A cable anti-external damage monitoring system and method

Abstract

The present invention relates to a cable anti-external-break monitoring system and method, belonging to the technical field of cable anti-external-break monitoring, including: monitoring and obtaining a monitoring signal sequence of a cable, and collecting a disturbance parameter sequence; performing interval analysis on the vibration frequency and vibration amplitude according to the monitoring signal sequence to obtain a vibration frequency interval and a vibration amplitude interval, and calculating to obtain a first disturbance probability; predicting the disturbance probability of the monitoring signal sequence according to the first disturbance probability to obtain a second disturbance probability, combining the first disturbance probability to calculate and obtain an external-break probability, which is used as the anti-external-break monitoring result, and sending a warning message. Through the present invention, the technical problem that the traditional method cannot effectively distinguish cable disturbance interference from external-break events, is prone to misjudgment in a disturbance environment, and results in low accuracy and reliability of cable anti-external-break monitoring can be solved; the external-break events can be accurately identified in a complex environment, and the accuracy and reliability of cable anti-external-break monitoring are significantly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cable external breakage monitoring, and particularly to a cable external breakage monitoring system and method. Background Art

[0002] Fiber optic sensing technology, especially φ-OTDR (distributed fiber optic sensing technology), is widely used in cable external breakage monitoring. This technology utilizes the optical signal propagation characteristics in the optical fiber and can effectively identify whether the cable is subjected to external force interference by detecting minute changes (such as vibration, strain, etc.) in the optical fiber. This technology has high sensitivity and distributed monitoring capabilities, and can monitor the status of the cable in real time and detect abnormalities in a timely manner.

[0003] The underground laying of cables can greatly save investment as it does not require materials such as poles, porcelain insulators, cross arms, and guy wires, and has become a trend for future cable erection. When using φ-OTDR for external breakage monitoring of underground cables, the vibration of animals, people, and passing vehicles near the cable will cause the cable to vibrate disturbingly, resulting in signal changes. However, traditional φ-OTDR monitoring methods usually rely on fixed thresholds to identify external breakage events, so they may misjudge the minute vibrations generated by disturbances as external damage signals, thereby triggering false alarms and increasing the false alarm rate, affecting the accuracy and reliability of cable external breakage monitoring. Summary of the Invention

[0004] Aiming at the technical problem that the traditional φ-OTDR monitoring method cannot effectively distinguish between cable disturbance interference and external breakage events, and is prone to misjudgment under disturbances, resulting in low accuracy and reliability of cable external breakage monitoring, the present invention provides a cable external breakage monitoring system and method to solve this problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In a first aspect, the present invention provides a cable external breakage monitoring system, including: a data monitoring and acquisition module, configured to monitor and acquire a monitoring signal sequence of a cable through an external breakage monitoring device based on φ-OTDR; a vibration characteristic interval analysis module, configured to perform interval analysis of vibration frequency and vibration amplitude according to the monitoring signal sequence, obtain a vibration frequency interval and a vibration amplitude interval, and calculate a first disturbance probability; an external breakage probability calculation module, configured to perform disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability, obtain a second disturbance probability, and calculate an external breakage probability in combination with the first disturbance probability as a monitoring result for external breakage prevention, and send a warning message.

[0007] Preferably, the cable external damage prevention monitoring system is further configured to: monitor the cable through an external damage monitoring device based on φ-OTDR, obtain monitoring signals, and arrange them in chronological order to obtain a monitoring signal sequence.

[0008] Preferably, the cable external damage prevention monitoring system is further configured to: extract the vibration frequency and vibration amplitude from the monitoring signal sequence to obtain a vibration frequency set and a vibration amplitude set; extract the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude within the vibration frequency set and vibration amplitude set; generate a vibration frequency range and a vibration amplitude range according to the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude; and calculate a first disturbance probability according to the vibration frequency range and the vibration amplitude range.

