A control system based on optical signal communication

Abstract

The invention discloses a control system based on optical signal communication, which relates to the technical field of optical signal communication, including obtaining the delay setting between several groups of multiple nodes according to the maximum tolerated delay; applying the delay setting between each group of multiple nodes to the nodes of optical fiber propagation respectively, and obtaining the clock synchronization data and link quality data during the optical signal communication; constructing a delay setting effect evaluation model based on a long-term and short-term neural network according to the clock synchronization data and the link quality data; taking the delay setting between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model as influencing variables; performing data analysis on the delay mathematical model to obtain the optimized delay setting between multiple nodes, and applying it to each optical fiber node of the optical signal communication; solving the problem of lack of dynamic adaptability in the setting of multi-node synchronization delay, which leads to data inconsistency, control delay or system failure.

Description

Technical Field

[0001] The present invention relates to the technical field of optical signal communication, and more specifically, to a control system based on optical signal communication. Background Art

[0002] The control system based on optical signal communication is a new technology that uses optical signals instead of traditional electrical signals for data transmission and control. Optical signal communication uses a light source such as laser or LED to transmit the signal, which is modulated and transmitted through optical fiber or free space. At the receiving end, the photodetector converts the optical signal into an electrical signal and demodulates it. This communication method has obvious advantages in anti-interference, transmission speed and transmission bandwidth, and is particularly suitable for control systems with high requirements for signal quality and real-time performance.

[0003] In the control system based on optical signals, optical signals are responsible for transmitting control instructions and sensor data, which can achieve remote and precise control. By using optical signals for signal transmission, the electromagnetic interference problem that may be encountered in traditional electrical signal communication is avoided, ensuring the stability of the system in complex or harsh environments. In addition, optical signal communication can support high-speed data transmission, providing stronger support for real-time feedback and dynamic adjustment.

[0004] This technology has a wide range of application scenarios. For example, in industrial automation, optical signals can be used to control and monitor automated production lines to improve production efficiency; in the fields of unmanned driving and robotics, optical signal communication can achieve efficient and real-time data exchange and control; in smart grids, optical communication can help monitor equipment status and load scheduling to ensure the safety and stable operation of the grid. The low latency and high confidentiality of optical signal communication also make it potential in fields with high security requirements such as aerospace and military.

[0005] For example, the invention patent announcement with announcement number: CN104391450B discloses a method for simulating signal communication delay in digital simulation, which simulates the communication delay of normal and interrupted signals by changing the communication state parameters; configures the transmission delay time parameters according to the different transmission delay times of various parts of the actual system; the data type of the transmitted signal is integer or floating point; the communication delay of signals with the same delay time, floating point and integer signals is simulated simultaneously or in groups; the communication delay of multiple signals of the same data type is simulated simultaneously or in groups. The method provided by the present invention can simulate the signal communication delay of the actual system and improve the accuracy of the model.

[0006] For example, the invention patent announcement with announcement number CN109324581B discloses a digital signal communication device and method based on Python language. The control host monitors the specified COM port through the Python language program segment. After opening the serial port, the switch signal data sent by the PLC is obtained in a loop; the switch signal data sent by the PLC is converted into hexadecimal; the switch signal data after the conversion is judged as a string; the specified string is executed in the custom function of the Python language program to send data, and the switch signal data is converted into a string type; the relay interface in the process of the control host sending the switch signal to the PLC is specified, and the data return module is called to control the host to send the switch signal data to the PLC. The present invention can realize the transmission of different types of digital signals between the PLC and the control host, and solve the communication and information interaction problems between the new program and the existing industrial control system.

[0007] The above-mentioned disclosed technical solution has at least the following technical problems: in a multi-node system of optical signal communication, in order to achieve synchronous control, the delay setting needs to take into account the communication delay between nodes; if the delay setting is too large, it will affect the response speed of the system and reduce the real-time performance; if the delay is too small, it may increase the difficulty of synchronization and cause deviations in data processing between nodes.

[0008] The prior art lacks dynamic adaptability and precise optimization mechanism in multi-node synchronization delay setting, which results in real-time response being affected when the delay is too large, and the difficulty of synchronization between nodes being increased when the delay is too small, which may cause data inconsistency, control delay or system failure. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0009] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a control system based on optical signal communication, which analyzes different multi-node synchronization delay settings to solve the problem of lack of dynamic adaptability in multi-node synchronization delay settings, resulting in data inconsistency, control delay or system failure.

