Cable external damage prevention monitoring system and method

Abstract

The invention relates to a cable external damage prevention monitoring system and method, and relates to the technical field of cable external damage prevention monitoring, and the method comprises the steps: monitoring and obtaining a monitoring signal sequence of a cable, and collecting a disturbance parameter sequence; performing interval analysis of 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; and performing disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability to obtain a second disturbance probability, performing calculation in combination with the first disturbance probability to obtain an external damage probability, taking the external damage probability as an external damage prevention monitoring result, and sending early warning information. According to the invention, the technical problem that the accuracy and reliability of cable external damage prevention monitoring are low due to the fact that cable disturbance interference and external damage events cannot be effectively distinguished by a traditional method and misjudgment is easy to occur in a disturbance environment can be solved; an external damage event can be accurately recognized in a complex environment, and the accuracy and reliability of cable external damage prevention monitoring are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cable anti-breakage monitoring, and in particular to a cable anti-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 damage prevention monitoring. This technology uses the optical signal propagation characteristics in the optical fiber to detect small changes in the optical fiber (such as vibration, strain, etc.) to effectively identify whether the cable is disturbed by external forces. 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 does not require poles, porcelain insulators, crossarms, guy wires and other materials, which can greatly save investment and has become a trend in future cable laying. When using φ-OTDR to monitor the external damage of underground cables, the vibration of animals, people and passing vehicles near the cables will cause disturbance vibrations in the cables, resulting in signal changes. However, the traditional φ-OTDR monitoring method usually relies on a fixed threshold to identify external damage events, so the tiny vibrations caused by the disturbance may be misjudged as external damage signals, which in turn triggers false alarms, resulting in an increase in the false alarm rate, affecting the accuracy and reliability of cable external damage prevention monitoring. Summary of the invention

[0004] The present invention aims to solve the technical problem that the traditional φ-OTDR monitoring method cannot effectively distinguish between cable disturbance interference and external damage events, and is prone to misjudgment under disturbance, resulting in low accuracy and reliability of cable external damage monitoring. A cable external damage monitoring system and method are provided to solve the problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: In a first aspect, the present invention provides a cable anti-external damage monitoring system, comprising: a data monitoring and acquisition module, used to monitor and acquire a monitoring signal sequence of the cable through an external damage monitoring device based on φ-OTDR; a vibration characteristic interval analysis module, used to perform interval analysis of vibration frequency and vibration amplitude according to the monitoring signal sequence, obtain vibration frequency interval and vibration amplitude interval, and calculate a first disturbance probability; an external damage probability calculation module, used to predict the disturbance probability of the monitoring signal sequence according to the first disturbance probability, obtain a second disturbance probability, and calculate the external damage probability in combination with the first disturbance probability as an anti-external damage monitoring result, and send an early warning message.

[0006] Preferably, the cable anti-external damage monitoring system is further used to: monitor the cable through an external damage monitoring device based on φ-OTDR, obtain monitoring signals, and arrange the monitoring signal sequences in chronological order.

[0007] Preferably, the cable anti-external damage monitoring system is also used to: extract the vibration frequency and vibration amplitude of 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 according to the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude and minimum vibration amplitude; calculate and obtain a first disturbance probability according to the vibration frequency interval and the vibration amplitude interval.

[0008] Preferably, the cable anti-external damage monitoring system is also used to: obtain the total vibration frequency interval and the total vibration amplitude interval according to the monitoring signal of the external damage monitoring device in the historical time; obtain the historical disturbance vibration frequency interval set and the historical disturbance vibration amplitude interval set according to the monitoring signal when the external damage monitoring device detects the disturbance in the historical time; calculate the interval length ratio 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 calculate the mean to obtain the average disturbance frequency proportion and the average disturbance amplitude proportion; calculate 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 proportion and the disturbance amplitude proportion; calculate the similarity between the disturbance frequency proportion and the disturbance amplitude proportion and the average disturbance frequency proportion and the average disturbance amplitude proportion, and calculate the mean to obtain the first disturbance probability.

[0009] Preferably, the cable anti-external damage monitoring system is also used to: train a disturbance integrated identification path for disturbance probability identification of a monitoring signal sequence, the disturbance integrated identification path including M disturbance identification paths; according to the first disturbance probability, calculate and configure to obtain N disturbance identification paths, input the monitoring signal sequence into the N disturbance identification paths, identify to obtain N disturbance probabilities, calculate the mean to obtain a second disturbance probability, N is greater than or equal to 1 and less than or equal to M.