[0009] Preferably, the cable external damage prevention monitoring system is further configured to: obtain a total vibration frequency range and a total vibration amplitude range according to the monitoring signals of the external damage monitoring device within a historical time; obtain a set of historical disturbance vibration frequency ranges and a set of historical disturbance vibration amplitude ranges according to the monitoring signals when disturbances are monitored by the external damage monitoring device within the historical time; calculate the ratio of the interval lengths of each historical disturbance vibration frequency range and historical disturbance vibration amplitude range within the set of historical disturbance vibration frequency ranges and the set of historical disturbance vibration amplitude ranges to the total vibration frequency range and the total vibration amplitude range, and calculate the mean value to obtain an average disturbance frequency ratio and an average disturbance amplitude ratio; calculate the ratios of the vibration frequency range and the vibration amplitude range to the total vibration frequency range and the total vibration amplitude range to obtain a disturbance frequency ratio and a disturbance amplitude ratio; calculate the similarity between the disturbance frequency ratio and the disturbance amplitude ratio and the average disturbance frequency ratio and the average disturbance amplitude ratio, and calculate the mean value to obtain a first disturbance probability.

[0010] Preferably, the cable external damage prevention monitoring system is further configured to: train a disturbance integrated recognition path for identifying the disturbance probability of the monitoring signal sequence, where M disturbance recognition paths are included in the disturbance integrated recognition path; calculate and configure N disturbance recognition paths according to the first disturbance probability, input the monitoring signal sequence into the N disturbance recognition paths, identify N disturbance probabilities, and calculate the mean value to obtain a second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

[0011] Preferably, the cable external damage prevention monitoring system is further configured to: collect a set of sample monitoring signal sequences based on the monitoring data of the external damage monitoring device over historical time, and collect the proportion of the cable being disturbed under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude, which is marked as a set of sample disturbance probabilities; randomly select M pieces of disturbance recognition training data with replacement from the set of sample monitoring signal sequences and the set of sample disturbance probabilities; use machine learning to train M disturbance recognition paths based on the M pieces of disturbance recognition training data, and integrate to obtain a disturbance integrated recognition path.

[0012] Preferably, the cable external damage prevention monitoring system is further configured to: calculate the mean value of the first disturbance probability and the second disturbance probability to obtain the total disturbance probability; calculate the external damage probability based on the total disturbance probability as the external damage prevention monitoring result, and send a warning message.

[0013] In a second aspect, the present invention provides a cable external damage prevention monitoring method, including: monitoring and obtaining a monitoring signal sequence of a cable through an external damage monitoring device based on φ-OTDR, and collecting a disturbance parameter sequence in the environment where the cable is located; performing interval analysis of the vibration frequency and the vibration amplitude according to the monitoring signal sequence to obtain a vibration frequency interval and a vibration amplitude interval, and calculating to obtain a first disturbance probability; predicting the disturbance probability of the monitoring signal sequence based on the first disturbance probability to obtain a second disturbance probability, combining the first disturbance probability, calculating to obtain the external damage probability as the external damage prevention monitoring result, and sending a warning message.

[0014] The beneficial effects of the present invention are as follows: a monitoring signal sequence of a cable is monitored and obtained through an external damage monitoring device based on φ-OTDR; then, interval analysis of the vibration frequency and the vibration amplitude is performed according to the monitoring signal sequence to obtain a vibration frequency interval and a vibration amplitude interval, and a first disturbance probability is calculated; further, based on the first disturbance probability, the disturbance probability of the monitoring signal sequence is predicted to obtain a second disturbance probability; finally, the mean value of the first disturbance probability and the second disturbance probability is calculated to obtain the total disturbance probability, and the external damage probability is calculated based on the total disturbance probability as the external damage prevention monitoring result, and a warning message is sent; through the above method, the intelligence and accuracy of cable disturbance recognition can be improved, and thus external damage events can be accurately recognized in a complex environment, false alarms can be reduced, thereby significantly improving the accuracy and reliability of cable external damage prevention monitoring and enhancing the cable safety monitoring ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic structural diagram of a cable external damage prevention monitoring system provided by the present invention.

[0016] Figure 2Schematic flow diagram of a cable anti-external damage monitoring method provided by the present invention;

[0017] In the accompanying drawings, the components represented by each reference numeral are described as follows:

[0018] Data monitoring and acquisition module 11, vibration characteristic interval analysis module 12, external damage probability calculation module 13. Specific implementation manners

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality of" means two or more, unless otherwise specifically defined.

[0021] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or more advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those skilled in the art can recognize that the present invention can be implemented without these specific details. In other instances, well-known structures and processes are not described 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 to be accorded the widest scope consistent with the principles and features disclosed herein.

