Optical communication abnormity detection method and system, electronic equipment and storage medium

Abstract

The invention provides an optical communication abnormity detection method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring real-time data of an optical communication system, and determining signal characteristics of the real-time data; determining a first abnormal value of the real-time data based on the signal features through a pre-trained anomaly detection model; the alarm signal is triggered in response to the first abnormal value, a target channel for abnormal positioning is determined from channels of the optical communication system, and the channel mode of the target channel is a detection channel mode; emitting light pulses to the optical fiber corresponding to the target channel to determine a measurement result of the optical fiber; and determining optical phase change information of the optical fiber based on the measurement result, and determining an abnormal position and / or an abnormal type of the abnormal event according to the optical phase change information. Therefore, according to the scheme, abnormity positioning is carried out by switching the channel modes of the channels, the change along the optical fiber can be monitored in real time while normal communication is carried out, and abnormity positioning is carried out on the basis of not influencing service transmission.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optical fiber monitoring, artificial intelligence, transmission and bearing, and particularly relates to an optical communication anomaly detection method and system, an electronic device and a storage medium. BACKGROUND

[0002] At present, optical communication system detection and positioning technology is mainly based on instrument direct detection. For example, distributed sensing detection of a single core, or polling detection of fixed period and frequency band by using time division method. Since the sensing module and the normal communication module are separated, it means that the deployment of the sensing module will occupy more additional core, time slot or frequency band resources. SUMMARY

[0003] The present application aims to at least solve one of the technical problems in the related art to some extent.

[0004] To this end, the first object of the present application is to provide an optical communication anomaly detection method to realize anomaly positioning without affecting service transmission, improve the reliability of optical fiber anomaly detection, and save channel resources.

[0005] The second object of the present application is to provide an optical communication anomaly detection system.

[0006] The third object of the present application is to provide an electronic device.

[0007] The fourth object of the present application is to provide a computer readable storage medium.

[0008] To achieve the above object, the first aspect of the present application provides an optical communication anomaly detection method, comprising: acquiring real-time data of an optical communication system, and determining signal features of the real-time data; determining a first abnormal value of the real-time data based on the signal features through a pre-trained anomaly detection model; in response to the first abnormal value, triggering an alarm signal, determining a target channel for anomaly positioning from channels of the optical communication system, and the channel mode of the target channel is a detection channel mode; transmitting an optical pulse to an optical fiber corresponding to the target channel to determine a measurement result of the optical fiber; determining optical phase change information of the optical fiber based on the measurement result, and determining an abnormal position and / or an abnormal type of an abnormal event according to the optical phase change information.

[0009] To achieve the above object, the second aspect of the present application provides a system for detecting optical communication anomaly, comprising: an optical transmitting module, an optical receiving module, a real-time monitoring module, an alarm module, and an anomaly positioning module; wherein the optical transmitting module and the optical receiving module are connected through a connecting component, the connecting component at least comprising an optical cable and an optical repeater; wherein the real-time monitoring module is connected with the anomaly positioning module through the alarm module; the optical receiving module is connected with the real-time monitoring module; the optical transmitting module is configured to transmit an optical signal in an optical communication system; the optical receiving module is configured to receive the optical signal and send the optical signal as real-time data to the real-time monitoring module; the real-time monitoring module is configured to determine a signal feature of the real-time data, and determine a first anomaly value of the real-time data based on the signal feature through a pre-trained anomaly detection model; the alarm module is configured to determine a target channel for anomaly positioning from channels of the optical communication system when the first anomaly value triggers an alarm signal, and a channel mode of the target channel is a detection channel mode; and the anomaly positioning module is configured to transmit an optical pulse to an optical fiber corresponding to the target channel to determine a measurement result of the optical fiber, determine optical phase change information of the optical fiber based on the measurement result, and determine an anomaly position and / or an anomaly type of an anomaly event according to the optical phase change information.

[0010] To achieve the above object, the third aspect of the present application provides an electronic device, comprising: a processor; and a memory connected with the processor in communication; the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory, so that the processor can execute the method for detecting optical communication anomaly as described in the first aspect of the present application.

[0011] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium having stored thereon a computer program, the computer instructions being configured to cause the computer to execute the method for detecting optical communication anomaly as described in the first aspect of the present application.

[0012] The method for detecting optical communication anomaly, the system, the electronic device, and the storage medium provided by the present application can acquire real-time data of an optical communication system, determine a first anomaly value according to a signal feature of the real-time data through an anomaly detection model, and trigger an alarm signal according to the first anomaly value, thereby positioning an anomaly of a target channel. By determining optical phase change information of an optical fiber corresponding to the target channel, the anomaly position and / or the anomaly type of an anomaly event can be determined according to the optical phase change information. Thus, the present application can position an anomaly by switching a channel mode, can monitor changes along an optical fiber in real time while normal communication is performed, can detect and position an anomaly event, can position an anomaly without affecting service transmission, and can improve the reliability of optical fiber anomaly detection and save channel resources.

