Online detection system and method for optical indexes of hollow-core fiber

Abstract

The invention discloses an online detection system and method for optical indexes of a hollow-core optical fiber, and relates to the technical field of optical performance detection of optical fibers, and the system comprises an optical fiber connection module, an optical performance detection module, a production linkage module and a data interaction module. The method comprises the following steps: welding the inner end of a production optical fiber with a system at one time; the industrial personal computer reads PLC production data and generates a test trigger condition; when the conditions are met, controlling the OTDR to test the optical indexes of the optical fiber; carrying out segment processing on the OTDR curve by using an improved Viterbi algorithm so as to identify fault features; performing automatic environment compensation based on an attenuation reference model established by the LSTM neural network; and finally, uploading the analysis data to a manufacturing execution system. According to the invention, on-line, real-time and accurate detection of the optical indexes of the hollow-core fiber is realized, traditional multi-time welding is replaced by one-time welding, the detection efficiency is greatly improved, and the problems of poor sealing performance, low efficiency and low data reliability in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optical fiber optical performance detection, and in particular to an online detection system and method for optical indicators of hollow-core optical fiber. BACKGROUND

[0002] Hollow-core fiber (HCF) is a new type of optical fiber technology with innovative structure. Similar to traditional optical fibers, it is composed of a core, a cladding and a coating layer to form a symmetrical cylindrical structure of multiple layers of media. The core difference lies in the hollow design of the core of the hollow-core fiber. This unique structure allows the optical signal to propagate through the air in the core, which can increase the transmission rate of the optical signal by 30% compared to traditional solid-core optical fibers, significantly expanding the application scenarios of optical fibers in the field of high-speed optical signal transmission, and making it an important research and application direction in the field of optical cable production.

[0003] In the process of optical cable production, the optical performance indicators of the optical fiber directly determine the quality of the optical signal transmission of the optical cable, and therefore are the core detection items in the production process of the optical cable. Currently, the conventional detection process for the optical performance of the optical fiber is as follows: after the production of the optical cable is completed and the cable is unwound, the coating layer of the optical fiber is first stripped by a professional quality detection personnel, and then the test optical fiber of the OTDR (Optical Time Domain Reflectometer) device is fused with the optical fiber to be detected by a special fusion machine. After the fusion operation is completed, the OTDR device is started to emit test signals, and the optical performance indicators (such as attenuation, fiber length, etc.) of the optical fiber are obtained by receiving and analyzing the reflected signals.

[0004] However, the above existing detection technology has significant defects when applied to hollow-core optical fibers, and cannot meet the production and detection requirements of hollow-core optical fibers. The specific problems are as follows: 1. Poor detection sealing leads to unreliable data: Since the hollow-core optical fiber relies on the air in the core to propagate the optical signal, unlike the traditional solid-core optical fiber which only needs to be simply connected in a specially designed capillary to complete the OTDR signal transmission, the existing conventional detection method cannot guarantee the sealing of the connection between the hollow-core optical fiber and the test optical fiber. Insufficient sealing will cause serious attenuation of the test signals emitted by the OTDR during transmission, resulting in large deviations in the measured optical performance data, which lacks credibility and cannot accurately reflect the actual performance of the hollow-core optical fiber.

[0005] 2. The detection process is time-consuming, laborious and inefficient: In order to ensure the accuracy of the optical performance detection of the hollow core optical fiber, the prior art needs to use professional equipment to fuse and seal the two ends of the hollow core optical fiber and the test optical fiber before detection; Taking a conventional section optical fiber (such as 50 kilometers per section, and each 1 kilometer is a section length) as an example, the method needs to fuse each section of optical fiber separately, and each fusion takes about 30 minutes, a total of 50 times of fusion is needed for the whole section, and the cumulative time consumption is up to 25 hours, which occupies a large amount of manpower and time cost, and the detection efficiency is very low.