[0022] Embodiment 1, as Figure 1 shown, the embodiment of the present invention provides a cable anti-external damage monitoring system, including:

[0023] A data monitoring and acquisition module 11, configured to monitor and acquire a monitoring signal sequence of a cable through an external damage monitoring device based on φ-OTDR.

[0024] Further, the data monitoring and acquisition module 11 is further configured to:

[0025] Monitor the cable through an external break monitoring device based on φ-OTDR, obtain the monitoring signal, and arrange it in chronological order to obtain a monitoring signal sequence.

[0026] Specifically, the φ-OTDR technology is based on the Rayleigh scattering principle. By emitting narrow linewidth pulsed light and detecting the returned backscattered signal, the phase information can reflect minute vibration changes along the fiber optic path. When the fiber is subjected to external forces (such as mechanical disturbances), the phase of its scattered light signal changes. Coherent detection technology can capture these changes, thereby achieving precise identification of external disturbance events. Continuously monitor the cable using an external break monitoring device based on φ-OTDR. The device can sense minute changes in the cable under forces, vibrations, etc. by emitting laser pulses and detecting the echo signal. Each monitoring generates a set of signal data for the optical fiber. These signals can be obtained in real time through the fiber optic network, recorded, and arranged in chronological order to form a complete monitoring signal sequence. This signal sequence reflects the state changes of the cable at different time periods.

[0027] In addition to possible external damage, the force on the cable is also affected by environmental factors such as disturbances. In an environment where people, animals, and vehicles generate vibration disturbances, the vibration of the cable will be affected by external vibrations. Therefore, the monitoring signal sequence may contain monitoring signals generated by external disturbances, and subsequent external break monitoring is carried out by collecting the monitoring signal sequence.

[0028] The vibration characteristic interval analysis module 12 is used to perform interval analysis of the vibration frequency and vibration amplitude according to the monitoring signal sequence, obtain the vibration frequency interval and the vibration amplitude interval, and calculate and obtain the first disturbance probability.

[0029] Furthermore, the vibration characteristic interval analysis module 12 is also used for:

[0030] Extract the vibration frequency and vibration amplitude from the monitoring signal sequence to obtain a vibration frequency set and a vibration amplitude set; extract the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude from the vibration frequency set and the vibration amplitude set; generate a vibration frequency interval and a vibration amplitude interval according to the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude.

[0031] Specifically, first, extract the vibration frequency and vibration amplitude at each monitoring time point in the monitored signal sequence. That is, through signal processing techniques such as Fourier transform, convert the time-domain signal into a frequency-domain signal, and then extract the frequency components and amplitude information in the signal. For example, perform frequency-domain analysis on the monitored signal sequence and extract each frequency component in the signal through methods such as FFT. Among them, for external break events, the frequency will be relatively high, while the frequency generated by disturbance interference is usually low. For example, the signal frequency caused by disturbances generated by people, animals, and vehicles passing by is generally 0.1 - 30 Hz, while the signal frequency generated when an external break event occurs is generally 0.1 - 100 Hz. Based on this, step-by-step identification of disturbance or external break events can be carried out. Obtain the vibration frequency set by extracting the vibration frequency of the signal; perform amplitude analysis on the signal to obtain the magnitude of the vibration amplitude. Among them, external disturbance interference is usually accompanied by a relatively small vibration amplitude, such as 0.1 mm - 1 mm. While an external break event will generate a relatively large vibration amplitude, such as 1 mm - 3 mm. Obtain the vibration amplitude set by extracting the vibration amplitude of the signal.

[0032] Next, extract the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude in the vibration frequency set and vibration amplitude set; then construct a vibration frequency interval according to the maximum vibration frequency and minimum vibration frequency, that is, use the minimum vibration frequency as the lower limit of the vibration frequency interval and the maximum vibration frequency as the upper limit of the vibration frequency interval; construct a vibration amplitude interval according to the maximum vibration amplitude and minimum vibration amplitude.

[0033] Calculate and obtain the first disturbance probability according to the vibration frequency interval and vibration amplitude interval.

