Cable safety monitoring system based on digital twin technology

Abstract

The invention provides a cable safety monitoring system based on a digital twin technology. The cable safety monitoring system comprises a digital modeling module, a data acquisition module and a simulation analysis module, wherein the digital modeling module is used for acquiring cable physical data and building a digital twin model according to the acquired cable physical data; wherein the cable physical data comprises cable basic information and cable field equipment basic information; the data acquisition module is used for acquiring cable safety monitoring data and inputting the acquired cable safety monitoring data into the digital twin model; wherein the cable safety monitoring data comprises cable monitoring data and field monitoring data; and the simulation analysis module is used for performing dynamic evolution simulation according to the digital twin model to obtain dynamic evolution information of the safety monitoring data, and performing safety analysis processing on the dynamic evolution information by adopting the trained safety analysis model to obtain a cable safety analysis result. According to the invention, the reliability and the intelligent level of cable safety monitoring can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cable safety monitoring, and particularly to a cable safety monitoring system based on digital twin technology. Background Art

[0002] With the continuous expansion of the scale of the power system and the complexity of the cable network, the safety monitoring and maintenance of cables have become the key to ensuring the stable operation of the power system. However, traditional cable safety monitoring methods often have limitations, such as the lag in monitoring data collection and processing, the inability to reflect the dynamic changes of cable status in real time, and the inability to conduct a comprehensive evaluation in multiple dimensions. These problems have affected the power company's ability to predict and prevent cable failures to a certain extent, and may even lead to equipment damage, production interruption, and even safety accidents.

[0003] In recent years, digital twin technology, as an innovative technical means, has been widely applied in various fields. By establishing a virtual model of a physical object and synchronizing the status information of the physical object in real time, digital twin can achieve full life cycle monitoring and analysis of the physical object. In the power system, the application of digital twin technology can make cable safety monitoring more accurate, real-time, and efficient.

[0004] Although there are currently some cable monitoring methods based on digital twin technology, there are still some problems in the existing technology. For example, the monitoring and analysis of cables are usually based on a static process, that is, only the status at a certain time point is analyzed, but there is a lack of temporal connection. Therefore, the analysis results are prone to fluctuations and large errors. Therefore, how to use the digital twin model to conduct refined and real-time dynamic evolution simulation of cables and combine it with a safety analysis model for effective safety warning and analysis has become an urgent technical problem to be solved. Summary of the Invention

[0005] In view of the above problems, the present invention aims to provide a cable safety monitoring system based on digital twin technology.

[0006] The object of the present invention is achieved by the following technical solutions: The present invention discloses a cable safety monitoring system based on digital twin technology, including: a digital modeling module, a data acquisition module, and a simulation analysis module; wherein, The digital modeling module is used to obtain cable physical data and build a digital twin model according to the obtained cable physical data; wherein the cable physical data includes cable basic information and basic information of on-site cable equipment; The data acquisition module is used to obtain cable safety monitoring data and input the obtained cable safety monitoring data into the digital twin model; wherein the cable safety monitoring data includes cable monitoring data and on-site monitoring data; The simulation analysis module is used to perform dynamic evolution simulation according to the digital twin model, obtain the dynamic evolution information of the safety monitoring data, and use the trained safety analysis model to perform safety analysis and processing on the dynamic evolution information to obtain the cable safety analysis result.

[0007] Preferably, the digital modeling module includes a physical information acquisition unit, a fusion calculation unit, and a twin body generation unit; among them, The physical information acquisition unit is used to acquire cable physical data, where the cable physical data includes cable basic information and basic information of on-site cable equipment; the cable basic information includes cable length information, cable laying information, cable flame retardant performance information, etc.; the basic information of on-site cable equipment includes building structure information, on-site acquisition node setting information, longitudinal slope information, elevation difference information, fireproof board setting information, on-site fireproof coating information, fire door information, ventilation system information, gas pipeline information, etc. The fusion calculation unit is used to extract corresponding characteristic data from the acquired cable physical data, perform data fusion and multi-physical quantity coupling according to the extracted characteristic data to obtain physical simulation parameters, and generate corresponding digital twins according to the physical simulation parameters to obtain a digital twin model.

[0008] Preferably, the data acquisition module includes a cable monitoring unit, an on-site monitoring unit, and an input unit; among them, The cable monitoring unit is used to acquire cable monitoring data of high-voltage cables, where the cable monitoring data includes load information, current information, voltage information, temperature information, grounding current information, vibration information, joint built-in information, partial discharge information, etc. The on-site monitoring unit is used to acquire on-site monitoring data, where the on-site monitoring data includes temperature and humidity information, smoke monitoring information, video monitoring information, fire monitoring information, gas concentration monitoring information, etc. The input unit is used to perform preprocessing according to the acquired cable monitoring data and on-site monitoring data, extract corresponding characteristic data, and input the extracted characteristic data into the digital twin model to update the real-time state of the model.

[0009] Preferably, the simulation analysis module includes a data simulation unit, a dynamic evolution unit, and a safety analysis unit; among them, The data simulation unit is used to perform prediction simulation on the cable safety monitoring data acquired by a single on-site acquisition node to obtain the simulation prediction result of the cable safety monitoring data. The dynamic evolution unit is used to perform dynamic evolution analysis by combining the simulation results of the cable safety monitoring data of multiple on-site acquisition nodes to obtain the dynamic evolution information of each position in the digital twin model. The security analysis unit is used to perform security analysis and processing on the dynamically evolving information based on the trained security analysis model according to the obtained dynamically evolving information, and obtain the cable security analysis result.

