standing wave ratio, obtain predicted leaky cable physical fault information, and analyze and obtain physical fault confidence based on the leaky cable physical fault information, wherein the physical fault confidence is analyzed based on reverse similarity and position deviation;

[0017] The fault warning and discrimination module is used to configure weights according to the physical fault confidence, combine the standing wave ratio and the leaky cable physical fault information, calculate and obtain communication equipment fault parameters, and perform fault warning and discrimination.

[0018] Beneficial effects:

[0019] 1. By implementing the present invention, it is possible to test and obtain the standing wave ratio in the target area of ​​the tunnel, and obtain monitoring data in the target area through monitoring equipment in the tunnel, which can intuitively present the physical status of the leaky cable, provide the original basis for subsequent analysis of the physical fault of the leaky cable, and provide multi-dimensional data support for subsequent fault analysis;

[0020] 2. By implementing the present invention, it is possible to perform physical morphology analysis of leaky cables based on monitoring data and obtain physical fault information of leaky cables, thereby accurately identifying changes in the physical morphology of leaky cables and converting abstract monitoring data into specific physical fault parameters of leaky cables, facilitating subsequent quantitative analysis and evaluation of physical faults of leaky cables.

[0021] 3. By implementing the present invention, it is possible to perform reverse prediction of leaky cable physical faults based on the standing wave ratio, obtain predicted leaky cable physical fault information, and analyze and obtain physical fault confidence based on the leaky cable physical fault information. The physical fault confidence is analyzed based on reverse similarity and position deviation. The reverse prediction utilizes the experience of historical data and, combined with actual monitored fault information, can comprehensively assess the reliability of the fault. The reverse similarity reflects the degree of consistency between the prediction and the actual fault, and the position deviation takes into account the accuracy of the monitoring location. The physical fault confidence obtained by combining the two improves the reliability of fault judgment.

[0022] 4. By implementing the present invention, it is possible to configure weights according to the physical fault confidence, combine the standing wave ratio and the leaky cable physical fault information, calculate the communication equipment fault parameters, and perform fault warning judgment. By configuring weights according to the physical fault confidence, the standing wave ratio and the leaky cable physical fault information occupy a reasonable proportion in the fault parameter calculation, thereby improving the accuracy of the fault parameters. By performing warning judgment based on the communication equipment fault parameters, it is possible to more accurately determine whether the communication equipment has a fault, issue a warning in time, and facilitate the staff to take corresponding maintenance measures, thereby improving the accuracy and reliability of the tunnel communication equipment fault warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic flow chart of a fault warning method for tunnel communication equipment provided by the present invention;

[0024] Figure 2 A structural schematic diagram of a fault warning system for tunnel communication equipment provided by the present invention.

[0025] In the accompanying drawings, the components represented by the reference numerals are as follows:

[0026] Monitoring data acquisition module 11, physical fault acquisition module 12, physical fault reverse deduction module 13, fault warning judgment module 14. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Therefore, features specified as "first" or "second" may explicitly or implicitly include one or more features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0029] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0030] Example 1, as Figure 1 As shown, an embodiment of the present invention provides a fault warning method for tunnel communication equipment, including:

[0031] S100: testing and obtaining the standing wave ratio in a target area in the tunnel, and obtaining monitoring data in the target area through monitoring equipment in the tunnel;

[0032] S200: Performing a leaky cable physical morphology analysis based on the monitoring data to obtain leaky cable physical fault information;

[0033] S300: performing reverse prediction of a leaky cable physical fault based on the standing wave ratio to obtain predicted leaky cable physical fault information, and analyzing the leaky cable physical fault information to obtain a physical fault confidence, wherein the physical fault confidence is analyzed based on reverse similarity and position deviation.

[0034] S400: configuring weights according to the physical fault confidence, combining the standing wave ratio and the leaky cable physical fault information, calculating and obtaining communication equipment fault parameters, and performing fault early warning judgment.

[0035] In step S100 of the embodiment of the present application, the standing wave ratio in the target area of ​​the tunnel is tested and acquired, and monitoring data in the target area is acquired through monitoring equipment in the tunnel, including:

[0036] Use a standing wave ratio tester to test and obtain the standing wave ratio in the target area in the tunnel;

[0037] The monitoring data in the target area is monitored and acquired through the monitoring equipment in the tunnel, wherein the monitoring data includes monitoring images.