[0034] Furthermore, the present invention further includes the following steps:

[0035] According to the monitored signals of the external break monitoring device within the historical time, obtain the total vibration frequency interval and total vibration amplitude interval; according to the monitored signals when the external break monitoring device monitors disturbances within the historical time, obtain the historical disturbance vibration frequency interval set and historical disturbance vibration amplitude interval set; calculate the ratio of the interval lengths of each historical disturbance vibration frequency interval and historical disturbance vibration amplitude interval in the historical disturbance vibration frequency interval set and historical disturbance vibration amplitude interval set to the total vibration frequency interval and total vibration amplitude interval, and calculate the mean value to obtain the average disturbance frequency ratio and average disturbance amplitude ratio; calculate the ratio of the vibration frequency interval and vibration amplitude interval to the total vibration frequency interval and total vibration amplitude interval to obtain the disturbance frequency ratio and disturbance amplitude ratio; calculate the similarity between the disturbance frequency ratio and disturbance amplitude ratio and the average disturbance frequency ratio and average disturbance amplitude ratio, and calculate the mean value to obtain the first disturbance probability.

[0036] Specifically, first, according to the historical monitoring signals of the external breakage monitoring device within a historical time period (such as the most recent month), all vibration frequencies in the historical monitoring data are extracted, and the maximum historical vibration frequency and the minimum historical vibration frequency are obtained. Then, the minimum historical vibration frequency is used as the lower limit, and the maximum historical vibration frequency is used as the upper limit to construct the total vibration frequency range. All vibration amplitudes in the historical monitoring data are extracted, the maximum historical vibration amplitude and the minimum historical vibration amplitude are obtained, and then the minimum historical vibration amplitude is used as the lower limit, and the maximum historical vibration amplitude is used as the upper limit to construct the total vibration amplitude range.

[0037] On the other hand, according to the monitoring signals when the external breakage monitoring device detects disturbances within a historical time period (such as the most recent month), that is, by analyzing the historical monitoring signals in the disturbance environment, the vibration frequency and amplitude ranges corresponding to the disturbance interference are extracted. First, according to the monitoring records within the historical time period, the vibration signal sequences clearly caused by disturbances (such as signals detected when a confirmed person or vehicle passes by) are extracted. Then, the vibration frequencies in all disturbance interference data are statistically analyzed, their maximum and minimum values are obtained, and the historical disturbance vibration frequency range is constructed. The vibration amplitudes in all disturbance interference data are statistically analyzed, their maximum and minimum values are obtained, and the historical disturbance vibration amplitude range is formed.

[0038] Next, the ratio of the interval length of each historical disturbance vibration frequency range in the set of historical disturbance vibration frequency ranges to the total vibration frequency range is calculated respectively, and is set as the disturbance frequency ratio, obtaining multiple disturbance frequency ratios. For example, assuming that the first historical disturbance vibration frequency range is from 5 Hz to 10 Hz, then the length of the first historical disturbance vibration frequency range is 5 Hz; the total vibration frequency range is from 1 Hz to 101 Hz, then the length of the total vibration frequency range is 100 Hz. Therefore, the first disturbance frequency ratio is 5 / 100, which is equal to 0.05. Then, the mean value of the multiple disturbance frequency ratios is calculated to obtain the average disturbance frequency ratio. On the other hand, the ratio of the interval length of each historical disturbance vibration amplitude range in the set of historical disturbance vibration amplitude ranges to the total vibration amplitude range is calculated respectively, and is set as the disturbance amplitude ratio, obtaining multiple disturbance amplitude ratios. For example, assuming that the first historical disturbance vibration amplitude range is from 0.3 mm to 0.6 mm, and the total vibration amplitude range is from 0.1 mm to 2.1 mm, then the first disturbance amplitude ratio is (0.6 - 0.3) / (2.1 - 0.1), which is equal to 0.15. Further, the mean value of the multiple disturbance amplitude ratios is calculated to obtain the average disturbance amplitude ratio.

[0039] Then, calculate the ratio of the vibration frequency range to the total vibration frequency range, which is set as the proportion of the disturbance frequency. Calculate the ratio of the vibration amplitude range to the total vibration amplitude range, which is set as the proportion of the disturbance amplitude, to obtain the proportion of the disturbance frequency and the proportion of the disturbance amplitude. Next, calculate the similarity between the proportion of the disturbance frequency and the average proportion of the disturbance frequency to obtain the disturbance frequency similarity. Among them, the disturbance frequency similarity is the ratio of 1 minus the absolute value of the difference between the proportion of the disturbance frequency and the average proportion of the disturbance frequency to the average proportion of the disturbance frequency. For example, assume that the proportion of the disturbance frequency is 0.16 and the average proportion of the disturbance frequency is 0.2. Then the absolute value of the difference between the two is 0.04, and the similarity between the two is 1 minus 0.04 / 0.2, which is equal to 0.8, that is, the similarity between the two is 80%. Among them, the smaller the deviation and the difference between the two, the higher the similarity.