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

[0011] A control system based on optical signal communication includes a delay setting acquisition module, an optical signal communication analysis module, a delay setting evaluation module, a delay model display module and a delay setting optimization module: the delay setting acquisition module is used to obtain the node type and communication mode between multiple optical fiber nodes, obtain the maximum tolerable delay according to the node type and the communication mode, and obtain the delay setting between several groups of multiple nodes according to the maximum tolerable delay; the optical signal communication analysis module is used to apply the delay setting between each group of multiple nodes to the nodes of optical fiber propagation respectively, and obtain clock synchronization data and link quality data during optical signal communication; the delay setting evaluation module is used to construct a delay setting effect evaluation model based on a long-term and short-term neural network according to the clock synchronization data and the link quality data; the delay model display module is used to use the delay setting between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model as influencing variables, construct a delay setting effect-delay setting display model, and convert the delay setting effect-delay setting display model into a delay mathematical model; the delay setting optimization module is used to perform data analysis on the delay mathematical model, obtain the optimized delay setting between multiple nodes, and apply it to each optical fiber node of optical signal communication.

[0012] In a preferred embodiment, the node types and communication modes between multiple fiber optic nodes are obtained, and the maximum tolerable delay is obtained according to the node types and communication modes. Specifically, each fiber optic node is classified, its type is identified, and the node hardware performance and processing requirements are obtained through the configuration files of NMS and fiber optic nodes; the communication mode between each node is identified by analyzing the system topology and communication protocol, and the network bandwidth and protocol requirements of the corresponding communication mode are obtained; the maximum tolerable delay is set according to the network bandwidth, processing requirements, node hardware performance and protocol requirements.

[0013] In a preferred embodiment, the delay settings between several groups of multiple nodes are obtained based on the maximum tolerable delay, specifically: based on the maximum tolerable delay of each node, the delay setting range between adjacent nodes is determined; within the delay setting range between each pair of adjacent nodes, several groups of different delay configurations are generated by random number interference.

[0014] In a preferred embodiment, the clock synchronization data includes a data packet loss fluctuation abnormality coefficient and a time synchronization error influence coefficient; the method for obtaining the data packet loss fluctuation abnormality coefficient is as follows: record each optical fiber transmission node in the optical signal communication, obtain the topological relationship number between each node, obtain the packet loss data ratio, packet loss detection frequency, and topological weight and distance between adjacent transmission nodes of each transmission node; according to the topological relationship number, obtain the packet loss data ratio, packet loss detection frequency, and topological weight and distance between adjacent transmission nodes to calculate the packet loss fluctuation value.

[0015] In a preferred embodiment, the method for obtaining the time synchronization error influence coefficient is as follows: set the time synchronization error standard value and mark it as , detect the system processing time value of the cumulative impact of multiple nodes. When the system processing time value of the cumulative impact of multiple nodes exceeds the preset value Time minus , when the system processing time value of the cumulative impact of multiple nodes is arrive Increase between , when the system processing time value of the cumulative impact of multiple nodes is lower than Time minus ; When the system processing time value of the cumulative impact of multiple nodes exceeds the preset value Time will and Set to 0; when the system processing time value of the cumulative impact of multiple nodes is arrive In between, and Set to 0; when the system processing time value of the cumulative impact of multiple nodes is lower than When and Set to 0; through the formula , set the system basic resource utilization ; Get the system resource utilization of the node, the system resource utilization is divided into high utilization, general utilization, and low utilization; when the system resource utilization is high utilization, increase , when the system resource utilization is low, subtract , when the system resource utilization rate is normal utilization rate, it remains unchanged; when the system resource utilization rate is high utilization rate, let =0, when the system resource utilization rate is normal =0, let =0; when the system resource utilization is low, =0, through the formula , calculate the system resource impact value ; Take the weighted sum of the system resource impact value and the system processing impact coefficient to obtain the time synchronization error impact coefficient .

[0016] In a preferred embodiment, the link quality data includes an optical signal attenuation influence fluctuation coefficient; a specific method for obtaining the optical signal attenuation influence fluctuation coefficient is as follows: obtaining waveforms of optical power and wavelength signals that vary with time, and collecting harmonics of the waveforms of optical power and wavelength signals that vary with time at a preset collection interval; performing harmonic analysis on the harmonics of the waveforms of optical power and wavelength signals that vary with time to obtain influence fluctuation quantities corresponding to the wavelength signal and the optical power signal; obtaining harmonic components of the wavelength signal and the optical power signal based on the influence fluctuation quantities of the wavelength signal and the optical power signal, and calculating the signal attenuation amplitude; and obtaining the optical signal attenuation influence fluctuation coefficient based on the variance of the signal attenuation amplitude.

[0017] In a preferred embodiment, the delay settings between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model are used as influencing variables to construct a delay setting effect-delay setting display model, specifically: the effect evaluation results of each group of delay settings are used as influencing variables, and the corresponding delay settings are used as independent variables, a relationship fluctuation curve is constructed based on a two-dimensional chart, and the relationship fluctuation curve is used as the delay setting effect-delay setting display model; and the delay setting effect-delay setting display model is converted into a delay mathematical model, specifically: a function model is constructed from the relationship fluctuation curve, and it is used as the delay mathematical model.