[0038] In an embodiment of the present application, step S100 is the basic data collection link for tunnel communication equipment fault warning, which aims to provide comprehensive, multi-source original information for subsequent fault analysis through data collection in two different dimensions. Among them, the standing wave ratio reflects the electrical performance status of the leaky cable and is a key indicator for determining whether the communication signal transmission is abnormal. Monitoring data, such as monitoring images, can intuitively present the physical form of the leaky cable and provide an objective visual basis for identifying physical faults of the leaky cable, such as deflection and movement. The combination of data from two different dimensions can realize dual monitoring of the electrical performance and physical status of the leaky cable, avoiding the limitations of a single data dimension.

[0039] Alternatively, the VSWR within a target tunnel area can be determined by using a VSWR tester to directly test the electrical parameters of the leaky cable in the target tunnel area and collect VSWR data for that area. The VSWR tester transmits a signal, receives a reflected signal, calculates the signal reflection coefficient, and then determines the VSWR value, which reflects the impedance matching of the leaky cable and the signal transmission quality.

[0040] For example, in a 500-meter-long tunnel, technicians use a portable standing wave ratio tester to conduct segmented tests on the leaky cable laid on the tunnel roof. The tester's signal interface is connected to the test port of the leaky cable, and a test signal of a specific frequency, such as 800MHz-2600MHz, is transmitted to the leaky cable. After receiving the reflected signal, the tester calculates the ratio of the reflection coefficient to the incident coefficient to obtain the standing wave ratio value of the leaky cable section. For example, if the standing wave ratio is usually ≤1.5 under normal conditions, if the test result of a certain section is 2.8, it indicates that there may be impedance mismatch or physical damage.

[0041] Alternatively, monitoring data from the target area within the tunnel can be obtained by using monitoring equipment deployed within the tunnel, such as existing cameras and other image acquisition devices, to conduct real-time or periodic monitoring of the leaky cable in the target area. This data, primarily in the form of monitoring images, should clearly show information such as the installation location and morphological changes of the leaky cable, providing visual input for subsequent physical fault analysis.

[0042] For example, in the aforementioned 500-meter tunnel, high-definition infrared cameras are installed every 50 meters on the tunnel's sidewalls as monitoring equipment, with the cameras focused on the leaky cable installation location. The cameras periodically capture real-time images of the leaky cable, clearly showing the cable's mounting bracket, cable path, and surroundings. For example, one image shows a leaky cable shifting from its original mounting position due to vibration, forming a 30° angle with the bracket. These images are then transmitted in real time to the backend system as monitoring data.

[0043] In step S200 of the embodiment of the present application, the physical morphology of the leaky cable is analyzed based on the monitoring data to obtain the physical fault information of the leaky cable, including:

[0044] Obtain a leaky cable physical fault identifier;

[0045] The monitoring data is input into the leaky cable physical fault identifier to perform a leaky cable physical morphology analysis to obtain leaky cable physical fault information, wherein the leaky cable physical fault information includes parameters of leaky cable deflection and movement.

[0046] In the embodiment of the present application, the function of step S200 is to accurately analyze and quantitatively evaluate the physical state of the leaky cable based on the monitoring data obtained in step S100. The core purpose is to extract the specific physical fault information of the leaky cable from the monitoring data and provide a physical-level quantitative basis for subsequent fault warning.

[0047] In step S200 of the embodiment of the present application, obtaining a leaky cable physical fault identifier includes:

[0048] Based on the historical monitoring data of the leaky cable equipment, a sample monitoring data set is collected, and the scale parameters of the leaky cable deflection and movement in each sample monitoring data are marked to obtain the sample leaky cable physical fault information set;

[0049] Build a leaky cable physical fault identifier based on deep learning;

[0050] The sample monitoring data set and the sample leaky cable physical fault information set are used to perform supervised training on the leaky cable physical fault identifier until the test converges, thereby obtaining the leaky cable physical fault identifier.

[0051] In the embodiment of the present application, obtaining a leaky cable physical fault identifier is the core link to achieve automated and accurate identification of leaky cable physical faults. The purpose is to convert the monitoring data collected in S100 into specific and quantified leaky cable physical fault information through a trained leaky cable physical fault identifier, thereby providing a reliable physical status basis for subsequent fault analysis and confidence calculation.

[0052] In the embodiments of the present application, training a leaky cable physical fault identifier first requires acquiring the sample data required for training. Specifically, a sample monitoring dataset is collected based on historical monitoring data from the leaky cable equipment. For example, historical monitoring data from the target area within the tunnel over the past year, i.e., the aforementioned monitoring images, must be collected. These images must encompass different tunnel scenes, such as normal conditions, slight deflections, and significant movement. A total of 10,000 monitoring images are collected, covering scenes with varying lighting conditions and varying degrees of leaky cable fault severity within the tunnel, to form the sample monitoring dataset.