[0040] On the other hand, calculate the similarity between the proportion of the disturbance amplitude and the average proportion of the disturbance amplitude, that is, use 1 minus the ratio of the absolute value of the difference between the proportion of the disturbance amplitude and the average proportion of the disturbance amplitude to the average proportion of the disturbance amplitude to obtain the disturbance amplitude similarity; then, calculate the mean value of the disturbance frequency similarity and the disturbance amplitude similarity, and use the mean value calculation result as the first disturbance probability. The first disturbance probability reflects the similarity between the current signal and the historical disturbance characteristics. The higher the value, the more likely the current signal is a disturbance interference rather than an external break event.

[0041] The external break probability calculation module 13 is used to predict the disturbance probability of the monitoring signal sequence according to the first disturbance probability, obtain the second disturbance probability, calculate and obtain the external break probability in combination with the first disturbance probability as the anti-external break monitoring result, and send a warning message.

[0042] Furthermore, the external break probability calculation module 13 is also used for:

[0043] Training the disturbance integrated recognition path for identifying the disturbance probability of the monitoring signal sequence. There are M disturbance recognition paths in the disturbance integrated recognition path.

[0044] Furthermore, the present invention also includes the following steps:

[0045] According to the monitoring data of the external break monitoring device within the historical time, collect the sample monitoring signal sequence set, and collect the proportion of the cables being disturbed under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude, which is marked as the sample disturbance probability set; randomly select M pieces of disturbance recognition training data with replacement from the sample monitoring signal sequence set and the sample disturbance probability set; use machine learning, based on the M pieces of disturbance recognition training data, train M disturbance recognition paths, and integrate them to obtain the disturbance integrated recognition path.

[0046] Specifically, according to the monitoring data of internal and external damage monitoring devices within a historical time period (such as the most recent month), multiple sample monitoring signal sequences are collected. These monitoring signal sequences should cover a variety of environmental conditions and event types (such as disturbance interference, external damage events, etc.), and a set of sample monitoring signal sequences is constructed. Then, the proportion of cables affected by disturbance interference under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude is collected. That is, for each group of signal sequences, the proportion of cables affected by disturbance interference is calculated. This proportion represents the frequency of disturbance interference occurring under the conditions of the same vibration frequency and vibration amplitude. The calculation of the proportion of disturbance interference can be obtained based on statistical methods, and the proportion of disturbance interference is labeled as the sample disturbance probability. For example, for a group of signal sequences with the same vibration characteristics (such as a vibration frequency of 10 Hz and a vibration amplitude of 1 mm), the proportion of cables affected by disturbance interference under this group of signal sequences is calculated. Assuming that for the samples of these signal sequences, the cables are affected by disturbance interference in 80% of the cases and damaged by external damage events in 20% of the cases, the disturbance probability of this group is 0.8, and multiple sample disturbance probabilities are obtained to construct a set of sample disturbance probabilities.

[0047] Then, the set of sample monitoring signal sequences and the set of sample disturbance probabilities are used as a sample data set, and the sample data set is equally divided into M parts to obtain M training sets, where M is an integer greater than 10, and the specific value of M can be set according to actual needs. Further, a disturbance recognition path is constructed based on machine learning. For example, a disturbance recognition path is constructed based on a BP neural network. The disturbance recognition path is a BP neural network model that can be iteratively optimized in machine learning, including an input layer, multiple hidden layers, and an output layer. Among them, the input data of the input layer is the monitoring signal sequence, and the output data of the output layer is the disturbance probability.

[0048] Next, using the sample monitoring signal sequences as the input and the sample disturbance probability as the supervision, the M training sets are used to perform supervised training on the BP neural network respectively until convergence, and M disturbance recognition paths are obtained. For example, the first training set is selected to perform supervised training on the first disturbance recognition path. First, the monitoring signal sequence is input, and after calculation by the input layer and the hidden layer, the disturbance probability is finally generated in the output layer. Then, the loss function is used to calculate the error between the output value and the true disturbance probability. Then, the error backpropagation algorithm is used to minimize the error by adjusting the weights and biases in the network. This process is achieved through the gradient descent method to optimize the parameters of the network. Further, the forward propagation, error calculation, and backpropagation steps are repeated until the loss function converges, such as the loss is less than 0.005, that is, the weights and biases of the network are stable and the error approaches the minimum value, and then the trained first disturbance recognition path is obtained. Finally, the M disturbance recognition paths are combined to construct a disturbance integrated recognition path.