[0018] In a preferred embodiment, the data analysis of the delay mathematical model is performed to obtain the optimized delay setting between multiple nodes, and the delay setting is applied to each optical fiber node of the optical signal communication, specifically: the preset real-time optical signal communication control requirements and restrictions are obtained, and the real-time optical signal communication control requirements and restrictions are constructed into constraints; the constraints are combined with the delay mathematical model, and the solution is performed with the goal of minimizing the variation amplitude and the output value of the maximum delay mathematical model, and the solved independent variables and the delay setting between multiple nodes are used as the optimized delay setting between multiple nodes, and applied to each optical fiber node of the optical signal communication.

[0019] The technical effects and advantages of a control system based on optical signal communication of the present invention are as follows:

[0020] 1. The present invention conducts a comprehensive analysis of factors such as the type of optical fiber node, communication mode, network bandwidth and protocol requirements. The system can reasonably set the maximum tolerable delay of each node, thereby ensuring the stability of data transmission under different load conditions. The data packet loss fluctuation abnormality coefficient is used to monitor the packet loss in the network in real time, so that the system can effectively identify and adjust unreasonable delay settings and improve the reliability of data transmission. The time synchronization error influence coefficient ensures the accuracy and integrity of data transmission by evaluating the impact of delay on system clock synchronization, avoiding the occurrence of problems such as misordering and loss of data packets. This multi-level delay setting and real-time optimization mechanism not only improves the robustness and fault tolerance of the system, but also ensures the transmission efficiency and quality of optical signal communication through intelligent regulation, thereby adapting to the needs of different complex scenarios.

[0021] 2. The present invention realizes the intelligent optimization of multi-node delay settings in optical fiber networks by constructing a delay setting effect evaluation model based on long short-term neural network (LSTM). Specifically, the method quantifies clock synchronization data, link quality data, data packet loss, time synchronization error, optical signal attenuation and other factors and combines them into delay setting effect evaluation coefficients, thereby realizing accurate evaluation of delay effects. By constructing a delay setting effect-delay display model and converting it into a mathematical model, the delay settings between multiple nodes are refined and analyzed. Finally, the optimal delay setting is generated through the analysis and optimization of the delay mathematical model, ensuring the minimum fluctuation and efficient transmission of the delay setting under the premise of meeting the control requirements of optical signal communication. This scheme effectively improves the transmission efficiency and stability of the optical fiber network, provides a high-precision delay control scheme for multi-node optical signal communication, and significantly reduces data packet loss and transmission delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The figure is a schematic diagram of the structure of a control system based on optical signal communication of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Embodiment 1, Figure 1 The present invention provides a control system based on optical signal communication, comprising the following steps:

[0025] S1, a delay setting acquisition module, used to obtain node types and communication modes between multiple optical fiber nodes, obtain the maximum tolerable delay according to the node types and communication modes, and obtain the delay settings between several groups of multiple nodes according to the maximum tolerable delay;

[0026] The node types and communication modes between multiple optical fiber nodes are obtained, and the maximum tolerable delay is obtained according to the node types and communication modes, specifically:

[0027] Classify each fiber node, identify its type, and obtain the node hardware performance and processing requirements through the NMS and fiber node configuration files;

[0028] By analyzing the system topology and communication protocol, the communication mode between each node is identified, and the network bandwidth and protocol requirements of the corresponding communication mode are obtained;

[0029] Set the maximum tolerable delay based on network bandwidth, processing requirements, node hardware performance, and protocol requirements.

[0030] It should be noted that latency is closely related to bandwidth. The larger the bandwidth, the faster the transmission speed, and the greater the latency that can be tolerated. However, the efficiency of network bandwidth usage is also related to the size of the data packet, network congestion, and link quality. To set the maximum tolerable latency, first determine the bandwidth requirements, and then estimate the appropriate latency range based on the actual network conditions;

[0031] It should be noted that the node hardware performance (such as CPU processing power, memory, cache size) will affect its data processing speed and response time. If the node has strong processing power and can quickly process and forward data, then the delay tolerance can be relatively large; but if the node performance is poor, the delay tolerance should be set to a smaller value to ensure timely response;

[0032] It should be noted that, assuming there are two nodes, one is a high-performance server node equipped with multi-core CPU and large-capacity memory, and the other is a low-performance edge device with only basic computing and storage capabilities. For the high-performance node, its delay tolerance can be set to 50ms, because it can process and forward data quickly. For the low-performance node, the delay tolerance should be set to 10ms to avoid communication bottlenecks caused by processing delays;

[0033] It should be noted that different protocols have different tolerance requirements for latency. For example, real-time communication protocols (such as VoIP and video conferencing) have strict latency requirements, which usually cannot exceed 150ms, while some bulk data transmission protocols (such as FTP) can tolerate longer latency.

[0034] It should be noted that, assuming the network bandwidth is 10 Gbps and the data size to be transmitted is 1 MB (8 Mb), the theoretical minimum time required for a single transmission is calculated by the ratio of bandwidth size to data size, which is 0.8 milliseconds;

[0035] It should be noted that if a real-time communication protocol (such as H.323, SIP) is used for video calls, the protocol requires a delay of no more than 150ms. According to the protocol requirements, the delay tolerance can be set to within 100ms. If the protocol is TCP / IP or FTP for file transfer, the delay tolerance can be set to 500ms or even longer, depending on the actual network load and bandwidth.

