Tunnel electromechanical equipment twin network synchronization control system based on IPv6+

Abstract

The present invention discloses a twin network synchronization control system for tunnel electromechanical equipment based on IPv6+, which relates to the field of digital twin technology and includes a model construction module, a synchronous acquisition module, an information fusion module, a synchronous control module, an analysis module, and an adaptive feedback module. Through the twin network synchronization control system, the present invention realizes precise management of the operation state of equipment and improvement of safety by synchronously acquiring, analyzing, and feeding back the operation data of tunnel electromechanical equipment in real time, effectively ensuring the safe operation of the tunnel.

Description

Technical Field

[0001] The present invention relates to the technical field of twin network synchronization control systems, and particularly to a twin network synchronization control system for tunnel electromechanical equipment based on IPv6+. Background Art

[0002] With the development of tunnel safety, equipment digitization, and information management, ensuring the effective convergence of facilities, traffic flow, and environmental factors within the tunnel is the key to the normal operation of equipment and safe passage. Currently, the broadcast service is developing towards full IP, and the IP data network is evolving towards fixed-mobile convergence, cloud-network collaboration, and multi-service convergence bearer. A series of "IPv6+" technologies represented by SRv6, FlexE, iFIT, etc. have become important technical bases for promoting tunnel informatization and intelligent control.

[0003] The development of digital twin technology has brought new opportunities for the intelligent management of tunnel electromechanical equipment. By establishing a digital twin model of the equipment, real-time monitoring of various types of equipment in the tunnel can be carried out with the combination of virtual and real, and all-round perception and analysis of the equipment operation status can be achieved. The twin network synchronization control system can establish a digital twin body of tunnel electromechanical equipment, collect and synchronize the control signals and operation parameters of the equipment in real time, and then through the synchronous control and analysis of virtual equipment and actual equipment, achieve precise control and risk warning of the equipment in the tunnel. This technology not only improves the intelligent level of equipment management but also significantly enhances the safety and reliability of the overall operation of the tunnel.

[0004] Currently, the twin network synchronization control system for tunnel electromechanical equipment based on IPv6+ is still in the exploration stage, lacking specific networking practices and standardized methods for constructing equipment twin models. At the same time, the existing network architecture still has bottlenecks in realizing the synchronous acquisition and processing of multi-source data, and it is difficult to effectively meet the real-time data transmission and control requirements of the equipment in the tunnel. Therefore, establishing an efficient and reliable twin network synchronization control system to achieve comprehensive monitoring, data fusion analysis, and intelligent optimization of tunnel electromechanical equipment is the key direction to solve the current technical bottleneck. Summary of the Invention

[0005] The purpose of the present invention is to provide a twin network synchronization control system for tunnel electromechanical equipment based on IPv6+ to solve the following technical problems:

[0006] How to achieve synchronous control and real-time data conversion of communication information and electrical signals, improve the information management of tunnel electromechanical equipment, and enhance network security control.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] Tunnel electromechanical equipment twin network synchronization control system based on IPv6+, characterized by including:

[0009] A model construction module, used to collect spatial data of the tunnel electromechanical area and establish a digital twin model of the electromechanical area according to the spatial data of the electromechanical area;

[0010] A synchronous acquisition module, used to synchronously collect real-time control signal data and real-time electrical performance parameters of tunnel electromechanical equipment through multiple sensors;

[0011] An information fusion module, used to perform fusion simulation analysis on the real-time control signal data obtained from each preset path according to the data fusion strategy and obtain the standard electrical performance parameters of each preset path;

[0012] A synchronous control module, used to synchronously control the safe operation state of tunnel electromechanical equipment on a preset path according to the real-time control signal data;

[0013] An analysis module, used to compare the real-time electrical performance parameters and standard electrical performance parameters of tunnel electromechanical equipment on each preset path under synchronous control, and judge the safety of the power supply state of the tunnel electromechanical equipment on the current path according to the comparison analysis result;

[0014] An adaptive feedback module, used to feedback and adjust the data fusion strategy according to the analysis result of the power supply state safety, and realize the automatic optimization of the control signal data of the synchronous control module.