[0010] Preferably, the cable anti-external damage monitoring system is also used to: collect a set of sample monitoring signal sequences based on the monitoring data of the external damage monitoring equipment in the historical time, and collect the proportion of the cable being disturbed under the sample monitoring signal sequence with the same average vibration frequency and the same vibration amplitude, and mark it as a sample disturbance probability set; randomly select M disturbance identification training data with replacement in the sample monitoring signal sequence set and the sample disturbance probability set; use machine learning to train M disturbance identification paths based on the M disturbance identification training data, and integrate them to obtain the disturbance integrated identification path.

[0011] Preferably, the cable anti-external damage monitoring system is also used to: calculate the average of the first disturbance probability and the second disturbance probability to obtain a total disturbance probability; calculate the external damage probability based on the total disturbance probability as an anti-external damage monitoring result, and send early warning information.

[0012] In a second aspect, the present invention provides a cable anti-external damage monitoring method, comprising: monitoring and obtaining a monitoring signal sequence of the cable, and collecting a disturbance parameter sequence in the environment in which the cable is located, through an external damage monitoring device based on φ-OTDR; performing interval analysis of vibration frequency and vibration amplitude according to the monitoring signal sequence, obtaining vibration frequency interval and vibration amplitude interval, and calculating a first disturbance probability; performing a disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability, obtaining a second disturbance probability, and calculating an external damage probability in combination with the first disturbance probability as an anti-external damage monitoring result, and sending an early warning message.

[0013] The beneficial effects of the present invention are as follows: by using an external damage monitoring device based on φ-OTDR, a monitoring signal sequence of the cable is monitored and obtained; then, according to the monitoring signal sequence, an interval analysis of the vibration frequency and the vibration amplitude is performed to obtain the vibration frequency interval and the vibration amplitude interval, and a first disturbance probability is calculated; further, according to the first disturbance probability, a disturbance probability prediction is performed on the monitoring signal sequence to obtain a second disturbance probability; finally, the mean of the first disturbance probability and the second disturbance probability is calculated to obtain a total disturbance probability, and according to the total disturbance probability, an external damage probability is calculated as an anti-external damage monitoring result, and an early warning message is sent; the above method can improve the intelligence and accuracy of cable disturbance interference identification, and then can accurately identify external damage events in complex environments, reduce false alarms, thereby significantly improving the accuracy and reliability of cable anti-external damage monitoring, and enhancing the cable safety monitoring capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic structural diagram of a cable anti-external damage monitoring system provided by the present invention.

[0015] Figure 2 A schematic diagram of a flow chart of a cable anti-breakage monitoring method provided by the present invention; In the accompanying drawings, the components represented by the reference numerals are described as follows: Data monitoring and acquisition module 11, vibration characteristic interval analysis module 12, external failure probability calculation module 13. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0017] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0018] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field 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 will not be 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 in the present invention.

[0019] Embodiment 1, as Figure 1 As shown, an embodiment of the present invention provides a cable anti-external damage monitoring system, comprising: The data monitoring and acquisition module 11 is used to monitor and acquire the monitoring signal sequence of the cable through an external damage monitoring device based on φ-OTDR.

[0020] Furthermore, the data monitoring and acquisition module 11 is also used for: The cable is monitored by an external damage monitoring device based on φ-OTDR, monitoring signals are obtained, and the monitoring signal sequence is obtained by arranging them in chronological order.

[0021] Specifically, φ-OTDR technology is based on the principle of Rayleigh scattering. By emitting narrow linewidth pulse light and detecting the returned backscattered signal, the phase information can reflect the tiny vibration changes along the optical fiber path. When the optical fiber is subjected to external force (such as mechanical disturbance), the phase of its scattered light signal changes. These changes can be captured using coherent detection technology, thereby achieving accurate identification of external disturbance events. The φ-OTDR-based external damage monitoring equipment is used to continuously monitor the cable. The equipment can sense the tiny changes of the cable under force, vibration, etc. by emitting laser pulses and detecting echo signals. Each monitoring will generate a set of optical fiber signal data. These signals can be obtained in real time through the optical fiber network, recorded and arranged in chronological order to form a complete monitoring signal sequence. This signal sequence reflects the state changes of the cable in different time periods.