[0010] Preferably, the data simulation unit includes a numerical simulation unit and an image analysis unit; The numerical simulation unit is used to perform simulation prediction on the numerical cable security monitoring data, extract change characteristics based on the cable security monitoring data within a time period, and predict the cable security monitoring data for a future time period according to the change characteristics, so as to obtain the simulation prediction result of the cable security monitoring data; The image analysis unit is used to perform image analysis and processing according to the acquired video monitoring information, identify the feature targets in the video monitoring information and track the movement trajectories of the feature targets, and obtain the image analysis result as the simulation prediction result of the video monitoring information.

[0011] Preferably, the dynamic evolution unit includes: Based on the preset evolution model, according to the simulation prediction results of the cable security monitoring data at each position in the digital twin model, combining the cable security monitoring data of multiple same features and different features within the regional range to perform dynamic evolution analysis on the cable security monitoring data at a certain position, and obtain the dynamic evolution information of the cable monitoring data at this position; where the evolution model includes physical models, geometric models, chemical models, behavior models, etc.

[0012] Preferably, it further includes a remote control module; where, The remote control module is used to, when the cable security analysis result is abnormal, retrieve the corresponding remote control strategy according to the abnormal result, and remotely control the security equipment at the cable site according to the remote control strategy to reduce or eliminate the impact of the abnormal situation.

[0013] Preferably, it further includes a visualization module; where, The visualization module is used to perform visualization display according to the dynamic digital twin model and the cable security analysis result.

[0014] Preferably, it further includes a warning notification module; where, The warning notification module is used to, when the cable security analysis result is abnormal, generate the corresponding warning information according to the abnormal result and send it to the management terminal.

[0015] The beneficial effects of the present invention are as follows: By using the physical data of the cable collected on-site and combining digital twin technology to construct a digital twin model that restores the real situation of the cable on-site, and at the same time, based on the cable safety monitoring data collected on-site, the digital twin model is updated in real time, so that the digital twin model can truly reflect the real situation of the cable and the cable on-site, which helps to improve the real-time and objectivity of cable safety monitoring. At the same time, through the simulation analysis module, dynamic evolution simulation is carried out for the digital twin model, and the digital twin model is used to predict the changes in the current cable on-site situation, so as to accurately and reliably predict and analyze the possible abnormal situations in the cable on-site. According to the obtained cable safety analysis results, the possible safety abnormal situations are monitored and warned in advance, which helps to improve the reliability and intelligent level of cable safety monitoring.

[0016] Among them, based on the digital twin model, the present invention proposes a safety analysis technical solution for dynamic evolution simulation of cable information and status, which can realize the dynamic evolution simulation and safety analysis of cable status, so as to provide more accurate and real-time cable safety monitoring and early warning services, and help to improve the operation safety, reliability and intelligent level of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0018] Figure 1 It is a framework structure diagram of a cable safety monitoring system based on digital twin technology shown in an embodiment of the present invention; Figure 2 It is a schematic diagram of the framework structure of the simulation analysis module shown in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The present invention will be further described in combination with the following application scenarios.

[0020] See Figure 1 , which shows a cable safety monitoring system based on digital twin technology, including: a digital modeling module, a data acquisition module and a simulation analysis module; among them, The digital modeling module is used to obtain the physical data of the cable and build a digital twin model according to the obtained physical data of the cable; the physical data of the cable includes the basic information of the cable and the basic information of the on-site equipment of the cable; The data acquisition module is used to obtain the cable safety monitoring data and input the obtained cable safety monitoring data into the digital twin model; the cable safety monitoring data includes cable monitoring data and on-site monitoring data; The simulation analysis module is used to perform dynamic evolution simulation based on the digital twin model, obtain the dynamic evolution information of the safety monitoring data, and use the trained safety analysis model to perform safety analysis and processing on the dynamic evolution information to obtain the cable safety analysis result.

[0021] In the above embodiments of the present invention, based on the cable physical data collected on-site, combined with digital twin technology, a digital twin model that restores the real situation of the cable site is constructed. At the same time, the digital twin model is updated in real time based on the cable safety monitoring data collected on-site, so that the digital twin model can truly reflect the real situation of the cable and the cable site, which helps to improve the real-time and objectivity of cable safety monitoring. At the same time, further through the simulation analysis module, dynamic evolution simulation is carried out for the digital twin model, and the change situation of the current cable site is predicted through the digital twin model, which can accurately and reliably predict and analyze the possible abnormal situations at the cable site. According to the obtained cable safety analysis result, the possible safety abnormal situations are monitored and warned in advance, which helps to improve the reliability and intelligent level of cable safety monitoring.

[0022] Among them, the system of the present invention can be built based on data processing devices such as local servers and cloud servers. By performing data interaction between the data processing device and the data collection device, measurement device, on-site device, manager's mobile terminal, etc. at the cable site, the corresponding monitoring data or the transmitted analysis results or instructions can be obtained to achieve the corresponding functions.

[0023] Preferably, the system further includes a remote control module; among them, The remote control module is used to, when the cable safety analysis result is abnormal, retrieve the corresponding remote control strategy according to the abnormal result, and remotely control the safety devices at the cable site according to the remote control strategy to reduce or eliminate the impact of the abnormal situation.

[0024] Among them, the system of the present invention can further set a remote control module, and the remote control module can remotely control the safety devices at the cable site (such as fire extinguishing devices, isolation devices, broadcasting devices, spraying devices, etc.). When the cable safety analysis result is abnormal, the corresponding control strategy is retrieved according to the abnormal result (or according to the control strategy set by the administrator according to the abnormal situation) to remotely control the safety devices at the cable site, so that the safety devices perform corresponding operations to eliminate or reduce the impact of the abnormal situation, which helps to improve the effect of cable safety protection in case of abnormal situations.