[0015] Preferably, the data fusion strategy is:

[0016] Set an initial calibration instruction to calibrate the real-time control signal data on each path to obtain different calibration parameters;

[0017] Extract the set of change curves of different calibration parameters under continuous calibration cycles;

[0018] Select and assign weight values according to the change characteristics of each curve, and input them into a deep learning model for data fusion;

[0019] Reconstruct according to the characteristics of the fused data, and output the standard electrical performance parameters through the electromechanical equipment operation simulation circuit.

[0020] Preferably, the comparison and analysis process of the analysis module is:

[0021] Through the formula Calculate the operation state risk value Ris of the i-th preset path i :

[0022] Where, N is the number of monitored electrical performance parameters, j ∈ [1, N]; Ls ij (t) is the real-time electrical performance parameter of the j-th item of the i-th preset path; Lsij (t) ′ is the standard electrical performance parameter of the j-th item of the i-th preset path; Ls (i-1)j (t) is the real-time electrical performance parameter of the j-th item of the (i - 1)-th preset path; Ls (i-1)j (t) ′ is the standard electrical performance parameter of the j-th item of the (i - 1)-th preset path; q i is the preset adjustment coefficient for the difference in the influence of the i-th preset path on each electrical performance parameter; q i-1 is the preset adjustment coefficient for the difference in the influence of the (i - 1)-th preset path on each electrical performance parameter; ΔLs j is the allowable error value of the j-th electrical performance parameter; σ j is the preset weight coefficient of the j-th electrical performance parameter.

[0023] Preferably, the process of judging the safety of the operating state is as follows:

[0024] Compare the operating state risk value Ris i with the preset standard threshold interval [Ris A , Ris B as follows:

[0025] If Ris A ≤Ris i ≤Ris B , it is judged that there is a risk in the power supply of the tunnel electromechanical equipment on the current path, and the data fusion strategy is fed back for adjustment; [[ID=4)]

[0026] If Ris i <Ris A , it is judged that the power supply state of the tunnel electromechanical equipment on the current path is normal;

[0027] If Ris i >Ris B , it is judged that the power supply state of the tunnel electromechanical equipment on the current path is abnormal, and a maintenance instruction is generated.

[0028] Preferably, the synchronization control module further includes:

[0029] A monitoring unit for obtaining the operating state information of the tunnel electromechanical equipment;

[0030] The operating state information includes the temperature data of the electromechanical equipment on each path, the running sound signal data of the electromechanical equipment on each path, and the voltage data of the electromechanical equipment on each path;

[0031] An early warning unit for performing safety monitoring on the operating state information of the tunnel electromechanical equipment according to the operating state of the tunnel electromechanical equipment.

[0032] Preferably, the process by which the monitoring unit obtains the operation status information of the tunnel electromechanical equipment is as follows:

[0033] Through the formula Calculate the real-time equipment operation risk value Equ(t); where M is the total number of monitoring paths, l ∈ [1, M]; [t1, t2] is the monitoring time period interval; T l (t) is the real-time electromechanical equipment temperature data of the l-th monitoring path; V l (t) is the real-time electromechanical equipment operation sound signal data of the l-th monitoring path; W l (t) is the real-time electromechanical equipment voltage data of the l-th monitoring path; α is the first influence function, β is the second influence function, γ is the third influence function, and α, β, γ are all greater than 0; τ l is the position coefficient of the l-th monitoring path;

[0034] Compare the real-time equipment operation risk value Equ(t) with the preset threshold Equ thr as follows:

[0035] If Equ(t) > Equ thr , it is determined that there is a safety risk in the operation status of the tunnel electromechanical equipment, and the warning unit issues a warning signal and generates a maintenance instruction.

[0036] Preferably, the twin network synchronization control system is connected to the electromechanical equipment communication control system through an IPV6+ converter, and the electromechanical equipment communication control system includes a device multi-service type interface, a service signal processing module, and a self-organizing network fusion module;

[0037] The multi-service type interface is electrically connected to the service signal processing module, and the multi-service type interface is used to generate multi-modal signals and perform electrical transmission;

[0038] The service signal processing module is used to receive the multi-modal signals and perform digital-to-analog conversion into control signal data;

[0039] The self-organizing network fusion module transmits the control signal numbers through multiple preset paths of the wireless network.