[0013] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0014] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a method for detecting optical communication anomalies provided in an embodiment of this application. Figure 2 This is a schematic diagram illustrating the determination of a first outlier based on an activation function, provided in an embodiment of this application. Figure 3 This is a schematic diagram illustrating the LSTM model training process provided in the embodiments of this application; Figure 4 This is a flowchart illustrating another method for detecting optical communication anomalies provided in an embodiment of this application. Figure 5 This is a flowchart illustrating another method for detecting optical communication anomalies provided in an embodiment of this application. Figure 6 This is a schematic diagram of the DAS system provided in the embodiments of this application; Figure 7 This is a schematic diagram of the anomaly detection system provided in the embodiments of this application; Figure 8 This is a schematic diagram of the fiber optic anomaly detection process provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of an optical communication anomaly detection system provided in an embodiment of this application.

[0015] Figure 10 This is a schematic diagram of the structure of an optical communication anomaly detection device provided in an embodiment of this application. Detailed Implementation

[0016] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0017] The following describes a method and apparatus for detecting optical communication anomalies according to embodiments of this application, with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of a method for detecting optical communication anomalies according to an embodiment of this application, as shown below.Figure 1 As shown, the optical communication anomaly detection method of this application includes, but is not limited to, the following steps: S101, acquire real-time data from the optical communication system and determine the signal characteristics of the real-time data.

[0019] It should be noted that the execution subject of the optical communication anomaly detection method provided in this application embodiment is an electronic device, which can be a terminal device. Optionally, the terminal device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be personal computers (PCs), televisions, etc. This application embodiment does not impose specific limitations.

[0020] In some embodiments, the optical communication system composed of optical fibers can be monitored to obtain real-time data during the optical fiber or optical cable communication process, which serves as the real-time data of the optical communication system. That is, the optical communication system communicates via optical fibers or optical cables composed of optical fibers.

[0021] Among them, the optical communication system is a technical system that uses light waves as the information carrier and optical fibers as the transmission medium to achieve high-speed, large-capacity, and low-latency data transmission through photoelectric conversion.

[0022] In some embodiments, the data during communication by the optical communication system can be monitored in real time using the system's own data monitoring equipment to determine the real-time data. Here, real-time data refers to the original optical signal and its envelope signal.

[0023] Optionally, real-time data may include received data, optical performance monitoring data, etc.

[0024] In some embodiments, after acquiring real-time data, feature extraction can be performed on the real-time data to obtain the signal features corresponding to the original signal and the envelope signal of the original signal.

[0025] In some embodiments, the short-time energy and short-time zero-crossing rate of the original signal can be extracted as signal features of the original signal; the mean, variance, and quartile statistics of the envelope signal can be extracted as signal features of the envelope signal.

[0026] In some embodiments, short-time energy helps distinguish normal signals from low-amplitude noise. When the energy difference between noise and normal signals is not significant, short-time zero-crossing rate provides a means of distinguishing normal signals from low-frequency noise.

[0027] S102 uses a pre-trained anomaly detection model to determine the first outlier in real-time data based on signal characteristics.

[0028] In this embodiment, a time-series correlation anomaly detection algorithm can be used to determine the first outlier in the real-time data. Optionally, a model based on a time-series correlation anomaly detection algorithm can be used to determine the first outlier in the real-time data.

[0029] For example, models based on time-series anomaly detection algorithms include, but are not limited to: Recurrent Neural Network (RNN) models, Long Short-Term Memory (LSTM) networks, Gated Recurrent Unit (GRU) models, Simple Recurrent Unit (SRU) models, Transformer models, K-means clustering models, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) models, and Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) models.

[0030] This disclosure uses an LSTM model as an example to explain how to determine the first outlier: by determining a pre-trained LSTM model and inputting signal features into the LSTM model for detection, the first outlier of the real-time data is output.

[0031] In some embodiments, the LSTM model includes an input layer, one or more LSTM layers, and an output layer. The input layer inputs signal features into one or more LSTM layers for iterative processing to obtain a first outlier as the output result, which is then output through the output layer.

[0032] S103, in response to the alarm signal triggered by the first abnormal value, determine the target channel for abnormal location from the channels of the optical communication system, and the channel mode of the target channel is the detection channel mode.

[0033] In some embodiments, an anomaly threshold can be predetermined, and an alarm signal can be triggered when a first anomaly value is greater than the anomaly threshold. If the first anomaly value is less than or equal to the anomaly threshold, it can be determined that the real-time data is fluctuating within the normal range, and no anomaly localization is required. Real-time data can be continuously acquired until the first anomaly value of the real-time data is greater than the anomaly threshold, triggering an alarm signal.

[0034] In some embodiments, after determining that an alarm signal has been triggered, anomaly localization can be performed on the channel of the optical communication system. Here, channel refers to the physical or logical path for signal transmission, and the optical communication system is a physical carrier of the channel; therefore, anomaly localization of the channel is equivalent to anomaly localization of the optical communication system.