[0025] Preferably, the system further includes a visualization module; among them, The visualization module is used to perform visualization display according to the dynamic digital twin model and the cable safety analysis result.

[0026] Through the visualization module, the characteristic data and monitoring data of the overall and each position of the digital twin model can be visually displayed, which helps the manager to intuitively and accurately understand the safety monitoring situation of the cable site and improve the effect of data display.

[0027] Preferably, the system further includes a warning notification module; wherein, The warning notification module is used to generate corresponding warning information according to the abnormal result and send it to the management terminal when the cable safety analysis result is abnormal.

[0028] Among them, the warning notification module communicates with the manager terminal or the on-site management terminal. When the system analyzes that the cable safety analysis result is abnormal, corresponding alarm information or warning information is generated according to the abnormal result and sent to the corresponding manager terminal to remind the manager to further monitor or process the abnormal analysis result, which helps to improve the intelligent level of cable safety monitoring.

[0029] Preferably, the digital modeling module includes a physical information acquisition unit, a fusion calculation unit and a twin generation unit; wherein, The physical information acquisition unit is used to acquire cable physical data, where the cable physical data includes cable basic information and basic information of on-site cable equipment; the cable basic information includes cable length information, cable laying information, cable flame retardant performance information, etc.; the basic information of on-site cable equipment includes building structure information, on-site acquisition node setting information, longitudinal slope information, elevation difference information, fireproof board setting information, on-site fireproof coating information, fire door information, ventilation system information, gas pipeline information, etc. The fusion calculation unit is used to extract corresponding characteristic data from the acquired cable physical data, perform data fusion and multi-physical quantity coupling according to the extracted characteristic data to obtain physical simulation parameters, and generate a corresponding digital twin according to the physical simulation parameters to obtain a digital twin model.

[0030] In one scenario, the digital modeling module can accurately establish a digital twin model of the cable through technical means such as physical information acquisition, characteristic data extraction, data fusion and physical quantity coupling. Among them, the physical information acquisition unit ensures that the digital twin has comprehensive physical characteristics and on-site environmental data by comprehensively collecting the physical data of the cable and on-site equipment information; the fusion calculation unit further optimizes the accuracy and applicability of the model through multi-dimensional characteristic data extraction and physical quantity coupling. The generated digital twin model can accurately reflect the actual operating state of the cable and its interaction with the surrounding environment.

[0031] Based on the established digital twin model, information such as the health status, fault risk, and dynamic evolution of the cable can be simulated and predicted in real time, providing a reliable basis for subsequent monitoring, maintenance, and safety analysis. Compared with traditional static models, the digital twin model established in the present invention can adapt to the changes in the cable environment and the dynamic characteristics under different operating conditions, thereby improving the real-time performance and accuracy of cable safety monitoring and significantly enhancing the security and stability of the power system.

[0032] In one scenario, the digital twin model is jointly used for model construction and virtual simulation based on Autodesk Revit 2023 and Siemens NX, and the access and synchronous update of the digital twin model and external sensor data are realized through the equipped IoT platform.

[0033] Preferably, the data acquisition module includes a cable monitoring unit, a on-site monitoring unit, and an input unit; wherein, The cable monitoring unit is used to obtain cable monitoring data of high-voltage cables, where the cable monitoring data includes load information, current information, voltage information, temperature information, grounding current information, vibration information, joint internal information, partial discharge information, etc.; The on-site monitoring unit is used to obtain on-site monitoring data, where the on-site monitoring data includes temperature and humidity information, smoke monitoring information, video monitoring information, fire monitoring information, gas concentration monitoring information, etc.; The input unit is used to preprocess the obtained cable monitoring data and on-site monitoring data, extract corresponding feature data, and input the extracted feature data into the digital twin model to update the real-time state of the model.

[0034] In the above embodiments of the present invention, the data acquisition module realizes the comprehensive monitoring of high-voltage cables and their working environments through the coordinated work of the cable monitoring unit, the on-site monitoring unit, and the input unit. The cable monitoring unit can collect key cable operation data such as current, voltage, temperature, and grounding current in real time to ensure the accurate tracking of the cable state; the on-site monitoring unit provides real-time feedback on external influencing factors related to the cable by obtaining environmental data such as temperature and humidity, smoke, and gas concentration. The input unit preprocesses and extracts features from these data and timely inputs the extracted feature data into the digital twin model to dynamically update the virtual state of the cable.

[0035] In a scenario, the sensors used in the cable monitoring unit and the on-site monitoring unit include, but are not limited to: ABBCM1-3L series current sensors, Schneider Electric PM8000 series voltage monitoring instruments, Fluke 572-2 temperature sensors, PCB Piezotronics 353B07 vibration sensors, Omicron MPD 8000 partial discharge detection equipment, Honeywell HONEYWELL HTPG1 temperature and humidity sensors, system Sensor SSM-300 smoke sensors, Hikvision DS-2CD2087G2-L network cameras, Honeywell FireSentry FS24X fire monitoring sensors, Dräger X-am 8000 gas detectors, etc.

[0036] Preferably, referring to Figure 2 , the simulation analysis module includes a data simulation unit, a dynamic evolution unit, and a security analysis unit; among them, The data simulation unit is used to perform predictive simulation on the cable safety monitoring data obtained by a single on-site acquisition node to obtain the simulation prediction result of the cable safety monitoring data; The dynamic evolution unit is used to perform dynamic evolution analysis by combining the simulation results of the cable safety monitoring data of multiple on-site acquisition nodes to obtain the dynamic evolution information of each position in the digital twin model; The security analysis unit is used to perform security analysis and processing on the dynamic evolution information based on the trained security analysis model according to the obtained dynamic evolution information to obtain the cable security analysis result.