[0040] By adopting the above technical solutions, the present invention mainly has the following technical effects:

[0041] The twin network synchronization control system of the present invention includes six components: a model construction module, a synchronization acquisition module, an information fusion module, a synchronization control module, an analysis module, and an adaptive feedback module. Through the twin network synchronization control system, the control signal data of multiple paths and the safe operation and data analysis process of its related electromechanical equipment are realized, and real-time signal response can be made according to the electromechanical equipment communication control system in a timely manner; through the generation of multi-modal signals, the acquisition method of control signal data, the data fusion strategy, and the comparison and analysis process, the process of timely warning and signal monitoring of the safe operation state of tunnel electromechanical equipment is realized. Brief Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic diagram of the twin network synchronization control system for tunnel electromechanical equipment based on IPV6+. Detailed Embodiments

[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0045] As Figure 1 shown, the present invention provides a twin network synchronization control system for tunnel electromechanical equipment based on IPV6+. When the twin network synchronization control system for tunnel electromechanical equipment based on IPV6+ is actually applied, in order to adapt to the electromechanical equipment communication control system, it is used for information management and network security control of tunnel electromechanical equipment.

[0046] In some embodiments, the electromechanical equipment communication control system may include a device multi-service type interface, a service signal processing module, and a self-organizing network fusion module;

[0047] The multi-service type interface is electrically connected to the service signal processing module, and the multi-service type interface is used to generate multi-modal signals and perform electrical transmission;

[0048] The service signal processing module is used to receive multi-modal signals and perform digital-to-analog conversion into control signal data;

[0049] The self-organizing network fusion module transmits control signal data through multiple preset paths of the wireless network.

[0050] In some embodiments, the twin network synchronization control system includes:

[0051] A model construction module, configured to collect spatial data of the tunnel electromechanical area and establish a digital twin model of the electromechanical area based on the spatial data of the electromechanical area;

[0052] A synchronous acquisition module, configured to synchronously acquire real-time control signal data and real-time electrical performance parameters of tunnel electromechanical equipment through multiple sensors;

[0053] An information fusion module, configured to perform fusion simulation analysis on the real-time control signal data obtained through each preset path according to a data fusion strategy and obtain standard electrical performance parameters of each preset path;

[0054] A synchronous control module, configured to synchronously control the safe operation state of tunnel electromechanical equipment on a preset path according to the real-time control signal data;

[0055] An analysis module, configured to compare the real-time electrical performance parameters and standard electrical performance parameters of tunnel electromechanical equipment on each preset path under synchronous control, and judge the safety of the power supply state of the tunnel electromechanical equipment on the current path according to the comparison analysis result;

[0056] An adaptive feedback module, configured to feedback and adjust the data fusion strategy according to the analysis result of the power supply state safety, and realize the automatic optimization of the control signal data of the synchronous control module.

[0057] In the above technical solution, in this embodiment, the twin network synchronization control system and the electromechanical equipment communication control system perform synchronous conversion control on network signals and electrical signals to ensure the synchronous input and output process of signals of the multi-network fusion control system of tunnel electromechanical equipment.

[0058] For example, the electromechanical equipment communication control system may include a device multi-service type interface, a service signal processing module, and a self-organizing network fusion module; through the electromechanical equipment communication control system, accurate acquisition, real-time processing, precise fusion of service communication control signals, and the digital output process of control signals are realized.

[0059] Specifically, the control data corresponding to the service communication signals transmitted by the electromechanical devices on different paths are different; specifically, by electrically connecting the multi-service type interface with the service signal processing module, and the multi-service type interface is used to generate multi-modal signals and perform electrical transmission; through the process of electrical transmission, the multi-service type signals are transmitted through the interface communication as multi-modal signals, and then the service signal processing module is set to receive the multi-modal signals and convert them into control signal data through digital-to-analog conversion, and ensure the further analysis and processing process of the device power data by converting the electrical signals into the data form of control signals; finally, the self-organizing network fusion module is set to transmit the control signal data through multiple preset paths of the wireless network to achieve the accurate transmission process of the control signal data.

