Fiber core on-line rapid monitoring system based on time division and space division multiplexing

Abstract

The invention belongs to the technical field of optical fibers, and particularly relates to a fiber core on-line rapid monitoring system based on time division and space division multiplexing, which comprises an OTDR function support module which works by emitting optical pulses and analyzing returned scattering and reflection signals, is internally provided with an OTDR communication module, uploads various data processed by an MCU to a cloud end, and sends the data to the cloud end; and the cloud end can perform secondary calculation learning and analysis on various data or directly display the data on the server platform. A high-precision instrument for testing the characteristics of an optical fiber network is used for emitting optical pulses and analyzing returned scattering and reflection signals, the optical signals are monitored on line, various parameters influencing the change of the optical signals are substituted into an algorithm module, and the change of the various parameters is combined with the influence of the algorithm module on the optical signals, so that the detection accuracy of the optical fiber network is improved. Therefore, the software unit can perform health assessment and fault prediction, and test and fault diagnosis tasks of the optical fiber network can be accurately and efficiently completed.

Description

Technical Field

[0001] The invention relates to the field of optical fiber technology, and in particular to an online fast monitoring system for optical fiber cores based on time-division and space-division multiplexing. Background Art

[0002] The fiber core online fast monitoring technology is based on the OTDR optical time domain reflectometer, combined with time division multiplexing and space division multiplexing technology, and achieves efficient real-time monitoring by allocating the monitoring tasks of multiple fiber cores to different time periods and spatial locations.

[0003] The current existing patent (publication number: CN118464378A) discloses a method and system for online rapid monitoring of fiber cores based on time-division and space-division multiplexing. The test data involved in this patent will be automatically uploaded to the central control center platform, which can automatically collect and analyze monitoring data, provide accurate early warning and prediction functions, so that the system can better adapt to the needs of new power systems and improve the intelligence level of power systems. However, the above patent does not provide a detailed description of the changes in optical signal monitoring. When different changes occur in the optical signal, it is necessary to combine parameters for accurate judgment. The above patent cannot complete health assessment and fault prediction for the changes in the optical signal of the core in time, which leads to a certain lag in its early warning and prediction functions.

[0004] Therefore, it is necessary to provide a fiber core online rapid monitoring system based on time division and space division multiplexing to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an online rapid monitoring system for the fiber core based on time-division and space-division multiplexing, which can further timely perform health assessment and fault prediction on the optical fiber, and can accurately and efficiently complete the testing and fault diagnosis tasks of the optical fiber network.

[0006] The present invention provides a fiber core online fast monitoring system based on time division and space division multiplexing, which includes the following: OTDR (Optical Time Domain Reflectometer) Function Support Module: It works by emitting light pulses and analyzing the returned scattered and reflected signals. It has a built-in OTDR communication module, which uploads the processed data from the MCU (single-chip microcomputer) to the cloud, where the cloud can perform secondary calculations, learning and analysis on the data or directly display them on the server platform; Algorithm module: The algorithm parameters in the algorithm module include: dynamic range, blind area, reflected light, attenuation blind area, pulse width, sampling resolution, sampling point and pulse noise response; MEMS optical switch (optical path switching device) module: including MEMS micromechanical structure, drive circuit, optical input and output ports, optical elements, packaging and alignment module, control and feedback circuit and heat dissipation module; Software unit: including: data receiving module, data cleaning module, data analysis module, optical cable health status assessment and fault prediction module, display module and alarm module; The real-time status of each optical fiber section is displayed through the graphical interface of the display module, including optical attenuation trend graph, health score, and fault risk prompt.

[0007] Preferably, the OTDR function support module includes: a laser light source, a pulse generator, a directional coupler, a light detector, an amplifier, a data analysis and display unit and a microcontroller unit.

