Infrastructure multi-source heterogeneous data fusion security situation holographic sensing control method

Abstract

The invention provides an infrastructure multi-source heterogeneous data fusion security situation holographic sensing control method. The method comprises the following steps: acquiring risk fault information of infrastructures in a target area; performing data cleaning and verification processing on the risk fault information of the infrastructure, and performing data correction on the risk fault information; in combination with a pre-constructed knowledge base, performing security situation awareness on the risk fault information of the infrastructure, and generating a plurality of decision-making schemes; and performing evaluation verification and scheme optimization on the decision scheme, and determining a target scheme for the risk fault information of the infrastructure. According to the invention, safe and stable operation of urban underground infrastructures can be effectively guaranteed, and the problem of insufficient sensing capability of the existing security situation sensing system is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban facility monitoring, and in particular to a holographic sensing and control method for the security situation of infrastructure by fusing multi-source heterogeneous data. Background Art

[0002] Urban underground infrastructure faces significant disaster challenges, including strong concealment, easy to trigger chain reactions, and high difficulty in prevention and control. As the scale of these facilities continues to expand and their service life increases, the safety risks in their operation process have also increased sharply. Therefore, the key issue that needs to be solved urgently is how to achieve instant and accurate perception of potential safety hazards, build an effective early warning mechanism, and formulate a rapid response emergency response plan to ensure the safe and stable operation of urban underground infrastructure.

[0003] At present, the main methods used at home and abroad to control this type of risk are to increase monitoring measures and manual inspections. There are problems such as incomplete risk monitoring, insufficient perception capabilities, insufficient hazard identification, lack of big data analysis capabilities, and insufficient independent correlation between data. It is difficult to timely, comprehensively and accurately discover and warn of potential safety hazards.

[0004] In addition, the current security situation awareness system of urban underground infrastructure generally has limitations, mainly reflected in the lack of intelligent decision-making and emergency response technologies with autonomous optimization and learning capabilities. This makes it difficult for the system to handle and control emergency security incidents in real time and efficiently, limiting its ability and efficiency to respond to emergencies. Therefore, the development and integration of intelligent decision-making and emergency response modules with autonomous optimization and learning capabilities has become an urgent need to improve the safety management level of urban underground infrastructure and ensure rapid and effective response to various security incidents.

[0005] The existing security situation awareness system has the problem of insufficient perception capability, and no effective solution has been proposed yet. Summary of the invention

[0006] The present invention provides a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation, which is used to solve the defect of insufficient sensing ability of the existing security situation perception system.

[0007] In a first aspect, the present invention provides a holographic sensing and control method for fusion of multi-source heterogeneous data of infrastructure security situation, comprising: Obtain risk failure information of infrastructure in the target area; Performing data cleaning and verification processing on the risk failure information of the infrastructure, and performing data correction on the risk failure information; Combined with the pre-built knowledge base, security situation awareness of risk failure information of the infrastructure is performed, and several decision-making plans are generated; The decision-making plan is evaluated, verified and optimized to determine a target plan for the risk failure information of the infrastructure.

[0008] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, risk fault information of infrastructure in a target area is obtained, including: The dynamic timing information and static discrete information of the infrastructure in the target area are sensed and captured in real time through pre-arranged sensing devices.

[0009] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, after obtaining risk fault information of infrastructure in a target area, the method further includes: The risk failure information is stored in a database through a cloud storage solution.

[0010] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, data cleaning and verification processing are performed on risk fault information of the infrastructure, including: filtering incomplete data in the risk failure information of the infrastructure; filtering erroneous data in the risk failure information of the infrastructure; Find and remove duplicate data in risk failure information for the infrastructure.

[0011] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, data correction is performed on the risk fault information, including: An automatic spatial alignment algorithm for monitoring and inspection time series data is used to correct the inherent deviation of multi-channel data in the risk fault information; the basic model of the automatic spatial alignment algorithm for monitoring and inspection time series data includes a minimum space-time deviation estimation-double interpolation correction model and a multi-channel time series signal feature data matching model.