[0035] It should be noted that channels have different channel modes, such as communication channel mode and detection channel mode. In communication channel mode, the channel can transmit signals normally, while in detection channel mode, the channel is used to sense the environment or device status.

[0036] In some embodiments, before anomaly localization, a target channel for anomaly localization can be determined from the channels, and the channel mode of the target channel can be switched to a detection channel mode to more accurately monitor and locate abnormal events.

[0037] In some embodiments, since there are multiple channels, a target number of channels can be selected as target channels, and their channel modes can be switched to detection channel mode. The number of target channels can be determined based on a first outlier.

[0038] It should be noted that severe anomalies have a significant impact on the channel, causing noticeable parameter changes, making detection and localization relatively easy and requiring minimal channel resources. In contrast, ordinary anomalies are more subtle and require cross-verification of localization results from multiple channels.

[0039] In other words, the larger the first outlier, the fewer the target channels; the smaller the first outlier, the more target channels.

[0040] S104, transmits an optical pulse to the optical fiber corresponding to the target channel to determine the measurement results of the optical fiber.

[0041] In some embodiments, a laser deployed in an optical fiber corresponding to a target channel can be controlled to emit light pulses into the optical fiber corresponding to the target channel. The light pulses propagate within the optical fiber, and due to factors such as material inhomogeneity and molecular vibration, the light pulses will generate backscattered light within the optical fiber.

[0042] If the backscattered light and the light pulse or other backscattered light satisfy the coherence condition, interference will occur, forming an interference signal. The optical phase change in the optical fiber can then be detected based on the interference signal, and the optical phase change can be determined as the measurement result of the optical fiber.

[0043] It should be noted that the strain effect and photoelastic effect within the optical fiber can cause changes in the optical phase. Therefore, the strain effect and photoelastic effect within the optical fiber can be determined based on the interference signal, and thus the changes in the optical phase can be determined based on the strain effect and photoelastic effect.

[0044] In some embodiments, strain effect and photoelastic effect are the physical effects of external disturbances on optical fibers, which cause changes in the length of the optical fiber. Since there is a linear relationship between the change in the length of the optical fiber and the change in the optical phase, the change in the optical phase can be determined by determining the change in the length of the optical fiber through this linear relationship.

[0045] S105, determine the optical phase change information of the optical fiber based on the measurement results, and determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

[0046] In some embodiments, optical phase change information of the optical fiber can be obtained from the measurement results, and abnormal events in the optical communication system can be located with high precision by measuring the time delay and spatial mapping relationship of the optical phase.

[0047] Optionally, since the phase change amount and the anomaly location are directly related through the light propagation time, that is, the timestamp of the light phase change information corresponds to the spatial coordinates of the anomaly point, the anomaly location of the abnormal event can be determined by determining the timestamp of the light phase change information.

[0048] In some embodiments, the anomaly type of the abnormal event can also be determined based on the optical phase change information. The optical phase change information can indicate the magnitude of the optical phase change. The correspondence between different optical phase change values ​​and anomaly types can be preset. When an abnormal event is determined to exist in the optical communication system and the optical phase change information is determined, the anomaly type of the abnormal event can be determined by querying the correspondence.

[0049] In some embodiments, acoustic vibrations alter the refractive index and length of the optical fiber through the photoelastic effect, leading to changes in the optical phase. Furthermore, the location of anomalies can be determined based on acoustic signals. By analyzing the propagation speed of the acoustic signal within the optical fiber, the time it was detected, and the fiber's geometric layout, the location of the anomaly can be determined.

[0050] In some embodiments, after determining the abnormal location of an abnormal event, alarm information can be generated based on the abnormal location. By responding to the alarm information, the optical communication system can be maintained and protected, thus avoiding losses caused by abnormalities in the optical communication system.

[0051] The optical communication anomaly detection method provided in this application acquires real-time data from the optical communication system and determines a first anomaly value based on the signal characteristics of the real-time data using an anomaly detection model. An alarm signal is then triggered based on the first anomaly value, thereby locating the anomaly in the target channel. By determining the optical phase change information of the fiber corresponding to the target channel, the location and / or type of the anomaly event can be determined. Therefore, this solution, by switching the channel mode for anomaly location, can monitor changes along the fiber in real time while maintaining normal communication, detect and locate anomaly events, and achieve anomaly location without affecting service transmission. This improves the reliability of fiber optic anomaly detection and saves channel resources.

[0052] Based on the above embodiments, the embodiments of this application can explain the process of determining the first outlier in the LSTM model. The LSTM layer in the LSTM model includes a forget gate. Input gate and output gate .