[0036] The above-mentioned maximum tolerable delay can be set in a different way according to the actual situation. There are many mature methods, which will not be described here.

[0037] It should be noted that optical signal communication is essentially the transmission of signals through media such as optical fibers, and the transmission speed of optical signals is usually close to the speed of light. In a multi-node system, when a signal is transmitted from one node to another, a propagation delay will be introduced, especially for long-distance transmission or multiple relay nodes, the delay difference may increase. In order to ensure the accuracy of system synchronization control, the signal propagation delay of each node needs to be calculated and compensated.

[0038] The delay settings between multiple groups of nodes are obtained according to the maximum tolerable delay, specifically:

[0039] Determine the delay setting range between adjacent nodes based on the maximum tolerable delay of each node;

[0040] Within the delay setting range between each pair of adjacent nodes, several groups of different delay configurations are generated through random number interference.

[0041] S2, an optical signal communication analysis module, is used to apply the delay setting between each group of multiple nodes to the nodes of optical fiber propagation respectively, and obtain clock synchronization data and link quality data during optical signal communication.

[0042] The clock synchronization data includes a data packet loss fluctuation abnormality coefficient and a time synchronization error influence coefficient; the link quality data includes an optical signal attenuation influence fluctuation coefficient;

[0043] The data packet loss fluctuation anomaly coefficient is used to measure the fluctuation and abnormality of data packet loss in the network under the multi-node synchronous delay setting of the optical signal communication system. This coefficient evaluates the network stability by analyzing the frequency and distribution pattern of data packet loss under different network load and delay conditions. A high fluctuation anomaly coefficient indicates that the packet loss phenomenon is more serious, which may be caused by excessive delay or unbalanced network settings, resulting in data loss and retransmission, thus affecting the reliability and stability of the system. Therefore, this coefficient is an important indicator for evaluating the performance of optical signal communication systems under different delay settings.

[0044] Analyzing the data packet loss fluctuation anomaly coefficient has the following advantages for evaluating the effect of optical signal communication systems under multi-node synchronous delay settings:

[0045] Accurately evaluate network stability: The data packet loss fluctuation anomaly coefficient can quantify the frequency and fluctuation of packet loss in the network, providing intuitive data support for evaluating the stability of the system under different delay settings. Through this coefficient, it is possible to effectively identify packet loss problems caused by excessive or unbalanced delays, and help optimize delay settings.

[0046] Identify latency imbalance: This coefficient can highlight data packet loss and network bottlenecks caused by latency imbalance, especially under high load or congestion conditions, where the system may experience large-scale data loss. By analyzing the abnormality of packet loss fluctuations, it can provide a basis for adjusting the latency between nodes, ensuring the balance of communication quality of each node, thereby improving the overall reliability of the network.

[0047] Improve system robustness: The data packet loss fluctuation anomaly coefficient helps evaluate the system's fault tolerance under different network conditions. When unreasonable delay settings lead to increased packet loss, the system's fault tolerance and robustness will decrease. This coefficient can be used to detect and adjust delays in advance, optimize system performance, and improve overall anti-interference capabilities.

[0048] Optimize network performance: By monitoring and analyzing the data packet loss fluctuation abnormality coefficient, it can help decision makers identify the negative impact of excessive or insufficient delay settings on optical signal transmission, and then optimize the multi-node synchronization delay settings, reduce packet loss rates, and improve network data transmission efficiency and quality.

[0049] Real-time optimization: The packet loss fluctuation anomaly coefficient provides real-time data feedback, so that the delay setting can be dynamically adjusted according to the packet loss fluctuation during actual operation, thereby achieving more refined and flexible network control and improving the system's adaptability in unstable environments.

[0050] The method for obtaining the data packet loss fluctuation abnormality coefficient is as follows:

[0051] Record each fiber transmission node in the optical signal communication, obtain the topological relationship number between each node, obtain the packet loss data ratio and packet loss detection frequency of each transmission node, and the topological weight and distance between adjacent transmission nodes;

[0052] According to the topological relationship number, the packet loss data ratio and packet loss detection frequency of each transmission node are obtained, and the packet loss fluctuation value is calculated based on the topological weight and distance between adjacent transmission nodes.

[0053] The calculation method of the packet loss fluctuation value is as follows:

[0054]

[0055] In the formula, is the packet loss fluctuation value, is the packet loss rate of the node, is the packet loss detection frequency, is the node number, is the total number of nodes, is the topological weight between two nodes, is the distance between two nodes; Label the topological relationships between nodes. is the total number of connections between nodes;

[0056] Calculate the data packet loss fluctuation abnormality coefficient. The specific calculation method is as follows:

[0057]

[0058] In the formula, is the data packet loss fluctuation abnormality coefficient, is the packet loss fluctuation value at time x, is the preset standard packet loss fluctuation value, and g is the range of detection time.