[0012] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, an automatic spatial alignment algorithm for monitoring and inspection time series data is adopted to correct the inherent deviation of multi-channel data in the risk fault information, including: Based on the minimum spatiotemporal deviation estimation-double interpolation correction model, determining the minimum spatiotemporal deviation of the risk fault information, and performing deviation correction on the risk fault information; Based on the multi-channel time series signal feature data matching model, representative features are extracted from the time series signals of multiple channels of the risk fault information, and the representative features are compared and matched with pre-set target features to perform feature alignment processing.

[0013] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, building the knowledge base includes: Based on the characteristics of the research results on the disaster mechanism of the infrastructure in the target area, basic knowledge is obtained and classified; Based on the basic knowledge, the knowledge base is constructed in combination with the disaster scenario type and disaster risk event type of the infrastructure.

[0014] According to a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation provided by the present invention, security situation perception is performed on risk fault information of the infrastructure, and several decision-making schemes are generated, including: Establishing a neural network model based on the monitoring time sequence of the infrastructure and the risk failure information of the infrastructure to predict the operation change trend of the infrastructure; Performing a safety assessment on the infrastructure based on the risk failure information of the infrastructure to obtain an assessment result; Generate a monitoring and analysis report for the infrastructure in combination with the operation change trend and evaluation results of the infrastructure; A pre-configured decision support system is called to generate several decision plans based on the monitoring and analysis report.

[0015] According to the present invention, a holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation is provided, comprising: Determine the evaluation criteria based on the specific application scenarios of the infrastructure; According to the evaluation criteria, each of the decision-making options is evaluated and preliminarily screened; Conduct simulation verification on the decision-making schemes initially screened out to optimize the screening results; Optimizing the decision-making plan to determine a target plan for the risk failure information of the infrastructure, including: On the basis of evaluation and verification, the parameters and strategies of the decision-making scheme are adjusted to obtain the target scheme.

[0016] In a second aspect, the present invention also provides an infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control system, comprising: An acquisition module, used to acquire risk failure information of infrastructure in a target area; A processing module, used for performing data cleaning and verification processing on the risk failure information of the infrastructure, and performing data correction on the risk failure information; A perception module, used to combine a pre-built knowledge base to conduct security situation perception of risk failure information of the infrastructure and generate a number of decision-making solutions; The optimization module is used to evaluate and verify the decision-making plan and optimize the plan to determine the target plan for the risk failure information of the infrastructure.

[0017] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation as described in the first aspect above is implemented.

[0018] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method as described in the first aspect above.

[0019] In a fifth aspect, the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method as described in the first aspect above.

[0020] Compared with the prior art, the present invention has the following beneficial effects: 1. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method provided by the present invention performs data cleaning and verification processing on risk fault information to remove invalid data information therein, and performs data correction on risk fault information with deviations therein, thereby ensuring the accuracy and effectiveness of subsequent decision-making plans. In order to further improve the scientificity and rationality of decision-making plans, the decision-making plans are evaluated, verified and optimized, and the optimal target plan is screened out to achieve rapid and accurate handling of emergency events, effectively ensure the safety and stable operation of urban underground infrastructure, and solve the problem of insufficient perception ability of existing security situation awareness systems.

[0021] 2. The present invention can correct the inherent deviation of multi-channel data of different monitoring equipment through the automatic spatial alignment algorithm of sampling monitoring and inspection time series data. It has anti-interference ability and strong robustness. It can effectively realize the automatic and precise local phase matching of risk characteristic multi-channel time series signals, thereby solving the problem of spatiotemporal islands of multi-source monitoring and inspection data.

[0022] 3. The present invention uses intelligent decision-making and emergency response strategies to strengthen the safety situation management and control of urban underground infrastructure. The optimization algorithm is introduced to accurately evaluate and screen out the best decision-making plan, significantly improving the scientificity and rationality of the decision-making process. At the same time, combined with an integrated intelligent control system, it can instantly capture the dynamic changes of emergency events, automatically trigger the preset emergency response process, realize rapid and accurate handling of emergency events, and effectively ensure the safety and stable operation of urban underground infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 It is a flow chart of the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method provided by the present invention; Figure 2 is a logical relationship diagram of the knowledge base in the embodiment of the present invention; Figure 3 It is a schematic diagram of the implementation process of security situation awareness in an embodiment of the present invention; Figure 4 is a schematic diagram of a process of intelligent decision making in an embodiment of the present invention; Figure 5 is a flow chart of emergency handling in an embodiment of the present invention; Figure 6 It is a structural block diagram of the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control platform provided by the present invention; Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] The present invention provides a holographic sensing and control method for fusion of multi-source heterogeneous data of infrastructure security situation. Figure 1 : is a flow chart of the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method provided by the present invention, such as Figure 1As shown, the method comprises the following steps: Step S101, obtaining risk failure information of infrastructure in a target area.