[0053] Can be accessed through the Gate of Oblivion Input gate and output gate Iterative calculations are performed based on signal features to obtain the first outlier. The signal features are used as... The input is fed into the LSTM layer. For the t-th iteration, from Get the current input information And according to the forget gate Input gate Based on the input information and the model's state at the (t-1)th iteration Determine the current state of the model. .

[0054] Furthermore, through the output gate Control model state For hidden state The contribution of the hidden state is used to determine the hidden state. By determining the hidden state weight value and combined with activation function Determine the final output , as the first outlier.

[0055] Forgotten Gate Input gate and output gate The process for determining the first outlier can be found in the following formula: (1) (2) (3) in, Indicates the function of the forget gate. Indicates the function of the input gate. This indicates the function of the output gate.

[0056] like Figure 2 The diagram shown illustrates the determination of the first outlier based on the activation function. Figure 2 x in the formula corresponds to , Figure 2 The activation function f(x) in the formula corresponds to the activation function f(x) in the formula. , Figure 2 The dashed line in the figure represents the anomaly threshold of 0.5. If the value processed by the activation function is greater than 0.5, an alarm signal can be triggered. Specifically, when the first abnormal value is greater than 0.8, it can be considered a serious anomaly. That is, when the input value of the activation function is greater than 2, the first abnormal value is determined to be greater than 0.8, which is considered a serious anomaly.

[0057] Based on the above embodiments, the embodiments of this application can further explain and illustrate the LSTM model training process, such as... Figure 3 The diagram illustrates the training process. By acquiring time-series data from the optical communication system, such as optical signal intensity, frequency, and optical performance monitoring parameters, and extracting features from the time-series data, the model's sample input data is obtained. The sample input data includes normal data and abnormal data.

[0058] By constructing an LSTM model and feeding sample input data into it, the LSTM model learns to distinguish between normal and abnormal patterns and trends of change. During the LSTM model training process, the forgetting gate described above can be used. Input gate and output gate Controlling the information flow helps the LSTM model distinguish between important and unimportant inputs, thereby effectively learning and adapting to complex changes in time series.

[0059] Once the LSTM model converges, the model parameters can be determined as weight values. After model training is complete, the signal features of real-time data can be input into the LSTM model to identify outliers, thus outputting the first outlier. The process for identifying the first outlier can be found in the example above and will not be repeated here. If the difference between the first outlier and the outliers in the training data is too large, it can be considered a data anomaly. The LSTM model is then updated, and its performance is evaluated after the update, using metrics such as accuracy and recall. If the performance metrics decline, model adjustments or retraining may be necessary.

[0060] Figure 4 This is a flowchart of a method for detecting optical communication anomalies according to an embodiment of this application, as shown below. Figure 4 As shown, the optical communication anomaly detection method of this application includes, but is not limited to, the following steps: S401: Acquire real-time data from the optical communication system and determine the signal characteristics of the real-time data.

[0061] S402 uses a pre-trained anomaly detection model to determine the first outlier in real-time data based on signal characteristics.

[0062] In the embodiments of this application, steps S401-S402 can be implemented in any of the embodiments of this application, and no limitation is made here, nor will it be described in detail.

[0063] S403, in response to the first abnormal value being greater than the abnormal threshold, triggers an alarm signal.

[0064] S404, Based on the target anomaly level corresponding to the first anomaly value, determine the target channel's proportion of the target channel in the channel.

[0065] In some embodiments, an abnormal threshold for triggering an alarm signal can be preset, and an alarm signal is triggered when a first abnormal value is greater than the abnormal threshold.

[0066] Optionally, the system can receive configuration information sent by the client and obtain the abnormal threshold from the configuration information; it can also determine the abnormal threshold based on historical data and the corresponding abnormal values ​​of the historical data.

[0067] In some embodiments, the channel modes include communication channel mode and detection channel mode. The target information is in detection channel mode, and the channels other than the target channel are in communication channel mode, i.e., communication channels. The target channel and the communication channel have different channel modes. If every communication channel is the target channel, it will affect the transmission of information. Therefore, the target channel can be selected from the channels according to the proportion of the target.

[0068] In some embodiments, the number of target channels is related to the anomaly level. Severe anomalies have a greater impact on channels, resulting in more significant parameter changes, making detection and localization relatively easy and requiring less channel resources for localization. In contrast, ordinary anomalies are more subtle and require cross-verification of localization results from multiple channels.

[0069] In other words, different anomaly levels correspond to different percentages. We can first determine the target anomaly level of the first anomaly based on its magnitude, and then determine the target percentage of the target channel within the channel based on the target anomaly level.

[0070] In some embodiments, different anomaly levels correspond to different anomaly value ranges. By determining different anomaly levels and the anomaly value ranges corresponding to different anomaly levels, the target anomaly level corresponding to the first anomaly value can be determined based on the anomaly value range and the first anomaly value.

[0071] For example, the anomaly levels include level 1 and level 2, and the corresponding anomaly value ranges are range 1 and range 2. If the first anomaly value is in range 1, the target anomaly level of the first anomaly value is determined to be level 1.

