Optical cable status intelligent monitoring system and method

Abstract

The present invention discloses an intelligent monitoring system and method for optical cable status, belonging to the technical field of optical cable status assessment. The method specifically comprises: real-time collection of optical cable-related data, including structural parameters and optical signals of the optical cable; preprocessing the collected optical cable-related data; calculating the status of the optical cable transmission line based on the preprocessed optical cable-related data; and assessing the status of the optical cable transmission line; combining multiple factors such as optical signal reflection intensity, structural parameters of the optical cable, environmental data, bending effects, etc. to form a comprehensive overall status assessment model. By integrating multiple influencing factors, the overall status of the optical cable line can be more comprehensively assessed, and the model can be adjusted and optimized according to different lines, equipment and environmental conditions to meet the needs of different scenarios.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical cable status evaluation, and in particular relates to an optical cable status intelligent monitoring system and method. Background Art

[0002] With the rapid development of information technology, optical fiber cables, as an efficient and stable data transmission method, have been widely used in various fields, especially in industries such as telecommunications, the internet, and data centers. Optical cables carry large amounts of information and data flows, and their quality and stability are crucial to the normal operation of information and communication networks. However, as the operating environment of optical cables becomes increasingly complex, optical cable lines may be affected by various factors during long-term operation, facing numerous problems.

[0003] Disadvantage 1: Especially during the operation of optical cables, factors such as changes in the external environment, equipment aging, and accidental damage may cause optical cables to malfunction or performance degradation, affecting communication quality.

[0004] Traditional optical cable monitoring methods mainly rely on manual inspections, regular testing and traditional sensor technology. In recent years, artificial intelligence technology has been widely used in the field of optical cable monitoring, but it still has shortcomings. The limitations of a single data source: Most existing monitoring methods rely on only a single data source (such as current, voltage, temperature, etc.) for judgment, ignoring the diversity and complexity of system operation; static threshold judgment: Many traditional systems use fixed thresholds to judge whether a line is faulty, but the status of optical cable transmission lines is affected by many factors. This simple threshold judgment method is prone to misjudgment or omission; difficult to adapt to dynamic changes: When faced with complex environmental changes, load fluctuations and changes in health status, the lack of real-time and adaptive adjustment capabilities makes it impossible to effectively predict potential faults.

[0005] Disadvantage 2: During long-term operation, optical cable lines may be subject to a variety of external factors, including temperature fluctuations, mechanical bending, external collisions, damage, and corrosion. These factors can cause performance degradation or even failure of the optical cable line. Therefore, real-time monitoring and status monitoring of optical cable transmission lines are particularly important.

[0006] Currently, fiber optic line monitoring methods primarily rely on analyzing the fiber's transmission signal. Commonly used technologies include time-domain reflectometry (OTDR), optical power monitoring, and sensor-based real-time data acquisition. These traditional methods can detect some line faults (such as fiber breaks and connector mismatches), but they have limitations, including insufficient ability to identify subtle damage, an inability to fully reflect the actual operating status of the line, and difficulty implementing large-scale online monitoring.

[0007] Insufficiency 3: The optical cable transmission channel is a vital part of the fiber optic network. Any slight damage or change may affect the signal transmission quality. When it is filled with huge amounts of data, it may even cause the entire network to be paralyzed. Optimizing the load of the optical cable transmission line is the key to ensuring that the optical cable can still maintain stable transmission under high-load environments. With the continuous growth of data transmission volume, the optimized management of the optical cable load has become particularly important. Optical cable maintenance is a complex and costly process. Especially when a fault occurs, it is crucial to repair it quickly and accurately.

[0008] However, during long-term use, optical cables are easily damaged due to factors such as changes in the external environment, natural disasters, and equipment aging, leading to problems such as signal attenuation and transmission interruption. Traditional optical cable monitoring and maintenance methods mostly rely on manual inspections, regular inspections, and fixed-position sensors. These methods suffer from problems such as unreasonable resource allocation, inaccurate load forecasting, difficulty in effectively modeling and predicting changing environmental factors, and high labor costs. Summary of the Invention

[0009] In response to the deficiency 1 of the prior art, the present invention proposes an intelligent monitoring system and method for optical cable status, which combines optical signal acquisition and optical cable line structural parameters to evaluate optical cable transmission lines, thereby realizing all-round and accurate monitoring of optical cable transmission lines. This method can achieve efficient damage location and health status assessment, which not only improves the reliability of optical cable lines but also reduces maintenance costs.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] An intelligent monitoring method for optical cable status, comprising:

[0012] Real-time collection of optical cable related data, including cable structural parameters and optical signals;

[0013] Preprocess the collected optical cable related data;

[0014] The status of the optical cable transmission line is calculated based on the pre-processed optical cable related data. Based on the optical signal of the optical cable, a time domain reflection diagram is generated to determine the location and severity of optical cable damage and evaluate the overall health status of the optical cable transmission line.

[0015] Specifically, the state of the optical cable transmission line is calculated based on the pre-processed optical cable related data, a time domain reflectogram is generated based on the optical signal of the optical cable, the location and severity of damage to the optical cable are determined, and the overall health state of the optical cable transmission line is evaluated, which specifically includes:

[0016] Calculate the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data;

[0017] Generate a time domain reflectogram based on the optical signal of the optical cable to determine the location and severity of the damage to the optical cable;

[0018] An overall status assessment model for optical cables is established by comprehensively considering the optical signal attenuation loss, optical cable damage location, and damage severity assessment value.

[0019] Specifically, calculating the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data includes:

[0020] The basic attenuation of the optical cable is determined by the material and structure of the optical cable. The basic attenuation A of the optical cable is calculated. basic (d);

[0021] When the optical cable is bent, the refractive index distribution of the optical cable will change, causing partial leakage of the optical signal and increasing attenuation. The bending loss of the optical cable is A bend (d,R);

[0022] According to the basic attenuation, bending loss and temperature-affected loss of the optical cable, the optical signal attenuation loss of the optical cable transmission line is calculated. The specific formula is:

[0023] A tatal (d, R, T) = A basic (d)+A bend (d,R)+α temp ×(T-T0),

[0024] Among them, A tatal (d, R, T) represents the optical signal attenuation loss of the optical cable transmission line, α temp Indicates the attenuation coefficient of the optical cable to temperature changes, T is the current ambient temperature of the optical cable, T0 is the reference temperature, d is the length of the optical cable, and R is the bending radius of the optical cable.

[0025] Specifically, generating a time domain reflectogram based on the optical signal of the optical cable to determine the damage location and severity of the optical cable includes:

[0026] The intensity of the optical signal reflected from the optical cable is calculated based on the transmitted optical signal power, the received reflected signal power, the change in reflected signal intensity caused by temperature, the change in reflected signal intensity caused by damage to the optical cable transmission line, and the reflection loss at the connectors and connection points. The specific formula is:

[0027]

[0028] Among them, S reflect Indicates the intensity of the optical signal reflected by the optical cable, log() represents the logarithmic function, P send Indicates the transmitted optical signal power, P recvrepresents the power of the received reflected signal, e represents a natural constant, ΔS reflect (T) represents the change in reflected signal intensity caused by temperature, S da Indicates the change in reflected signal strength caused by damage to the optical cable transmission line, A joint Indicates the reflection loss of joints and connection points;

[0029] With the optical signal's propagation distance as the horizontal axis and the optical signal's intensity reflected by the optical cable as the vertical axis, a time domain reflectogram is constructed and the damage point is determined based on the time domain reflectogram.