[0006] 3. Offline detection cannot meet the real-time control requirements: The existing detection process needs to be carried out offline after the cable is unwound, and cannot monitor the optical performance of the optical fiber in real time during the production process; This not only leads to a lag in the detection results, making it difficult to find quality problems (such as abnormal fiber attenuation and joint failure) in the production process in a timely manner, but also may cause problems in the production and circulation of the cable (such as the need to wait for the detection results before entering the subsequent packaging link), which seriously restricts the production efficiency and quality control level of the hollow core optical fiber cable. In summary, with the increasing demand for hollow core optical fiber applications, the existing offline, inefficient and low data reliability detection technology cannot meet the real-time and accurate detection needs of large-scale production of hollow core optical fiber cables, and there is an urgent need to develop a testing system that can realize online real-time detection of optical indicators of hollow core optical fiber, automatic analysis of data and intelligent control, to solve the bottleneck problem of the existing technology. SUMMARY

[0007] Therefore, the embodiments of the present application provide an online detection system and method for optical indicators of hollow core optical fiber, which solves the problems in the prior art that the optical performance detection of hollow core optical fiber needs to be carried out offline, the optical fiber needs to be fused multiple times (time-consuming and inefficient), the sealing is poor, the OTDR test signal is lost, the data is not reliable, the detection is lagging, the production circulation is affected, and the test data needs to be manually counted, which cannot meet the real-time and accurate control needs of large-scale production of hollow core optical fiber cables.

[0008] In order to solve the above technical problems, the embodiments of the present application provide an online detection system for optical indicators of hollow core optical fiber, which comprises a fiber connection module, an optical performance detection module, a production linkage module and a data interaction module; The fiber connection module is a fusion machine, which is used to fixedly connect the inner end of the production optical fiber in the cable production process with the optical performance detection module; The optical performance detection module comprises an optical time domain reflectometer, an industrial computer and a pre-stored optical performance test program, the optical performance test program is configured in the industrial computer, and is used to control the optical time domain reflectometer to perform fiber length measurement and attenuation measurement of the hollow core optical fiber; The production linkage module is a PLC for optical cable production, and the industrial computer is in communication connection with the PLC for optical cable production to read optical cable production speed and production length data and take the production length data as a trigger condition for optical performance detection. The data interaction module is in communication connection with a manufacturing execution system to receive detection data output by the optical performance detection module and upload the detection data to the manufacturing execution system to realize online detection of optical indexes of the hollow optical fiber.

[0009] Preferably, the optical performance detection module is based on a three-layer distributed network, which comprises a client, an application server and a data service layer; the client is a human-computer interaction interface for receiving user instructions and feeding back detection information; the application server is used for instruction processing and network service of the optical performance test program; and the data service layer is a database system for storing detection data.

[0010] Preferably, the optical performance detection module further comprises a display in electrical connection with the industrial computer for real-time display of optical cable production data, fiber length and attenuation data of the hollow optical fiber and fault alarm information.

[0011] Preferably, the industrial computer is further configured with an attenuation reference model, which is based on a long short-term memory neural network and realizes automatic environmental compensation for the attenuation measurement value of the hollow optical fiber by learning features of historical detection data.

[0012] Preferably, an improved Viterbi algorithm is integrated in the optical performance test program, which is used for segmented processing of a detection curve output by an optical time domain reflectometer, identifies typical fault features including a step joint and a poor curve, and triggers an alarm prompt when the fault features are identified.

[0013] The embodiment of the application further provides an online detection method for optical indexes of a hollow optical fiber, which is applied to the online detection system for optical indexes of the hollow optical fiber and comprises the following steps: S1: setting detection parameters through a client, wherein the detection parameters comprise a range of the hollow optical fiber, a pulse width, a finished product order length, a test attenuation trigger length and a test fiber length trigger length; S2: starting a PLC access program to enable the industrial computer to read optical cable production speed and real-time production length data output by a PLC for optical cable production, and then starting an optical time domain reflectometer, an optical fiber connection program and an optical fiber length test program in sequence to obtain an initial total fiber length of a production optical fiber; S3: starting an optical cable production process, and when real-time production length of the optical cable reaches the test attenuation trigger length, the industrial computer controls the optical time domain reflectometer to start detection to output total fiber length and average attenuation of the current production optical fiber; S4: when the optical cable is produced to the order length and the segmentation is completed, the industrial computer starts the optical fiber length test program, obtains the total fiber length of the remaining production optical fiber after segmentation, calculates the difference between the initial total fiber length and the total fiber length before segmentation and the remaining total fiber length, and obtains the actual fiber length of the segmented down disc optical cable; S5: analyzing the total fiber length, average attenuation and actual fiber length through the optical performance test program, and uploading the analyzed detection data to the manufacturing execution system to complete the online detection of the optical index of the hollow core optical fiber.