[0022] In addition to possible external damage, the stress condition of the cable will also be affected by environmental factors such as disturbance. In an environment where vibration disturbances are generated by humans, animals, and vehicles, the vibration of the cable will be affected by external vibrations. Therefore, there may be monitoring signals generated by external disturbances in the monitoring signal sequence, and subsequent external damage monitoring is performed by collecting the monitoring signal sequence.

[0023] The vibration characteristic interval analysis module 12 is used to perform interval analysis of the vibration frequency and the 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.

[0024] Furthermore, the vibration characteristic interval analysis module 12 is also used for: Extract the vibration frequency and vibration amplitude of 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 according to the maximum vibration frequency, minimum vibration frequency, maximum vibration amplitude and minimum vibration amplitude.

[0025] Specifically, first, extract the vibration frequency and vibration amplitude at each monitoring time point in the monitoring signal sequence, that is, convert the time domain signal into a frequency domain signal through signal processing techniques such as Fourier transform, and then extract the frequency component and amplitude information in the signal. For example, perform frequency domain analysis on the monitoring signal sequence, and extract the frequency components in the signal through methods such as FFT. For external damage events, the frequency will be relatively high, while the frequency generated by disturbance interference is usually low. For example, the signal frequency caused by the disturbance caused by people, animals, and vehicles passing by is generally 0.1-30Hz, while the signal frequency generated when the external damage event occurs is generally 0.1-100Hz. Based on this, the disturbance or external damage event can be gradually identified. The vibration frequency set is obtained by extracting the vibration frequency of the signal; the amplitude of the signal is analyzed to obtain the size of the vibration amplitude, wherein external disturbance interference is usually accompanied by a smaller vibration amplitude, such as 0.1mm-1mm. External damage events will produce a larger vibration amplitude, such as 1mm-3mm. The vibration amplitude set is obtained by extracting the vibration amplitude of the signal.

[0026] Next, the maximum vibration frequency, the minimum vibration frequency, the maximum vibration amplitude and the minimum vibration amplitude in the vibration frequency set and the vibration amplitude set are extracted; then a vibration frequency interval is constructed according to the maximum vibration frequency and the minimum vibration frequency, that is, the minimum vibration frequency is used as the lower limit of the vibration frequency interval, and the maximum vibration frequency is used as the upper limit of the vibration frequency interval; and a vibration amplitude interval is constructed according to the maximum vibration amplitude and the minimum vibration amplitude.

[0027] A first disturbance probability is obtained by calculation according to the vibration frequency interval and the vibration amplitude interval.

[0028] Furthermore, the present invention further comprises the following steps: According to the monitoring signal of the external damage monitoring device in the historical time, the total vibration frequency interval and the total vibration amplitude interval are obtained; according to the monitoring signal when the external damage monitoring device detects the disturbance in the historical time, the historical disturbance vibration frequency interval set and the historical disturbance vibration amplitude interval set are obtained; the interval length ratio 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 is calculated, and the mean is calculated to obtain the average disturbance frequency proportion and the average disturbance amplitude proportion; the ratio of the vibration frequency interval and the vibration amplitude interval to the total vibration frequency interval and the total vibration amplitude interval is calculated to obtain the disturbance frequency proportion and the disturbance amplitude proportion; the similarity between the disturbance frequency proportion and the disturbance amplitude proportion and the average disturbance frequency proportion and the average disturbance amplitude proportion is calculated, and the mean is calculated to obtain the first disturbance probability.

[0029] Specifically, first, based on the historical monitoring signals of the external damage monitoring equipment within the historical time (such as the last 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 taken as the lower limit, and the maximum historical vibration frequency is taken as the upper limit to construct a total vibration frequency range; all vibration amplitudes are extracted from the historical monitoring data, the maximum historical vibration amplitude and the minimum historical vibration amplitude are obtained, and then the minimum historical vibration amplitude is taken as the lower limit, and the maximum historical vibration amplitude is taken as the upper limit to construct a total vibration amplitude range.