[0030] The location of the optical cable damage point is calculated based on the reflection time delay of the optical signal reflected by the optical cable, the refractive index of the optical cable, and the speed of light. The specific formula is: Among them, x da represents the location of the optical cable damage point, c1 represents the speed of light, Δt represents the time delay of the reflected light signal, and n1 represents the refractive index of the optical cable;

[0031] Establish an optical cable damage assessment model to assess the severity of optical cable damage. Perform weighted summation on the intensity of the optical cable reflected light signal, the distance from the optical cable damage point to the monitoring equipment, the coefficient of the optical cable damage type, and the temperature change to obtain the optical cable damage severity assessment value. The specific formula is:

[0032]

[0033] in, Indicates the severity assessment value of optical cable damage, d da Indicates the distance from the optical cable damage point to the monitoring equipment, η type The coefficient representing the type of optical cable damage, ΔT represents the temperature change, α reflect , α dis , α type and α tem represents the weight coefficient;

[0034] The severity of optical cable damage is defined according to the optical cable damage severity assessment value. When it is less than 10, it is a minor damage, usually manifested as a minor joint loss or bending. When the value is greater than or equal to 10 and less than or equal to 30, it is considered moderate damage. When it is greater than 30, it is a serious injury.

[0035] Specifically, the overall condition assessment model of the optical cable is established by comprehensively considering the optical signal attenuation loss, the optical cable damage location and the damage severity assessment value, including:

[0036] According to the optical signal attenuation loss, optical cable damage location and damage severity assessment value, the overall condition assessment model of the optical cable is established to obtain the health status assessment value of the optical cable transmission line. The specific formula is:

[0037]

[0038] in, represents the health status assessment value of the optical cable transmission line, n represents the number of sampling points of the optical cable transmission line, A total (d i ,R i ,T i ) represents the optical signal attenuation loss of the optical cable transmission line at the i-th sampling point, P recv (d i ) represents the power of the reflected signal received by the optical cable at the i-th sampling point, m represents the number of damage points, represents the damage severity assessment value at the jth damage point of the optical cable, (x da ,j) represents the position of the jth damage point;

[0039] Set the cable health threshold to like Greater than the optical cable health threshold When the optical cable transmission line is faulty or damaged, it is determined that there is a fault or damage in the optical cable transmission line.

[0040] Specifically, the structural data of the optical cable includes: the geometric shape and material properties of the optical cable, the laying environment of the optical cable, the type of the optical cable and the attenuation rate of the optical cable.

[0041] Specifically, the preprocessing includes: data cleaning, deduplication and standardization;

[0042] The data cleaning includes removing invalid, duplicate, erroneous or incomplete data records;

[0043] The data deduplication, identifying and removing duplicate records or redundant information;

[0044] Normalization converts raw data from one format into another format suitable for analysis and processing.

[0045] An optical cable status intelligent monitoring system, used to implement the optical cable status intelligent monitoring method, comprising: a data acquisition module, a data preprocessing module and a status evaluation module;

[0046] The data acquisition module is used to collect optical cable related data in real time, including structural parameters and optical signals of the optical cable;

[0047] The data preprocessing module is used to preprocess the collected optical cable related data;

[0048] The status assessment module is used to calculate the status of the optical cable transmission line based on the preprocessed optical cable related data, generate a time domain reflectogram based on the optical signal of the optical cable, determine the location and severity of optical cable damage, and evaluate the overall health status of the optical cable transmission line.

[0049] Specifically, the state assessment module includes: an attenuation loss calculation unit, a damage judgment unit and an overall state assessment unit;

[0050] The attenuation loss calculation unit is used to calculate the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data;

[0051] The damage judgment unit is used to generate a time domain reflection diagram based on the optical signal of the optical cable to judge the damage location and damage severity of the optical cable;

[0052] The overall status evaluation unit is used to comprehensively consider the optical signal attenuation loss, the optical cable damage position and the damage severity evaluation value to establish an overall status evaluation model for the optical cable.

[0053] Specifically, the damage judgment unit includes: a loss location calculation subunit and a loss severity assessment subunit;

[0054] The loss position calculation subunit is used to calculate the position of the optical cable damage point based on the reflection time delay of the optical signal reflected by the optical cable;

[0055] The loss severity assessment subunit is used to establish an optical cable damage assessment model and assess the severity of optical cable damage.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention proposes an intelligent optical cable status monitoring method. By comprehensively considering factors such as optical fiber attenuation, reflection, bending, and temperature, it provides more accurate damage location and diagnosis capabilities, especially for the detection of minor damage, local faults, and joint problems.

[0058] 2. The present invention proposes an intelligent monitoring method for optical cable status. This method not only relies on changes in the reflection intensity of optical signals, but also combines the structural parameters of the optical cable and environmental data, such as temperature changes and bending effects, to form a comprehensive overall status assessment model. By integrating multiple influencing factors, it can more comprehensively assess the overall status of the optical cable line and identify potential problems that traditional methods cannot detect.

[0059] 3. The present invention proposes an intelligent monitoring method for optical cable status, which is not only applicable to ordinary optical cable transmission lines, but can also be widely used for optical cable monitoring in different environments, such as high temperature, high humidity, high electromagnetic interference and other harsh environments. It can be adjusted and optimized according to different lines, equipment and environmental conditions to meet the needs of different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 Flowchart of the optical cable status intelligent monitoring method provided by the present invention;

[0061] Figure 2 The time domain reflectogram provided by the present invention;

[0062] Figure 3 Flowchart of the intelligent optical cable monitoring method provided by the present invention;

[0063] Figure 4 Flowchart of the optical cable monitoring and data analysis method provided by the present invention;

[0064] Figure 5 This is an architecture diagram of the optical cable status intelligent monitoring system provided by the present invention;

[0065] Figure 6 This is an architecture diagram of the intelligent optical cable monitoring system provided by the present invention;

[0066] Figure 7 This is an architecture diagram of the optical cable monitoring and data analysis system provided by the present invention. DETAILED DESCRIPTION

[0067] The present application is described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present application, but are not intended to limit the present application in any form. It should be noted that those skilled in the art may make several variations and improvements without departing from the scope of the present application. These all fall within the scope of protection of the present application.

[0068] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0069] It should be noted that, if there is no conflict, the various features in the embodiments of the present application can be combined with each other and are all within the scope of protection of the present application. In addition, although the functional modules are divided in the device schematic and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device or the order in the flow chart. In addition, the words "first", "second", "third", etc. used in this application do not limit the data and execution order, but only distinguish between the same items or similar items with basically the same functions and effects.

[0070] Unless otherwise defined, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs. The terms used in this specification and in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the relevant listed items.

[0071] Example 1

[0072] See also Figure 1-Figure 2 The present invention provides an embodiment of an optical cable status intelligent monitoring method, comprising the following specific steps:

[0073] Step S1: Real-time collection of optical cable related data, including optical cable structural parameters, optical signals, temperature and humidity, pressure, vibration and acceleration, etc.

[0074] The optical cable structural data includes: optical cable geometry, material properties, cable installation environment, cable type, and cable attenuation rate; the optical cable related data also includes: vibration monitoring, cable installation status, load conditions, etc.