[0060] Furthermore, the twin network synchronization control system includes six components: a model construction module, a synchronization acquisition module, an information fusion module, a synchronization control module, an analysis module, and an adaptive feedback module. Through the twin network synchronization control system, the safe operation and data analysis process of the control signal data on multiple paths and its related electromechanical devices are realized, and real-time signal response can be made according to the electromechanical device communication control system in a timely manner. [[ID=!]]

[0061] Specifically, the model construction module is set to realize the real-time acquisition of the spatial data of the tunnel electromechanical area, and establish a digital twin model of the electromechanical area according to the electromechanical area space; through the digital twin model of the electromechanical area, the synchronization process between virtual and reality is realized. Then, the synchronization acquisition module is set to synchronously acquire the real-time control signal data and real-time electrical performance parameters of the tunnel electromechanical devices through multiple sensors; and, through the information fusion module, the real-time control signal data obtained from each preset path is subjected to fusion simulation analysis according to the data fusion strategy to obtain the standard electrical performance parameters of each preset path.

[0062] Next, the synchronization control module is set to synchronously control the safe operation state of the tunnel electromechanical devices on the preset path according to the real-time control signal data; and through the synchronization control module, the operation conditions of the tunnel electromechanical devices are further analyzed, and then the acquisition method of the real-time control signal data of the devices is adjusted according to the operation state of the tunnel electromechanical devices; further, the analysis module is set to compare the real-time electrical performance parameters and standard electrical performance parameters of the tunnel electromechanical devices on each preset path under synchronization control, and judge the safety of the power supply state of the tunnel electromechanical devices on the current path according to the comparison analysis result; through the comparison analysis of the analysis module to judge the power supply state, the power supply state is predicted and judged in advance; finally, the adaptive feedback module is set to feedback and adjust the data fusion strategy according to the analysis result of the power supply state safety, and realize the automatic optimization of the control signal data of the synchronization control module, and realize the optimization process of the electrical performance parameters.

[0063] For example, the generation process of multimodal signals can be as follows:

[0064] Use a pre-verified encoder to convert the input of electromechanical device control data in different modalities into numerical vectors;

[0065] Utilize the LLM language model to decode the input numerical vectors, and select and generate specific signals according to the pre-introduced "modal signal" mechanism;

[0066] Receive the generation instructions from the LLM language model, map the specific signals through a customized output layer, and then transfer them to the corresponding multimodal decoder for multimodal signal generation operations;

[0067] Optimize the LLM language model by using the real-time constructed dataset and according to the tuning signal instructions.

[0068] In the above technical solution, the generation process of the multimodal signals in this embodiment depends on the encoder to convert the electromechanical device control data into numerical vectors and perform decoding and generating relevant instructions; specifically, first, use a pre-verified encoder to convert the input of electromechanical device control data in different modalities into numerical vectors; then, utilize the LLM language model to decode the input numerical vectors, and select and generate specific signals according to the pre-introduced "modal signal" mechanism. The "modal signal" mechanism set here is a predefined rule for guiding the model to convert the input numerical vectors into specific signals; then, receive the generation instructions from the LLM language model, map the specific signals through a customized output layer, and then transfer them to the corresponding multimodal decoder for multimodal signal generation operations; the goal of this setting is to generate corresponding multimodal outputs, such as text descriptions, images, audio, or videos, according to the input information and the guidance of the LLM; finally, optimize the LLM language model by using the real-time constructed dataset and according to the tuning signal instructions; this process is to better understand and execute complex modal interleaved instructions, and helps the LLM language model to generate reasonable and coherent multimodal signals and output through autoregressive methods in the continuous feature space.

[0069] As an implementation manner of the present invention, the acquisition method of control signal data is as follows:

[0070] Capture multimodal signals through a multi-sensor and signal receiving device;

[0071] Perform preprocessing on the received multimodal signals, including noise removal, amplification, and filtering;

[0072] The preprocessed multimodal signals are converted into control signal data through an analog-to-digital converter (ADC).