[0037] Based on the digital twin model, the present invention proposes a security analysis technical solution for dynamically evolving simulation of cable information and status, which can realize the dynamic evolution simulation and security analysis of cable status, thereby providing more accurate and real-time cable safety monitoring and early warning services, and helping to improve the operation safety, reliability, and intelligent level of the power system.

[0038] Preferably, the data simulation unit includes a numerical simulation unit and an image analysis unit; The numerical simulation unit is used to perform simulation prediction on the numerical cable safety monitoring data, extract the change characteristics according to the cable safety monitoring data within a time period, and predict the cable safety monitoring data for a future time period according to the change characteristics to obtain the simulation prediction result of the cable safety monitoring data; The image analysis unit is used to perform image analysis and processing according to the acquired video monitoring information, identify the feature targets in the video monitoring information and track the movement trajectories of the feature targets to obtain the image analysis result as the simulation prediction result of the video monitoring information.

[0039] In the above embodiments of the present invention, through the numerical simulation unit, based on numerical information such as current, temperature, and load in the cable safety monitoring data, by extracting change characteristics and trend analysis, the cable safety monitoring data in a future period can be accurately predicted. This helps managers identify abnormal behaviors of cables in advance, such as overload and overheat problems, and prevent possible failures from occurring.

[0040] Among them, the characteristic targets include personnel or birds. By collecting video images of the cable area through a camera and identifying biological targets therein based on the image analysis unit, and further tracking and analyzing the biological targets, abnormal targets within the cable safety area can be identified and tracked, thereby improving the reliability of cable monitoring and safety analysis.

[0041] The image analysis unit, through real-time processing of the on-site monitoring video stream, identifies characteristic targets in the image, mainly for the situation where personnel or birds invade the area around the cable. This unit first uses image preprocessing techniques (such as image enhancement, denoising, etc.) to optimize the image quality, and then applies a deep learning model to detect targets in the image, accurately identifying personnel or bird targets. In the target recognition stage, the image analysis unit adopts a deep learning model based on convolutional neural network (CNN), such as YOLOv4 (version: 4.0), for efficient target detection and positioning. The YOLOv4 model can detect personnel and birds in the image with high accuracy and speed and mark their positions. By setting a threshold to determine whether there is a potential threat (such as personnel or birds approaching the cable), a safety analysis result of abnormal personnel or bird damage is obtained. In addition to target recognition, the image analysis unit also combines trajectory analysis to make a more accurate prediction of cable safety. By further using the DeepSORT algorithm to track consecutive frames for the identified personnel or bird targets, the system can calculate the moving trajectory of the target in real time and predict its proximity to the cable or potential threat based on the trajectory change, further improving the intelligence level of the safety analysis result of abnormal personnel or bird damage around the cable.

[0042] Among them, considering that the cable video monitoring information obtained is usually image information collected in an outdoor environment, and affected by factors such as sunlight or the difference in light between day and night, the cable video monitoring information collected is prone to poor consistency. Therefore, if the directly collected cable images are directly used for the recognition and tracking of personnel or birds, the accuracy is likely to be low (for images with a large difference in light environment, the fitness requirements for the image recognition model are relatively high. Therefore, in the case of a low fitness of the image recognition model for the image, it is difficult to use the same image recognition model to simultaneously meet the recognition accuracy in different light environments. At the same time, for an image recognition model with a high fitness, its training difficulty and cost are relatively high. At the same time, the abnormal light in the cable image usually generates noise areas, which also reduces the accuracy of feature target recognition). Therefore, the present invention particularly sets an image preprocessing unit to first preprocess the obtained cable images, thereby improving the clarity and light consistency of the cable images, so that the cable images can better adapt to the subsequent application of the image recognition model, which indirectly improves the accuracy and effect of feature target recognition.

[0043] Preferably, the image analysis unit includes an image preprocessing unit; Among them, the image preprocessing unit includes: Extract image frames according to the obtained video monitoring information to obtain video monitoring images Pc; Based on the Lab color space, extract the luminance component values of each pixel point in the video monitoring image L(x, y) , and further calculate the average luminance component value of the video monitoring image avcL ; Perform image category analysis based on the obtained average luminance component value: when the average luminance component value avcL is less than the preset luminance threshold avcTL , mark the current video monitoring image as a low-light image Pc ∈ TypeA ; otherwise, when the average luminance component value avcL is greater than or equal to the preset luminance threshold avcTL , mark the current video monitoring image as a normal-light image Pc ∈ TypeB , where the luminance threshold avcTL ∈ [25, 35]; For normal-light images, perform foreground target detection according to the video monitoring image, identify the foreground targets existing in the video monitoring image, and divide the area covered by the foreground targets into target areas AreaT , and divide other areas into background areas AreaB ; For low-light images, mark the area composed of pixel points with luminance component values greater than the light standard moTL as the target area AreaT, other regions are marked as background regions AreaB , where moTL ∈ [50, 60]; According to the divided target regions and background regions, perform adaptive brightness adjustment processing on the image. The brightness adjustment processing function used is:

[0044] Where,

[0045]

[0046] Where, L ' (x, y) represents the brightness component value of the pixel point after brightness adjustment (x, y) , dis p2T (x, y) represents the pixel point (x, y) to the pixel distance of the target region. If the pixel point is a pixel point within the target region, then dis p2T (x, y) = 0 , DisT represents the set distance threshold, DisT ∈ [5, 20] , L(x, y) represents the pixel point (x, y) 's brightness component value, L tar represents the set target brightness value, where L tar ∈[60,70] ; φ represents the set adjustment factor, avcL AB represents the average brightness component value of the background region, LSC(a, b) represents the pixel point (a, b) 's illumination influence value, where the pixel point (a, b) is the target region pixel point closest to the pixel point (x, y) , L(c, d) represents the pixel point (c, d) 's brightness component value, L N (c, d) represents centered on the pixel point (c, d) of the 3×3 range of the average brightness component value, N(a, b) represents centered on the pixel point (a, b) of the 3×3 range, δ represents the set influence attenuation factor, k represents N(a, b) the total number of pixel points within the range, τ represents the set influence adjustment factor,Low(x, y) Indicates a pixel point (x, y) The influence compensation factor of σ Indicates the set compensation adjustment factor; Update the image brightness according to the brightness component values of each pixel point after brightness adjustment to obtain the preprocessed video monitoring image.