[0075] The geometry of the optical cable includes: obtaining the length and diameter of the optical cable, the outer diameter of a single optical fiber, the wiring method of each optical fiber, the distance between the optical fiber and the protective layer, etc.; the material properties include: the refractive index of different optical fibers, the type of optical fiber (such as single-mode optical fiber, multi-mode optical fiber) and the optical transmission characteristics of the optical fiber (such as transmission loss, optical fiber transmission rate, etc.); the parameters of the laying environment include: the climatic conditions of the optical cable installation, temperature, humidity, geographical location, possible mechanical stress and other environmental factors; the attenuation rate of the optical cable: the attenuation coefficient of the optical fiber provided by the manufacturer, which can also be obtained by testing the loss of the optical fiber at different wavelengths.

[0076] Collecting optical signals specifically involves: Selecting a signal acquisition device: Using a high-precision fiber optic sensor (such as an optical time-domain reflectometer (OTDR)) to capture optical signals propagating along the optical cable. Optical signals typically include information such as wavelength, light intensity, delay, and phase; Signal acquisition timing: Sampling data regularly or upon specific events (such as a sudden load increase or temperature anomaly) to obtain accurate line status information; Data acquisition method: Using a synchronized acquisition system, multi-channel acquisition of optical signals of different wavelengths ensures comprehensive analysis of signals from different dimensions. The acquisition process is as follows: 1) Using the OTDR device to send optical pulses and monitor the reflected signal; 2) Recording the reflection intensity and delay at different locations to generate a time-domain reflectometry map; 3) Sampling the optical signal strength at different points along the transmission path, based on the distance of the transmission path.

[0077] Optical signal types include: optical reflection signal, optical attenuation signal and transmission delay.

[0078] Step S2: pre-processing the collected optical cable related data;

[0079] The preprocessing includes data cleaning, deduplication and standardization;

[0080] Data cleaning is the first step in data preprocessing, which removes invalid, duplicate, erroneous or incomplete data records. The cleaning process can be completed by setting rules, algorithms, manual intervention, etc., with the aim of improving data quality and ensuring the accuracy of subsequent analysis.

[0081] During data preprocessing, the same information may be stored repeatedly in different data sources. Data deduplication is achieved by identifying and removing duplicate records or redundant information to ensure that each piece of data appears only once, thereby reducing redundant storage and computing burden.

[0082] Standardization converts raw data from one format into another format that is more suitable for analysis and processing. For example, text data can be converted into structured data (such as JSON, XML, etc.), or unstructured data (such as logs, pictures, videos) can be converted into structured or semi-structured data. Through these conversion operations, data is easier to analyze and store.

[0083] Step S3: Calculate the status of the optical cable transmission line based on the pre-processed optical cable related data, generate a time domain reflectogram based on the optical signal of the optical cable, determine the location and severity of the optical cable damage, and evaluate the overall health status of the optical cable transmission line;

[0084] The specific steps of step S3 are:

[0085] Step S31: Calculating the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data;

[0086] The specific steps of step S31 are:

[0087] Step S311: The basic attenuation of the optical cable is determined by the material of the optical cable (such as glass or plastic) and the structure of the optical cable (such as the difference in refractive index between the optical cable core and cladding). The basic attenuation of the optical cable is calculated using the following formula:

[0088] A basic (d) = α0 × d,

[0089] Among them, A basic (d) represents the basic attenuation of the optical cable, α0 represents the basic attenuation coefficient of the optical cable, and d represents the length of the optical cable;

[0090] The basic attenuation coefficient α0 is usually a constant and can be obtained through technical data provided by the optical cable manufacturer or through experiments;

[0091] Step S312: When the optical cable is bent, the refractive index distribution of the optical cable changes, causing partial leakage of the optical signal and increasing attenuation. The bending loss formula of the optical cable is:

[0092]

[0093] Among them, A bend (d,R) represents the bending loss of the optical cable, α bend Indicates the bending loss coefficient of the optical cable, which is related to the material and bending angle of the optical cable. R represents the bending radius of the optical cable. When the optical cable is bent excessively, the loss will increase significantly.

[0094] Step S313: Calculate the optical signal attenuation loss of the optical cable transmission line. The specific formula is:

[0095]

[0096] Among them, A tatal (d, R, T) represents the optical signal attenuation loss of the optical cable transmission line, α temp It indicates the attenuation coefficient of the optical cable to temperature changes. It is usually a constant and can be obtained through experiments. T represents the current ambient temperature of the optical cable, and T0 represents the reference temperature, which is usually 25 degrees Celsius.

[0097] Step S32: Generate a time domain reflectogram based on the optical signal of the optical cable to determine the damage location and severity of the optical cable;

[0098] The specific steps of step S32 are:

[0099] Step S321: Calculate the intensity of the optical signal reflected by the optical cable. The specific formula is:

[0100]

[0101] Among them, S reflect represents the intensity of the optical signal reflected by the optical cable, log(·) represents the logarithmic function, and P send Indicates the transmitted optical signal power, P recv represents the power of the received reflected signal, e represents a natural constant, ΔS reflect (T) represents the change in reflected signal intensity caused by temperature, S da Indicates the change in reflected signal strength caused by damage to the optical cable transmission line, A joint Indicates the reflection loss of joints and connection points;

[0102] The principle of the above formula: The transmitted optical signal power P send It is usually provided by a light source or laser and is directly related to the light source intensity of the system. Due to factors such as cable damage, joints or bending, the optical signal will be reflected. Part of the optical signal is reflected and returned to the monitoring device. The received reflected signal power P recv It is an important basis for judging the status of optical fiber. Generally, the greater the reflection intensity, the more serious the damage or other problems. Comprehensively considering the impact of multiple factors on the optical signal can more accurately reflect the status of the optical cable transmission line. Through the comprehensive calculation of these factors, it can more carefully evaluate whether there are problems with the optical cable (such as damage, joint problems, excessive bending, etc.).

[0103] Step S322: constructing a time domain reflectometry graph with the propagation distance of the optical signal as the horizontal axis and the intensity of the optical signal reflected by the optical cable as the vertical axis;

[0104] A time domain reflectogram (OTDRTrace) is a graph of optical signal reflection data collected by an optical time domain reflectometer (OTDR). OTDR technology sends short pulses of optical signals and measures the time and intensity of the signals reflected from various locations on the optical cable. This helps locate problems such as damage, bends, and joint loss in the optical cable.

[0105] refer to Figure 2, where DamagePoint: a severely damaged reflection point, Bend: reflection caused by a minor bend, Joint Loss: loss reflection of the joint, Starting Point: the left side of the figure is the starting point where the OTDR starts testing, usually the point where the OTDR device is connected to the optical cable; Signal Attenuation Area: most of the area in the middle of the optical cable shows gradual attenuation, reflecting the signal propagation loss in the optical cable. This attenuation can be caused by factors such as the material, length and loss of the optical cable; Reflection Peak: If there is a joint, breakpoint or damage in the optical cable, the OTDR will display a reflection spike at the corresponding position. The height of the spike is proportional to the severity of the damage. Large reflection spike: usually indicates more serious problems such as fiber breakage and joint failure. Small reflection spike: may indicate minor damage, such as a slight bend or slight loss of the joint; End Reflection: There is usually a large reflection spike at the end of the optical cable, indicating that the light signal reaches the end of the optical fiber and is reflected back to the OTDR. There is a quantitative threshold for large reflection spikes and small reflection spikes, which can be set according to actual conditions.