[0014] Preferably, in step S3, the optical time domain reflectometer synchronously outputs the total fiber length and the average attenuation of the hollow core optical fiber after starting detection; in step S4, the difference is the actual fiber length of the current segmented down disc optical cable, and the disc optical cable does not need to be detected by secondary fusion.

[0015] Preferably, in step S5, the optical performance test program identifies the fault characteristics by analyzing the total fiber length and average attenuation data, and outputs an alarm prompt through the display when the fault characteristics are identified, and the fault characteristics include typical fault characteristics such as steps and poor curves.

[0016] Preferably, in step S5, the optical performance test program first automatically classifies the detection data to form a data report, and then uploads the data report to the manufacturing execution system through the data interaction module, without manual statistics.

[0017] Preferably, before step S2, the method further comprises the step of fixing and connecting the inner end of the production optical fiber to the optical time domain reflectometer in the optical performance detection module through the fusion machine, and each disc of production optical fiber only needs to be fused once.

[0018] From the above technical solutions, the present application has the following beneficial effects: (1) The present application realizes continuous online monitoring of the entire disc of optical fiber by permanently fusing the inner end of the production optical fiber to the online test system once, completely abandoning the cumbersome process of fusing once per kilometer in the traditional method (such as fusing 50 times for 50 kilometers of optical fiber). This shortens the fusion time from dozens of hours to once, improves the efficiency by dozens of times, and greatly reduces the labor and time costs. At the same time, the product can directly enter the packaging link without waiting for the offline detection result after being taken out, which significantly optimizes the production circulation and improves the overall optical cable production efficiency.

[0019] (2) The application innovatively introduces two intelligent algorithms of improved Viterbi algorithm and LSTM neural network attenuation benchmark model. The former can automatically and accurately identify various fault characteristics (such as interface steps, poor curves, etc.) in the OTDR curve, and changes the judgment depending on artificial experience into objective automatic analysis; the latter realizes high-precision automatic environmental compensation of the order of ±0.02dB through learning from historical data, effectively eliminates the influence of environmental fluctuations on test results, thereby ensuring the high reliability and accuracy of detection data, and greatly improving the prediction ability of quality hidden dangers.

[0020] (3) The application constructs a three-layer distributed network system deeply integrated with production PLC and manufacturing execution system (MES). The system can automatically read production data as a trigger condition, automatically execute testing, and automatically analyze data, generate reports and upload to MES using intelligent algorithms. This realizes the full-process automation and informatization from production to detection and then to data management, forms a complete closed-loop intelligent management and control, completely eliminates the lag and errors of manual statistics, and lays a solid foundation for lean production and digital factory. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the application or the prior art, the drawings needed in the embodiments will be briefly described below. The features and advantages of the application can be more clearly understood by referring to the drawings. The drawings are schematic and should not be understood as any limitation on the application. Those skilled in the art can obtain other drawings according to these drawings without creative labor. Among them: Figure 1 is a block diagram of an online detection system for optical indicators of hollow core optical fiber provided by the application; Figure 2 is a flowchart of an online detection method for optical indicators of hollow core optical fiber provided by the application.

[0022] Description of the drawings: 100, fiber connection module; 200, optical performance detection module; 300, production linkage module; 400, data interaction module. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical scheme and advantages of the embodiments of the application more clear, the technical scheme in the embodiments of the application will be clearly and completely described below in conjunction with the drawings of the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the application.

[0024] This invention aims to address the problems of poor sealing, low efficiency, inability to perform real-time online monitoring, and reliance on manual data in existing hollow fiber optical performance testing methods. By constructing an online testing system that integrates intelligent algorithms and production linkage, real-time, accurate, and intelligent testing of hollow fiber optical indicators is achieved.

[0025] Example 1: As Figure 1 As shown, the present invention provides an online testing system for the optical properties of hollow optical fibers, comprising an optical fiber connection module 100, an optical performance testing module 200, a production linkage module 300, and a data interaction module 400. 1. Fiber optic connection module 100 The core equipment of this module is the fusion splicer. Its key function is to permanently splice the inner end of the production optical fiber (i.e., the starting or fixed end inside the reel) to the guide fiber in the optical performance testing module 200 at the beginning of optical cable production. This splicing ensures the airtightness of the optical signal transmission path, effectively preventing OTDR test signal attenuation caused by air gaps, and laying the physical foundation for subsequent online testing of the entire reel of optical fiber. Each reel of optical fiber only needs to undergo this splicing once, which fundamentally improves efficiency compared to the traditional method of splicing once per kilometer.