[0053] Among them, the scale parameters of the deflection and movement of the leaky cable in each sample monitoring data can be measured using "deflection angle" and "movement distance". The deflection angle refers to the angle between the central axis of the leaky cable and the initial position of the leaky cable installation, which is used to quantify the degree of deviation of the leaky cable in spatial angle. For example, the deflection angle can be 5°, 6°, etc., and generally does not exceed 45°. The movement distance refers to the displacement length of the leaky cable as a whole or in part relative to the initial position of the leaky cable installation, which is used to quantify the degree of displacement of the leaky cable in spatial position. For example, the movement distance can be 30cm, 20cm, etc., and generally does not exceed 50cm.

[0054] Then, the “deflection angle” and “movement distance” of the leaky cable in each image are annotated, such as deflection 0°-45° and movement 0-50cm, to form a sample leaky cable physical fault information set.

[0055] Furthermore, it is necessary to build a leaky cable physical fault identifier based on deep learning. Considering that the specific task of the leaky cable physical fault identifier is to process monitoring images, a convolutional neural network (CNN) can be used to build it.

[0056] The structure of the leaky cable physical fault identifier is three-layer, including input layer, feature extraction layer and fully connected layer.

[0057] Among them, the input layer is used to receive monitoring image data. The image size can be set to 256×256 pixels, using 3 channels and RGB format to adapt to the image characteristics under complex lighting in the tunnel.

[0058] The feature extraction layer has a 6-layer structure, including 3 convolutional layers and 3 pooling layers, which are arranged in an interleaved manner. The order from front to back is as follows: convolution layer 1, containing 32 3×3 convolution kernels, with a stride of 1, the same padding method, and the activation function ReLU, which is used to extract basic features such as the edge of the leaky cable and the fixed bracket; pooling layer 1, using 2×2 maximum pooling with a stride of 2, is used to compress the feature map size to 128×128; convolution layer 2, containing 64 3×3 convolution kernels, with a stride of 1, the same padding method, and the activation function ReLU, which is used to extract the distinguishing features between the leaky cable and the background; pooling layer 2, using 2×2 maximum pooling with a stride of 2, is used to compress the feature map size to 64×64; convolution layer 3, containing 128 3×3 convolution kernels, with a stride of 1, the same padding method, and the activation function ReLU, which is used to refine the detailed features of the deflection and movement of the leaky cable; pooling layer 3, using 2×2 maximum pooling with a stride of 2, is used to compress the feature map size to 32×32.

[0059] The fully connected layer has a three-layer structure, including the flatten layer, fully connected layer 1, and fully connected layer 2. The flatten layer is used to flatten the pooled feature map into a one-dimensional vector; fully connected layer 1 contains 512 neurons and uses the ReLU activation function to fuse high-dimensional features; fully connected layer 2 contains two neurons and has no activation function for the parameters of the leaky cable deflection and movement. It outputs the predicted values ​​of the leaky cable deflection angle (°) and movement distance (cm).

[0060] The parameters for the leaky cable physical fault identifier were set using the Adam optimizer, a learning rate of 0.001, and the mean squared error (MSE) loss function. The prediction error was measured by calculating the mean squared difference between the predicted deflection and movement parameters and the labeled values. The batch size was set to 32, and L2 regularization was added to the first fully connected layer with a coefficient of 0.0001 to prevent overfitting. The maximum number of training rounds was initially set to 200, with each round traversing all 10,000 samples.

[0061] When the test set loss value (MSE) for 10 consecutive rounds is stable within 0.5, that is, the predicted deflection angle error is ≤0.5° and the moving distance error is ≤0.5cm, the model is judged to have converged, the training is stopped, and the final leaky cable physical fault identifier is obtained.

[0062] Finally, the monitoring data is fed into the leaky cable physical fault identifier, which performs a physical morphological analysis of the leaky cable and obtains leaky cable physical fault information, including parameters related to the cable's deflection and movement. For example, the system feeds a recently acquired leaky cable monitoring image at 350 meters into the trained leaky cable physical fault identifier, which identifies and outputs a leaky cable deflection angle of 12° and a movement distance of 8 cm.