[0030] On the other hand, according to the monitoring signals when the external damage monitoring equipment detects disturbances within the historical time (such as the last month), that is, by analyzing the historical monitoring signals under the disturbance environment, the vibration frequency and amplitude range corresponding to the disturbance interference are extracted. First, according to the monitoring records within the historical time, a vibration signal sequence that is clearly caused by the disturbance (such as the signal monitored when a person or vehicle passes by) is extracted; then, the vibration frequencies in all the disturbance interference data are counted, and their maximum and minimum values ​​are obtained to construct a historical disturbance vibration frequency range; the vibration amplitudes in all the disturbance interference data are counted, and their maximum and minimum values ​​are obtained to form a historical disturbance vibration amplitude range.

[0031] Next, the ratio of the interval length of each historical disturbance vibration frequency interval in the historical disturbance vibration frequency interval set to the total vibration frequency interval is calculated respectively, and is set as the disturbance frequency ratio, to obtain multiple disturbance frequency ratios. For example, assuming that the first historical disturbance vibration frequency interval is 5 Hz to 10 Hz, the length of the first historical disturbance vibration frequency interval is 5 Hz; the total vibration frequency interval is 1 Hz to 101 Hz, and the length of the total vibration frequency interval is 100 Hz, so the first disturbance frequency ratio is 5 / 100, which is equal to 0.05; then the average 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 interval to the total vibration amplitude interval in the historical disturbance vibration amplitude interval set is calculated respectively, and set as the disturbance amplitude ratio, to obtain multiple disturbance amplitude ratios. For example, assuming that the first historical disturbance vibration amplitude interval is 0.3 mm to 0.6 mm, and the total vibration amplitude interval is 0.1 mm to 2.1 mm, then the first disturbance amplitude ratio is (0.6-0.3) / (2.1-0.1) equals 0.15; further, the average of the multiple disturbance amplitude ratios is calculated to obtain the average disturbance amplitude ratio.

[0032] Then, the ratio of the vibration frequency interval to the total vibration frequency interval is calculated and set as the disturbance frequency ratio, the ratio of the vibration amplitude interval to the total vibration amplitude interval is calculated and set as the disturbance amplitude ratio, and the disturbance frequency ratio and the disturbance amplitude ratio are obtained. Next, the similarity between the disturbance frequency ratio and the average disturbance frequency ratio is calculated to obtain the disturbance frequency similarity, wherein the disturbance frequency similarity is 1 minus the absolute value of the difference between the disturbance frequency ratio and the average disturbance frequency ratio and the difference between the average disturbance frequency ratio. For example, assuming that the disturbance frequency ratio is 0.16 and the average disturbance frequency ratio is 0.2, 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%, wherein the smaller the difference between the two, the higher the similarity.

[0033] On the other hand, the similarity between the disturbance amplitude ratio and the average disturbance amplitude ratio is calculated, that is, the disturbance amplitude similarity is obtained by subtracting the absolute value of the difference between the disturbance amplitude ratio and the average disturbance amplitude ratio from 1 and the average disturbance amplitude ratio to the average disturbance amplitude ratio; then, the disturbance frequency similarity and the disturbance amplitude similarity are averaged, and the average calculation result is used 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 to be a disturbance interference rather than an external damage event.

[0034] The external damage 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, combine the first disturbance probability, calculate the external damage probability as the external damage prevention monitoring result, and send warning information.

[0035] Furthermore, the external failure probability calculation module 13 is also used for: A disturbance integrated identification path for performing disturbance probability identification on a monitoring signal sequence is trained, wherein the disturbance integrated identification path includes M disturbance identification paths.

[0036] Furthermore, the present invention further comprises the following steps: According to the monitoring data of internal and external damage monitoring equipment in historical time, a set of sample monitoring signal sequences is collected, and the proportion of cables disturbed by disturbances under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude is collected, which is marked as a sample disturbance probability set; M disturbance identification training data are randomly selected with replacement in the sample monitoring signal sequence set and the sample disturbance probability set; machine learning is used to train M disturbance identification paths based on the M disturbance identification training data, and the disturbance integrated identification path is obtained by integration.

[0037] Specifically, according to the monitoring data of internal and external damage monitoring equipment in historical time (such as the last 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 being disturbed under the sample monitoring signal sequence 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 being disturbed is calculated. This proportion represents the frequency of disturbance interference 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 marked as the sample disturbance probability. For example, for signal sequences with the same vibration characteristics (such as a vibration frequency of 10Hz and a vibration amplitude of 1mm), the proportion of cables being disturbed under the group of signal sequences is calculated. Assuming that for the samples of these signal sequences, the cables are disturbed in 80% of the cases, and the cables are damaged by external damage events in 20% of the cases, then the disturbance probability of the group is 0.8, and multiple sample disturbance probabilities are obtained to construct a sample disturbance probability set.