[0049] By constructing a disturbance recognition path based on machine learning, it is possible to predict the probability of disturbance interference by monitoring the vibration characteristics in the signal sequence, achieve efficient and accurate identification of cable disturbance interference, thereby improving the accuracy of cable anti-external damage monitoring and reducing false alarms.

[0050] According to the first disturbance probability, N disturbance recognition paths are calculated and configured. The monitoring signal sequence is input into the N disturbance recognition paths, N disturbance probabilities are obtained through recognition, and the mean value is calculated to obtain the second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

[0051] Specifically, N is obtained by taking the integer part of multiplying the first disturbance probability by M. For example, assuming the first disturbance probability is 0.8 and M is 20, then N is 16. Then, randomly select N disturbance recognition paths from the M disturbance recognition paths, and input the monitoring signal sequence into the N disturbance recognition paths for disturbance probability recognition. Each recognition path will output a disturbance probability, indicating the probability of recognizing disturbance interference under the given signal sequence. N disturbance probabilities are obtained, and the mean value is calculated to obtain the second disturbance probability.

[0052] By performing disturbance probability analysis by setting an appropriate number of disturbance recognition paths according to the first disturbance probability, it is possible to avoid the situation of too many or too few disturbance recognition paths. If the first disturbance probability is low, a relatively small number of recognition paths can be appropriately selected, which helps to concentrate computing power resources and avoid redundant calculations; if the first disturbance probability is high, more recognition paths are needed to increase the recognition accuracy; thus, it can effectively balance the computational burden and recognition accuracy and rationally utilize computing power resources.

[0053] Furthermore, the external damage probability calculation module 13 is further configured to:

[0054] Calculate the mean value of the first disturbance probability and the second disturbance probability to obtain the total disturbance probability; according to the total disturbance probability, calculate and obtain the external damage probability as the anti-external damage monitoring result, and send a warning message.

[0055] Specifically, calculate the mean value of the first disturbance probability and the second disturbance probability to obtain the total disturbance probability; then subtract the total disturbance probability from 1, and use the difference as the external damage probability. For example, assuming the first disturbance probability is 0.8 and the second disturbance probability is 0.76, then the total disturbance probability is 0.78, and the external damage probability is 1 - 0.78 = 0.22; and use the external damage probability as the anti-external damage monitoring result, and send a warning message, such as prompting the cable maintenance personnel to perform cable maintenance operations according to the anti-external damage monitoring result to avoid the inability to maintain the cable in time when external damage occurs, which affects power transmission.

[0056] The cable anti-external damage monitoring system provided by the embodiments of the present invention has at least the following technical effects:

[0057] Through a φ-OTDR-based external break monitoring device, monitor and obtain the monitoring signal sequence of the cable, and collect the disturbance parameter sequence in the environment where the cable is located; then, based on the monitoring signal sequence, perform interval analysis of the vibration frequency and vibration amplitude to obtain the vibration frequency interval and the vibration amplitude interval, and calculate the first disturbance probability; further, based on the first disturbance probability, perform disturbance probability prediction on the monitoring signal sequence to obtain the second disturbance probability; finally, calculate the mean value of the first disturbance probability and the second disturbance probability to obtain the total disturbance probability, and calculate the external break probability based on the total disturbance probability as the anti-external break monitoring result, and send a warning message; through the above method, the intelligence and accuracy of cable disturbance interference recognition can be improved, and thus the external break event can be accurately identified in a complex environment, reducing false alarms, thereby significantly improving the accuracy and reliability of cable anti-external break monitoring and enhancing the cable safety monitoring ability.