[0063] In step S300 of the embodiment of the present application, a leaky cable physical fault is reversely predicted based on the standing wave ratio to obtain predicted leaky cable physical fault information, and the physical fault confidence is obtained by analyzing the leaky cable physical fault information, including:

[0064] According to the monitoring data of the tunnel communication equipment in the historical time, all the historical leaky cable physical fault information when the standing wave ratio appears is obtained, and the average is calculated to obtain the predicted leaky cable physical fault information;

[0065] According to the predicted leaky cable physical fault information and the leaky cable physical fault information, the reverse similarity and position deviation are calculated, and the physical fault confidence is obtained through analysis.

[0066] In the embodiment of the present application, this step aims to establish an association between the standing wave ratio and the physical fault of the leaky cable through historical data, and generate predictive physical fault information based on the current standing wave ratio, that is, the predicted leaky cable physical fault information, so as to calculate the physical fault confidence and evaluate the credibility of the result output by the leaky cable physical fault identifier in step S200.

[0067] Specifically, all records with the same standing wave ratio value as that obtained in the current test are screened from historical tunnel communication equipment monitoring data, and the corresponding leaky cable physical fault information is extracted as the complete historical leaky cable physical fault information when the standing wave ratio appears. The historical leaky cable physical fault information can be leaky cable physical fault information collected within the past three years. The leaky cable physical fault information includes the standing wave ratio at the time the leaky cable physical fault information was collected, as well as the collected leaky cable deflection angle parameters and movement distance parameters.

[0068] For example, if the current standing wave ratio is 2.2, find all leaky cable physical fault records when the standing wave ratio is 2.2 from the historical data. Assume there are 10 records in total, including "deflection angle 10°, moving distance 5cm" and "deflection angle 14°, moving distance 7cm".

[0069] Then, the deflection and movement parameters from all extracted historical leaky cable physical fault records are averaged to obtain the predicted leaky cable physical fault information. For example, in the 10 historical records, the average deflection angle is (10° + 14° + …) / 10 = 12°, and the average movement distance is (5cm + 7cm + …) / 10 = 6cm. Therefore, the predicted leaky cable physical fault information is "deflection angle 12°, movement distance 6cm."

[0070] Furthermore, it is necessary to calculate the reverse similarity and position deviation based on the predicted leaky cable physical fault information and the leaky cable physical fault information, and analyze and obtain the physical fault confidence.

[0071] In step S300 of the embodiment of the present application, based on the predicted leaky cable physical fault information and the leaky cable physical fault information, the reverse similarity and position deviation are calculated, and the physical fault confidence is obtained through analysis, including:

[0072] Calculating the similarity between the predicted leaky cable physical fault information and the leaky cable physical fault information to obtain a reverse inference confidence;

[0073] Calculate the actual leaky cable location based on the leaky cable physical fault information and the standard location where the leaky cable is installed;

[0074] Calculating the position deviation between the actual leaky cable position and the monitoring center position of the monitoring device, and calculating the monitoring confidence;

[0075] The physical fault confidence is obtained by calculation based on the inverse inference confidence and the monitoring confidence.

[0076] In the embodiment of the present application, the physical fault confidence is obtained by analysis, which is used as an example to comprehensively judge the reliability of the physical fault information and provide a credibility basis for subsequent weight configuration and fault warning.

[0077] First, the confidence level of the inference needs to be calculated. Specifically, the predicted leaky cable physical fault information needs to be compared with the leaky cable physical fault information obtained in S200 and the similarity between the two needs to be calculated. For example, the similarity between "deflection angle 12°, movement distance 6cm" and "deflection angle 11°, movement distance 5cm" needs to be calculated.

[0078] Optionally, the specific calculation method is: reverse similarity = 1 - (|predicted parameter - actual parameter| / maximum parameter), calculate the similarity of the deflection angle and movement distance separately, and then take the average. For example, in the above example, you can set the maximum deflection angle to 45° and the maximum movement distance to 50cm. Then the deflection angle similarity = 1 - (|12° - 11°| / 45°) ≈ 0.978, the movement distance similarity = 1 - (|6cm - 5cm| / 50cm) = 0.98, and the reverse confidence = (0.978 + 0.98) / 2 ≈ 0.979.

[0079] Next, the monitoring confidence level needs to be calculated. Specifically, the actual leaky cable location needs to be calculated based on the leaky cable physical fault information and the standard location of the leaky cable installation.