[0027] Step S102: performing data cleaning and verification processing on the risk failure information of the infrastructure, and performing data correction on the risk failure information.

[0028] Step S103, combining with the pre-built knowledge base, conduct security situation awareness on the risk failure information of the infrastructure and generate several decision-making plans.

[0029] Step S104, evaluating and verifying the decision-making plan and optimizing the plan, and determining a target plan for the risk failure information of the infrastructure.

[0030] Exemplarily, first, the risk fault information of the infrastructure in the target area is obtained through the Internet of Things sensing technology. In order to improve the effectiveness of the risk fault information, in this method, the risk fault information is cleaned and verified to remove invalid data information, and the risk fault information with deviations is corrected to ensure the accuracy and effectiveness of subsequent decision-making plans. Then, combined with the pre-built knowledge base, the risk fault information of the infrastructure is perceived in a safe situation. The knowledge base contains a lot of basic knowledge about the operating status of the infrastructure. Combined with these basic knowledge, several decision-making plans for the current risk faults can be generated. Finally, in order to further improve the scientificity and rationality of the decision-making plan, the decision-making plan is evaluated, verified and optimized, and the optimal target plan is selected to achieve rapid and accurate handling of emergency events, effectively ensure the safety and stable operation of urban underground infrastructure, and solve the problem of insufficient perception ability of the existing security situation awareness system.

[0031] In some of the embodiments, step S101, obtaining risk failure information of infrastructure in the target area, includes: sensing and capturing dynamic timing information and static discrete information of the infrastructure in the target area in real time through pre-arranged sensing devices.

[0032] For example, by integrating advanced IoT sensing technology, the system can penetrate into various monitoring areas and implement all-round, high-precision urban underground infrastructure risk fault information collection. The sensing technology includes but is not limited to wireless sensor networks, radio frequency identification (RFID), ultrasonic detection, video monitoring systems, intelligent positioning systems, regular / irregular inspection robots, etc. This sensing technology can sense and capture various dynamic time series information (real-time monitoring of subway tunnel structure instability, rail failure, etc.) and static discrete information (robot inspection data of contact network / rail failure, foreign body intrusion, etc.) in the area in real time.

[0033] In addition, in order to achieve seamless integration and accurate transmission of data between different collection devices and data platforms, a distributed storage architecture is also deployed to provide a standardized data interface. In some embodiments, after obtaining the risk failure information of the infrastructure in the target area in step S101, it also includes: storing the risk failure information in a database through a cloud storage solution.

[0034] Specifically, the cloud storage solution is introduced, which provides a flexible and economical storage environment for massive risk failure information with its on-demand storage capacity and high security guarantee. The integration of cloud storage makes the data backup, recovery and disaster recovery process of risk failure information simpler and faster, ensuring the safety of enterprise data assets. In addition, in order to meet the challenges of unstructured data, NoSQL database technology is adopted, whose flexible data model and high concurrent processing capabilities provide strong support for data storage and access in a big data environment.

[0035] In some of the embodiments, step S102 performs data cleaning and verification processing on the risk failure information of the infrastructure, including: filtering incomplete data in the risk failure information of the infrastructure; filtering erroneous data in the risk failure information of the infrastructure; and finding and deleting duplicate data in the risk failure information of the infrastructure.

[0036] Specifically, data cleaning and verification requires filtering incomplete data, feeding back the missing content to the client, and writing it into the database after the client completes it; it also requires filtering erroneous data, feeding back the client error prompt, and reorganizing and uploading it according to the protocol; and completing the automatic deletion of duplicate data records. The client is a device used to implement the communication between this method and the user.