[0059] The time synchronization error impact coefficient is used to measure the impact of time synchronization errors on data transmission caused by improper delay settings in optical signal communication systems. This coefficient evaluates the coordination and accuracy of delay settings on data transmission between multiple nodes by analyzing the relationship between synchronization errors and delays. Too long or too short delays will cause synchronization errors, which may cause data packets to be misordered, lost, or delayed, especially in systems that require high-precision synchronization (such as synchronous optical transmission networks). Therefore, the time synchronization error impact coefficient is an important indicator for evaluating the signal transmission order and data integrity of optical signal communication systems under different delay settings.

[0060] Analyzing the time synchronization error influence coefficient has the following advantages for evaluating the effect of optical signal communication system under multi-node synchronization delay setting:

[0061] Accurately evaluate synchronization accuracy: The time synchronization error impact coefficient can quantify the impact of the delay setting on the system clock synchronization accuracy, providing an objective evaluation standard for multi-node synchronization control. Through this coefficient, the synchronization error caused by unreasonable delay settings can be clearly identified, thereby optimizing the delay setting and ensuring higher synchronization accuracy.

[0062] Improve data transmission integrity: The impact of delay settings on synchronization accuracy is directly related to the transmission order and integrity of data packets. By analyzing the time synchronization error influence coefficient, the delay settings can be identified and optimized to avoid data loss, misordered or repeated reception, and improve the reliability and data accuracy of the optical signal communication system.

[0063] Avoid signal conflicts and interference: Improper delay settings may cause signal conflicts or interference between multiple nodes, affecting system stability. By analyzing this coefficient, inappropriate delay settings can be discovered and adjusted in a timely manner to reduce synchronization errors between nodes, thereby reducing the risk of signal conflicts and ensuring smooth operation of the system.

[0064] Optimize system performance: The time synchronization error impact coefficient helps to evaluate the impact of the delay setting on the entire network, thereby optimizing network performance. By analyzing this coefficient, the optimal delay setting can be determined so that each node can achieve a lower error when synchronizing data, improving the transmission efficiency and accuracy of the system.

[0065] Improve system robustness: The time synchronization error impact coefficient provides a sensitivity assessment of the effect of delay changes on synchronization, so that in actual applications, the delay setting can be dynamically adjusted according to network conditions, improving the system's adaptability under different working conditions and enhancing overall robustness.

[0066] Enhance system fault tolerance: Through the analysis of this coefficient, possible synchronization problems and potential risk points can be identified in advance, so as to adjust the delay settings and enhance the system's fault tolerance, ensuring that even under some extreme conditions, the system can still maintain good synchronization accuracy and reduce the impact of errors on communication quality.

[0067] The method for obtaining the time synchronization error influence coefficient is as follows:

[0068] Set the time synchronization error standard value to mark it as , detect the system processing time value of the cumulative impact of multiple nodes. When the system processing time value of the cumulative impact of multiple nodes exceeds the preset value Time minus , when the system processing time value of the cumulative impact of multiple nodes is arrive Increase between , when the system processing time value of the cumulative impact of multiple nodes is lower than Time minus ;

[0069] When the system processing time value affected by multiple nodes cumulatively exceeds the preset value Time will and Set to 0;

[0070] When the system processing time value of the cumulative impact of multiple nodes is arrive In between, and Set to 0;

[0071] When the system processing time value of the cumulative impact of multiple nodes is lower than When and Set to 0;

[0072] By formula , obtain the system processing influence coefficient ;

[0073] Set the system basic resource utilization ; Obtain the system resource utilization of the node, wherein the system resource utilization is divided into high utilization, general utilization, and low utilization;

[0074] Increase when system resource utilization is high , when the system resource utilization is low, subtract , when the system resource utilization belongs to the general utilization, it remains unchanged;

[0075] When the system resource utilization is high, =0, when the system resource utilization rate is normal =0, let =0; when the system resource utilization is low, =0, through the formula , calculate the system resource impact value ;

[0076] The system resource impact value and the system processing impact coefficient are weighted and summed to obtain the time synchronization error impact coefficient. .

[0077] It should be noted that the above parameters are preset values ​​based on actual conditions and real-time requirements. The weight of the weighted sum of the system resource impact value and the system processing impact coefficient is 1 by default and can be adjusted as needed.

[0078] The optical signal attenuation fluctuation coefficient is used to measure the impact of signal attenuation on link quality in optical fiber communications. This coefficient reflects the quality fluctuation caused by attenuation during the transmission process, which usually increases with the increase of transmission distance. The increase in delay means that the signal takes longer to propagate on the link, which increases the chance of attenuation. If the delay is set too long and the link quality is poor, the signal attenuation may exceed the tolerance threshold of the system, resulting in signal distortion, increased bit error rate, and even data loss or reception failure. Therefore, the optical signal attenuation fluctuation coefficient can effectively evaluate the signal quality changes and provide a basis for optimizing the delay setting under the multi-node synchronous delay setting.