[0047] Recombine the preprocessed video monitoring images of each frame to obtain the preprocessed video monitoring information.

[0048] The image analysis unit further performs image analysis and processing on the preprocessed video monitoring image, identifies the feature targets in the processed video monitoring image, and tracks the movement trajectories of the feature targets to obtain the image analysis result as the simulation prediction result of the video monitoring information.

[0049] Among them, in the image preprocessing unit, the foreground target detection method can be completed by the foreground target recognition technology based on the convolutional neural network, or by the foreground extraction technology based on the color space or morphology, or by the method based on template matching, etc. This application does not make specific limitations here.

[0050] Among them, in the above embodiments, the 3×3 range centered on the pixel point can also be modified to the 5×5 range centered on the pixel point, the 7×7 range centered on the pixel point, etc., and adjusted according to the specific situation.

[0051] The above embodiments of the present invention propose a technical solution for preprocessing cable video images. Based on the overall brightness information of the image, the lighting condition of the image is first preliminarily judged. For general lighting images, the foreground objects in the image are further identified, and the foreground objects and background objects are used as a reference; for low-light images, considering the large error in foreground recognition, another method is adopted, that is, the highlighted area in the image is used as a reference, so as to further divide the image into a target area and a background area. Considering that during the image acquisition process, the target area in the image is usually an area with complex lighting, so the lighting information in the target area will cause reflection, scattering, etc. to other areas in the actual environment, resulting in that in addition to natural light, a large amount of reflected light and scattered light are mixed in the lighting characteristics of the target area and the surrounding area of the target area. As a result, after traditional lighting consistency processing, the lighting information in the target area and the surrounding area of the target area will be unnatural. Based on the above idea, in the processing solution of the above embodiments, for the target area and the surrounding area of the target area, a compensation processing part for complex lighting conditions is added during the lighting consistency processing, so as to be able to adaptively compensate for the complex lighting part, and for the background area with relatively simple lighting characteristics, a general lighting consistency processing method is used to adaptively adjust the brightness. The image adaptively adjusted in brightness in the above way can eliminate the influence of lighting noise, thereby improving the clarity of the image and the clarity of key feature display in the image, so that the cable image can better adapt to the application of the subsequent image recognition model, and indirectly improve the accuracy and effect of feature target recognition.

[0052] Preferably, the data simulation unit performs prediction simulation on the cable safety monitoring data obtained by a single on-site acquisition node X(t) to predict the predicted value of the cable safety monitoring data in a future period of time X(t + 1) ; Among them, the prediction simulation method can be to perform linear statistics according to the time series of the cable safety monitoring data to predict the change rate of the data, so as to predict the cable safety monitoring data at a future moment according to the change rate; or use the machine learning method to complete the prediction of the cable safety monitoring data at a future moment based on a time series of the cable safety monitoring data and based on methods such as the LSTM neural network. In addition, other prediction methods based on statistical or machine learning theories can also achieve the prediction of the cable safety monitoring data at a future moment as described above, and the present invention does not make specific limitations here.

[0053] Among them, the above cable safety monitoring data X(t) is a general term, XSpecifically, it can be any one of the cable monitoring data or on-site monitoring data specifically described in the above embodiments, and t represents the current moment, t+1 represents the future moment.

[0054] In the above embodiments of the present invention, the data simulation unit simulates and predicts the monitoring data of a single on-site acquisition node, and can accurately predict the cable safety status at a certain monitoring point (such as a cable joint or a specific area) within a future period of time, and identify possible safety risks in advance. For example, through the prediction simulation of data such as current, temperature, and partial discharge, the system can predict whether the cable may have overload or overheat problems.

[0055] Preferably, the dynamic evolution unit includes: Based on a preset evolution model, according to the simulation prediction results of the cable safety monitoring data at each position in the digital twin model, combining the cable safety monitoring data of multiple same characteristics and different characteristics within the regional range to perform dynamic evolution analysis on the cable safety monitoring data at a certain position, and obtaining the dynamic evolution information of the cable monitoring data at this position; where the evolution model includes a physical model, a geometric model, a chemical model, a behavior model, etc.

[0056] Preferably, the dynamic evolution unit specifically includes: According to the simulation prediction results X(s,t + 1) of the cable safety monitoring data at each position in the digital twin model, combining the cable safety monitoring data of multiple same characteristics and different characteristics within the regional range to perform dynamic evolution analysis on the cable safety monitoring data at a certain position, where the dynamic evolution function used is:

[0057] In the formula, X'(S, t + 1) represents the predicted value of the safety monitoring data at the position after dynamic evolution S for the safety monitoring data X of, X(S, t + 1) represents the predicted value of the safety monitoring data at the position S for the safety monitoring data X of, φ represents the evolution amount adjustment factor, μ i,S represents the weighted influence factor of the surrounding position i on the position S , where the size of the influence factor is obtained according to the evolution model, and the influence factors of all surrounding positions i are weighted so that , X(i, t + 1) represents the predicted value of the safety monitoring data at the position i , where i = 1, 2, …, n , nRepresents the total number of other positions within the indicated area range; F[X(S)] Represents a perturbation factor, the magnitude of which is set according to different types of safety monitoring data.