[0058] Example 2, as Figure 2 shown, based on the same inventive concept as the cable anti-external break monitoring system provided in Example 1, the embodiment of the present invention further provides a cable anti-external break monitoring method, including: through a φ-OTDR-based external break monitoring device, monitor and obtain the monitoring signal sequence of the cable; based on the monitoring signal sequence, perform interval analysis of the vibration frequency and vibration amplitude to obtain the vibration frequency interval and the vibration amplitude interval, and calculate the first disturbance probability; based on the first disturbance probability, perform disturbance probability prediction on the monitoring signal sequence to obtain the second disturbance probability, and combine the first disturbance probability to calculate the external break probability as the anti-external break monitoring result, and send a warning message.

[0059] Further, the cable anti-external break monitoring method further includes: through a φ-OTDR-based external break monitoring device, monitor the cable to obtain monitoring signals, and arrange them in chronological order to obtain a monitoring signal sequence.

[0060] Further, the cable anti-external break monitoring method further includes: extract the vibration frequency and vibration amplitude from the monitoring signal sequence to obtain a vibration frequency set and a vibration amplitude set; extract the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude in the vibration frequency set and the vibration amplitude set; generate a vibration frequency interval and a vibration amplitude interval based on the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude; calculate the first disturbance probability based on the vibration frequency interval and the vibration amplitude interval.

[0061] Further, the cable external damage prevention monitoring method further includes: obtaining a total vibration frequency range and a total vibration amplitude range according to the monitoring signals of the external damage monitoring device within a historical time period; obtaining a set of historical disturbance vibration frequency ranges and a set of historical disturbance vibration amplitude ranges according to the monitoring signals when the external damage monitoring device monitors disturbances within the historical time period; calculating the ratio of the interval lengths of each historical disturbance vibration frequency range and historical disturbance vibration amplitude range in the set of historical disturbance vibration frequency ranges and the set of historical disturbance vibration amplitude ranges to the total vibration frequency range and the total vibration amplitude range, and calculating the mean value to obtain an average disturbance frequency ratio and an average disturbance amplitude ratio; calculating the ratios of the vibration frequency range and the vibration amplitude range to the total vibration frequency range and the total vibration amplitude range to obtain a disturbance frequency ratio and a disturbance amplitude ratio; calculating the similarity between the disturbance frequency ratio and the disturbance amplitude ratio and the average disturbance frequency ratio and the average disturbance amplitude ratio, and calculating the mean value to obtain a first disturbance probability.

[0062] Further, the cable external damage prevention monitoring method further includes: training a disturbance integrated recognition path for identifying the disturbance probability of a monitoring signal sequence, where the disturbance integrated recognition path includes M disturbance recognition paths; calculating and configuring N disturbance recognition paths according to the first disturbance probability, inputting the monitoring signal sequence into the N disturbance recognition paths, identifying N disturbance probabilities, and calculating the mean value to obtain a second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

[0063] Further, the cable external damage prevention monitoring method further includes: collecting a set of sample monitoring signal sequences according to the monitoring data of the external damage monitoring device within a historical time period, and collecting the ratio of the cable being disturbed under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude, which is marked as a set of sample disturbance probabilities; randomly selecting M pieces of disturbance recognition training data with replacement from the set of sample monitoring signal sequences and the set of sample disturbance probabilities; using machine learning, training M disturbance recognition paths based on the M pieces of disturbance recognition training data, and integrating them to obtain a disturbance integrated recognition path.

[0064] Further, the cable external damage prevention monitoring method further includes: calculating the mean value of the first disturbance probability and the second disturbance probability to obtain a total disturbance probability; calculating an external damage probability according to the total disturbance probability as the result of the external damage prevention monitoring, and sending a warning message.

[0065] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concept.

[0066] Obviously, those skilled in the art can 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 equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A cable anti-external damage monitoring system, characterized in that The system includes: A data monitoring and acquisition module, which is used to monitor and acquire the monitoring signal sequence of the cable through an external break monitoring device based on φ-OTDR; A vibration characteristic interval analysis module, which is used to perform interval analysis of the vibration frequency and vibration amplitude according to the monitoring signal sequence, obtain the vibration frequency interval and the vibration amplitude interval, and calculate and obtain the first disturbance probability; An external break probability calculation module, which is used to perform disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability, obtain the second disturbance probability, combine the first disturbance probability, calculate and obtain the external break probability as the anti-external break monitoring result, and send a warning message; Among them, performing disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability to obtain the second disturbance probability includes: Training a disturbance integration recognition path for recognizing the disturbance probability of the monitoring signal sequence, where M disturbance recognition paths are included in the disturbance integration recognition path; Calculating and configuring N disturbance recognition paths according to the first disturbance probability, inputting the monitoring signal sequence into the N disturbance recognition paths, recognizing N disturbance probabilities, and calculating the mean value to obtain the second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

2. The cable external damage prevention monitoring system according to claim 1, characterized in that Monitoring and acquiring the monitoring signal sequence of the cable through an external break monitoring device based on φ-OTDR, and collecting the disturbance parameter sequence in the environment where the cable is located, including: Monitoring the cable through an external break monitoring device based on φ-OTDR, acquiring the monitoring signal, and arranging it in chronological order to obtain the monitoring signal sequence.