[0008] Preferably, an OTDR (optical time domain reflectometer) function support module generates light pulses of a specific wavelength by a laser light source for injection into the optical fiber, uses a laser diode as a light source to generate light pulses of a specific wavelength, controls the time of emitting the light pulses from the light source by a pulse generator, ensures synchronization with the data analysis and display circuit, couples the light emitted by the light source to the optical fiber under test by a directional coupler, and couples the light reflected from each point along the optical fiber to a photodetector, converts the light signal reflected from the optical fiber under test into an electrical signal by a detector, then amplifies the electrical signal sent from the photodetector by an amplifier and shapes it, processes the reflected signal by a data analysis and display unit, calculates relevant data, and displays a curve of the test results on a display, and coordinates the operation of the OTDR, including user interface, data processing, and report generation, by a microcontroller unit.

[0009] Preferably, the core mechanical element of the MEMS micromechanical structure is a micromirror, which is responsible for reflecting or deflecting light signals, and realizes movement through electrostatic, electromagnetic, thermal or piezoelectric drive to change the direction of the light beam.

[0010] Preferably, the data receiving module includes real-time data acquisition, communication protocol support and data storage; Real-time data acquisition: Receive the monitoring data of the optical fiber in real time from the OTDR function support module; the OTDR device sends pulsed light into the optical fiber, and the returned reflected signal is converted into data, and the data contains information about the length and light attenuation of the optical fiber; Communication protocol support: Data is transmitted via RS485 (2-wire, half-duplex, balanced transmission line multi-point communication), Ethernet or 4G module. The software needs to implement the corresponding communication protocol interface to ensure reliable reception and processing of real-time data; Data storage: Data received in real time should be stored in a local database to facilitate subsequent cleaning and analysis.

[0011] Preferably, the data cleaning module includes: noise filtering and data deduplication and abnormal data processing; Noise filtering and data deduplication: Monitoring data contains noise signals (such as curve jitter, reflection noise, etc.). Through big data cleaning technology, multiple measurement data are averaged to remove outliers and noise to ensure data accuracy; Abnormal data processing: When sudden abnormalities occur in the monitoring data, it is necessary to set a threshold detection mechanism to filter out abnormal data for further analysis.

[0012] Preferably, the data analysis module includes: light decay value extraction, trend analysis and algorithm support; Optical attenuation value extraction: By analyzing the OTDR curve, the optical attenuation value (dB / km) of the optical fiber is extracted. The attenuation value of the optical fiber is calculated from Rayleigh backscattering and other phenomena. The algorithm automatically recognizes and calculates the slope of the curve to extract the attenuation of each section of the optical fiber. Trend analysis: Use historical data and time series analysis to draw a trend chart of optical fiber attenuation. Combined with big data analysis technology, predict the future attenuation trend of optical fiber and evaluate the health of optical cables. Algorithm support: Use machine learning algorithms (such as time series prediction, random forest, etc.) to train historical data on fiber attenuation, predict the probability of future failures, and perform comparative analysis in combination with known fiber damage models.

[0013] Preferably, the cable health status assessment and fault prediction module includes health assessment and fault prediction; Health assessment: Based on the real-time optical attenuation data of the optical fiber and combined with historical data, the health score of the optical fiber is obtained through an algorithm. According to the change trend of the attenuation value, emergencies, blind spots and other factors, the health status of each section of the optical cable is evaluated and a health report is generated; Fault prediction: Based on big data analysis, trend analysis is performed on the historical attenuation data of each section of optical fiber to predict future fault risks in advance. When the attenuation rate of the optical fiber exceeds the set threshold, the system automatically generates an alarm and prompts the location of the optical cable that needs maintenance.

[0014] Preferably, the system display and alarm module includes: data visualization and alarm mechanism; Data visualization: The software displays the real-time status of each fiber segment through a graphical interface, including optical attenuation trend graph, health score, and fault risk prompt; Alarm mechanism: When the fiber attenuation value exceeds the set threshold, or the health status score is lower than the set threshold, the system will trigger an alarm. The alarm methods include pop-up prompts, sound alarms, or notifications to relevant maintenance personnel via email or SMS.