[0072] In some embodiments, there is also a corresponding relationship between the anomaly level and the percentage quantity. The corresponding relationship can be queried based on the target anomaly level, and the percentage quantity of the target anomaly level can be determined as the target percentage quantity.

[0073] S405, determine the target channel from the channels with a number equal to the target proportion, and switch the channel mode of the target channel from communication channel mode to detection channel mode.

[0074] In some embodiments, a number of channels that represent the target percentage can be randomly selected from the channels as target channels. Alternatively, a selection interval can be determined based on the target percentage and the total number of channels, and channels that represent the target percentage can be selected from the channels based on the selection interval as target channels.

[0075] For example, if the target anomaly level is level 1 and the target proportion is determined to be 5%, then 5% of the channels in the channel are the target channels; if the target anomaly level is level 2 and the target proportion is determined to be 2%, then 2% of the channels in the channel are the target channels; where level 2 is greater than level 1.

[0076] In some embodiments, the optical fiber in the optical communication system serves as the physical carrier of the channel, and signals are transmitted through the channel. The channel mode of this channel is the communication channel mode to ensure normal signal transmission. Once the channel is determined to be the target channel, the target channel is switched to enable environmental awareness and anomaly localization; that is, the target channel is in detection channel mode.

[0077] S406, transmits an optical pulse to the optical fiber corresponding to the target channel to determine the measurement results of the optical fiber.

[0078] S407, determine the optical phase change information of the optical fiber based on the measurement results, and determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

[0079] In the embodiments of this application, steps S406-S407 can be implemented in any of the embodiments of this application, and no limitation is made here, nor will it be described in detail.

[0080] In the optical communication anomaly detection method provided in this application embodiment, when a first anomaly value triggers an alarm signal, the target anomaly level corresponding to the first anomaly value can be determined, and channels with a target proportion can be selected from the channels according to the target anomaly level as target channels for anomaly localization. By switching the channel mode for anomaly localization, changes along the optical fiber can be monitored in real time while maintaining normal communication, and anomaly events can be detected and located, thus ensuring communication efficiency while locating anomalies.

[0081] Figure 5 This is a flowchart of a method for detecting optical communication anomalies according to an embodiment of this application, as shown below. Figure 5 As shown, the optical communication anomaly detection method of this application includes, but is not limited to, the following steps: S501 acquires real-time data from the optical communication system and determines the signal characteristics of the real-time data.

[0082] S502 uses a pre-trained anomaly detection model to determine the first outlier in real-time data based on signal characteristics.

[0083] S503, in response to the alarm signal triggered by the first abnormal value, determines the target channel for abnormal location from the channels of the optical communication system, and the channel mode of the target channel is the detection channel mode.

[0084] In the embodiments of this application, steps S501-S503 can be implemented in any of the embodiments of this application, and no limitation is made here, nor will it be described in detail.

[0085] S504 transmits an optical pulse to the optical fiber corresponding to the target channel and acquires the interference signal generated by the optical pulse within the optical fiber.

[0086] In some embodiments, a laser can emit light pulses into the optical fiber corresponding to the target channel. By controlling the laser in the optical fiber corresponding to the target channel to emit light pulses, interference signals generated within the optical fiber based on the light pulses can be received.

[0087] In some embodiments, controlling the laser to emit light pulses can be based on control commands, wherein the control commands include parameters required for the light pulses. The laser emits light pulses according to these parameters.

[0088] S505 determines the optical phase change information within the optical fiber as the measurement result based on the interference signal.

[0089] It should be noted that optical pulses produce strain and photoelastic effects within the optical fiber, and these effects lead to changes in the optical phase. Interference signals are a detectable manifestation of these optical phase changes, and thus, the optical phase changes can be determined based on the interference signals.

[0090] In some embodiments, the presence of strain and photoelastic effects in the optical fiber can be detected based on interference signals. Since strain and photoelastic effects cause changes in the length of the optical fiber, and there is a linear relationship between the change in the length of the optical fiber and the optical phase change information, the optical phase change information can be determined based on the change in the length of the optical fiber.

[0091] It is understandable that when abnormal events occur along the optical fiber (such as vibration, excavation, breakage, etc.), the strain effect will cause changes in the length of the optical fiber; while the photoelastic effect will cause changes in the refractive index of the optical fiber, thereby causing a change in phase.

[0092] In other words, in response to the existence of strain and photoelastic effects, the changes in fiber length caused by strain and photoelastic effects are determined, and based on these changes, optical phase change information is determined.

[0093] Alternatively, the formula for determining the optical phase change information is as follows: (4) in, Indicates information about changes in the phase of light. Indicates wavelength. This represents the change in fiber length. It is an integer.

[0094] S506, determine the optical phase change information of the optical fiber based on the measurement results, and determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

[0095] In the embodiments of this application, step S506 can be implemented in any of the ways described in the various embodiments of this application. This is not limited here and will not be described in detail.