[0026] 2. Optical performance testing module 200 This module is the core analysis unit of this system, consisting of both hardware and software.

[0027] Hardware components include an Optical Time Domain Reflectometer (OTDR), an industrial computer, and a monitor. The OTDR is responsible for transmitting optical signals and receiving backscattered signals, serving as the direct source of fiber length and attenuation data. The industrial computer acts as the control center, responsible for running all test programs and algorithms. The monitor displays production data, test curves, analysis results, and alarm information in real time.

[0028] Software component: An optical performance testing program pre-stored in the industrial computer controls the OTDR's start / stop and parameter settings, and integrates two core intelligent algorithms: Improved Viterbi algorithm: This algorithm is not used in the traditional way in the field of communication, but is innovatively applied to the segmentation processing of the OTDR curve. The improvement lies in: defining a set of hidden states corresponding to the physical events of hollow optical fiber (such as normal attenuation, Fresnel reflection, non-reflection loss, fiber end, etc.); constructing a non-uniform state transition probability matrix based on the constraints of the physical properties of the optical fiber; using a Gaussian mixture model trained based on historical data as an observation probability model to process the power value and slope characteristics of the OTDR curve. Through this algorithm, 7 typical fault characteristics including "stepped connection" (i.e. non-end reflection peak caused by connectors, fracture surfaces, etc.) and "poor curve" (such as macro-bend loss, micro-bend loss, curve noise, etc.) can be accurately identified.

[0029] LSTM neural network attenuation benchmark model: This model is used to achieve high-precision automatic environmental compensation. The implementation process is as follows: first, collect a large amount of hollow optical fiber attenuation data containing environmental parameters (such as temperature) in a stable laboratory environment as the training set; then, use environmental parameters and measured attenuation as input, and calibrated standard attenuation value as output target to train the LSTM network; after training is completed, the model can learn the complex nonlinear mapping relationship between environment and attenuation. In online detection, the model predicts the attenuation compensation amount introduced by the environment according to real-time data, and removes it from the measured value, thereby achieving ±0.02dB precision of environmental compensation and obtaining the true attenuation value reflecting the quality of the optical fiber.

[0030] In addition, this module is based on a three-layer distributed network structure, including a client (human-computer interaction interface), an application server (deploying intelligent algorithms and business logic), and a data service layer (for data storage), ensuring the high availability and scalability of the system. The module also supports up to 128-channel fiber channel round-trip detection, with a channel switching time of less than 10 milliseconds, and integrates OSA (optical spectrum analyzer) and PMD (polarization mode dispersion) analysis units, working with OTDR to realize multi-mode joint analysis and provide more comprehensive optical index evaluation.

[0031] 3. Production linkage module 300 The core of this module is the PLC (Programmable Logic Controller) of optical cable production. The industrial computer establishes a connection with the PLC through a communication interface (such as Ethernet) and reads real-time data such as optical cable production speed and real-time production length. These production data are converted into triggering conditions for system detection (for example, when the production length reaches the preset test attenuation triggering length, the OTDR is automatically triggered for testing), realizing seamless linkage between detection and production.

[0032] 4. Data interaction module 400 This module is responsible for communication between the system and the upper-level information management system (such as the Manufacturing Execution System, MES). It automatically categorizes the intelligently analyzed test data and alarm information output by the optical performance testing module 200, forming structured data reports, and uploads them to the MES in real time via the network. This achieves fully automated archiving and information management of test data, completely avoiding the tediousness and errors of manual statistics.