[0106] Step S323: Calculate the location of the optical cable damage point based on the reflection time delay of the optical signal reflected from the optical cable. The specific formula is:

[0107]

[0108] Among them, x da Indicates the location of the optical cable damage point, c1 represents the speed of light, Δt represents the time delay of the reflected optical signal, usually recorded by an OTDR device, and n1 represents the refractive index of the optical cable;

[0109] Step S324: Establish an optical cable damage assessment model to assess the severity of optical cable damage. The specific formula is:

[0110]

[0111] in, Indicates the severity assessment value of optical cable damage, d da Indicates the distance from the optical cable damage point to the monitoring equipment. Considering the effect of distance on signal attenuation, η type The coefficient representing the type of optical cable damage describes the impact of the damage type on the severity. ΔT represents the temperature change, which affects the accuracy of damage assessment. α reflect , α dis , α type and α tem It represents the weight coefficient, which describes the proportion of each factor in the evaluation of the severity of optical cable loss and can be obtained through experiments;

[0112] In this embodiment, the coefficient η of the optical cable damage type is type, is set according to the specific type of injury, and the following classification standards can be used: η type =1, it shows as breakage and serious joint failure, η type = 0.5, it shows a slight mismatch of the joint, η type =0.1, it manifests as microbends and slight damage. Different types of damage will have different effects on the intensity of the reflected signal. For example, the reflection signal intensity generated by optical fiber breakage is larger, while the reflection signal intensity generated by connector mismatch or slight bending is smaller.

[0113] Step S325: Define the severity of the optical cable damage according to the optical cable damage severity assessment value. When it is less than 10, it is a minor damage, usually manifested as a minor joint loss or bending. When the value is greater than or equal to 10 and less than or equal to 30, it is considered moderate damage. When it is greater than 30, it is a serious injury.

[0114] Step S33: comprehensively considering the optical signal attenuation loss, the optical cable damage location and the damage severity assessment value, and establishing an overall status assessment model for the optical cable.

[0115] The specific steps of step S33 are:

[0116] Step S331: Establish an overall condition assessment model for the optical cable based on the optical signal attenuation loss, the optical cable damage location, and the damage severity assessment value. The specific formula is:

[0117]

[0118] in, represents the health status assessment value of the optical cable transmission line, n represents the number of sampling points of the optical cable transmission line, A total (d i ,R i ,T i ) represents the optical signal attenuation loss of the optical cable transmission line at the i-th sampling point, P recv (d i ) represents the power of the reflected signal received by the optical cable transmission line at the i-th sampling point, m represents the number of damage points, represents the damage severity assessment value at the jth damage point of the optical cable transmission line, (x da ,j) represents the position of the jth damage point;

[0119] The principle behind the above formula is that the health status of an optical cable transmission line is calculated through weighted averaging based on the effects of various physical phenomena (such as bending loss, temperature changes, and damage reflections) on the optical signal. The cable length d is used to normalize the entire optical cable line to eliminate the impact of line length differences on the status calculation. The longer the optical cable, the greater the cumulative loss and reflection. Therefore, the total length d ensures that the comprehensive status parameters remain comparable across different line lengths. To obtain an accurate fiber status assessment, measurements are usually performed at multiple points, recording information such as loss, temperature, and bend radius at each point, and then calculating the impact of the status at that point on the entire fiber.

[0120] The formula calculates the health status assessment value of the optical cable transmission line by comprehensively considering the transmission distance, temperature change, bending loss, basic attenuation and damage reflection signal of the optical cable, combined with the information of the sampling point. Each factor has a different weight on the final result, and the overall assessment value of the optical fiber status is obtained through weighted summation.

[0121] Step S332: Set the cable health threshold to like Greater than the optical cable health threshold When the optical cable transmission line is faulty or damaged, it is determined that there is a fault or damage in the optical cable transmission line.

[0122] Example 2

[0123] See also Figure 3 The present invention provides an embodiment of an intelligent optical cable monitoring method, comprising the following specific steps:

[0124] Step 1: Real-time collection of optical cable related data, including cable structural parameters, optical signals, temperature and humidity, pressure, vibration, acceleration, etc.

[0125] The optical cable structural data includes: optical cable geometry, material properties, cable installation environment, optical fiber type and cable attenuation rate; the optical cable related data also includes: vibration monitoring, cable installation status, load conditions, etc.

[0126] The geometry of the optical cable includes: obtaining the length and diameter of the optical cable, the outer diameter of a single optical fiber, the wiring method of each optical fiber, the distance between the optical fiber and the protective layer, etc.; the material properties include: the refractive index of different optical fibers, the type of optical fiber (such as single-mode optical fiber, multi-mode optical fiber) and the optical transmission characteristics of the optical fiber (such as transmission loss, optical fiber transmission rate, etc.); the parameters of the laying environment include: the climatic conditions of the optical cable installation, temperature, humidity, geographical location, possible mechanical stress and other environmental factors; the attenuation rate of the optical cable: the attenuation coefficient of the optical fiber provided by the manufacturer, which can also be obtained by testing the loss of the optical fiber at different wavelengths.

[0127] Collecting optical signals specifically involves: Selecting a signal acquisition device: Using a high-precision fiber optic sensor (such as an optical time-domain reflectometer (OTDR)) to capture optical signals propagating along the optical cable. Optical signals typically include information such as wavelength, light intensity, delay, and phase; Signal acquisition timing: Sampling data regularly or upon specific events (such as a sudden load increase or temperature anomaly) to obtain accurate line status information; Data acquisition method: Using a synchronized acquisition system, multi-channel acquisition of optical signals of different wavelengths ensures comprehensive analysis of signals from different dimensions. The acquisition process is as follows: 1) Using the OTDR device to send optical pulses and monitor the reflected signal; 2) Recording the reflection intensity and delay at different locations to generate a time-domain reflectometry map; 3) Sampling the optical signal strength at different points along the transmission path, based on the distance of the transmission path.

[0128] Optical signal types include: optical reflection signal, optical attenuation signal and transmission delay.

[0129] Step 2: Preprocess the collected optical cable related data;

[0130] The preprocessing includes data cleaning, deduplication and standardization;

[0131] Data cleaning is the first step in data preprocessing, which removes invalid, duplicate, erroneous or incomplete data records. The cleaning process can be completed by setting rules, algorithms, manual intervention, etc., with the aim of improving data quality and ensuring the accuracy of subsequent analysis.

[0132] During data preprocessing, the same information may be stored repeatedly in different data sources. Data deduplication is achieved by identifying and removing duplicate records or redundant information to ensure that each piece of data appears only once, thereby reducing redundant storage and computing burden.

[0133] Standardization converts raw data from one format into another format that is more suitable for analysis and processing. For example, text data can be converted into structured data (such as JSON, XML, etc.), or unstructured data (such as logs, pictures, videos) can be converted into structured or semi-structured data. Through these conversion operations, data is easier to analyze and store.

[0134] Step 3: Based on the pre-processed optical cable data and the health assessment results of the optical cable transmission line, an optical cable fault identification model is established to determine the abnormal conditions and types of abnormalities in the optical cable and predict the fault conditions within a preset time period.