[0096] In some embodiments, after determining the abnormal location and / or abnormal type of an abnormal event, alarm information can be generated based on the abnormal location and / or abnormal type, and the alarm information can be sent to the client to handle the abnormal event based on the alarm information.

[0097] In some embodiments, alarm information is generated based on the location and / or type of the anomaly and sent to the client. When the maintenance personnel receive the alarm information from the client, they can handle the abnormal event based on the location and / or type of the anomaly in the alarm information, such as repairing the fiber optic cable, adjusting the system configuration, etc., to avoid losses caused by fiber optic cable anomalies.

[0098] In some embodiments, after processing the abnormal event, the real-time data of the processed optical fiber can be reacquired, and anomaly detection can be performed using an anomaly detection model based on the real-time data of the processed optical fiber to determine the second abnormal value of the processed optical fiber.

[0099] In some embodiments, after obtaining the second abnormal value, it can be determined whether an alarm needs to be triggered for the second abnormal value. If the second abnormal value is a set value that indicates the abnormal event has been handled, then a channel mode switch can be performed. That is, in response to the second abnormal value being a set value, the channel mode of the target channel is switched from the detection channel mode to the communication channel mode.

[0100] The optical communication anomaly detection method provided in this application determines the interference signal of the optical fiber corresponding to the target channel and determines the optical phase change information based on the interference signal. Based on the optical phase change information, the abnormal location and / or abnormal type of the abnormal event are determined, thereby realizing real-time monitoring and location of the abnormal event and improving the accuracy and precision of anomaly location.

[0101] It should be noted that the embodiments of this application can perform anomaly localization using distributed optical fiber sensing technology. This technology utilizes the non-uniformity of the medium density within the optical cable to detect and analyze the backscattered light propagating in the optical fiber. By detecting changes in the backscattered Rayleigh light, it can detect abnormal events such as fiber attenuation, breakpoints, and losses, as well as anomalies around the line.

[0102] For example, distributed acoustic sensing (DAS) systems, such as Figure 6 As shown, the DAS system consists of a narrow linewidth laser, pulse modulation, pulse amplification, signal amplification, coupler, detector, and computer.

[0103] A narrow-linewidth laser emits light pulses, which are then modulated and amplified by pulse modulation and amplification before being transmitted to an optical fiber. The interference signal returned from the fiber is received, amplified, and the phase change is obtained from the interference signal through a coupler and detector. The computer then uses the phase change to determine the location of the abnormal event.

[0104] Based on any of the above embodiments, an anomaly detection system can be determined based on the optical communication anomaly detection method provided in the embodiments of this application. Figure 7 The diagram shown is a structural diagram of an anomaly detection system. Figure 7 The system includes an optical transmitter and an optical receiver, with the optical receiver connected to a real-time monitoring system. The acquired real-time data is transmitted to the real-time monitoring system to determine the first abnormal value. In other words, the real-time monitoring system is equipped with the abnormality detection model in this application embodiment.

[0105] The connection between the transmitting and receiving ends is represented by two optical cables and an optical repeater. The real-time monitoring system can be a server; optionally, the optical receiver can integrate a real-time monitoring system. The optical cables are composed of optical fibers.

[0106] Once the real-time monitoring system determines the first abnormal value based on real-time data, it can send the first abnormal value to the alarm module. If the alarm module determines that the first abnormal value is greater than the abnormal threshold, it will trigger an alarm signal and send the alarm signal to the abnormal location system.

[0107] The anomaly localization system switches some channels to sensing channels, and the sensing channels are the target channels in this application. Figure 7 (As shown in the image, it is connected to a DAS device). The DAS device can accurately locate abnormal events by emitting light pulses and based on the reflected interference signals.

[0108] Figure 8 The diagram shows a flowchart for fiber optic anomaly detection. Figure 8 It includes an anomaly detection module and an anomaly location module.

[0109] The anomaly detection module is used to receive real-time data from the optical communication system and determine the first anomaly value based on the real-time data. If the first anomaly value is greater than the anomaly threshold, the anomaly detection module is triggered to alarm, thereby activating the anomaly location module.

[0110] The anomaly localization module is used to switch the channel mode of some channels to the detection channel mode and obtain the sensing results of the channel in the detection channel mode, namely the optical phase change information, so as to locate the abnormal event based on the optical phase change information, thereby generating alarm information to handle the abnormal event.

[0111] Then switch back to the anomaly detection module to re-detect and locate the anomaly until the anomaly event in the optical communication system is successfully handled.

[0112] Figure 9 This is a schematic diagram of the structure of an optical communication anomaly detection system provided in an embodiment of this application.

[0113] like Figure 9As shown, the optical communication anomaly detection system 900 includes: an optical transmitting module 901, an optical receiving module 902, a real-time monitoring module 903, an alarm module 904, and an anomaly location module 905.