[0073] In the above technical solution, the acquisition method of the control signal data in this embodiment is obtained by preprocessing the multi-modal signals of the collected sensor data and converting them through a converter. The purpose is to realize the digitalization process of electrical signals. Specifically, first, a multi-sensor and a signal receiving device are used to process and analyze the types of received multi-modal analog signals. The types of multi-modal analog signals include temperature signals, pressure signals, light signal intensities, sound signals, etc. Through preprocessing such as noise removal, amplification, and filtering, an accurate preprocessing operation for removing interference from the multi-modal analog signals is achieved, facilitating the further electrical signal conversion process. It is mainly converted into control signal data through an analog-to-digital converter (ADC). Here, the control signal is a comprehensive data form obtained through joint control based on temperature signals, pressure signals, light signal intensities, and sound signals, and is used as the current control signal data for tunnel electromechanical equipment.

[0074] As an implementation manner of the present invention, the data fusion strategy is as follows:

[0075] Set an initial calibration instruction to calibrate the real-time control signal data on each path to obtain different calibration parameters;

[0076] Extract the set of change curves of different calibration parameters under continuous calibration cycles;

[0077] Select and assign weight values according to the change characteristics of each curve, and input them into a deep learning model for data fusion;

[0078] Reconstruct according to the data characteristics after fusion, and output standard electrical performance parameters through the electromechanical equipment operation simulation circuit.

[0079] In the above technical solution, the data fusion strategy in this embodiment is a process of processing and analyzing the real-time control signal data on each path. It mainly calibrates the real-time control signal data on each path first. The calibration is achieved according to the initial calibration instruction, and different calibration parameters on each path are output according to the initial calibration instruction. And by obtaining the set of change curves of different calibration parameters under continuous calibration cycles, the continuous change situation of the calibration parameters is judged, and weight values are selected and assigned according to the change characteristics of each curve, and input into a deep learning model for data fusion; finally, reconstruct according to the data characteristics after fusion, and output standard electrical performance parameters through the electromechanical equipment operation simulation circuit. The types of electrical performance-related obtained during the process of the electromechanical equipment operation simulation circuit include data gain situation, noise figure, and broadband setting, etc.

[0080] As an implementation manner of the present invention, the comparison and analysis process of the analysis module is as follows:

[0081] Through the formula Calculate the operation status risk value Ris of the i-th preset pathi :

[0082] Where N is the number of items of monitored electrical performance parameters, and j ∈ [1, N]; Ls ij (t) is the real-time electrical performance parameter of the j-th item of the i-th preset path; Ls ij (t) ′ is the standard electrical performance parameter of the j-th item of the i-th preset path; Ls (i-1)j (t) is the real-time electrical performance parameter of the j-th item of the (i - 1)-th preset path; Ls (i-1)j (t) ′ is the standard electrical performance parameter of the j-th item of the (i - 1)-th preset path; q i is the preset adjustment coefficient for the difference in the influence of the i-th preset path on each electrical performance parameter; q i-1 is the preset adjustment coefficient for the difference in the influence of the (i - 1)-th preset path on each electrical performance parameter; ΔLs j is the error tolerance value of the j-th electrical performance parameter; σ j is the preset weight coefficient of the j-th electrical performance parameter.

[0083] In the above technical solution, in this embodiment, the comparison and analysis process of the analysis module is through the calculation formula to calculate the operation state risk value Ris of the i-th preset path i to judge and analyze and obtain. Specifically, the power supply state of the tunnel electromechanical equipment in the current path is judged by analyzing the size of the operation state risk value, and the power supply risk situation is analyzed for the next operation and the maintenance of the relevant equipment during the power supply process.

[0084] Specifically, the operation of the signal during the power supply process of the previous path and the operation of the current signal are analyzed for calculation. By analyzing the change of its corresponding power supply index, the size of all electrical performance parameters is judged, and the judgment of the size of the operation state risk value of the current path is realized.

[0085] As an implementation manner of the present invention, the operation state safety judgment process is as follows:

[0086] Compare the operation state risk value Ris i with the preset standard threshold interval [Ris A , Ris B :

[0087] If Ris A ≤Ris i ≤Ris B , it is judged that there is a risk in the power supply of the tunnel electromechanical equipment in the current path, and the data fusion strategy is fed back and adjusted;

[0088] If Ris i<Ris A , it is determined that the power supply status of the tunnel electromechanical equipment on the current path is normal;

[0089] If Ris i >Ris B , it is determined that the power supply status of the tunnel electromechanical equipment on the current path is abnormal, and a maintenance instruction is generated.