[0135] The specific steps of step 3 are:

[0136] Step 31: extracting features of the pre-processed optical cable related data;

[0137] The specific steps of step 31 are:

[0138] Step 311: Extract the time domain features of the pre-processed optical cable related data, including: the change rate of optical cable transmission loss ΔA(t), the maximum value of optical signal intensity fluctuation V max (t) and minimum value V min (t);

[0139] Specifically, the specific formula for the rate of change of optical cable transmission loss ΔA(t) is: ΔA(t) = A total (d,R,T,t)-A total (d,R,T,t-1), where A tatal (d, R, T, t) represents the optical signal attenuation loss of the optical cable transmission line at time t, A tatal (d, R, T, t-1) represents the optical signal attenuation loss of the optical cable transmission line at time t-1, and the maximum value of the optical signal intensity fluctuation V max (t) and minimum value V min The specific formula for (t) is: max (t) = max(P signal (t)-pj(P signal )), V min (t) = min(P signal (t)-pj(P signal )), where max(·) represents the maximum value function, min(·) represents the minimum value function, and P signal (t) represents the optical signal intensity at time t, pj(P signal ) represents the average value of the optical signal intensity over a period of time.

[0140] Step 312: extracting frequency domain features of the pre-processed optical cable related data, including: spectrum features of the optical signal and frequency response and resonance features of the optical signal;

[0141] The frequency components of signals transmitted through optical cables can be analyzed using Fourier transforms. Characteristic frequency points in the spectrum (such as fundamental frequency and harmonic frequencies) can provide valuable information, such as signal distortion, nonlinear effects, or other physical damage. Abnormal frequency components in the spectrum may indicate a fault in the optical fiber or equipment. Environmental factors (such as temperature and humidity changes) may cause changes in the physical properties of optical cables, resulting in changes in the frequency response of optical signals. By comparing the spectral differences between the input and output signals, the signal attenuation characteristics, transmission loss, and whether there are any abnormal frequency responses can be analyzed. This is very effective for detecting possible damage to the optical cable or the influence of environmental factors.

[0142] Step 313: extracting frequency characteristics of the pre-processed optical cable related data, including instantaneous frequency f(t);

[0143] The instantaneous frequency of the optical signal is extracted using the Hilbert transform, which can reflect the frequency change of the optical signal over time. It is applicable to nonlinear distortion caused by vibration or external interference during optical cable transmission. The instantaneous frequency f(t) is the frequency component of the optical signal at time t. The specific formula is: Represents the complex signal after Hilbert transform, which contains the original optical signal P sign The real part of (t) and the imaginary part produced by the Hilbert transform, Represents a complex signal The phase angle, Indicates the rate of change of phase angle. Derivative with respect to time t;

[0144] Instantaneous frequency principle: Instantaneous frequency is defined by solving the rate of change of the signal's phase angle. Specifically, the rate at which the phase angle changes with time is the instantaneous frequency. Since optical fiber signals may be affected by environmental changes, damage, noise and other factors during propagation, these factors will cause fluctuations in the instantaneous frequency. Therefore, by analyzing the instantaneous frequency, signal anomalies or potential faults can be detected. By calculating the instantaneous frequency of a complex signal, nonlinear distortion, frequency drift caused by vibration, external interference and other problems in the optical fiber transmission process can be identified.

[0145] Step 314: Fusing the extracted features to obtain a fused feature vector F(t) of the optical cable related data.

[0146] Step 32: Based on deep learning and the historical data set of optical cables, establish an optical cable fault identification model and train the optical cable fault identification model;

[0147] It should be explained that the historical data set of optical cables here has been processed, that is, each piece of data has been labeled accordingly;

[0148] Step 321: Select a deep learning algorithm to build an optical cable fault recognition model. Use the historical data set of optical cables to train the optical cable fault recognition model. Set the training objective of the model to minimize the loss function. The formula of the loss function is:

[0149]

[0150] Where Γ represents the loss function, y a Indicates the label of the ath data in the historical data set of the annotated optical cable, that is, whether a fault occurs at the time corresponding to the data. represents the prediction result of the optical cable fault identification model for the ath data, xl represents the number of data in the historical data set with annotated optical cables, Represents the category weight of the a-th data, which is used to deal with category imbalance. For example, if a certain category has fewer samples, it can be given a higher weight;

[0151] Cross-entropy loss is a common method for measuring the difference between two probability distributions. In classification problems, it evaluates the distance between the predicted distribution of the model output and the true distribution. Weights are introduced to balance the impact of class imbalance. In many real-world applications, some classes may have significantly fewer samples than other classes, causing the model to favor the dominant class. By assigning higher weights to minority class samples, the model can place greater emphasis on these samples during training, thereby improving its predictive performance. The goal of minimizing this loss function is to adjust the model parameters through iterative optimization (such as gradient descent) so that the prediction results are closer to the true label. This approach not only improves model accuracy but also enhances the ability to identify minority class faults.

[0152] Step 322: Train the optical cable fault recognition model until the minimization loss function of the model's training objective converges and remains unchanged, then stop training to obtain a trained optical cable fault recognition model.

[0153] The historical data set of optical cables includes normal data and fault data.

[0154] Step 33: Use the trained optical cable fault identification model and the health assessment results of the optical cable transmission line to perform real-time detection of optical cable transmission faults.

[0155] The specific steps of step 33 are:

[0156] Step 331: Input the fused feature vector F(t) of the optical cable related data into the trained optical cable fault identification model to calculate the preliminary fault identification probability during optical cable transmission. The specific formula is:

[0157]

[0158] Among them, P flaut (t,y=c|F(t)) represents the probability of the cth type fault occurring at time t given the feature vector F(t), W c represents the weight associated with category c, b c represents the bias term associated with category c, m1 represents the total number of fault categories, exp(·) represents the exponential function, and W e1 represents the weight associated with category e1, b e1 represents the bias term related to category e1, and y represents the fault category;

[0159] Step 332: Taking into account the health assessment results of the optical cable transmission line and the influence of external environmental factors, the fault identification probability during optical cable transmission is calculated. The specific formula is:

[0160]

[0161] Among them, P flaut (t) represents the fault identification probability during optical cable transmission at time t, β1, β2, and β3 represent weight coefficients, which are used to control the influence of each factor in the comprehensive decision-making, and φ(t) represents the environmental influence factor at time t, which is used to describe the influence of environmental factors (such as temperature, humidity, pressure, etc.) on the probability of fault occurrence. represents the health status assessment value of the optical cable transmission line at time t;

[0162] Explanation and principle of the above formula: The specific formula of the environmental impact factor φ(t) at time t is: Among them, δ represents the adjustment factor of environmental impact, which is used to adjust the degree of influence of environmental factors in comprehensive decision-making, H represents the number of environmental impact factors, and Hj h It represents the influence function of the change of the hth environmental factor on the occurrence of optical cable fault. For example, the specific formula of the temperature influence function is: Among them, Hj wd represents the temperature influence function, α T It represents the temperature sensitive parameter, which controls the influence of temperature on the probability of failure. T(t) represents the temperature of the environment where the optical cable is located at time t. threshold Represents the temperature threshold, which is a reference temperature. The effect of temperature on optical cables is nonlinear. Too high or too low a temperature may cause optical cables to fail. The specific formula for the humidity impact function is: Among them Hj sd represents the humidity influence function, α Hs Represents the humidity sensitive parameter, which controls the intensity of the impact of humidity on the probability of failure. Hs env (t) represents the humidity of the environment where the optical cable is located at time t, Hs threshold Indicates the humidity threshold, which is a benchmark humidity. Humidity is one of the important factors affecting optical cable materials and equipment. Excessive humidity can cause corrosion of optical cable connection points, deterioration of the insulation layer, and other problems, indirectly leading to optical cable failure.