[0079] Analyzing the influence of optical signal attenuation on the fluctuation coefficient has the following advantages for evaluating the effect of optical signal communication systems under multi-node synchronous delay settings:

[0080] Accurately evaluate link quality: This coefficient can effectively reflect the link quality fluctuation caused by attenuation during optical fiber transmission, thereby helping to analyze the impact of latency on signal transmission quality. By quantifying the impact of attenuation, the performance of the link under different latency settings can be more accurately evaluated.

[0081] Optimize latency configuration: By monitoring attenuation fluctuations, the potential risk of excessive attenuation when the latency is too long or the link is unstable can be discovered, thereby providing data support for optimizing latency settings and ensuring that signal quality remains within an acceptable range under different transmission distances and conditions.

[0082] Enhance system robustness: The attenuation impact fluctuation coefficient helps reveal the impact of signal attenuation on the robustness and reliability of the communication system. Effective delay settings can reduce the impact of attenuation, reduce the risk of bit error rate and data loss, and thus improve the overall reliability of the system.

[0083] Improve fault prediction capabilities: This coefficient can also identify and warn in advance when potential problems occur in the optical fiber communication link, reduce communication failures caused by unreasonable delays or poor link quality, and make corrections and optimizations in advance.

[0084] In summary, the fluctuation coefficient of optical signal attenuation provides an effective measurement tool for the evaluation of multi-node synchronization delay, which helps to optimize the delay setting and improve the quality and stability of the optical signal communication system.

[0085] Acquire the waveform of the optical power and wavelength signal changing with time, and collect the harmonics of the waveform of the optical power and wavelength signal changing with time at a preset collection interval;

[0086] Perform harmonic analysis on the harmonics of the waveforms of the optical power and wavelength signals that vary with time, and obtain the influencing fluctuation quantities corresponding to the wavelength signal and the optical power signal;

[0087] The harmonic components of the wavelength signal and the optical power signal are obtained according to the influence fluctuation quantity of the wavelength signal and the optical power signal, and the signal attenuation amplitude is calculated;

[0088] The optical signal attenuation influence fluctuation coefficient is calculated based on the variance of the signal attenuation amplitude.

[0089] The specific calculation formula for the fluctuation coefficient affected by the attenuation of the optical signal is as follows:

[0090]

[0091] In the formula, is the fluctuation coefficient affected by the attenuation of the optical signal, is the amount that affects the fluctuation, is the number of wavelength time series, z is the time point of the wavelength time series, j is the number that affects the fluctuation amount, is the inverse Fourier transform, is the optical power waveform, is the wavelength waveform, is the average optical power, is the average wavelength.

[0092] This embodiment conducts a comprehensive analysis of factors such as the type of optical fiber node, communication mode, network bandwidth, and protocol requirements. The system can reasonably set the maximum tolerable delay for each node, thereby ensuring the stability of data transmission under different load conditions. The data packet loss fluctuation abnormality coefficient is used to monitor the packet loss in the network in real time, so that the system can effectively identify and adjust unreasonable delay settings and improve the reliability of data transmission. The time synchronization error influence coefficient ensures the accuracy and integrity of data transmission by evaluating the impact of delay on system clock synchronization, avoiding the occurrence of problems such as misordering and loss of data packets. This multi-level delay setting and real-time optimization mechanism not only improves the robustness and fault tolerance of the system, but also ensures the transmission efficiency and quality of optical signal communication through intelligent regulation, thereby adapting to the needs of different complex scenarios.

[0093] S3, a delay setting evaluation module, is used to build a delay setting effect evaluation model based on long-term and short-term neural networks according to clock synchronization data and link quality data.

[0094] The delay setting effect evaluation model is constructed based on the long-term and short-term neural network according to the clock synchronization data and the link quality data, specifically:

[0095] The acquired data packet loss fluctuation abnormality coefficient, time synchronization error influence coefficient and optical signal attenuation influence fluctuation coefficient are used to establish a delay setting effect evaluation model, and generate a delay setting effect evaluation coefficient;

[0096] The calculation formula of the delay setting effect evaluation coefficient is as follows:

[0097]

[0098] In the formula, Set the effect evaluation coefficient for the delay. is the preset proportional coefficient of the data packet loss fluctuation abnormality coefficient, is the preset proportional coefficient of the time synchronization error influence coefficient, is the preset proportional coefficient of the fluctuation coefficient affected by the attenuation of the optical signal, is the data packet loss fluctuation abnormality coefficient, is the time synchronization error influence coefficient, The fluctuation coefficient is affected by the attenuation of the optical signal.

[0099] S4, a delay model display module, is used to take the delay settings between several groups of multi-nodes and the output of the corresponding delay setting effect evaluation model as influencing variables, construct a delay setting effect-delay setting display model, and convert the delay setting effect-delay setting display model into a delay mathematical model.