[0015] Compared with the related art, the fiber core online fast monitoring system based on time division and space division multiplexing provided by the present invention has the following beneficial effects: The present invention utilizes a high-precision instrument for testing the characteristics of an optical fiber network to emit optical pulses and analyze the returned scattered and reflected signals. Through online monitoring of optical signals, various parameters that affect changes in optical signals are brought into an algorithm module. The algorithm module combines changes in various parameters with the impact on optical signals, allowing a software unit to perform health assessment and fault prediction of the optical fiber, thereby accurately and efficiently completing the testing and fault diagnosis tasks of the optical fiber network. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of transmission of the fiber core online rapid monitoring system based on time-division and space-division multiplexing provided by the present invention in a standard optical fiber; Figure 2 A schematic diagram of dual-wavelength test curves of different non-reflective events of the fiber core online rapid monitoring system based on time-division and space-division multiplexing provided by the present invention; Figure 3 A schematic diagram of the Fresnel reflection in the OTDR curve of the fiber core online fast monitoring system based on time-division and space-division multiplexing provided by the present invention; Figure 4 A schematic diagram showing the change of pulse width over time for the fiber core online fast monitoring system based on time-division and space-division multiplexing provided by the present invention; Figure 5 A schematic diagram of the overall composition of the fiber core online rapid monitoring system based on time-division and space-division multiplexing provided by the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example A fiber core online fast monitoring system based on time-space division multiplexing: This system requires the following hardware support: OTDR function support module An optical time domain reflectometer (OTDR), a high-precision instrument used to test the characteristics of fiber-optic networks, works by transmitting pulses of light and analyzing the returning scattered and reflected signals.

[0019] It usually includes the following parts: Laser light source: generates light pulses of a specific wavelength for injection into optical fibers.

[0020] Use laser diodes: as light sources to generate light pulses of a specific wavelength; select appropriate laser diodes to ensure that their wavelengths are compatible with fiber-optic communication systems, such as 1310nm or 1550nm.

[0021] Pulse generator: controls the timing of light pulses emitted by the light source to ensure synchronization with the data analysis and display circuits.

[0022] Directional coupler: couples the light emitted by the light source to the optical fiber under test, and couples the light reflected back from each point along the optical fiber to the photodetector.

[0023] Photodetector: converts the optical signal reflected from the optical fiber under test into an electrical signal.

[0024] Amplifier: Amplifies the electrical signal sent by the photodetector and shapes it.

[0025] Data analysis and display: Process the reflected signal, calculate the relevant data, and display the curve of the test results on the monitor.

[0026] Microcontroller Unit (MCU): Coordinates the operations of the OTDR, including the user interface, data processing, and report generation.

[0027] Comprehensively study and consider processing speed, memory capacity, peripheral interfaces {such as ADC (electronic component that converts analog signals into digital signals), DAC (electronic component that converts digital signals into analog signals), timer, etc.} and compatibility with OTDR hardware modules.

[0028] Consider the following factors: Dynamic range: The maximum fiber length or total loss that an OTDR can measure.

[0029] Blind zone: The area that the OTDR cannot detect when detecting a fiber link, including the event blind zone and the attenuation blind zone.

[0030] Sampling resolution: The minimum distance at which the OTDR acquires data, which affects distance accuracy and fault finding capabilities.

[0031] Wavelength selection: Select the appropriate wavelength according to the fiber type and test requirements. Common wavelengths are 850nm, 1300nm, 1310nm and 1550nm.

[0032] The hardware design of OTDR needs to take the above factors into consideration to ensure that the equipment can accurately and efficiently complete the testing and fault diagnosis tasks of the optical fiber network.

[0033] OTDR Communication Module A 4G communication module dedicated to OTDR will be integrated, and a SIM card slot will be reserved for mobile data communication.

[0034] OTDR communication module selection: Quectel EC25 (encoder) communication module.

[0035] The communication module can upload various data processed by the MCU (single-chip microcomputer) to the cloud, and the cloud can perform secondary calculation, learning and analysis on the data or directly display it on the server platform.