[0163] Through external environmental influencing factors, it can automatically adjust the response strategy, identify and adapt to the impact of environmental factors on the probability of fault occurrence, combine health status assessment and fault identification model, and through multi-dimensional data fusion (such as sensor data, historical fault data, environmental factors, etc.), it can more comprehensively reflect the status of the optical cable, rather than simply relying on a single fault identification technology.

[0164] Step 333: Select P flaut The fault category corresponding to the maximum value of (t) is taken as the fault category of the optical cable.

[0165] Step 34: Based on the fault detection, predict the fault condition of the optical cable within a preset time.

[0166] Example 3

[0167] See also Figure 4 The present invention provides an embodiment of a method for monitoring and analyzing optical cables, comprising the following specific steps:

[0168] Step A1: Real-time collection of optical cable related data, including structural parameters, optical signals, temperature and humidity, pressure, vibration, acceleration, transmission data, and load data of the optical cable;

[0169] The optical cable structural data includes: optical cable geometry, material properties, cable installation environment, optical fiber type and cable attenuation rate; the optical cable related data also includes: vibration monitoring, cable installation status, load conditions, etc.

[0170] The geometry of the optical cable includes: obtaining the length and diameter of the optical cable, the outer diameter of a single optical fiber, the wiring method of each optical fiber, the distance between the optical fiber and the protective layer, etc.; the material properties include: the refractive index of different optical fibers, the type of optical fiber (such as single-mode optical fiber, multi-mode optical fiber) and the optical transmission characteristics of the optical fiber (such as transmission loss, optical fiber transmission rate, etc.); the parameters of the laying environment include: the climatic conditions of the optical cable installation, temperature, humidity, geographical location, possible mechanical stress and other environmental factors; the attenuation rate of the optical cable: the attenuation coefficient of the optical fiber provided by the manufacturer, which can also be obtained by testing the loss of the optical fiber at different wavelengths.

[0171] Collecting optical signals specifically involves: Selecting a signal acquisition device: Using a high-precision fiber optic sensor (such as an optical time-domain reflectometer (OTDR)) to capture optical signals propagating along the optical cable. Optical signals typically include information such as wavelength, light intensity, delay, and phase; Signal acquisition timing: Sampling data regularly or upon specific events (such as a sudden load increase or temperature anomaly) to obtain accurate line status information; Data acquisition method: Using a synchronized acquisition system, multi-channel acquisition of optical signals of different wavelengths ensures comprehensive analysis of signals from different dimensions. The acquisition process is as follows: 1) Using the OTDR device to send optical pulses and monitor the reflected signal; 2) Recording the reflection intensity and delay at different locations to generate a time-domain reflectometry map; 3) Sampling the optical signal strength at different points along the transmission path, based on the distance of the transmission path.

[0172] Optical signal types include: optical reflection signal, optical attenuation signal and transmission delay.

[0173] Step A2: pre-processing the collected optical cable related data;

[0174] The preprocessing includes data cleaning, deduplication and standardization;

[0175] Data cleaning is the first step in data preprocessing, which removes invalid, duplicate, erroneous or incomplete data records. The cleaning process can be completed by setting rules, algorithms, manual intervention, etc., with the aim of improving data quality and ensuring the accuracy of subsequent analysis.

[0176] During data preprocessing, the same information may be stored repeatedly in different data sources. Data deduplication is achieved by identifying and removing duplicate records or redundant information to ensure that each piece of data appears only once, thereby reducing redundant storage and computing burden.

[0177] Standardization converts raw data from one format into another format that is more suitable for analysis and processing. For example, text data can be converted into structured data (such as JSON, XML, etc.), or unstructured data (such as logs, pictures, videos) can be converted into structured or semi-structured data. Through these conversion operations, data is easier to analyze and store.

[0178] Step A3: Analyze the pre-processed optical cable related data, combine the fault prediction results of the optical cable transmission line and the optical cable fault detection results, allocate the transmitted optical signal data to the optical cable, and make an optimization decision on the operating status of the optical cable transmission line.

[0179] The specific steps of step A3 are:

[0180] Step A31: Allocate the transmitted optical signal data to the optical cable and select the optimal optical cable transmission channel;

[0181] The specific steps of step A31 are:

[0182] Step A311: Set the set of transmission channels for optical signal data transmission in the optical cable to L, where L = {l1, l2, ..., l o}, l o Indicates the oth transmission channel of optical signal data transmission in the optical cable;

[0183] Step A312: Calculate the priority of the oth transmission channel using the following formula:

[0184]

[0185] Among them, YX o Indicates the priority of the oth transmission channel, eff indicates the signal quality indicator. The better the signal quality, the higher the channel priority. rl represents the capacity adjustment factor, reflecting the impact of channel capacity on priority, r represents the historical transmission rate. The higher the rate, the higher the priority. e represents the natural constant. sjl represents the amount of optical signal data. Z fsIndicates the period from optical signal data to the target receiving device. It reflects the impact of data volume and transmission cycle on priority. The larger the data volume and the shorter the cycle, the higher the priority. κ represents the penalty factor, fz o represents the load of the oth transmission channel, fz o_max represents the maximum load of the oth transmission channel, max(·) represents the maximum value function, The penalty part indicates that when the channel load is too high, its priority is reduced. These factors are comprehensively evaluated to evaluate the channel priority and achieve the optimal channel selection;

[0186] The principle behind the above formula is that the better the signal quality of the transmission channel, the higher the priority. Channel quality can be measured by transmission rate ratio, transmission time, and penalty. By evaluating the priority of each channel, transmission channels and computing resources can be reasonably allocated among multiple communication channels, ensuring that critical tasks receive priority processing, improving the overall transmission quality of the system, and reducing packet loss and latency.

[0187] Step A313: Take max(YX o ) corresponding transmission channel serves as the optimal optical cable transmission channel for sending optical signal data to the target receiving device.

[0188] Step A32: monitoring the load of the optical cable transmission line in real time;

[0189] The load of the optical cable transmission line at time t is calculated based on the voltage of the optical cable transmission line at time t, the current of the optical cable transmission line at time t, the phase difference between the voltage and current of the optical cable transmission line at time t, the temperature difference of the optical cable transmission line at time t, and the health status assessment value of the optical cable transmission line at time t. The calculation formula of the load of the optical cable transmission line is:

[0190]

[0191] Among them, U realtime (t) represents the load of the optical cable transmission line at time t, V(t) represents the voltage of the optical cable transmission line at time t, I(t) represents the current of the optical cable transmission line at time t, ι(t) represents the phase difference between the voltage and current of the optical cable transmission line at time t, γ dz represents the temperature coefficient of resistance, T1(t) represents the temperature of the optical cable transmission line at time t, T0 represents the reference temperature, It represents the health status assessment value of the optical cable transmission line at time t.