[0114] The optical transmitting module 901 and the optical receiving module 902 are connected by a connecting component 906, which includes at least an optical cable 61 and an optical repeater 62.

[0115] The real-time monitoring module 903 is connected to the anomaly location module 905 via the alarm module 904; the optical receiving module 902 is connected to the real-time monitoring module 903.

[0116] Among them, the optical transmitting module 901 is used to transmit optical signals in the optical communication system; The optical receiving module 902 is used to receive optical signals and send the optical signals as real-time data to the real-time monitoring module 903. The real-time monitoring module 903 is used to determine the signal characteristics of real-time data and, based on the signal characteristics, determine the first outlier of the real-time data using a pre-trained anomaly detection model. The alarm module 904 is used to determine the target channel for anomaly location from the channels of the optical communication system when the first abnormal value triggers the alarm signal. The channel mode of the target channel is the detection channel mode. The anomaly location module 905 is used to transmit optical pulses to the optical fiber corresponding to the target channel to determine the measurement results of the optical fiber, determine the optical phase change information of the optical fiber based on the measurement results, and determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

[0117] In some embodiments, the specific implementation of the optical communication anomaly detection system 900 for anomaly localization of the optical communication system can be found in any of the above examples, and will not be repeated here.

[0118] In the optical communication anomaly detection system provided in this application embodiment, the real-time monitoring module acquires real-time data from the optical communication system and determines a first anomaly value based on the signal characteristics of the real-time data using an anomaly detection model. The alarm module can trigger an alarm signal based on the first anomaly value, thereby locating the anomaly in the target channel. The anomaly location module determines the optical phase change information of the optical fiber corresponding to the target channel and can determine the anomaly location and / or anomaly type based on the optical phase change information. Therefore, this solution performs anomaly location by switching the channel mode, enabling real-time monitoring of changes along the optical fiber while maintaining normal communication, detecting and locating anomaly events, and achieving anomaly location without affecting service transmission. This improves the reliability of optical fiber anomaly detection and saves channel resources.

[0119] Corresponding to the optical communication anomaly detection methods proposed in the above embodiments, an embodiment of this application also proposes an optical communication anomaly detection device. Since the optical communication anomaly detection device proposed in this application corresponds to the optical communication anomaly detection methods proposed in the above embodiments, the implementation methods of the above optical communication anomaly detection methods are also applicable to the optical communication anomaly detection device proposed in this application, and will not be described in detail in the following embodiments.

[0120] Figure 10 This is a schematic diagram of the structure of an optical communication anomaly detection device provided in an embodiment of this application.

[0121] like Figure 10 As shown, the optical communication anomaly detection device 1000 includes: The acquisition module 1001 is used to acquire real-time data from the optical communication system and determine the signal characteristics of the real-time data. The first determining module 1002 is used to determine the first outlier value of the real-time data based on the signal features using a pre-trained anomaly detection model. The second determining module 1003 is used to determine the target channel for anomaly location from the channels of the optical communication system in response to the alarm signal triggered by the first abnormal value, wherein the channel mode of the target channel is a detection channel mode. The third determining module 1004 is used to transmit an optical pulse to the optical fiber corresponding to the target channel in order to determine the measurement result of the optical fiber; The positioning module 1005 is used to determine the optical phase change information of the optical fiber based on the measurement results, and to determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

[0122] In one possible implementation of this application embodiment, the first determining module 1002 is further configured to: determine different anomaly levels and the range of anomaly values ​​corresponding to the different anomaly levels; and determine the target anomaly level corresponding to the first anomaly value based on the range of anomaly values ​​and the first anomaly value.

[0123] In one possible implementation of this application embodiment, the second determining module 1003 is further configured to: trigger the alarm signal in response to the first abnormal value being greater than the abnormal threshold; determine the target proportion of the target channel in the channel based on the target abnormality level corresponding to the first abnormal value; determine the channel with the number of the target proportion from the channel as the target channel, and switch the channel mode of the target channel from the communication channel mode to the detection channel mode.

[0124] In one possible implementation of this application embodiment, the third determining module 1004 is further configured to: acquire the interference signal generated in the optical fiber based on the optical pulse; and determine the optical phase change information in the optical fiber as the measurement result based on the interference signal.

[0125] In one possible implementation of this application embodiment, the third determining module 1004 is further configured to: detect whether there is a strain effect and a photoelastic effect in the optical fiber based on the interference signal; determine the change value of the strain effect and the photoelastic effect on the length of the optical fiber in response to the presence of the strain effect and the photoelastic effect; and determine the optical phase change information based on the change value.

[0126] In one possible implementation of this application embodiment, the positioning module 1005 is further configured to: generate alarm information based on the abnormal location, and send the alarm information to the client.

[0127] In one possible implementation of this application embodiment, the positioning module 1005 is further configured to: process the abnormal event based on the alarm information; determine a second abnormal value of the optical fiber after abnormal processing; and, in response to the second abnormal value being a set value, switch the channel mode of the target channel from the target channel mode to the original channel mode.