[0036] It is also necessary to consider the internal security of the power grid. The 4G communication module needs to be removed and other communication methods need to be used for LAN transmission. An external interface will be reserved when the equipment leaves the factory, and external LAN data transmission can be carried out through RS485 (2-wire, half-duplex, balanced transmission line multi-point communication) and other methods.

[0037] Algorithm Module Dynamic Range This parameter shows the maximum optical loss that the OTDR can analyze when the backscattering level at the OTDR port drops to a certain noise level. In other words, it is the maximum length of the fiber that the longest pulse can reach.

[0038] Therefore, the greater the dynamic range (in dB), the greater the distance that can be reached. The maximum distance varies from application to application because the loss of the link being tested varies. Connectors, splices, and splitters are factors that reduce the maximum reach of the OTDR.

[0039] Therefore, averaging over a longer period of time and using the appropriate distance range is key to increasing the maximum measurable distance. Most dynamic range specifications are given using the longest pulse width averaged over 3 minutes with a signal-to-noise ratio (SNR) of 1 (the average level of the root mean square (RMS) noise value).

[0040] It is important to select an OTDR with a dynamic range that is 5-8 dB higher than the maximum loss you may encounter. For example, a single-mode OTDR with a dynamic range of 35 dB has a usable dynamic range of approximately 30 dB.

[0041] Assuming a typical fiber attenuation of 0.20 dB / km at a wavelength of 1550 nm, and splices every 2 km (each splice has a loss of 0.1 dB), the longest distance that similar equipment can accurately verify is 120 km. The maximum distance can be roughly calculated by dividing the fiber attenuation by the dynamic range of the OTDR. This can help determine the dynamic range of the equipment that can reach the end of the fiber.

[0042] The higher the losses in the network, the larger the dynamic range required. However, it is important to note that a dynamic range specified at 20 μs does not guarantee such a large dynamic range for short pulses - excessive curve filtering will artificially increase the dynamic range for all pulses at the expense of reduced fault finding resolution.

[0043] Blind Spot Fresnel reflections lead to an important OTDR parameter called "blind zone". There are two types of blind zones: event blind zone and attenuation blind zone. Both are caused by Fresnel reflections and are expressed as a distance (in meters) that varies depending on the power of the reflections. The blind zone is defined as the length of time between when the detector is temporarily blinded by a large amount of reflected light and when it recovers and can read optical signals again.

[0044] For example, when driving at night, your eyes will be blinded for a short time when you meet oncoming traffic. In the field of OTDR, time is converted into distance. Therefore, the more light is reflected, the longer the detector needs to recover, resulting in a longer blind zone. In most cases, the blind zone is specified when the shortest available pulse width is used, the single-mode fiber reflectance is -45 dB and the multimode fiber reflectance is -35 dB. For this reason, the test method and conditions for measuring the blind zone require special attention. In particular, pay attention to the pulse width and reflectance value.

[0045] For example, a single-mode fiber reflectance of -55 dB will produce a shorter blind zone than a -45 dB reflectance because -55 dB is a lower reflectance and the detector will recover faster. In addition, using different methods to calculate distance will also result in a lower blind zone than the actual level.

[0046] Reflected Light There are two levels of reflected light: a steady, low-level reflected light caused by the fiber, called “Rayleigh backscatter,” and a high-reflection peak at the connection point, called “Fresnel reflection.” Rayleigh backscatter is used to calculate the attenuation level (in dB / km) within the fiber as it varies with distance, and is represented by the slope of the line in the OTDR trace.

[0047] This phenomenon is caused by the natural reflection and absorption of light by impurities in the optical fiber. When encountering light, some particles will reflect the light in different directions, causing signal attenuation and backscattering. The longer the wavelength, the less signal attenuation, so the signal needs less power to transmit the same distance in a standard optical fiber. Figure 1 shown.