[0058] In one scenario, for on-site monitoring data such as temperature and humidity as safety monitoring data, the spatial connectivity of each monitoring position is analyzed based on the physical model, geometric model, etc. of each monitoring position. Among them, the stronger the spatial connectivity between two positions, the greater the obtained influence factor; conversely, the smaller the spatial connectivity, the smaller the corresponding influence factor.

[0059] In another scenario, for cable monitoring data such as current and voltage of the cable itself, the influence degree of the current transmission direction at different positions is checked according to the topological model of the cable distribution. When the position correlation degree between the two is higher, the corresponding influence factor is greater; conversely, the lower the correlation degree between the two, the smaller the corresponding influence factor.

[0060] The dynamic evolution unit can comprehensively evaluate the dynamic evolution process of the cable at different positions and different time nodes by jointly analyzing the data of multiple on-site acquisition nodes. When predicting and evolving the safety monitoring data, it can correct local physical quantities through neighborhood interaction, realizing the dynamic evolution process in which the same physical quantity affects each other at different positions, and can further improve the effect of dynamic evolution.

[0061] Preferably, the safety analysis unit specifically includes: Obtain the cable safety monitoring data X(s,t) of each position at the current moment in the digital twin model, as well as the predicted value X ’ (s,t + 1) of the cable safety monitoring data after corresponding dynamic evolution, to perform safety analysis on the safety state of a specific position S. The safety analysis function used is:

[0062] Among them,

[0063] Among them, Represents the safety state factor of position S at time t + 1, where , when is smaller, It indicates that the safety state of position S is safer; represents the real-time safety factor of position S at time t, Represents the evolution safety factor; among them Represents the cable state factor of position S at time t, where , where Represents the safety analysis result of each cable monitoring data. Among them, the variable k corresponds to different cable monitoring data. When the value of the cable monitoring data of position S at time t is within the preset standard range, then , otherwise when the value of the cable monitoring data exceeds the preset standard range, , where the larger the exceeded value, the larger the value of ; represents the corresponding weight factor, where ; represents the on-site state factor of position S at time t, where , where represents the safety analysis result of each on-site monitoring data, where the variable j corresponds to different on-site monitoring data. When the value of the on-site monitoring data of position S at time t is within the preset standard range, then , otherwise when the value of the on-site monitoring data exceeds the preset standard range, , where the larger the exceeded value, the larger the value of ; represents the corresponding weight factor, where ; represents the real-time safety factor of the surrounding position i at time t - 1, represents the corresponding weight factor, where , and n represents the total number of surrounding positions; represents the abnormal target state factor of position S at time t, where , represents the abnormal target recognition result of the image analysis unit for position S at time t, where the variable u represents different abnormal targets. When it is recognized that there are no abnormal targets within the cable safety range, then , otherwise when it is recognized that there are abnormal targets within the cable safety range, , where the more the number of recognized abnormal targets, the larger the value of ; represents the corresponding weight factor, where ; α, γ, δ, ζ represents the set weighting coefficient; represents the cable state change factor of position S at time t + 1, where , represents the change analysis result of each cable monitoring data. When the change amount obtained from the predicted value of the cable monitoring data of position S at time t + 1 according to dynamic evolution is within the preset standard range, then , otherwise when exceeds the preset standard range, The larger the value of ; represents the on-site state change factor of position S at time t + 1, where , represents the change analysis result of each on-site monitoring data. When the change amount obtained from the predicted value of the on-site monitoring data of position S at time t + 1 according to the dynamic evolution is within the preset standard range, then , otherwise when exceeds the preset standard range, , where the larger the exceeded value, the larger the value of ; represents the safety change factor of position S at time t, ; represents the abnormal target state change factor of position S at time t, where , represents the abnormal target change result of position S at time t + 1 by the image analysis unit. The variable u represents different abnormal targets. When the change amount of the abnormal target within the cable safety range predicted according to the movement trajectory of the characteristic target is less than or equal to 0 (including reducing the abnormal target), then , otherwise when the change amount of the abnormal target within the cable safety range is predicted to be greater than 0, , where the more the number of predicted increased abnormal targets, the larger the value of ; Obtain the cable safety analysis result according to the obtained safety state factor. Among them, the smaller the safety state factor, the safer the cable safety analysis result.

[0064] Preferably, when it is detected that the safety state factor of a specific position S exceeds the preset standard value, the cable safety analysis result of this position S is abnormal, and corresponding abnormal alarm information is generated.

[0065] Among them, the cable safety monitoring data X(s, t) includes on-site monitoring data and cable monitoring data.

[0066] Among them, the on-site monitoring data includes temperature and humidity information, smoke monitoring information, video monitoring information, fire monitoring information, gas concentration monitoring information, etc.

[0067] Among them, the cable monitoring data includes load information, current information, voltage information, temperature information, ground current information, vibration information, joint built-in information, and partial discharge information, etc.

[0068] Among them, the abnormal targets include personnel and birds.

[0069] In the above embodiments of the present invention, based on the predicted values of the monitoring data obtained by the dynamic evolution unit, the safety analysis of the cables at each location is further realized. Among them, a safety analysis function is proposed, which comprehensively analyzes the cable safety by combining the real-time safety factor obtained from the real-time monitoring data and the evolution safety factor obtained from the dynamic evolution. Among them, by fusing the monitoring data of different dimensions (cable monitoring data, on-site monitoring data, data of other nodes, and video monitoring data-based data) and the predicted change values of the monitoring data, the accurate prediction of the cable health status and fault risk is realized, the adaptability and collaboration ability to the dynamic change data of the cables are enhanced, and thus the reliability and accuracy of the overall and local safety analysis of the cable area by the system are improved.