[0080] The standard location for the leaky cable installation is the preset standard coordinates of the leaky cable in the tunnel, such as "30 cm from the tunnel side wall, 5 m from the tunnel bottom, and laid along the tunnel axis", which is recorded as three-dimensional coordinates (X, Y, Z)

[0081] The actual position is calculated in combination with the fault information. In order to convert the physical parameters into spatial coordinate offsets based on the physical fault information of the leaky cable, such as the deflection angle and the movement distance, the deflection angle is based on the tunnel axis, and the movement distance is the lateral displacement perpendicular to the axis.

[0082] For example, if the standard position is (30cm, 5m, 100m), where x is the distance from the side wall, y is the height from the tunnel bottom, z is the axial mileage, the leaky cable deflection angle is 15°, and the moving distance is 10cm, then the actual position can be: x=30cm+10cm×cos15°≈39.66cm, y=5m+10cm×sin15°≈5.026m, z=100m, that is, the actual leaky cable position is (39.66cm, 5.026m, 100m).

[0083] The monitoring center of a monitoring device is the center of the field of view of the monitoring device, such as a camera. The closer the monitoring center is to the tunnel center, the higher the reliability of the captured image. Assume the monitoring center is the tunnel center. Preset the spatial coordinates of the tunnel center. Assume the tunnel width is 5m; the distance from the tunnel center to the sidewall, half the tunnel width, is 2.5m; and the tunnel center height is 5m, expressed as (xcenter, ycenter, zcenter) = (2.5m, 5m, 100m). The position deviation is the ratio of the straight-line distance between the actual leaky cable position and the tunnel center, calculated using the spatial distance formula, to half the tunnel width. For example, in the above example, if half the tunnel width is 2.5m, the straight-line distance between the actual leaky cable position and the tunnel center = √[(0.3966m - 2.5m)² + (5.026m - 5m)²] ≈ 2.103m. Therefore, the position deviation is 2.103m / 2.5m ≈ 0.841. The smaller the deviation, the closer the leaky cable captured by the camera is to the center of the image, the clearer the data is, and the higher the confidence level is.

[0084] For example, if the monitoring confidence level is 1-0.841≈0.159, or 15.9%, this indicates that the leaky cable is located close to the tunnel wall, far from the monitoring center, and the monitoring data reliability is low. For another example, if the position deviation is 0.04, the corresponding monitoring confidence level is 1-0.04=0.96, or 96%, indicating that the leaky cable is located close to the tunnel center, that is, close to the monitoring center, and the monitoring data reliability is high.

[0085] Finally, the physical fault confidence level needs to be calculated based on the inference confidence level and the monitoring confidence level. Specifically, the inference confidence level and the monitoring confidence level can be weighted and summed to obtain the physical fault confidence level. For example, the weights for the inference confidence level and the monitoring confidence level can be 0.5 and 0.5, respectively. In practice, these weights can be adjusted based on actual needs. For example, if the inference confidence level is 0.979 and the monitoring confidence level is 0.96, then the physical fault confidence level = (0.979 + 0.96) / 2 ≈ 0.97.

[0086] In step S400 of the embodiment of the present application, according to the physical fault confidence configuration weight, combined with the standing wave ratio and the leaky cable physical fault information, the communication equipment fault parameters are calculated and the fault warning is judged, including:

[0087] Using the physical fault confidence, optimizing and calculating the preset physical fault weight to obtain the physical fault weight;

[0088] According to the physical fault weight, the standing wave ratio weight is calculated;

[0089] According to the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and the fault early warning is judged.

[0090] This step aims to dynamically adjust the weights of physical fault information and standing wave ratio in fault parameter calculations based on the confidence level of the physical fault, so that the weight distribution is more closely aligned with the reliability of the fault information, avoiding errors caused by fixed weights and laying the foundation for subsequent accurate calculation of communication equipment fault parameters.

[0091] Specifically, the preset physical fault weight is an initial value set based on historical experience, such as 0.5. The physical fault weight can be calculated as follows: physical fault weight = preset physical fault weight × physical fault confidence. If the preset physical fault weight is 0.5 and the physical fault confidence is 0.9695, then the physical fault weight = 0.5 × 0.97 = 0.485.

[0092] The VSWR weight can be calculated based on the physical fault weight using a complementary relationship where the sum of the weights is 1: VSWR weight = 1 - physical fault weight. If the physical fault weight is 0.485, then the VSWR weight = 1 - 0.485 = 0.515.