[0033] Example 2: Figure 2 As shown, this invention provides an online detection method for the optical properties of hollow-core optical fibers. This method is applied to the online detection system for the optical properties of hollow-core optical fibers in Embodiment 1 above, and includes the following steps: S1: Set the detection parameters through the client. The detection parameters include the range of hollow fiber, pulse width, finished order segment length, test attenuation trigger length, and test fiber length trigger length. S2: Start the PLC access program to enable the industrial control computer to read the optical cable production speed and real-time production length data output by the optical cable production PLC. Then, start the optical time domain reflectometer, optical fiber connection program and optical fiber length test program in sequence to obtain the initial total fiber length of the produced optical fiber. S3: Start the optical cable production process. When the real-time production length of the optical cable reaches the test attenuation trigger length, the industrial control computer controls the optical time domain reflectometer to start detection and outputs the total fiber length and average attenuation of the currently produced optical fiber. S4: When the optical cable is produced to the length of the finished order and the segmentation is completed, the industrial control computer starts the optical fiber length test program to obtain the total fiber length of the remaining production optical fiber after segmentation, calculates the difference between the initial total fiber length / the total fiber length before segmentation and the remaining total fiber length, and obtains the actual fiber length of the segmented optical cable. S5: Analyze the total fiber length, average attenuation, and actual fiber length through the optical performance testing program, and upload the analyzed test data to the manufacturing execution system to complete the online testing of the optical indicators of the hollow fiber.

[0034] Specifically, in step S1, the inner end of the produced optical fiber is fused to the optical performance testing module 200 in one step using a fusion splicer. Subsequently, the operator sets the testing parameters, including but not limited to: the OTDR's range, pulse width, test wavelength, finished order segment length, test attenuation trigger length, and test fiber length trigger length, according to the current optical fiber model and process requirements, through the client's human-machine interface.

[0035] In step S2, the PLC access program is started, and the industrial control computer reads the optical cable production speed and real-time production length data from the optical cable production PLC. Subsequently, the system sequentially starts the OTDR, optical fiber connection program, and optical fiber length test program to perform an initial scan of the entire optical fiber reel, and obtains and records the initial total fiber length.

[0036] In step S3, the optical cable production process (including mold installation, main machine extrusion, optical cable speed-up, etc.) is officially started. The system continuously monitors the real-time production length, and when the length reaches the preset test attenuation trigger length, the industrial computer immediately controls the OTDR to start a detection, and synchronously obtains the total fiber length and average attenuation data of the optical fiber at the current production position.

[0037] In step S4, when the optical cable production reaches the finished product order segment length and is cut into segments, the industrial computer automatically starts the optical fiber length test program to obtain the total fiber length of the remaining optical fiber on the disc after segmentation. The system then calculates the difference in fiber length before and after segmentation (initial total fiber length - remaining total fiber length), and automatically obtains the actual fiber length of the disc of optical cable just off the disc without the need for secondary fusion detection of the disc of optical cable.

[0038] In step S5, the core algorithm of the optical performance test program comes into play: The improved Viterbi algorithm is applied to real-time analysis of the OTDR curve obtained in step S1, automatic segmentation and identification of fault characteristics (such as interface steps, poor curves, etc.), and once a fault is identified, an audible and visual alarm prompt is issued through the display.

[0039] The measured attenuation value is compensated in real time by the LSTM neural network attenuation reference model to obtain high-precision true attenuation data.

[0040] Finally, the system automatically classifies all the analyzed data (including compensated attenuation, actual fiber length, fault event points, etc.), forms a standardized data report, and uploads it to the manufacturing execution system (MES) through the data interaction module 400, completing the entire online detection process.

[0041] In summary, the present application successfully builds an efficient, accurate, and intelligent hollow optical fiber optical index online detection scheme by systematically integrating one-time fusion, production data linkage, multi-layer distributed network architecture, and advanced intelligent algorithms (improved Viterbi algorithm and LSTM neural network), effectively overcoming all the defects of the prior art.

[0042] Those skilled in the art will appreciate that embodiments of the application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0043] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0044] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0045] Obviously, the above-described embodiments are only examples for clarity and are not intended to limit the implementation. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, all the implementations are not required to be exhausted, and the obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. An online detection system for optical parameters of hollow-core optical fiber, characterized in that, It includes a fiber optic connection module, an optical performance testing module, a production linkage module, and a data interaction module; The fiber optic connection module is a fusion splicer, used to fix the inner end of the production fiber in the optical cable production process to the optical performance testing module. The optical performance testing module includes an optical time domain reflectometer, an industrial control computer, and a pre-stored optical performance testing program. The optical performance testing program is configured in the industrial control computer and is used to control the optical time domain reflectometer to perform fiber length measurement and attenuation measurement of hollow optical fiber. The production linkage module is a PLC for optical cable production. The industrial control computer is connected to the optical cable production PLC to read the optical cable production speed and production length data, and uses the production length data as the trigger condition for optical performance testing. The data interaction module is communicatively connected to the manufacturing execution system and is used to receive the test data output by the optical performance testing module and upload the test data to the manufacturing execution system to realize online testing of the optical indicators of hollow fiber.