[0048] Rayleigh backscattering detects physical non-reflective events by a sudden drop in signal level. You can see that there is a discontinuity in the downward sloping curve signal slope. This event is usually caused by a fusion splice, macrobend or microbend in the fiber. To correctly distinguish between physical bends and fusion splices in the fiber, dual wavelength testing is required. Macrobends usually show higher losses at higher wavelengths, while the loss caused by fusion splices is almost unaffected by wavelength. Dual wavelength test curves for different non-reflective events are shown below. Figure 2 As shown: The second type of reflection that OTDR uses is Fresnel reflection, which can detect physical events along the entire link. When the reflectivity of light changes dramatically (such as when it goes from glass to air), more light will be reflected back, causing Fresnel reflection, which can be thousands of times stronger than Rayleigh backscattering. Fresnel reflection is represented as a spike in the OTDR curve. Figure 3 Examples of such reflections include connectors, mechanical splices, flanges, fiber breaks, or disconnected connectors.

[0049] Attenuation blind area The attenuation blind zone is the minimum distance at which the OTDR can accurately measure the loss of consecutive events after Fresnel reflection occurs. Using the driving example above, after a long period of time, the eyes will recover sufficiently to recognize and analyze the properties of objects on the road.

[0050] The detector is given enough time to recover so that it can detect and measure the loss of a continuous event. The minimum distance required is measured from the start of the reflective event until the reflection returns to 0.5 dB above the backscatter level of the fiber.

[0051] Pulse Width The pulse width is actually the time that the laser is on. As we know, time is converted to distance, so the pulse width has a length value. In an OTDR, the pulse carries the energy needed to produce backscatter to characterize the link. Because there are losses along the link (i.e. attenuation, connectors and splices), the shorter the pulse, the lower the energy it carries and the shorter the distance it travels. Longer pulses can carry more energy and can be used in very long fiber lengths. Figure 4 The variation of pulse width over time is shown.

[0052] Sampling resolution and sampling points The ability of an OTDR to pinpoint the correct event distance depends on a combination of different parameters, including sampling resolution and sampling points. Sampling resolution is defined as "the minimum distance between two consecutive sampling points acquired by the instrument."

[0053] This parameter is critical as it defines the ultimate distance accuracy and fault finding capability of the OTDR. Depending on the pulse width and distance range selected, this value can range from 4 cm to several meters. Therefore, to ensure the highest resolution, sampling must be performed at a higher number of sampling points during data acquisition.

[0054] Sampling resolution and sampling points The ability of an OTDR to pinpoint the correct event distance depends on a combination of different parameters, including sampling resolution and sampling points. Sampling resolution is defined as "the minimum distance between two consecutive sampling points acquired by the instrument."

[0055] This parameter is critical as it defines the ultimate distance accuracy and fault finding capability of the OTDR. Depending on the pulse width and distance range selected, this value can range from 4 cm to several meters. Therefore, to ensure the highest resolution, sampling must be performed at a higher number of sampling points during data acquisition.

[0056] Impulse noise protection When the curve is very noisy, there are two simple ways to achieve a cleaner curve. First, the sampling time can be increased, which can significantly improve (increase) the SNR while maintaining the high resolution achieved with short pulses. However, increasing the averaging time has its limitations as it will not increase the SNR indefinitely.

[0057] If the curve is still not smooth enough, we need to take the second approach, which is to use the next available higher pulse (carrying more energy). It is important to remember that the blind zone will be extended as the pulse increases. Fortunately, most OTDRs on the market are equipped with an automatic mode to select the appropriate pulse width for the fiber under test.

[0058] This method is very convenient when the length or loss of the fiber under test is unknown and provides the best compromise for single pulse width data acquisition.

[0059] MEMS optical switch (optical path switching device) module The basic structure of a MEMS optical switch includes several core parts, usually involving the integration of mechanical, optical and electronic control. Its main components are as follows: MEMS micromechanical (24-core optical switch) structure Micromirror: The micromirror is the core mechanical element of the optical MEMS switch, which is responsible for reflecting or deflecting the light signal. The micromirror can be driven by electrostatic, electromagnetic, thermal or piezoelectric motion to change the direction of the light beam.