[0038] Then, the sample monitoring signal sequence set and the sample disturbance probability set 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. A disturbance identification path is further constructed based on machine learning, for example, a disturbance identification path is constructed based on a BP neural network, and the disturbance identification 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, where the input data of the input layer is a monitoring signal sequence, and the output data of the output layer is a disturbance probability.

[0039] Then, the sample monitoring signal sequence is used as input, the sample disturbance probability is used as supervision, and the M training sets are used to supervise the BP neural network until convergence, and M disturbance identification paths are obtained. For example, the first training set is selected to supervise the first disturbance identification path. First, the monitoring signal sequence is input, and after calculation in the input layer and the hidden layer, the disturbance probability is finally generated in the output layer; then, the error between the output value and the true disturbance probability is calculated using the loss function; then, the error back propagation algorithm is used to minimize the error by adjusting the weights and biases in the network. This process is achieved by the gradient descent method to optimize the parameters of the network; the forward propagation, error calculation and back propagation steps are further repeated until the loss function converges, for example, 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, then the first disturbance identification path completed by training is obtained. Finally, the M disturbance identification paths are combined to construct the disturbance integrated identification path.

[0040] By building a disturbance identification path based on machine learning, it is possible to predict the probability of disturbance interference by monitoring the vibration characteristics in the signal sequence, and achieve efficient and accurate identification of cable disturbance interference, thereby improving the accuracy of cable anti-external damage monitoring and reducing false alarms.

[0041] According to the first disturbance probability, N disturbance identification paths are calculated and configured, the monitoring signal sequence is input into the N disturbance identification paths, N disturbance probabilities are identified, and the mean is calculated to obtain the second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

[0042] Specifically, the first disturbance probability is multiplied by M and rounded to obtain N. For example, assuming that the first disturbance probability is 0.8 and M is 20, then N is 16. Then, N disturbance identification paths are randomly selected from the M disturbance identification paths, and the monitoring signal sequence is input into the N disturbance identification paths for disturbance probability identification. Each identification path outputs a disturbance probability, indicating the probability of the path identifying disturbance interference under a given signal sequence, and N disturbance probabilities are obtained. The average value is calculated to obtain the second disturbance probability.

[0043] By setting the appropriate number of disturbance identification paths according to the first disturbance probability for disturbance probability analysis, it is possible to avoid the situation where the number of disturbance identification paths is too large or too small. If the first disturbance probability is low, fewer identification paths can be appropriately selected, which helps to concentrate computing resources and avoid redundant calculations. If the first disturbance probability is high, more identification paths are required to increase the accuracy of identification. This can effectively balance the computing burden and identification accuracy and make rational use of computing resources.

[0044] Furthermore, the external failure probability calculation module 13 is also used for: The average of the first disturbance probability and the second disturbance probability is calculated to obtain a total disturbance probability; based on the total disturbance probability, an external failure probability is calculated as an anti-external failure monitoring result, and an early warning message is sent.

[0045] Specifically, the first disturbance probability and the second disturbance probability are averaged to obtain a total disturbance probability. Then, 1 is subtracted from the total disturbance probability, and the difference between the two is used as the external damage probability. For example, assuming that the first disturbance probability is 0.8 and the second disturbance probability is 0.76, the total disturbance probability is 0.78, and the external damage probability is 1-0.78, which is equal to 0.22. The external damage probability is used as an anti-external damage monitoring result, and an early warning message is sent, for example, to prompt cable maintenance personnel to perform cable maintenance operations according to the anti-external damage monitoring results, so as to avoid the failure to maintain the cable in time when external damage occurs, which affects power transmission.

[0046] The cable damage prevention monitoring system provided by the embodiment of the present invention has at least the following technical effects: Through the external damage monitoring equipment based on φ-OTDR, the monitoring signal sequence of the cable is monitored and acquired, as well as the disturbance parameter sequence in the environment where the cable is located; then, according to the monitoring signal sequence, the interval analysis of the vibration frequency and the vibration amplitude is performed to obtain the vibration frequency interval and the vibration amplitude interval, and the first disturbance probability is calculated; further according to the first disturbance probability, the disturbance probability of the monitoring signal sequence is predicted to obtain the second disturbance probability; finally, the mean of the first disturbance probability and the second disturbance probability is calculated to obtain the total disturbance probability, and according to the total disturbance probability, the external damage probability is calculated as the external damage prevention monitoring result, and an early warning message is sent; the above method can improve the intelligence and accuracy of cable disturbance interference identification, and then can accurately identify external damage events in complex environments, reduce false alarms, thereby significantly improving the accuracy and reliability of cable external damage prevention monitoring, and enhancing the cable safety monitoring capability.