[0070] It should be noted that in each embodiment of the present invention, each functional unit / module can be integrated in a processing unit / module, or each unit / module can exist physically alone, or two or more units / module can be integrated in one unit / module. The above integrated unit / module can be implemented in the form of hardware or in the form of a software functional unit / module.

[0071] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments described here can be implemented in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described here, or a combination thereof. For software implementation, part or all of the processes of the embodiments can be completed by a computer program instructing the relevant hardware. When implemented, the above program can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. The computer-readable medium includes a computer storage medium and a communication medium, where the communication medium includes any medium facilitating the transfer of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a computer. The computer-readable medium can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting the protection scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A cable safety monitoring system based on digital twin technology, characterized in that: include: Digital modeling module, data acquisition module and simulation analysis module; among them, The digital modeling module is used to obtain the physical data of the cable and build a digital twin model based on the obtained physical data of the cable; the physical data of the cable includes basic information of the cable and basic information of the cable on-site equipment; The data acquisition module is used to obtain cable safety monitoring data and input the obtained cable safety monitoring data into the digital twin model; the cable safety monitoring data includes cable monitoring data and field monitoring data; The simulation analysis module is used to perform dynamic evolution simulation based on the digital twin model to obtain the dynamic evolution information of the safety monitoring data, and use the trained safety analysis model to perform safety analysis processing on the dynamic evolution information to obtain the cable safety analysis results; The simulation analysis module includes a data simulation unit, a dynamic evolution unit and a security analysis unit; The data simulation unit is used to perform prediction simulation on the cable safety monitoring data acquired by a single field acquisition node to obtain simulation prediction results of the cable safety monitoring data; The dynamic evolution unit is used to combine the simulation results of cable safety monitoring data from multiple field collection nodes to perform dynamic evolution analysis and obtain the dynamic evolution information of each location in the digital twin model; The safety analysis unit is used to perform safety analysis processing on the dynamic evolution information based on the obtained dynamic evolution information and the trained safety analysis model to obtain the cable safety analysis result.

2. According to claim 1, a cable safety monitoring system based on digital twin technology is characterized in that: The digital modeling module includes a physical information acquisition unit, a fusion calculation unit and a twin generation unit; The physical information acquisition unit is used to acquire the cable physical data, wherein the cable physical data includes basic cable information and basic cable on-site equipment information; wherein the basic cable information includes cable length information, cable laying information, and cable flame retardant performance information; the basic cable on-site equipment information includes building architecture information, on-site acquisition node setting information, longitudinal slope information, drop information, fireproof board setting information, on-site fireproof coating information, fireproof door information, ventilation system information, and gas pipeline information; The fusion calculation unit is used to extract corresponding characteristic data from the acquired cable physical data, and perform data fusion and multi-physical quantity coupling according to the extracted characteristic data to obtain physical simulation parameters, and generate corresponding digital twins according to the physical simulation parameters to obtain a digital twin model.

3. According to claim 1, a cable safety monitoring system based on digital twin technology is characterized in that: The data acquisition module includes a cable monitoring unit, a field monitoring unit and an input unit; among them, The cable monitoring unit is used to obtain cable monitoring data of the high-voltage cable, wherein the cable monitoring data includes load information, current information, voltage information, temperature information, ground current information, vibration information, joint built-in information and partial discharge information; The field monitoring unit is used to obtain field monitoring data, wherein the field monitoring data includes temperature and humidity information, smoke monitoring information, video monitoring information, fire monitoring information, and gas concentration monitoring information; The input unit is used to preprocess the acquired cable monitoring data and field monitoring data, extract the corresponding feature data, and input the extracted feature data into the digital twin model to update the real-time status of the model.

4. According to claim 1, a cable safety monitoring system based on digital twin technology is characterized in that: The data simulation unit includes a numerical simulation unit and an image analysis unit; The numerical simulation unit is used to simulate and predict the numerical cable safety monitoring data, extract the change characteristics of the cable safety monitoring data within a time period, and predict the cable safety monitoring data for a period of time in the future based on the change characteristics to obtain the simulation prediction results of the cable safety monitoring data; The image analysis unit is used to perform image analysis processing according to the acquired video monitoring information, identify characteristic targets in the video monitoring information and track the movement trajectory of the characteristic targets, and obtain image analysis results as simulation prediction results of the video monitoring information.

5. According to claim 4, a cable safety monitoring system based on digital twin technology is characterized in that: Dynamic evolution units include: Based on the preset evolution model, according to the simulation prediction results of the cable safety monitoring data at each location in the digital twin model, a dynamic evolution analysis is performed on the cable safety monitoring data at a certain location by combining multiple cable safety monitoring data with the same characteristics and cable safety monitoring data with different characteristics within the regional range to obtain the dynamic evolution information of the cable monitoring data at this location; the evolution model includes physical model, geometric model, chemical model and behavioral model.