[0192] The principle of the above formula: Through this comprehensive formula, the real-time load of the optical cable transmission line under different environmental conditions and health status can be accurately calculated. This formula not only takes into account the electrical parameters, but also incorporates the influence of temperature and health status into the calculation, thereby improving the accuracy and reliability of the load calculation. Here, the load of the optical cable transmission line and the load of the transmission channel are not the same concept. One is the data transmission load, and the other is the electrical-related load.

[0193] Step A33: intelligently optimizing the load distribution of the optical cable transmission line according to the health status evaluation value, fault prediction result, and real-time load of the optical cable transmission line;

[0194] The specific steps of step A33 are:

[0195] Step A331: Set the load of the u-th optical cable transmission line to U realtime,u (t), the maximum load capacity is The health status assessment value is Construct an overall efficiency model of optical cable transmission lines;

[0196] Step A332: Set the objective function of the overall efficiency model of the optical cable transmission line. The specific formula is:

[0197]

[0198] Among them, load (t) represents the objective function of the overall efficiency model of the optical cable transmission line. The goal is to minimize this value, which indicates the degree of optimization of the load, that is, the overall efficiency of the optical cable transmission line. The function represents the healthy load of the u-th optical cable transmission line at time t. It dynamically adjusts the safety load based on the health status of each optical cable transmission line to avoid safety issues caused by line failures. It is a function derived from health assessment and reflects the impact of health status on the maximum load. us represents the number of optical cable transmission lines, and θ is an adjustment factor that determines the degree of influence of load safety on the objective function. The introduction of this factor makes load safety an important weight in the optimization objective.

[0199] Principle and parameter analysis of the above formula: 1) Balanced load Reflects the balance of load distribution. Specifically, this item represents the ratio of the actual load of the u-th optical cable transmission line to its maximum load capacity. The smaller the ratio, the less overloaded the optical cable transmission line is and the load is evenly distributed. The larger the ratio, the closer the load is to its maximum load capacity and the more unbalanced the load distribution is. The optimization goal is to adjust the load distribution so that the load of each optical cable transmission line is as close to its maximum load capacity as possible without exceeding its load limit. 2) Safe load limit Used to measure the security of load distribution. Specifically, It is a dynamically adjusted upper limit of the safe load based on the health status and environmental factors of the optical cable transmission line. When the health status of the optical cable transmission line deteriorates, the value will decrease, reflecting the decrease in the load bearing capacity of the optical cable transmission line. The purpose of this item is to avoid excessive loading on lines with poor health, thereby preventing the optical cable transmission line from failing or being damaged. 3) The adjustment factor θ is used to make a trade-off between load balance and safety. Specifically, when θ is small (for example, close to zero), the objective function focuses on load balance, that is, trying to make the load ratio of all optical cable transmission lines close to the maximum value, ignoring safety. When θ is large, the objective function pays more attention to safety, that is, avoiding allocating too much load to optical cable transmission lines with poor health, even if this may lead to unbalanced load distribution. Therefore, adjusting the value of θ can flexibly control the optimization objectives of the system and balance the relationship between load balance and safety.

[0200] In general, through This item makes the load of each optical cable transmission line as close to the maximum carrying capacity as possible, thus achieving load balancing of the system; This item dynamically adjusts load distribution to avoid overburdening lines in poor health and ensure safe system operation. Through the θ adjustment factor, the balance between load balancing and safety can be flexibly adjusted to achieve optimization goals for different application scenarios.

[0201] Step A333: Set the constraint conditions. The specific formula is:

[0202]

[0203] Among them, U total (t) represents the total load demand. The total load distribution should meet the power supply demand of the system, that is, the sum of the loads of all optical cable transmission lines is equal to the total demand;

[0204] Step A334: Solve the overall efficiency model of the optical cable transmission line through the objective function and the constraint conditions to obtain the optimal load distribution and the highest overall efficiency of the optical cable transmission line.

[0205] Step A34: Intelligently schedule maintenance and overhaul work.

[0206] Intelligent scheduling of maintenance and overhaul work aims to intelligently schedule maintenance and overhaul work based on fault prediction results and the health status of optical cable transmission lines, thereby minimizing downtime and operation and maintenance costs. The optimization goal is to balance maintenance costs and system uptime to ensure efficient and low-risk maintenance.

[0207] In this embodiment, load balancing and maintenance scheduling optimization are the two core functions of the intelligent decision-making and optimization layer. They complement each other and jointly improve the overall performance of the system. In practical applications, these two optimization processes can be integrated and coordinated. Specifically, load balancing can be combined with maintenance scheduling information to avoid frequent downtime for overloaded lines, thereby reducing operation and maintenance costs and the risk of failures.

[0208] Example 4

[0209] See also Figure 5-Figure 7 , another embodiment provided by the present invention: an optical cable status intelligent monitoring system, comprising: a data acquisition module, a data preprocessing module, a status evaluation module, a fault detection module and a data analysis and decision module;

[0210] The data acquisition module is used to collect optical cable related data in real time;

[0211] The data preprocessing module is used to preprocess the collected optical cable related data;

[0212] The status assessment module is used to calculate the status of the optical cable transmission line based on the pre-processed optical cable related data, generate a time domain reflectogram based on the optical signal of the optical cable, determine the location and severity of optical cable damage, and evaluate the overall health status of the optical cable transmission line;

[0213] A state assessment module includes: an attenuation loss calculation unit, a damage judgment unit, and an overall state assessment unit;

[0214] The attenuation loss calculation unit is used to calculate the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data;

[0215] The damage judgment unit is used to generate a time domain reflection diagram based on the optical signal of the optical cable to judge the damage location and damage severity of the optical cable;

[0216] The overall status evaluation unit is used to comprehensively consider the optical signal attenuation loss, the optical cable damage position and the damage severity evaluation value to establish an overall status evaluation model for the optical cable.

[0217] Damage judgment unit, including: loss location calculation subunit and loss severity assessment subunit;

[0218] The loss position calculation subunit is used to calculate the position of the optical cable damage point based on the reflection time delay of the optical signal reflected by the optical cable;

[0219] The loss severity assessment subunit is used to establish an optical cable damage assessment model and assess the severity of optical cable damage.

[0220] The fault detection module is used to establish an optical cable fault identification model based on the pre-processed optical cable related data and the health assessment results of the optical cable transmission line, determine the abnormal conditions and abnormality types of the optical cable, and predict the fault conditions of the optical cable within a preset time;

[0221] Fault detection module, including feature extraction unit, model training unit, fault detection unit and prediction unit;

[0222] The feature extraction unit is used to extract features of the pre-processed optical cable related data;

[0223] The model training unit is used to establish an optical cable fault identification model based on deep learning and a historical data set of optical cables, and to train the optical cable fault identification model;

[0224] The fault detection unit is used to use the trained optical cable fault identification model and the health assessment results of the optical cable transmission line to perform real-time detection of faults during optical cable transmission;

[0225] The prediction unit is used to predict the fault condition of the optical cable within a preset time based on the fault detection.

[0226] The fault detection unit includes: a preliminary fault identification subunit and a fault identification subunit;

[0227] The preliminary fault identification subunit is used to calculate the preliminary fault identification probability during optical cable transmission using the trained optical cable fault identification model;

[0228] The fault identification subunit is used to comprehensively consider the health assessment results of the optical cable transmission line and the influence of external environmental factors to calculate the fault identification probability during optical cable transmission.