[0128] The optical communication anomaly detection device provided in this application acquires real-time data from the optical communication system and determines a first anomaly value based on the signal characteristics of the real-time data using an anomaly detection model. An alarm signal is then triggered based on the first anomaly value, thereby locating the anomaly in the target channel. By determining the optical phase change information of the fiber corresponding to the target channel, the location and / or type of the anomaly event can be determined based on the optical phase change information. Therefore, this solution performs anomaly location by switching the channel mode, enabling real-time monitoring of changes along the fiber optic cable while maintaining normal communication. This allows for the detection and location of anomaly events without affecting service transmission, improving the reliability of fiber optic anomaly detection and conserving channel resources.

[0129] It should be noted that the explanation of the aforementioned embodiment of the optical communication anomaly detection method also applies to the optical communication anomaly detection device of this embodiment, and will not be repeated here.

[0130] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0131] The collection, storage, use, processing, transmission, provision, and application of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0132] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0133] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this application is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0134] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0135] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0136] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0137] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0138] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0139] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0140] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0141] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for detecting optical communication anomalies, characterized in that, The method includes: Acquire real-time data from the optical communication system and determine the signal characteristics of the real-time data; The first outlier value of the real-time data is determined based on the signal features using a pre-trained anomaly detection model. In response to the alarm signal triggered by the first abnormal value, a target channel for abnormal location is determined from the channels of the optical communication system, wherein the channel mode of the target channel is a detection channel mode; An optical pulse is transmitted into the optical fiber corresponding to the target channel to determine the measurement results of the optical fiber; Based on the measurement results, the optical phase change information of the optical fiber is determined, and the abnormal location and / or abnormal type of the abnormal event is determined according to the optical phase change information.

2. The method according to claim 1, characterized in that, After determining the first outlier of the real-time data based on the signal characteristics, the process includes: Determine the different anomaly levels and the range of outliers corresponding to the different anomaly levels; Based on the range of outliers and the first outlier, the target outlier level corresponding to the first outlier is determined.

3. The method according to claim 2, characterized in that, The step of determining the target channel for anomaly localization from the channels of the optical communication system in response to the alarm signal triggered by the first anomaly value includes: The alarm signal is triggered in response to the first abnormal value being greater than the abnormal threshold; Based on the target anomaly level corresponding to the first anomaly value, determine the target channel's target proportion in the channel; The target channel is selected from the channels, and its channel mode is switched from communication channel mode to detection channel mode.

4. The method according to claim 1, characterized in that, The step of transmitting an optical pulse into the optical fiber corresponding to the target channel to determine the measurement result of the optical fiber includes: Acquire the interference signal generated within the optical fiber based on the optical pulse; Based on the interference signal, the optical phase change information within the optical fiber is determined as the measurement result.

5. The method according to claim 4, characterized in that, The step of determining the optical phase change information within the optical fiber as the measurement result based on the interference signal includes: Based on the interference signal, detect whether the optical fiber exhibits strain and photoelastic effects; In response to the presence of the strain effect and photoelastic effect, determine the change in the fiber length caused by the strain effect and photoelastic effect; Based on the change value, the optical phase change information is determined.

6. The method according to any one of claims 1-5, characterized in that, After determining the location of the abnormal event, the process includes: Based on the abnormal location, an alarm message is generated and sent to the client.

7. The method according to claim 6, characterized in that, After sending the alarm information to the client, the process includes: The abnormal event is processed based on the alarm information; Determine the second anomaly value of the optical fiber after anomaly handling; In response to the second abnormal value being a set value, the channel mode of the target channel is switched from the detection channel mode to the communication channel mode.

8. A detection system for optical communication anomalies, characterized in that, The system includes: an optical transmitting module, an optical receiving module, a real-time monitoring module, an alarm module, and an anomaly location module; wherein the optical transmitting module and the optical receiving module are connected by a connecting component, the connecting component including at least an optical cable and an optical repeater; wherein the real-time monitoring module is connected to the anomaly location module through the alarm module; and the optical receiving module is connected to the real-time monitoring module. The optical transmitting module is used to transmit optical signals in the optical communication system; The optical receiving module is used to receive the optical signal and send the optical signal as real-time data to the real-time monitoring module; The real-time monitoring module is used to determine the signal characteristics of the real-time data and, based on the signal characteristics, determine the first outlier value of the real-time data using a pre-trained anomaly detection model. The alarm module is used to determine the target channel for anomaly location from the channels of the optical communication system when the first abnormal value triggers an alarm signal, wherein the channel mode of the target channel is a detection channel mode. The anomaly location module is used to transmit optical pulses to the optical fiber corresponding to the target channel to determine the measurement results of the optical fiber, and to determine the optical phase change information of the optical fiber based on the measurement results, and to determine the abnormal location and / or abnormal type of the abnormal event based on the optical phase change information.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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