[0047] Embodiment 2, as Figure 2 As shown, based on the same inventive concept of a cable anti-external damage monitoring system provided in Example 1, an embodiment of the present invention further provides a cable anti-external damage monitoring method, including: monitoring and obtaining a monitoring signal sequence of the cable through an external damage monitoring device based on φ-OTDR; performing interval analysis of vibration frequency and vibration amplitude according to the monitoring signal sequence, obtaining a vibration frequency interval and a vibration amplitude interval, and calculating a first disturbance probability; performing a disturbance probability prediction on the monitoring signal sequence according to the first disturbance probability, obtaining a second disturbance probability, and calculating an external damage probability in combination with the first disturbance probability as an anti-external damage monitoring result, and sending an early warning message.

[0048] Furthermore, the cable anti-external damage monitoring method also includes: monitoring the cable by using an external damage monitoring device based on φ-OTDR, acquiring monitoring signals, and arranging the monitoring signal sequences in chronological order.

[0049] Furthermore, the cable anti-external damage monitoring method also includes: extracting the vibration frequency and vibration amplitude of 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; and calculating and obtaining a first disturbance probability according to the vibration frequency interval and the vibration amplitude interval.

[0050] Furthermore, the cable anti-external damage monitoring method also includes: obtaining a total vibration frequency interval and a total vibration amplitude interval according to the monitoring signal of the external damage monitoring device in the historical time; obtaining a historical disturbance vibration frequency interval set and a historical disturbance vibration amplitude interval set according to the monitoring signal when the external damage monitoring device detects a disturbance in the historical time; calculating the interval length ratio 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 to obtain the average disturbance frequency proportion and the average disturbance amplitude proportion; 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 proportion and the disturbance amplitude proportion; calculating the similarity between the disturbance frequency proportion and the disturbance amplitude proportion and the average disturbance frequency proportion and the average disturbance amplitude proportion, and calculating the mean to obtain the first disturbance probability.

[0051] Furthermore, the cable anti-external damage monitoring method also includes: training a disturbance integrated identification path for disturbance probability identification of a monitoring signal sequence, the disturbance integrated identification path including M disturbance identification paths; according to the first disturbance probability, calculating and configuring to obtain N disturbance identification paths, inputting the monitoring signal sequence into the N disturbance identification paths, identifying to obtain N disturbance probabilities, and calculating the mean to obtain a second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

[0052] Furthermore, the cable anti-external damage monitoring method also includes: collecting a set of sample monitoring signal sequences based on the monitoring data of the external damage monitoring equipment in the historical time, and collecting the proportion of the cable being disturbed under the sample monitoring signal sequence with the same average vibration frequency and the same vibration amplitude, and marking it as a sample disturbance probability set; randomly selecting M disturbance identification training data with replacement in the sample monitoring signal sequence set and the sample disturbance probability set; using machine learning to train M disturbance identification paths based on the M disturbance identification training data, and integrating them to obtain a disturbance integrated identification path.

[0053] Furthermore, the cable anti-external damage monitoring method also includes: calculating the average of the first disturbance probability and the second disturbance probability to obtain a total disturbance probability; based on the total disturbance probability, calculating the external damage probability as an anti-external damage monitoring result, and sending an early warning message.

[0054] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art understand the basic inventive concepts.

[0055] 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 belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A cable anti-external damage monitoring system, characterized in that: The system comprises: A data monitoring and acquisition module is used to monitor and acquire the monitoring signal sequence of the cable through an external damage monitoring device based on φ-OTDR; A vibration characteristic interval analysis module, used to perform interval analysis of vibration frequency and vibration amplitude according to the monitoring signal sequence, obtain vibration frequency interval and vibration amplitude interval, and calculate and obtain a first disturbance probability; The external damage probability calculation module is used to predict the disturbance probability of the monitoring signal sequence according to the first disturbance probability, obtain the second disturbance probability, combine the first disturbance probability, calculate the external damage probability as the anti-external damage monitoring result, and send warning information.