2. The online detection system for optical parameters of hollow-core optical fiber according to claim 1, characterized in that, The optical performance testing module is built on a three-layer distributed network, which includes a client, an application server, and a data service layer. The client is a human-computer interaction interface used to receive user commands and feedback testing information. The application server is used to execute the instruction processing and network services of the optical performance testing program. The data service layer is a database system used to store the testing data.

3. The online detection system for optical parameters of hollow-core optical fiber according to claim 2, characterized in that, The optical performance testing module also includes a display, which is connected to the industrial control computer and is used to display optical cable production data, fiber length and attenuation data of hollow optical fibers, and fault alarm information in real time.

4. The online detection system for optical parameters of hollow-core optical fiber according to claim 1, characterized in that, The industrial control computer is also equipped with an attenuation reference model, which is built based on a long short-term memory neural network. By learning the characteristics of historical detection data, it realizes automatic environmental compensation for the attenuation measurement value of hollow fiber.

5. The online detection system for optical parameters of hollow-core optical fiber according to claim 1, characterized in that, The optical performance testing program integrates an improved Viterbi algorithm, which is used to segment the detection curve output by the optical time-domain reflectometer, identify typical fault characteristics including step defects and poor curves, and trigger an alarm when a fault characteristic is identified.

6. An online detection method for optical parameters of hollow-core optical fiber, applied to the online detection system for optical parameters of hollow-core optical fiber as described in any one of claims 1 to 5, characterized in that, Includes the following steps: S1: Set the detection parameters through the client. The detection parameters include the range of hollow fiber, pulse width, finished order segment length, test attenuation trigger length, and test fiber length trigger length. S2: Start the PLC access program to enable the industrial control computer to read the optical cable production speed and real-time production length data output by the optical cable production PLC. Then, start the optical time domain reflectometer, optical fiber connection program and optical fiber length test program in sequence to obtain the initial total fiber length of the produced optical fiber. S3: Start the optical cable production process. When the real-time production length of the optical cable reaches the test attenuation trigger length, the industrial control computer controls the optical time domain reflectometer to start detection and outputs the total fiber length and average attenuation of the currently produced optical fiber. S4: When the optical cable is produced to the length of the finished order and the segmentation is completed, the industrial control computer starts the optical fiber length test program to obtain the total fiber length of the remaining production optical fiber after segmentation, calculates the difference between the initial total fiber length / the total fiber length before segmentation and the remaining total fiber length, and obtains the actual fiber length of the segmented optical cable. S5: Analyze the total fiber length, average attenuation, and actual fiber length through the optical performance testing program, and upload the analyzed test data to the manufacturing execution system to complete the online testing of the optical indicators of the hollow fiber.

7. The online detection method for optical parameters of hollow-core optical fiber according to claim 6, characterized in that, In step S3, after the optical time domain reflectometer starts detection, it synchronously outputs the total fiber length and average attenuation of the hollow fiber; in step S4, the difference is the actual fiber length of the current segmented optical cable, and there is no need to perform secondary splicing detection on the optical cable.

8. The online detection method for optical parameters of hollow-core optical fiber according to claim 6, characterized in that, Its features are, In step S5, the optical performance testing program identifies fault characteristics by analyzing the total fiber length and average attenuation data. When a fault characteristic is identified, an alarm is output on the display. The fault characteristics include typical fault characteristics such as joint steps and poor curves.

9. The online detection method for optical parameters of hollow-core optical fiber according to claim 6, characterized in that, Its features are, In step S5, the optical performance testing program first automatically categorizes the test data to form a data report, and then uploads the data report to the manufacturing execution system through the data interaction module, without the need for manual statistics.

10. The online detection method for optical parameters of hollow-core optical fiber according to claim 6, characterized in that, Before step S2, there is also a step of fixing the inner end of the production optical fiber to the optical time domain reflectometer in the optical performance testing module by means of a fusion splicer, and each roll of production optical fiber only needs to be fused once.

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