[0090] As an implementation manner of the present invention, the synchronization control module further includes:

[0091] A monitoring unit for obtaining the operation status information of the tunnel electromechanical equipment;

[0092] The operation status information includes the temperature data of the electromechanical equipment on each path, the operation sound signal data of the electromechanical equipment on each path, and the voltage data of the electromechanical equipment on each path;

[0093] An early warning unit for performing safety monitoring on the operation status information of the tunnel electromechanical equipment according to the operation status of the tunnel electromechanical equipment.

[0094] In the above technical solution, the synchronization control module in this embodiment further sets a detection unit and an early warning unit to implement the process of timely warning and signal monitoring of the operation safety status of the tunnel electromechanical equipment. Specifically, the operation status information of the tunnel electromechanical equipment is obtained through calculation by the monitoring unit, and the early warning unit outputs a monitoring warning signal for the operation status of the tunnel electromechanical equipment according to the magnitude of the operation status information.

[0095] As an implementation manner of the present invention, the process by which the monitoring unit obtains the operation status information of the tunnel electromechanical equipment is as follows:

[0096] Through the formula The real-time equipment operation risk value Equ(t) is calculated; where M is the total number of monitoring paths, l ∈ [1, M]; [t1, t2] is the monitoring time period interval; T l (t) is the real-time electromechanical equipment temperature data of the l-th monitoring path; V l (t) is the real-time electromechanical equipment operation sound signal data of the l-th monitoring path; W l (t) is the real-time electromechanical equipment voltage data of the l-th monitoring path; α is the first influence function, β is the second influence function, γ is the third influence function, and α, β, and γ are all greater than 0; τ l is the position coefficient of the l-th monitoring path;

[0097] The real-time equipment operation risk value Equ(t) is compared with the preset threshold Equ thr :

[0098] If Equ(t) > Equthr , it is determined that there is a safety risk in the operation status of the tunnel electromechanical equipment, and the warning unit issues a warning signal and generates a maintenance instruction.

[0099] In the above technical solution, in this embodiment, the calculation process of the monitoring unit obtaining the operation status information of the tunnel electromechanical equipment is through the formula The real-time equipment operation risk value Equ(t) is calculated, and the temperature of the electromechanical equipment, the operation sound signal of the electromechanical equipment, and the voltage of the electromechanical equipment are introduced in the process of calculating the real-time equipment operation risk value to reflect the safety status of the operation of the tunnel electromechanical equipment. The size of the equipment operation risk value of multiple paths is obtained by accumulating different data change situations of the tunnel electromechanical equipment, so as to realize the early prediction of the operation status of the electromechanical equipment.

[0100] Among them, it should be further noted that the influence functions α, β, and γ are respectively pre-determined according to the influence ratios of the temperature of the electromechanical equipment, the operation sound signal of the electromechanical equipment, and the voltage of the electromechanical equipment on the operation of the electromechanical equipment under the current path, and are functions obtained by fitting according to historical data in advance; the position coefficient τ l is determined by fitting in advance according to the position information of the historical monitoring path distribution, and is obtained by fitting according to the operation status data of the equipment on the historical monitoring path. All of these are not described in detail here.

[0101] In some embodiments, the twin network synchronization control system can also be connected to the electromechanical equipment communication control system through an IPV6+ converter

[0102] In the above technical solution, this system is a process of upgrading and processing based on some common communication networks. By introducing new data network technologies such as SRv6, SDN, FlexE, Telemetry, and iFIT, the network architecture is reconstructed, the bearing capacity is doubled, and the operation and maintenance management is intelligentized, and the IPv6+ scale deployment and application at all levels are promoted as a whole. This system commonly uses an IPV6+ converter to achieve the connection processing with the electromechanical equipment communication control system.

[0103] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0104] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications, supplements or use similar methods for substitution to the described specific embodiments, as long as they do not deviate from the concept of the invention or exceed the scope defined by this application, they should all fall within the protection scope of the present invention.