[0037] To solve the spatiotemporal island problem of multi-source heterogeneous monitoring data, in some embodiments, step S102, data correction of risk fault information, including: using the automatic spatial alignment algorithm of monitoring and inspection time series data to correct the inherent deviation of multi-channel data in risk fault information; the basic model of the automatic spatial alignment algorithm of monitoring and inspection time series data includes the minimum spatiotemporal deviation estimation-double interpolation correction model and the multi-channel time series signal feature data matching model. The data spatiotemporal alignment algorithm has anti-interference ability and strong robustness, and can realize the automatic and accurate local phase matching of risk feature multi-channel time series signals, and finally effectively solve the spatiotemporal island phenomenon of multi-source data.

[0038] Specifically, an automatic spatial alignment algorithm for monitoring and inspection time series data is used to correct the inherent deviation of multi-channel data in risk fault information, including: based on the minimum space-time deviation estimation-double interpolation correction model, determining the minimum space-time deviation of risk fault information, and correcting the deviation of risk fault information; based on the multi-channel time series signal feature data matching model, extracting representative features from the time series signals of multiple channels of risk fault information, and comparing and matching the representative features with pre-set target features to perform feature alignment processing.

[0039] Minimum spatiotemporal deviation estimation-double interpolation correction model mainly uses the minimum calculation method for the deviation between time data and space data. The formula is as follows:

[0040] in, Represents a certain spatial data information, Indicates time data information, represents interpolation, In the interpolation domain The minimum spatiotemporal deviation function is obtained. The minimum spatiotemporal deviation estimation-double interpolation correction model can flexibly deal with data deviation problems under different spatial distributions and complex environmental conditions. By constructing rectangular compensation grids or field compensation grids, the model can more accurately capture the spatiotemporal variation characteristics of urban underground infrastructure risk data, and perform accurate deviation estimation and correction based on this.

[0041] The multi-channel time series signal feature data matching model can automatically extract representative and identifiable features from the time series signals of multiple channels. These features may include statistical features, frequency domain features, time-frequency domain features, and nonlinear features (such as autocorrelation function, cross-correlation function), etc. In terms of extracted information, the sampling 2D convolution algorithm can be used to extract features of input data (such as images) and match these features with target features to achieve precise alignment between signals from different channels. The convolution calculation formula of multi-channel vibration signals and historical multi-channel data is as follows:

[0042] in, R represents the convolution result matrix, ( i , j ) represents the convolution result matrix R The coordinate size of I Represents input data, T Represents the target data, ( u , v ) represents the coordinates in the target data, m and n is the size of the target data. In addition to the basic convolution formula, the normalized cross-correlation function (NCC) is also used to standardize the convolution results, making the matching algorithm more robust and further optimizing or enhancing the matching effect. The formula of the normalized cross-correlation function is as follows:

[0043] in, represents the average value of the local area of ​​the channel signal, Represents the mean value of the target data.

[0044] In some of the embodiments, constructing the knowledge base includes: acquiring and classifying basic knowledge based on the characteristics of the research results on the disaster action mechanism of the infrastructure in the target area; and constructing the knowledge base based on the basic knowledge, combining the disaster scenario type and disaster risk event type of the infrastructure.

[0045] Specifically, Figure 2 is a logical relationship diagram of the knowledge base in the embodiment of the present invention, such as Figure 2As shown in the figure, the knowledge base mainly includes seven parts, namely, the plan library, the case library, the archive library, the indicator threshold library, the algorithm library, the rule library and the sample library. Based on the characteristics of the research results on the mechanism of underground infrastructure disasters, the logical relationship of different disaster risk event knowledge is analyzed by summarizing and inductive methods, and the research results are divided into 10 categories of knowledge, including tracking and identification indicators, indicator thresholds, suppression models / algorithms, fault trees / event trees, vulnerability assessment algorithms, coupling models / algorithms, risk classification rules, trend evolution models / algorithms, intelligent emergency plans, and disaster cases. According to the six disaster scenarios of underground infrastructure (disasters caused by failure of civil structure functions, disasters caused by failure of key equipment and pipeline systems, disasters caused by foreign object intrusion, fires, floods, and disasters caused by emergencies) and 20 disaster risk events, the relationship between the decision-making support knowledge base and the mechanism research results is established through demand surveys, and a knowledge base is formulated to sort out the disaster risk knowledge in multiple dimensions, providing basic knowledge for seven major libraries, including the plan library, case library, archive library, indicator threshold library, algorithm model library, reasoning rule library, and sample library for three scenarios (underground complexes, underground comprehensive pipe corridors, and subways) and six disaster scenarios, and a total of more than 100 knowledge base materials have been formed.