[0060] This motion can be rotation, tilt, or linear movement to switch the input light path to a different output fiber.

[0061] Gratings or microlenses: In some optical MEMS switches, the micromechanical structure may use gratings or microlens arrays to diffract or focus the light beam instead of simply reflecting it.

[0062] Drive circuit The drive circuit is responsible for providing energy to control the movement of micromechanical components. Common drive methods include: Electrostatic drive: Electrostatic force is generated by applying voltage to deflect or move the micromirror.

[0063] Electromagnetic drive: Use electromagnetic force to control the rotation or displacement of the micromirror.

[0064] Thermal actuation: heating is used to deform micromechanical components and change the optical path.

[0065] Piezoelectric drive: The mechanical deformation of piezoelectric materials under the action of voltage is used to drive the movement of the micromirror.

[0066] Optical input and output ports Input fiber: Used to transmit the optical signal entering the switch, usually transmitted via single-mode or multimode fiber.

[0067] Output fiber: Depending on the switching state of the micromirror, the output optical signal is transmitted to the corresponding fiber path.

[0068] The arrangement of the fiber ports determines the paths along which the optical signals can be routed. The optical MEMS switch can be in different configurations such as 1xN and NxM to meet different application requirements.

[0069] Optical components Collimating lens: Between the input optical fiber and the micromirror, there is usually a collimating lens to collimate the divergent light beam into a parallel beam so that the micromirror can reflect and deflect more easily.

[0070] Mirror array: If it is a multi-channel optical MEMS switch, it may contain multiple mirror arrays to handle the parallel switching of multiple optical signals.

[0071] Packaging and Alignment Systems Micro-alignment system: Optical fibers and micro-mirrors require very precise alignment to ensure minimal loss of optical signals between input and output. Therefore, a sophisticated micro-alignment system is often used to ensure a stable optical path.

[0072] Package structure: Optical MEMS switches are usually in a hermetic package to prevent environmental factors such as dust or moisture from affecting the movement of the micromechanical structure or the transmission of optical signals.

[0073] Control and feedback circuits Control system: used to control the switching state of micromechanical components, usually managed in real time through control chips such as microprocessors or FPGAs to control the angle, moving position, etc. of the micromirror.

[0074] Sensors and feedback loops: Some optical MEMS switches may include position sensors to detect the motion of the micromirror, ensuring that it reaches the target position accurately, providing a closed-loop control system, and improving switching accuracy and stability.

[0075] Cooling System In high-density switching applications, the switch structure may generate heat, so heat dissipation design is required to ensure that the system temperature remains within an acceptable range during long-term operation to prevent the performance of the mechanical structure from degrading.

[0076] In summary, the composition of optical MEMS switches includes micro-mechanical components such as micro-mirrors or gratings, drive circuits, input and output optical fibers, collimating lenses and optical components, packaging and alignment systems, and control and feedback circuits. These components work together to ensure efficient switching and transmission of optical signals.

[0077] The OTDR host equipment, 24-core optical switch, and OTDR 24-core optical switch equipment with the following functions are developed and designed for internal data transmission in substations.

[0078] 1.24-port online OTDR monitoring equipment, with common functions of OTDR equipment, compatible with 19-inch standard cabinet, 1U height.

[0079] 2. Based on the time-space dual-mode multiplexing fiber core monitoring technology, 24-core optical fibers can be monitored simultaneously.

[0080] 3. Light endpoint detection.

[0081] 4. It can provide data open interface to facilitate the development of our own software system.

[0082] 5.24 wires were tested within 7 minutes.

[0083] Software Unit Data receiving module Real-time data acquisition: The software needs to receive the monitoring data of the optical fiber from the online OTDR monitoring device in real time. The OTDR device sends pulsed light into the optical fiber and converts the returned reflected signal into data. The data contains key information such as the length of the optical fiber and the optical attenuation.