6. The cable safety monitoring system based on digital twin technology according to claim 5 is characterized in that: The dynamic evolution unit specifically includes: According to the simulation prediction results X(s, t+1) of the cable safety monitoring data at each location in the digital twin model, a dynamic evolution analysis of the cable safety monitoring data at a certain location is performed by combining multiple cable safety monitoring data with the same characteristics and cable safety monitoring data with different characteristics within the regional range. The dynamic evolution function used is: In the formula, X'(S,t+1) Represents the position after dynamic evolution S Safety monitoring data X The predicted amount, X(S,t+1) Indicates location S Safety monitoring data X The predicted amount, φ represents the evolution adjustment factor, μ i,S Indicates surrounding location i About Location S The weighted impact factor of the impact factor is obtained according to the evolution model for all surrounding locations. i The impact factors of , X(i,t+1) Indicates location i Safety monitoring data The predicted amount, where i=1,2,…,n , n Indicates the total number of other locations within the region; F[X(S)] Represents the disturbance factor, and its size is set according to different types of safety monitoring data.

7. The cable safety monitoring system based on digital twin technology according to claim 6 is characterized in that: The security analysis unit specifically includes: Obtain cable safety monitoring data at each location in the digital twin model at the current moment X(s,t) , and the corresponding cable safety monitoring data prediction after dynamic evolution X ’ (s,t+1) , to a specific location S The safety analysis function used is: in, in, SC(S,t+1) Indicates location S right t+1 The safety state factor at the moment, where SC(S,t+1)∈[0,2] ,when SC(S,t+1) The smaller the value, the higher the position. S The more secure the security status is; SH(S,t) Indicates location S right t Real-time safety factor at all times, ST(S,t+1) represents the evolutionary safety factor; M(S,t) Indicates location S right t The cable state factor at time t, where ,in Represents the safety analysis results of each cable monitoring data, where the variable k Corresponding to different cable monitoring data, when the location S right t When the value of the cable monitoring data at the moment is within the preset standard range, Otherwise, when the value of the cable monitoring data exceeds the preset standard range, , where the larger the value exceeded, The larger the value of ; represents the corresponding weight factor, where ; A(S,t) Indicates location S right t The on-site status factor at the moment, where ,in Represents the safety analysis results of each field monitoring data, where the variable j Corresponding to different on-site monitoring data, when the location S right t When the value of the on-site monitoring data at the moment is within the preset standard range, a j (S,t)=0 Otherwise, when the value of the on-site monitoring data exceeds the preset standard range ，a j (S,t)>0 , where the larger the value exceeded, a j (S,t) The larger the value of a j (S,t)∈[0,1] ; ω k represents the corresponding weight factor, where ; SH(i,t-1) Indicates surrounding location i right t-1 Real-time safety factor at all times, ω i represents the corresponding weight factor, where , n Indicates the total number of surrounding locations; B (S,t) Indicates location S right t The abnormal target state factor at time, where , b u (S,t) Indicates that the image analysis unit targets the position S right t The abnormal target recognition result at time , where the variable u Indicates the corresponding abnormal targets. When it is identified that there are no abnormal targets within the cable safety range, b u (S,t)=0 Otherwise, when an abnormal target is identified within the cable safety range, b u (S,t)>0 , where the more abnormal targets are identified, b u (S,t) The larger the value of b u (S,t)∈[0,1] ; ω u represents the corresponding weight factor, where ; α,γ,δ,ζ Indicates the set weighting coefficient; ∆M(S,t+1) Indicates location S right t+1 The cable state change factor at time , ∆m k (S,t+1) Indicates the change analysis results of each cable monitoring data. S right t+1 The change in the predicted amount of cable monitoring data at the time When the value of is within the preset standard range, ∆m k (S,t+1)=0 , otherwise when When the value of exceeds the preset standard range, ∆m k (S,t+1)>0 , where the larger the value exceeded, ∆m k (S,t+1) The larger the value of ,; ∆A(S,t+1) Indicates location S right t+1 The on-site status change factor at the moment, where , ∆a j (S,t+1) Indicates the change analysis results of each field monitoring data. S right t+1 The change amount obtained by the predicted amount of on-site monitoring data at the moment When the value of is within the preset standard range, ∆a j (S,t+1)=0 , otherwise when When the value of exceeds the preset standard range, ∆a j (S,t+1)>0 , where the larger the value exceeded, ∆a j (S,t+1) The larger the value of ; ∆SH(i,t) Indicates location S right t The safety change factor at each moment, ∆SH(i,t)=SH(i,t)-SH(i,t-1) ; ∆B(S,t+1) Indicates location S right t The abnormal target state change factor at the moment, where , ∆b u (S,t+1) Indicates that the image analysis unit targets the position S right t+1 The abnormal target change result at the moment, where the variable u Indicates that the corresponding abnormal targets are different. When the change of the abnormal target within the cable safety range is predicted to be less than or equal to 0 according to the moving trajectory of the characteristic target, then ∆b u (S,t+1)=0 Otherwise, when the change of abnormal target within the cable safety range is predicted to be greater than 0, ∆b u (S,t+1)=0 , where the more the predicted abnormal targets increase, ∆b u (S,t+1) The larger the value of ∆b u (S,t+1)∈[0,1] ; The cable safety analysis result is obtained according to the obtained safety state factor, wherein the smaller the safety state factor is, the safer the cable safety analysis result is.

8. The cable safety monitoring system based on digital twin technology according to claim 1 is characterized in that: Also includes a remote control module; wherein, The remote control module is used to call the corresponding remote control strategy according to the abnormal result when the cable safety analysis result is abnormal, and remotely control the safety equipment at the cable site according to the remote control strategy to reduce or eliminate the impact of the abnormal situation.

9. The cable safety monitoring system based on digital twin technology according to claim 1, characterized in that: Also includes a visualization module; wherein, The visualization module is used to perform visualization based on the dynamic digital twin model and cable safety analysis results.

10. The cable safety monitoring system based on digital twin technology according to claim 1, characterized in that: It also includes an early warning notification module; The early warning notification module is used to generate corresponding early warning information based on the abnormal results and send it to the management terminal when the cable safety analysis results are abnormal.

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