2. The cable anti-external damage monitoring system according to claim 1 is characterized in that: Through the φ-OTDR-based external damage monitoring equipment, the monitoring signal sequence of the cable is monitored and the disturbance parameter sequence in the environment where the cable is located is collected, including: The cable is monitored by an external damage monitoring device based on φ-OTDR, monitoring signals are obtained, and the monitoring signal sequence is obtained by arranging them in chronological order.

3. The cable anti-external damage monitoring system according to claim 1 is characterized in that: According to the monitoring signal sequence, performing interval analysis of the vibration frequency and the vibration amplitude to obtain the vibration frequency interval and the vibration amplitude interval, and calculating and obtaining the first disturbance probability, including: Extracting 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, the minimum vibration frequency, the maximum vibration amplitude and the minimum vibration amplitude in 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, the minimum vibration frequency, the maximum vibration amplitude and the minimum vibration amplitude; A first disturbance probability is obtained by calculation according to the vibration frequency interval and the vibration amplitude interval.

4. The cable anti-external damage monitoring system according to claim 3 is characterized in that: Calculating and obtaining a first disturbance probability according to the vibration frequency interval and the vibration amplitude interval includes: According to the monitoring signal of the external damage monitoring device in the historical time, the total vibration frequency range and the total vibration amplitude range are obtained; According to the monitoring signal when the external damage monitoring device detects disturbance in the historical time, a historical disturbance vibration frequency interval set and a historical disturbance vibration amplitude interval set are obtained; Calculating the interval length ratio 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 to obtain the average disturbance frequency proportion and the average disturbance amplitude proportion; 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 proportion and the disturbance amplitude proportion; The similarity between the disturbance frequency proportion and the disturbance amplitude proportion and the average disturbance frequency proportion and the average disturbance amplitude proportion is calculated, and the mean is calculated to obtain a first disturbance probability.

5. The cable anti-external damage monitoring system according to claim 1, characterized in that: According to the first disturbance probability, predicting the disturbance probability of the monitoring signal sequence to obtain a second disturbance probability includes: Training a disturbance integrated identification path for performing disturbance probability identification on a monitoring signal sequence, wherein the disturbance integrated identification path includes M disturbance identification paths; According to the first disturbance probability, N disturbance identification paths are calculated and configured, the monitoring signal sequence is input into the N disturbance identification paths, N disturbance probabilities are identified, and the mean is calculated to obtain the second disturbance probability, where N is greater than or equal to 1 and less than or equal to M.

6. The cable anti-external damage monitoring system according to claim 5, characterized in that: The disturbance integration recognition path for training the disturbance probability recognition of the monitoring signal sequence includes: According to the monitoring data of internal and external damage monitoring equipment in the historical time, a set of sample monitoring signal sequences is collected, and the proportion of cables disturbed by disturbances under the sample monitoring signal sequences with the same average vibration frequency and the same vibration amplitude is collected, and marked as a sample disturbance probability set; M pieces of disturbance identification training data are randomly selected with replacement in the sample monitoring signal sequence set and the sample disturbance probability set; Using machine learning, based on M disturbance recognition training data, M disturbance recognition paths are trained and integrated to obtain disturbance integrated recognition paths.

7. The cable anti-external damage monitoring system according to claim 1, characterized in that: In combination with the first disturbance probability, the external failure probability is calculated as the external failure prevention monitoring result, and early warning information is sent, including: Calculating the mean of the first disturbance probability and the second disturbance probability to obtain a total disturbance probability; According to the total disturbance probability, the external failure probability is calculated as the external failure prevention monitoring result, and an early warning message is sent.

8. A cable anti-breakage monitoring method, characterized in that: The method is implemented by a cable anti-external damage monitoring system according to any one of claims 1 to 7, comprising: The monitoring signal sequence of the cable is obtained through the external damage monitoring equipment based on φ-OTDR; According to the monitoring signal sequence, an interval analysis of the vibration frequency and the vibration amplitude is performed to obtain the vibration frequency interval and the vibration amplitude interval, and a first disturbance probability is calculated; According to the first disturbance probability, the monitoring signal sequence is predicted for disturbance probability to obtain a second disturbance probability, which is combined with the first disturbance probability to calculate an external damage probability as an anti-external damage monitoring result, and an early warning message is sent.

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