[0093] In step S400 of the embodiment of the present application, based on the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and the fault warning is judged, including:

[0094] Calculating the deviation between the standing wave ratio and the standard standing wave ratio to obtain the standing wave ratio failure coefficient;

[0095] Calculating the ratio of the leaky cable physical fault information to the maximum leaky cable physical fault information to obtain a physical fault parameter;

[0096] The physical fault weight and the standing wave ratio weight are used to perform weighted calculation on the physical fault parameter and the standing wave ratio fault coefficient to obtain the communication equipment fault parameter, determine whether it is greater than or equal to the fault parameter threshold, and perform a fault warning.

[0097] This step aims to quantify the degree of electrical performance abnormality of the standing wave ratio and the severity of the physical fault of the leaky cable, and perform comprehensive calculations based on dynamic weights to obtain quantitative indicators that can be directly used to judge faults, namely the communication equipment fault parameters, and ultimately achieve accurate early warning of tunnel communication equipment failures.

[0098] First, the VSWR failure coefficient needs to be calculated. The standard VSWR is a reference value for leaky cables operating normally, such as ≤1.5. The VSWR failure coefficient can be calculated as: (Current VSWR - Standard VSWR) / (Maximum Allowable VSWR - Standard VSWR). For example, if the standard VSWR is 1.5, the maximum allowable VSWR is 3.0, and the current VSWR is 2.4, then the VSWR failure coefficient = (2.4 - 1.5) / (3.0 - 1.5) = 0.6. A larger value indicates a more severe electrical performance anomaly.

[0099] Next, the physical fault parameters need to be calculated. This involves comparing the current leaky cable physical fault information with the maximum leaky cable physical fault information and calculating a ratio to quantify the severity of the physical fault. The maximum leaky cable physical fault information represents the extreme fault parameters that may occur for a leaky cable, such as a maximum deflection of 45° and a maximum movement of 50 cm. The physical fault parameters can be calculated as follows: (actual deflection angle / maximum deflection angle + actual movement distance / maximum movement distance) / 2. For example, if the actual leaky cable deflection angle is 18° and the movement distance is 20 cm, and the maximum deflection angle is 45° and the maximum movement distance is 50 cm, then the physical fault parameter is (18 / 45 + 20 / 50) / 2 = (0.4 + 0.4) / 2 = 0.4. A larger value indicates a more severe physical fault.

[0100] Finally, the physical fault weight and the standing wave ratio weight are used to perform a weighted calculation on the physical fault parameter and the standing wave ratio fault coefficient to obtain the communication equipment fault parameter. Specifically, the physical fault weight and the standing wave ratio weight are used to perform a weighted summation on the standing wave ratio fault coefficient and the physical fault parameter. That is, the communication equipment fault parameter = physical fault parameter × physical fault weight + standing wave ratio fault coefficient × standing wave ratio weight. If the physical fault weight is 0.485, the standing wave ratio weight is 0.515, the physical fault parameter is 0.4, and the standing wave ratio fault coefficient is 0.6, then the communication equipment fault parameter = 0.4 × 0.485 + 0.6 × 0.515 = 0.194 + 0.309 = 0.503.

[0101] If the communication equipment fault parameter is greater than or equal to the preset threshold, a fault warning is triggered; otherwise, it is determined to be normal. The preset threshold can be determined according to actual needs during implementation, such as 0.5.

[0102] Example 2, as Figure 2 As shown, based on the same inventive concept as the fault warning method for a tunnel communication device provided in Example 1, an embodiment of the present invention further provides a fault warning system for a tunnel communication device, including:

[0103] The monitoring data acquisition module 11 is used to test and obtain the standing wave ratio in the target area in the tunnel, and obtain monitoring data in the target area through monitoring equipment in the tunnel;

[0104] A physical fault acquisition module 12 is configured to perform a physical morphology analysis of the leaky cable based on the monitoring data to obtain physical fault information of the leaky cable;

[0105] a physical fault reverse prediction module 13, configured to reversely predict the leaky cable physical fault based on the standing wave ratio, obtain predicted leaky cable physical fault information, and analyze and obtain physical fault confidence based on the leaky cable physical fault information, wherein the physical fault confidence is analyzed based on reverse similarity and position deviation;

[0106] The fault warning judgment module 14 is used to configure weights according to the physical fault confidence, combine the standing wave ratio and the leaky cable physical fault information, calculate the communication equipment fault parameters, and perform fault warning judgment.

[0107] Furthermore, the monitoring data acquisition module 11 includes the following execution steps:

[0108] Use a standing wave ratio tester to test and obtain the standing wave ratio in the target area in the tunnel;

[0109] The monitoring data in the target area is monitored and acquired through the monitoring equipment in the tunnel, wherein the monitoring data includes monitoring images.