[0100] The delay settings between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model are used as influencing variables to construct a delay setting effect-delay setting display model, specifically:

[0101] The effect evaluation results of each group of delay settings are used as influencing variables, and the corresponding delay settings are used as independent variables. A relationship fluctuation curve is constructed based on a two-dimensional chart, and the relationship fluctuation curve is used as a delay setting effect-delay setting display model;

[0102] The delay setting effect-delay setting display model is converted into a delay mathematical model, specifically:

[0103] The relationship fluctuation curve is constructed into a function model and used as a mathematical model of time delay.

[0104] S5, a delay setting optimization module, is used to perform data analysis on the delay mathematical model, obtain the optimized delay setting between multiple nodes, and apply it to each optical fiber node of the optical signal communication.

[0105] The data analysis of the delay mathematical model is performed to obtain the optimized delay setting between multiple nodes, and is applied to each optical fiber node of the optical signal communication, specifically:

[0106] Obtaining preset requirements and restrictions of real-time optical signal communication control, and constructing the requirements and restrictions of real-time optical signal communication control into constraint conditions;

[0107] The constraints are combined with the delay mathematical model, and the solution is performed with the goal of minimizing the variation range and the output value of the maximum delay mathematical model. The solved independent variables and the delay settings between multiple nodes are used as the optimized delay settings between multiple nodes and applied to each optical fiber node of optical signal communication.

[0108] This embodiment realizes the intelligent optimization of multi-node delay settings in the optical fiber network by constructing a delay setting effect evaluation model based on the long short-term neural network (LSTM). Specifically, this method quantifies clock synchronization data, link quality data, data packet loss, time synchronization error, optical signal attenuation and other factors and combines them into delay setting effect evaluation coefficients, thereby realizing accurate evaluation of delay effects. By constructing a delay setting effect-delay display model and converting it into a mathematical model, the delay settings between multiple nodes are refined and analyzed. Finally, through the analysis and optimization of the delay mathematical model, the optimal delay setting is generated, ensuring the minimum fluctuation and efficient transmission of the delay setting under the premise of meeting the control requirements of optical signal communication. This solution effectively improves the transmission efficiency and stability of the optical fiber network, provides a high-precision delay control solution for multi-node optical signal communication, and significantly reduces data packet loss and transmission delay.

[0109] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0110] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0111] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0112] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0113] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0114] Finally: The above description is only a preferred 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 should be included in the protection scope of the present invention.

Claims

1. A control system based on optical signal communication, characterized in that: It includes delay setting acquisition module, optical signal communication analysis module, delay setting evaluation module, delay model display module and delay setting optimization module: A delay setting acquisition module is used to obtain the node type and communication mode between multiple optical fiber nodes, obtain the maximum tolerable delay according to the node type and the communication mode, and obtain the delay setting between several groups of multiple nodes according to the maximum tolerable delay; An optical signal communication analysis module, used to apply the delay setting between each group of multiple nodes to the nodes of optical fiber propagation respectively, and obtain clock synchronization data and link quality data during optical signal communication; A delay setting evaluation module is used to construct a delay setting effect evaluation model based on a long-term and short-term neural network according to clock synchronization data and link quality data; The delay model display module is used to use the delay settings between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model as influencing variables, construct a delay setting effect-delay setting display model, and convert the delay setting effect-delay setting display model into a delay mathematical model; The delay setting optimization module is used to perform data analysis on the delay mathematical model, obtain the optimized delay setting between multiple nodes, and apply it to each optical fiber node of the optical signal communication.

2. The control system based on optical signal communication according to claim 1, characterized in that: The node types and communication modes between multiple optical fiber nodes are obtained, and the maximum tolerable delay is obtained according to the node types and communication modes, specifically: Classify each fiber node, identify its type, and obtain the node hardware performance and processing requirements through the NMS and fiber node configuration files; By analyzing the system topology and communication protocol, the communication mode between each node is identified, and the network bandwidth and protocol requirements of the corresponding communication mode are obtained; Set the maximum tolerable delay based on network bandwidth, processing requirements, node hardware performance, and protocol requirements.

3. The control system based on optical signal communication according to claim 2, characterized in that: The delay settings between multiple groups of nodes are obtained according to the maximum tolerable delay, specifically: Determine the delay setting range between adjacent nodes based on the maximum tolerable delay of each node; Within the delay setting range between each pair of adjacent nodes, several groups of different delay configurations are generated through random number interference.

4. The control system based on optical signal communication according to claim 3, characterized in that: The clock synchronization data includes a data packet loss fluctuation abnormality coefficient and a time synchronization error influence coefficient; the method for obtaining the data packet loss fluctuation abnormality coefficient is as follows: Record each fiber transmission node in the optical signal communication, obtain the topological relationship number between each node, obtain the packet loss data ratio and packet loss detection frequency of each transmission node, and the topological weight and distance between adjacent transmission nodes; According to the topological relationship number, the packet loss data ratio and packet loss detection frequency of each transmission node are obtained, and the packet loss fluctuation value is calculated based on the topological weight and distance between adjacent transmission nodes.