Claims

1. The IPV6+-based twin network synchronization control system for tunnel electromechanical equipment is characterized by: include: The model building module is used to collect spatial data of the tunnel electromechanical area and establish a digital twin model of the electromechanical area based on the electromechanical area space; Synchronous acquisition module, used to synchronously acquire real-time control signal data and real-time electrical performance parameters of tunnel electromechanical equipment through multi-sensor; An information fusion module is used to perform fusion simulation analysis on the real-time control signal data obtained from each preset path according to the data fusion strategy and obtain the standard electrical performance parameters of each preset path; A synchronous control module is used to synchronously control the safe operation status of tunnel electromechanical equipment along a preset path according to real-time control signal data; An analysis module is used to compare the real-time electrical performance parameters of the tunnel electromechanical equipment of each preset path under synchronous control with the standard electrical performance parameters, and determine the power supply status safety of the tunnel electromechanical equipment of the current path based on the comparison and analysis results; Adaptive feedback module, used to adjust the data fusion strategy based on the power supply status safety analysis results and realize automatic tuning of the control signal data of the synchronous control module; The data fusion strategy is: Set the initial calibration instruction to calibrate the real-time control signal data on each path to obtain different calibration parameters; Extracting a set of variation curves of different calibration parameters under consecutive calibration cycles; According to the changing characteristics of each curve, weight values are selected and assigned, and input into the deep learning model for data fusion; Reconstruct the data based on the fused features and run the simulated circuit through electromechanical equipment to output standard electrical performance parameters.

2. The IPV6+-based tunnel electromechanical equipment twin network synchronization control system according to claim 1 is characterized in that: The comparative analysis process of the analysis module is as follows: By formula ， Calculate the operating status risk value of the i-th preset path : in, is the number of monitored electrical performance parameters, ∈ ; is the real-time electrical performance parameter of the jth item of the i-th preset path; is the standard electrical performance parameter of the jth item of the i-th preset path; is the real-time electrical performance parameter of the jth item of the i-1th preset path; is the standard electrical performance parameter of item j of the i-1th preset path; is the preset adjustment coefficient for the difference in the impact of the i-th preset path on various electrical performance parameters; is the preset adjustment coefficient for the difference in the impact of the i-1th preset path on various electrical performance parameters; is the allowable error value of the jth electrical performance parameter; is the preset weight coefficient of the jth electrical performance parameter.

3. The IPV6+-based tunnel electromechanical equipment twin network synchronization control system according to claim 1 is characterized in that: The operation status safety judgment process is as follows: The operating status risk value and the preset standard threshold range To compare: like ≤ ≤ , then it is judged that there is a risk in the power supply of the electromechanical equipment in the tunnel on the current path, and feedback is given to adjust the data fusion strategy; like < , then it is judged that the power supply status of the electromechanical equipment in the tunnel of the current path is normal; like > , then it is judged that the power supply status of the electromechanical equipment in the tunnel of the current path is abnormal and a maintenance instruction is generated.

4. The IPV6+-based tunnel electromechanical equipment twin network synchronization control system according to claim 1 is characterized in that: The synchronization control module also includes: Monitoring unit, used to obtain operating status information of tunnel electromechanical equipment; The operation status information includes temperature data of electromechanical equipment in each path, operation sound signal data of electromechanical equipment in each path, and voltage data of electromechanical equipment in each path; The early warning unit is used to conduct safety monitoring of the operating status information of the tunnel electromechanical equipment according to the operating status of the tunnel electromechanical equipment.

5. The IPV6+-based tunnel electromechanical equipment twin network synchronization control system according to claim 4 is characterized in that: The process of the monitoring unit obtaining the operating status information of the tunnel electromechanical equipment is as follows: ， Calculate real-time equipment operation risk value ;in, is the total number of monitoring paths, ∈ ; is the monitoring time period; For the Real-time electromechanical equipment temperature data for each monitoring path; For the Real-time electromechanical equipment operation sound signal data for each monitoring path; For the Real-time voltage data of electromechanical equipment in each monitoring path; is the first influence function, is the second influence function, is the third influence function, and 、 、 All greater than 0; For the The location coefficient of each monitoring path; t is the real-time state of the time when the above data characteristics are obtained; Real-time equipment operation risk value With preset threshold To compare: like > , it is judged that there is a safety risk in the operation status of the tunnel electromechanical equipment, and the early warning unit sends a warning signal and generates a maintenance instruction.

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