[0110] Furthermore, the physical fault acquisition module 12 includes the following execution steps:

[0111] Obtain a leaky cable physical fault identifier;

[0112] The monitoring data is input into the leaky cable physical fault identifier to perform a leaky cable physical morphology analysis to obtain leaky cable physical fault information, wherein the leaky cable physical fault information includes parameters of leaky cable deflection and movement.

[0113] The step of obtaining a leaky cable physical fault identifier includes:

[0114] Based on the historical monitoring data of the leaky cable equipment, a sample monitoring data set is collected, and the scale parameters of the leaky cable deflection and movement in each sample monitoring data are marked to obtain the sample leaky cable physical fault information set;

[0115] Build a leaky cable physical fault identifier based on deep learning;

[0116] The sample monitoring data set and the sample leaky cable physical fault information set are used to perform supervised training on the leaky cable physical fault identifier until the test converges, thereby obtaining the leaky cable physical fault identifier.

[0117] Furthermore, the physical fault reverse estimation module 13 includes the following execution steps:

[0118] According to the monitoring data of the tunnel communication equipment in the historical time, all the historical leaky cable physical fault information when the standing wave ratio appears is obtained, and the average is calculated to obtain the predicted leaky cable physical fault information;

[0119] According to the predicted leaky cable physical fault information and the leaky cable physical fault information, the reverse similarity and position deviation are calculated, and the physical fault confidence is obtained through analysis.

[0120] The method of calculating the reverse similarity and position deviation based on the predicted leaky cable physical fault information and the leaky cable physical fault information, and analyzing and obtaining the physical fault confidence level includes:

[0121] Calculating the similarity between the predicted leaky cable physical fault information and the leaky cable physical fault information to obtain a reverse inference confidence;

[0122] Calculate the actual leaky cable location based on the leaky cable physical fault information and the standard location where the leaky cable is installed;

[0123] Calculating the position deviation between the actual leaky cable position and the monitoring center position of the monitoring device, and calculating the monitoring confidence;

[0124] The physical fault confidence is obtained by calculation based on the inverse inference confidence and the monitoring confidence.

[0125] Furthermore, the fault warning determination module 14 includes the following execution steps:

[0126] Using the physical fault confidence, optimizing and calculating the preset physical fault weight to obtain the physical fault weight;

[0127] According to the physical fault weight, the standing wave ratio weight is calculated;

[0128] According to the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and the fault early warning is judged.

[0129] The method includes calculating and obtaining communication equipment fault parameters based on the standing wave ratio, leaky cable physical fault information, physical fault weight, and standing wave ratio weight, and performing fault early warning judgment, including:

[0130] Calculating the deviation between the standing wave ratio and the standard standing wave ratio to obtain the standing wave ratio failure coefficient;

[0131] Calculating the ratio of the leaky cable physical fault information to the maximum leaky cable physical fault information to obtain a physical fault parameter;

[0132] The physical fault weight and the standing wave ratio weight are used to perform weighted calculation on the physical fault parameter and the standing wave ratio fault coefficient to obtain the communication equipment fault parameter, determine whether it is greater than or equal to the fault parameter threshold, and perform a fault warning.

[0133] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] Those skilled in the art will appreciate that embodiments of the present invention may provide methods, systems, or computer program products. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0135] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0136] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0138] Although preferred embodiments of the present invention have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts become known.

[0139] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A fault warning method for tunnel communication equipment, characterized in that: The method comprises: The test obtains the standing wave ratio in the target area of ​​the tunnel, and obtains the monitoring data in the target area through the monitoring equipment in the tunnel; Performing a leaky cable physical morphology analysis based on the monitoring data to obtain leaky cable physical fault information; Performing reverse prediction of a leaky cable physical fault based on the standing wave ratio to obtain predicted leaky cable physical fault information, combining the leaky cable physical fault information to obtain a physical fault confidence, wherein the similarity between the predicted leaky cable physical fault information and the leaky cable physical fault information is calculated to obtain the reverse prediction confidence; Calculate the actual leaky cable location based on the leaky cable physical fault information and the standard location where the leaky cable is installed; Calculating the position deviation between the actual leaky cable position and the monitoring center position of the monitoring device, and calculating the monitoring confidence; Calculating and obtaining a physical fault confidence level based on the inverse inference confidence level and the monitoring confidence level; According to the physical fault confidence configuration weight, combined with the standing wave ratio and the leaky cable physical fault information, the communication equipment fault parameters are calculated and the fault early warning is judged.