5. The control system based on optical signal communication according to claim 4, characterized in that: The method for obtaining the time synchronization error influence coefficient is as follows: Set the time synchronization error standard value to mark it as , detect the system processing time value of the cumulative impact of multiple nodes. When the system processing time value of the cumulative impact of multiple nodes exceeds the preset value Time minus , when the system processing time value of the cumulative impact of multiple nodes is arrive Increase between , when the system processing time value of the cumulative impact of multiple nodes is lower than Time minus ; When the system processing time value affected by multiple nodes cumulatively exceeds the preset value Time will and Set to 0; When the system processing time value of the cumulative impact of multiple nodes is arrive In between, and Set to 0; When the system processing time value of the cumulative impact of multiple nodes is lower than When and Set to 0; By formula , obtain the system processing influence coefficient ; Set the system basic resource utilization ; Obtain the system resource utilization of the node, wherein the system resource utilization is divided into high utilization, general utilization, and low utilization; Increase when system resource utilization is high , when the system resource utilization is low, subtract , when the system resource utilization belongs to the general utilization, it remains unchanged; When the system resource utilization is high, =0, when the system resource utilization rate is normal =0, let =0; when the system resource utilization is low, =0, through the formula , calculate the system resource impact value ; The system resource impact value and the system processing impact coefficient are weighted and summed to obtain the time synchronization error impact coefficient. .

6. The control system based on optical signal communication according to claim 5, characterized in that: The link quality data includes the optical signal attenuation influence fluctuation coefficient; the specific method for obtaining the optical signal attenuation influence fluctuation coefficient is as follows: Acquire the waveform of the optical power and wavelength signal changing with time, and collect the harmonics of the waveform of the optical power and wavelength signal changing with time at a preset collection interval; Perform harmonic analysis on the harmonics of the waveforms of the optical power and wavelength signals that vary with time, and obtain the influencing fluctuation quantities corresponding to the wavelength signal and the optical power signal; The harmonic components of the wavelength signal and the optical power signal are obtained according to the influence fluctuation quantities of the wavelength signal and the optical power signal, and the signal attenuation amplitude is calculated; The optical signal attenuation influence fluctuation coefficient is calculated based on the variance of the signal attenuation amplitude.

7. The control system based on optical signal communication according to claim 6, characterized in that: The delay settings between several groups of multiple nodes and the output of the corresponding delay setting effect evaluation model are used as influencing variables to construct a delay setting effect-delay setting display model, specifically: The effect evaluation results of each group of delay settings are used as influencing variables, and the corresponding delay settings are used as independent variables. A relationship fluctuation curve is constructed based on a two-dimensional chart, and the relationship fluctuation curve is used as a delay setting effect-delay setting display model; The delay setting effect-delay setting display model is converted into a delay mathematical model, specifically: The relationship fluctuation curve is constructed into a function model and used as a mathematical model of time delay.

8. The control system based on optical signal communication according to claim 7, characterized in that: The data analysis of the delay mathematical model is performed to obtain the optimized delay setting between multiple nodes, and is applied to each optical fiber node of the optical signal communication, specifically: Obtaining preset requirements and restrictions of real-time optical signal communication control, and constructing the requirements and restrictions of real-time optical signal communication control into constraint conditions; The constraints are combined with the delay mathematical model, and the solution is performed with the goal of minimizing the variation range and the output value of the maximum delay mathematical model. The solved independent variables and the delay settings between multiple nodes are used as the optimized delay settings between multiple nodes and applied to each optical fiber node of optical signal communication.

9. The control system based on optical signal communication according to claim 8, characterized in that: The specific calculation formula of the fluctuation coefficient affected by the optical signal attenuation is as follows: In the formula, is the fluctuation coefficient affected by the attenuation of the optical signal, is the amount that affects the fluctuation, is the number of wavelength time series, z is the time point of the wavelength time series, j is the number that affects the fluctuation amount, is the inverse Fourier transform, is the optical power waveform, is the wavelength waveform, is the average optical power, is the average wavelength.

10. The control system based on optical signal communication according to claim 9, characterized in that: The calculation method of the packet loss fluctuation value is as follows: In the formula, is the packet loss fluctuation value, is the packet loss rate of the node, is the packet loss detection frequency, is the node number, is the total number of nodes, is the topological weight between two nodes, is the distance between two nodes; Label the topological relationships between nodes. is the total number of connections between nodes; Calculate the data packet loss fluctuation abnormality coefficient. The specific calculation method is as follows: In the formula, is the data packet loss fluctuation abnormality coefficient, is the packet loss fluctuation value at time x, is the preset standard packet loss fluctuation value, and g is the range of detection time.

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