[0229] The data analysis and decision-making module is used to analyze the pre-processed optical cable related data, combine the fault prediction results and optical cable fault detection results of the optical cable transmission line, allocate the transmitted optical signal data to the optical cable, and make optimization decisions on the operating status of the optical cable transmission line.

[0230] Data analysis and decision-making module, including: channel optimization unit, load calculation unit, load intelligent distribution unit and intelligent scheduling unit;

[0231] The channel optimization unit is used to calculate and select the optimal transmission channel for optical signal data transmission;

[0232] The load calculation unit is used to calculate the real-time load of the optical cable transmission line;

[0233] The load intelligent distribution unit is used to solve the overall efficiency model of the optical cable transmission line to obtain the optimal load distribution and the highest overall efficiency of the optical cable transmission line;

[0234] The intelligent scheduling unit is used for intelligently scheduling the maintenance and inspection of optical cables.

[0235] The load intelligent distribution unit includes: a modeling subunit, an objective function subunit, a constraint subunit and a solution subunit;

[0236] The modeling subunit is used to build an overall efficiency model of the optical cable transmission line based on the health status evaluation value, fault prediction result and real-time load of the optical cable transmission line;

[0237] The objective function subunit is used to set the objective function of the overall efficiency model of the optical cable transmission line;

[0238] The constraint subunit is used to set the constraint conditions of the overall efficiency model of the optical cable transmission line;

[0239] The solving subunit is used to solve the overall efficiency model of the optical cable transmission line through the objective function and constraint conditions.

[0240] In addition, the parts of the above technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive redundancy.

[0241] The above-described specific embodiments further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is merely a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for intelligent monitoring of optical cable status, characterized in that: include: Real-time collection of optical cable related data, including cable structural parameters and optical signals; Preprocess the collected optical cable related data; The status of the optical cable transmission line is calculated based on the pre-processed optical cable data. Based on the optical signal of the optical cable, a time domain reflectogram is generated to determine the location and severity of optical cable damage and evaluate the overall health of the optical cable transmission line. Generating a time domain reflectogram based on the optical signal of the optical cable to determine the damage location and severity of the optical cable includes: The intensity S of the optical signal reflected from the optical cable is calculated based on the transmitted optical signal power, the received reflected signal power, the change in reflected signal intensity caused by temperature, the change in reflected signal intensity caused by damage to the optical cable transmission line, and the reflection loss at the joints and connection points. reflect ; With the propagation distance of the optical signal as the horizontal axis, the intensity S of the optical signal reflected by the optical cable is reflect As the vertical axis, a time domain reflectogram is constructed and the damage point is determined according to the time domain reflectogram; Calculate the position x of the optical cable damage point based on the reflection time delay of the optical signal reflected by the optical cable, the refractive index of the optical cable and the speed of light. da ; Establish an optical cable damage assessment model to assess the severity of optical cable damage. Perform weighted summation on the intensity of the optical cable reflected light signal, the distance from the optical cable damage point to the monitoring equipment, the coefficient of the optical cable damage type, and the temperature change to obtain the optical cable damage severity assessment value. The severity of optical cable damage is defined according to the optical cable damage severity assessment value. When it is less than 10, it is a slight damage. When the value is greater than or equal to 10 and less than or equal to 30, it is considered moderate damage. When it is greater than 30, it is a serious injury; Taking into account the optical signal attenuation loss, the location of the optical cable damage, and the damage severity assessment value, an overall condition assessment model for the optical cable is established, including: According to the optical signal attenuation loss, optical cable damage location and damage severity assessment value, the overall condition assessment model of the optical cable is established to obtain the health status assessment value of the optical cable transmission line. Set the cable health threshold to like Greater than the optical cable health threshold When the optical cable transmission line is faulty or damaged, it is determined that there is a fault or damage in the optical cable transmission line.

2. The optical cable status intelligent monitoring method according to claim 1, characterized in that: The method of calculating the status of the optical cable transmission line based on the pre-processed optical cable related data, generating a time domain reflectogram based on the optical signal of the optical cable, determining the location and severity of damage to the optical cable, and evaluating the overall health status of the optical cable transmission line specifically includes: Calculate the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data; Generate a time domain reflectogram based on the optical signal of the optical cable to determine the location and severity of the damage to the optical cable; An overall status assessment model for optical cables is established by comprehensively considering the optical signal attenuation loss, optical cable damage location, and damage severity assessment value.

3. The optical cable status intelligent monitoring method according to claim 2, characterized in that: The calculating of the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data includes: The basic attenuation of the optical cable is determined by the material and structure of the optical cable. The basic attenuation A of the optical cable is calculated. basic (d), d represents the length of the optical cable; When the optical cable is bent, the refractive index distribution of the optical cable will change, causing partial leakage of the optical signal and increasing attenuation. The bending loss of the optical cable is A bend (d, R), R represents the bending radius of the optical cable; Calculate the optical signal attenuation loss A of the optical cable transmission line based on the basic attenuation, bending loss and temperature loss of the optical cable. tatal (d, R, T), where T represents the current ambient temperature of the optical cable.

4. The optical cable status intelligent monitoring method according to claim 3, characterized in that: The structural data of the optical cable includes: the geometric shape and material properties of the optical cable, the laying environment of the optical cable, the type of the optical cable and the attenuation rate of the optical cable.

5. The optical cable status intelligent monitoring method according to claim 4, characterized in that: The preprocessing includes: data cleaning, deduplication and standardization; The data cleaning includes removing invalid, duplicate, erroneous or incomplete data records; The data deduplication, identifying and removing duplicate records or redundant information; Normalization converts raw data from one format into another for analysis and processing.

6. An optical cable status intelligent monitoring system, used to implement an optical cable status intelligent monitoring method according to any one of claims 1 to 5, characterized in that: include: Data acquisition module, data preprocessing module and status assessment module; The data acquisition module is used to collect optical cable related data in real time, including structural parameters and optical signals of the optical cable; The data preprocessing module is used to preprocess the collected optical cable related data; The status assessment module is used to calculate the status of the optical cable transmission line based on the preprocessed optical cable related data, generate a time domain reflectogram based on the optical signal of the optical cable, determine the location and severity of optical cable damage, and evaluate the overall health status of the optical cable transmission line.

7. The optical cable status intelligent monitoring system according to claim 6, characterized in that: The state assessment module includes: an attenuation loss calculation unit, a damage judgment unit and an overall state assessment unit; The attenuation loss calculation unit is used to calculate the optical signal attenuation loss of the optical cable transmission line based on the pre-processed optical cable related data; The damage judgment unit is used to generate a time domain reflection diagram based on the optical signal of the optical cable to judge the damage location and damage severity of the optical cable; The overall status evaluation unit is used to comprehensively consider the optical signal attenuation loss, the optical cable damage position and the damage severity evaluation value to establish an overall status evaluation model for the optical cable.

8. The optical cable status intelligent monitoring system according to claim 7, characterized in that: The damage judgment unit includes: a loss location calculation subunit and a loss severity assessment subunit; The loss position calculation subunit is used to calculate the position of the optical cable damage point based on the reflection time delay of the optical signal reflected by the optical cable; The loss severity assessment subunit is used to establish an optical cable damage assessment model and assess the severity of optical cable damage.

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