2. The fault warning method for tunnel communication equipment according to claim 1, characterized in that: The test obtains the standing wave ratio in the target area of ​​the tunnel, and obtains monitoring data in the target area through monitoring equipment in the tunnel, including: Use a standing wave ratio tester to test and obtain the standing wave ratio in the target area in the tunnel; The monitoring data in the target area is monitored and acquired through the monitoring equipment in the tunnel, wherein the monitoring data includes monitoring images.

3. The fault warning method for tunnel communication equipment according to claim 1, characterized in that: Based on the monitoring data, the physical morphology of the leaky cable is analyzed to obtain the physical fault information of the leaky cable, including: Obtain a leaky cable physical fault identifier; The monitoring data is input into the leaky cable physical fault identifier to perform a leaky cable physical morphology analysis to obtain leaky cable physical fault information, wherein the leaky cable physical fault information includes parameters of leaky cable deflection and movement.

4. The fault warning method for tunnel communication equipment according to claim 3, characterized in that: Obtain leaky cable physical fault identifier, including: Based on the historical monitoring data of the leaky cable equipment, a sample monitoring data set is collected, and the scale parameters of the leaky cable deflection and movement in each sample monitoring data are marked to obtain the sample leaky cable physical fault information set; Build a leaky cable physical fault identifier based on deep learning; The sample monitoring data set and the sample leaky cable physical fault information set are used to perform supervised training on the leaky cable physical fault identifier until the test converges, thereby obtaining the leaky cable physical fault identifier.

5. The fault warning method for tunnel communication equipment according to claim 1, characterized in that: Performing reverse prediction of the leaky cable physical fault based on the standing wave ratio to obtain predicted leaky cable physical fault information includes: According to the monitoring data of the tunnel communication equipment in the historical time, all the historical leaky cable physical fault information when the standing wave ratio appears is obtained, and the average is calculated to obtain the predicted leaky cable physical fault information.

6. The fault warning method for tunnel communication equipment according to claim 1, characterized in that: According to the physical fault confidence configuration weight, combined with the standing wave ratio and the leaky cable physical fault information, the communication equipment fault parameters are calculated and the fault early warning judgment is performed, including: Using the physical fault confidence, optimizing and calculating the preset physical fault weight to obtain the physical fault weight; According to the physical fault weight, the standing wave ratio weight is calculated; According to the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and the fault early warning is judged.

7. The fault warning method for tunnel communication equipment according to claim 6, characterized in that: According to the standing wave ratio, the leaky cable physical fault information, the physical fault weight and the standing wave ratio weight, the communication equipment fault parameters are calculated and the fault early warning is judged, including: Calculating the deviation between the standing wave ratio and the standard standing wave ratio to obtain the standing wave ratio failure coefficient; Calculating the ratio of the leaky cable physical fault information to the maximum leaky cable physical fault information to obtain a physical fault parameter; The physical fault weight and the standing wave ratio weight are used to perform weighted calculation on the physical fault parameter and the standing wave ratio fault coefficient to obtain the communication equipment fault parameter, determine whether it is greater than or equal to the fault parameter threshold, and perform a fault warning.

8. A fault warning system for tunnel communication equipment, characterized in that: The system comprises: A monitoring data acquisition module is used to test and obtain the standing wave ratio in the target area of ​​the tunnel, and to obtain monitoring data in the target area through monitoring equipment in the tunnel; A physical fault acquisition module is used to perform a physical morphology analysis of the leaky cable based on the monitoring data to obtain physical fault information of the leaky cable; a physical fault reverse prediction module, configured to reversely predict the physical fault of the leaky cable based on the standing wave ratio, obtain predicted physical fault information of the leaky cable, and analyze and obtain a physical fault confidence by combining the physical fault information of the leaky cable, wherein the similarity between the predicted physical fault information of the leaky cable and the physical fault information of the leaky cable is calculated to obtain the reverse prediction confidence; Calculate the actual leaky cable location based on the leaky cable physical fault information and the standard location where the leaky cable is installed; Calculating the position deviation between the actual leaky cable position and the monitoring center position of the monitoring device, and calculating the monitoring confidence; Calculating and obtaining a physical fault confidence level based on the inverse inference confidence level and the monitoring confidence level; The fault warning and discrimination module is used to configure weights according to the physical fault confidence, combine the standing wave ratio and the leaky cable physical fault information, calculate and obtain communication equipment fault parameters, and perform fault warning and discrimination.

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