3. The cable anti-external damage monitoring system according to claim 1, characterized in that, Performing interval analysis of the vibration frequency and vibration amplitude according to the monitoring signal sequence, obtaining the vibration frequency interval and the vibration amplitude interval, and calculating and obtaining the first disturbance probability, including: Extracting the vibration frequency and vibration amplitude from the monitoring signal sequence to obtain a vibration frequency set and a vibration amplitude set; Extracting the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude in the vibration frequency set and the vibration amplitude set; Generating a vibration frequency interval and a vibration amplitude interval according to the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude, and minimum vibration amplitude; Calculating and obtaining the first disturbance probability according to the vibration frequency interval and the vibration amplitude interval.

4. The cable external damage prevention monitoring system according to claim 3, wherein Calculating and obtaining the first disturbance probability according to the vibration frequency interval and the vibration amplitude interval, including: Obtaining the total vibration frequency interval and the total vibration amplitude interval according to the monitoring signals of the external break monitoring device within the historical time; Obtaining the historical disturbance vibration frequency interval set and the historical disturbance vibration amplitude interval set according to the monitoring signals when the external break monitoring device monitors disturbances within the historical time; Calculating the ratio of the interval length of each historical disturbance vibration frequency interval and historical disturbance vibration amplitude interval in the historical disturbance vibration frequency interval set and the historical disturbance vibration amplitude interval set to the total vibration frequency interval and the total vibration amplitude interval, and calculating the mean value to obtain the average disturbance frequency ratio and the average disturbance amplitude ratio; Calculating the ratio of the vibration frequency interval and the vibration amplitude interval to the total vibration frequency interval and the total vibration amplitude interval to obtain the disturbance frequency ratio and the disturbance amplitude ratio; Calculate the similarity between the proportion of the disturbance frequency and the proportion of the disturbance amplitude and the average proportion of the disturbance frequency and the average proportion of the disturbance amplitude, and calculate the mean value to obtain the first disturbance probability.

5. The cable anti-external damage monitoring system according to claim 1, characterized in that Train a disturbance integrated recognition path for identifying the disturbance probability of the monitored signal sequence, including: According to the monitoring data of the external and internal break monitoring equipment in the historical time, collect a set of sample monitored signal sequences, and collect the proportion of the cable being disturbed under the sample monitored signal sequences with the same average vibration frequency and the same vibration amplitude, and label it as the sample disturbance probability set; Randomly select M pieces of disturbance recognition training data with replacement from the set of sample monitored signal sequences and the sample disturbance probability set; Adopt machine learning, based on M pieces of disturbance recognition training data, train M disturbance recognition paths, and integrate them to obtain a disturbance integrated recognition path.

6. The cable anti-external damage monitoring system according to claim 1, characterized in that Combined with the first disturbance probability, calculate the external break probability as the anti-external break monitoring result, and send a warning message, including: Calculate the mean value of the first disturbance probability and the second disturbance probability to obtain the total disturbance probability; According to the total disturbance probability, calculate the external break probability as the anti-external break monitoring result, and send a warning message.

7. A cable anti-external damage monitoring method, characterized in that, Execute through a cable anti-external break monitoring system according to any one of claims 1 to 6, including: Monitor and obtain the monitored signal sequence of the cable through an external break monitoring device based on φ-OTDR; According to the monitored signal sequence, conduct interval analysis of the vibration frequency and the vibration amplitude to obtain the vibration frequency interval and the vibration amplitude interval, and calculate the first disturbance probability; According to the first disturbance probability, conduct disturbance probability prediction on the monitored signal sequence to obtain the second disturbance probability, combined with the first disturbance probability, calculate the external break probability as the anti-external break monitoring result, and send a warning message.

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