[0046] In some of the embodiments, step S103 performs security situation awareness on the risk failure information of the infrastructure and generates several decision-making plans, including: establishing a neural network model based on the monitoring time series of the infrastructure and the risk failure information of the infrastructure to predict the operation change trend of the infrastructure; performing a security assessment on the infrastructure based on the risk failure information of the infrastructure to obtain an assessment result; generating a monitoring and analysis report for the infrastructure in combination with the operation change trend of the infrastructure and the assessment result; calling a pre-configured decision support system to generate several decision-making plans based on the monitoring and analysis report.

[0047] For example, Figure 3 is a schematic diagram of the implementation process of security situation awareness in an embodiment of the present invention, such as Figure 3As shown in the figure, security situation awareness can complete three specific functions: security warning, trend prediction, and comprehensive evaluation. Based on the above three specific functions, it can generate monitoring and analysis reports online and send the analysis reports to multi-level management terminals. Security warning and trend prediction are mainly based on monitoring time series and discrete data and data analysis results as well as existing historical data results to establish a neural network model. The neural network model can learn and train these data to discover patterns and correlations, thereby achieving real-time warning and prediction of changing trends in the future. Comprehensive evaluation uses reliable evaluation methods (such as qualitative evaluation methods (such as safety checklist method), quantitative evaluation methods (such as fault tree analysis method and risk matrix method), comprehensive evaluation methods (such as hierarchical analysis method and fuzzy comprehensive evaluation method) and data-based evaluation methods (such as data mining and machine learning)), and evaluates the safety of urban underground infrastructure according to the structural composition of the evaluation object, indicator weights, perception data thresholds, etc., and reserves upgrade interfaces for the development of evaluation technology, so that new evaluation methods and algorithms can be easily integrated when the evaluation technology is updated or upgraded.

[0048] The analysis report generated by security situation awareness mainly includes the following contents: monitoring items and basis; monitoring data collection method; monitoring data charts: monitoring point layout, cumulative value of monitoring data, change rate, time curve, etc.; monitoring disaster risk events; analysis and explanation of monitoring data; conclusions and suggestions.

[0049] In addition, the present invention also realizes the interactive effect with users through three-dimensional full-system visualization. Specifically, three-dimensional holographic visualization is realized by using digital twin technology to build an accurate three-dimensional digital model of the physical entity and integrate a real-time data interface. In addition, holographic projection technology is used on the visualization platform to display the layout, operation status, security situation and other information of underground infrastructure to users in an intuitive and dynamic way. Users can interact with the model through the interactive interface to realize real-time monitoring and optimization decision-making.

[0050] For the generation of decision-making plans, in this embodiment, relying on the structured decision-making mechanism of human-computer interaction, it not only efficiently responds to established problems, but also has a powerful adaptive learning ability, which can effectively analyze and respond to unknown decision-making challenges. This feature opens up a new perspective for the generation of emergency plans for comprehensive monitoring systems, and through intelligent decision-making and dynamic adjustment, it can significantly improve the accuracy and efficiency of emergency response.

[0051] Specifically, first, receive fault information data from multiple sensors, monitoring systems, historical data and other external information sources, which may include but are not limited to sensor data, video surveillance, environmental data, historical maintenance records, etc. Ensure the accuracy and consistency of the data through data preprocessing techniques (such as data cleaning and verification, data time and space alignment). Then, use machine learning algorithms, data mining technology and situation awareness models to analyze the current status of underground infrastructure in real time and identify potential risks and abnormal situations. Build a holographic sensing control model to display the current situation through visualization. Finally, based on the real-time situation analysis results, apply the decision-making support system (DSS) to generate a variety of decision plans. These decision plans can include emergency response measures, maintenance plans, resource scheduling strategies, etc.