[0084] Communication protocol support: Considering that OTDR equipment may transmit data through RS485, Ethernet or 4G modules, the software needs to implement the corresponding communication protocol interface to ensure reliable reception and processing of real-time data.

[0085] Data storage: Data received in real time should be stored in a local database (such as MySQL, PostgreSQL, etc.) to facilitate subsequent cleaning and analysis.

[0086] Data cleaning module Noise filtering and data deduplication: OTDR monitoring data contains noise signals (such as curve jitter, reflection noise, etc.). Through big data cleaning technology, multiple measurement data are averaged to remove outliers and noise to ensure data accuracy.

[0087] Abnormal data processing: If sudden abnormalities (such as sudden huge attenuation) occur in the monitoring data, it is necessary to set a threshold detection mechanism to filter out the abnormal data for further analysis.

[0088] Data Analysis Module Optical attenuation value extraction: By analyzing the OTDR curve, the optical attenuation value (dB / km) of the optical fiber is extracted. The attenuation value of the optical fiber is calculated from Rayleigh backscattering and other phenomena. The software implements an algorithm to automatically identify and calculate the slope of the curve, and extract the attenuation of each section of the optical fiber.

[0089] Trend analysis: Use historical data and time series analysis to draw a trend chart of optical fiber attenuation. Combined with big data analysis technology, predict the future attenuation trend of optical fiber and evaluate the health of optical cables.

[0090] Algorithm support: Use machine learning algorithms (such as time series prediction, random forest, etc.) to train historical data on fiber attenuation and predict the probability of future failures. Comparative analysis can be performed in combination with known fiber damage models.

[0091] Optical cable health status assessment and fault prediction module Health assessment: Based on the real-time optical attenuation data of the optical fiber and combined with historical data, the health score of the optical fiber is obtained through an algorithm. The software will evaluate the health status of each section of the optical cable and generate a health report based on factors such as the change trend of the attenuation value, emergencies, and blind spots.

[0092] Fault prediction: Based on big data analysis, the historical attenuation data of each section of optical fiber is trend analyzed to predict future fault risks in advance. When the attenuation rate of the optical fiber exceeds the set threshold, the system automatically generates an alarm and prompts the location of the optical cable that needs maintenance.

[0093] System display and alarm module Data visualization: The software displays the real-time status of each fiber section through a graphical interface, including optical attenuation trend graph, health score, fault risk prompt, etc. The ECharts chart library is used to update data in real time.

[0094] Alarm mechanism: When the fiber attenuation value exceeds the set threshold, or the health status score is lower than the set threshold, the system will trigger an alarm. The alarm method includes pop-up window prompts, sound alarms, or notifying relevant maintenance personnel via email or SMS.

[0095] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A fiber core online fast monitoring system based on time division and space division multiplexing, characterized in that: These include: OTDR function support module: It works by emitting optical pulses and analyzing the returned scattered and reflected signals. It has a built-in OTDR communication module, which uploads the data processed by the MCU to the cloud. The cloud can perform secondary calculation, learning and analysis on the data or directly display it on the server platform. Algorithm module: The algorithm parameters in the algorithm module include: dynamic range, blind area, reflected light, attenuation blind area, pulse width, sampling resolution, sampling point and pulse noise response; MEMS optical switch module: including MEMS micromechanical structure, drive circuit, optical input and output ports, optical elements, packaging and alignment module, control and feedback circuit and heat dissipation module; Software unit: including: data receiving module, data cleaning module, data analysis module, optical cable health status assessment and fault prediction module, display module and alarm module; The real-time status of each optical fiber section is displayed through the graphical interface of the display module, including optical attenuation trend graph, health score, and fault risk prompt.

2. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: The OTDR function support modules include: laser light source, pulse generator, directional coupler, photodetector, amplifier, data analysis and display unit and microcontroller unit.

3. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 2 is characterized in that: The OTDR function support module generates light pulses of specific wavelengths by a laser light source for injection into optical fibers. A laser diode is used as a light source to generate light pulses of specific wavelengths. The time when the light source emits the light pulses is controlled by a pulse generator to ensure synchronization with the data analysis and display circuits. A directional coupler is used to couple the light emitted by the light source to the optical fiber under test, and the light reflected from each point along the optical fiber is coupled to a photodetector. The detector is used to convert the light signal reflected from the optical fiber under test into an electrical signal, and then the amplifier is used to amplify and shape the electrical signal sent by the photodetector. The data analysis and display unit processes the reflected signal, calculates relevant data, and displays the curve of the test results on the display. The microcontroller unit is used to coordinate the operation of the OTDR, including the user interface, data processing, and report generation.

4. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: The core mechanical element of MEMS micromechanical structure is the micromirror, which is responsible for reflecting or deflecting light signals, achieving movement through electrostatic, electromagnetic, thermal or piezoelectric drive, and changing the direction of the light beam.

5. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: The data receiving module includes real-time data acquisition, communication protocol support and data storage; Real-time data acquisition: The OTDR function support module receives the monitoring data of the optical fiber in real time. The OTDR device sends pulsed light into the optical fiber, and the returned reflected signal is converted into data, and the data contains information about the length and optical attenuation of the optical fiber. Communication protocol support: Data is transmitted via RS485, Ethernet or 4G modules. The software needs to implement the corresponding communication protocol interface to ensure reliable reception and processing of real-time data; Data storage: Data received in real time should be stored in a local database to facilitate subsequent cleaning and analysis.

6. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: The data cleaning module includes: noise filtering, data deduplication and abnormal data processing; Noise filtering and data deduplication: Monitoring data contains noise signals. Through big data cleaning technology, multiple measurement data are averaged to remove outliers and noise to ensure data accuracy; Abnormal data processing: When sudden abnormalities occur in the monitoring data, it is necessary to set a threshold detection mechanism to filter out abnormal data for further analysis.

7. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: Data analysis modules include: light decay value extraction, trend analysis and algorithm support; Optical attenuation value extraction: By analyzing the OTDR curve, the optical attenuation value of the optical fiber is extracted. The attenuation value of the optical fiber is calculated from the Rayleigh backscattering phenomenon. The algorithm automatically recognizes and calculates the slope of the curve to extract the attenuation of each section of the optical fiber. Trend analysis: Use historical data and time series analysis to draw a trend chart of optical fiber attenuation. Combined with big data analysis technology, predict the future attenuation trend of optical fiber and evaluate the health of optical cables. Algorithm support: Use machine learning algorithms to train historical data on fiber attenuation, predict the probability of future failures, and perform comparative analysis based on known fiber damage models.

8. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1 is characterized in that: The optical cable health status assessment and fault prediction module includes health assessment and fault prediction; Health assessment: Based on the real-time optical attenuation data of the optical fiber and combined with historical data, the health score of the optical fiber is obtained through an algorithm. According to the change trend of the attenuation value, emergencies, and blind spot factors, the health status of each section of the optical cable is evaluated and a health report is generated; Fault prediction: Based on big data analysis, trend analysis is performed on the historical attenuation data of each section of optical fiber to predict future fault risks in advance. When the attenuation rate of the optical fiber exceeds the set threshold, the system automatically generates an alarm and prompts the location of the optical cable that needs maintenance.

9. The fiber core online fast monitoring system based on time division and space division multiplexing according to claim 1, characterized in that: The system display and alarm module includes: data visualization and alarm mechanism; Data visualization: The software displays the real-time status of each fiber segment through a graphical interface, including optical attenuation trend graph, health score, and fault risk prompt; Alarm mechanism: When the fiber attenuation value exceeds the set threshold, or the health status score is lower than the set threshold, the system will trigger an alarm. The alarm methods include pop-up prompts, sound alarms, or notifications to relevant maintenance personnel via email or SMS.

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