[0052] In some of the embodiments, step S104, evaluating and verifying the decision plan, includes: determining evaluation criteria based on the specific application scenarios of the infrastructure; evaluating each decision plan according to the evaluation criteria, and performing preliminary screening; simulating and verifying the decision plans preliminarily screened, and optimizing the screening results.

[0053] Specifically, Figure 4 is a schematic diagram of the process of intelligent decision making in an embodiment of the present invention, such as Figure 4 As shown in the figure, first, multiple evaluation criteria and weights are determined according to the specific application scenario. These criteria may include response speed, resource utilization, economic cost, safety, operability, etc. Then, each generated solution is evaluated, and the comprehensive score of each solution is calculated using the Multiple Attribute Decision Making (MADM) method, such as the Analytic Hierarchy Process (AHP), the TOPSIS analysis method (Technique for Order Preference by Similarity to an Ideal Solution), and the elimination and selection conversion method (ELECTRE). By comparing the comprehensive scores, the better decision-making solutions are preliminarily screened out. Finally, the decision-making solutions preliminarily screened out are subjected to in-depth risk assessment and simulation verification to simulate the feasibility and effect of the decision-making solutions under different conditions. Simulation tools (such as simulation software) are used to verify the feasibility of the solution and further optimize the solution evaluation results.

[0054] Based on the above embodiment, step S104 optimizes the decision-making plan and determines the target plan for the risk failure information of the infrastructure, including: adjusting the parameters and strategies of the decision-making plan based on evaluation and verification to obtain the target plan to ensure the optimal performance of the decision-making plan in actual application.

[0055] After determining the target plan, a specific implementation plan is formulated based on the target plan, including details such as resource allocation, time arrangement, and division of responsibilities. During the implementation of the plan, the holographic sensing control platform is used for real-time monitoring to collect data and feedback information during the implementation process. Through the closed-loop feedback mechanism, the plan is continuously adjusted and optimized to ensure its effectiveness and reliability.

[0056] In actual application scenarios, the process of emergency response to the target solution is as follows: Figure 5 As shown, Figure 5 It is a flowchart for emergency disposal in an embodiment of the present invention. The emergency disposal function automatically starts the emergency response process according to the early warning information based on the emergency response plan library integrated by intelligent decision support. Specifically, the automatic emergency disposal function is realized through the following steps based on the selection result of the decision plan: First, according to the target plan, specific execution instructions are automatically generated. These instructions include emergency response operations, resource scheduling plans, personnel deployment arrangements, etc. And according to the instructions, necessary emergency resources are deployed, including equipment, personnel, materials, etc. Ensure the rapid arrival and reasonable allocation of emergency resources. Then, during the emergency disposal process, the execution of emergency operations is monitored in real time through the holographic sensing control platform. Sensor data, video monitoring information and other relevant data are collected to ensure the correctness and timeliness of the operation. And according to the real-time monitoring data and feedback information, the emergency disposal plan is automatically adjusted. For example, if it is found that a certain emergency operation cannot be carried out as planned, the plan will be automatically adjusted according to the actual situation and the instructions will be regenerated. Then, specific emergency operations are performed through automatic control systems (such as automation equipment, robots, etc.). For example, automatically closing certain valves, starting drainage systems, etc. The system automatically coordinates the actions of various emergency teams to ensure the coordinated implementation of various emergency operations. Use the communication system to maintain real-time contact with on-site personnel to ensure timely transmission of information. After the emergency response is completed, the system automatically collects all data from the response process and conducts a comprehensive evaluation. Analyze the effectiveness of the emergency response and identify successes and shortcomings. Based on the evaluation results, automatically generate improvement suggestions and optimization measures to improve the efficiency and effectiveness of future emergency response.

[0057] The present invention also provides a holographic sensing and control system for infrastructure multi-source heterogeneous data fusion security situation, including: An acquisition module, used to acquire risk failure information of infrastructure in a target area; A processing module is used to clean and verify the risk failure information of the infrastructure, and to correct the data of the risk failure information; The perception module is used to combine the pre-built knowledge base to conduct security situation awareness of risk failure information of the infrastructure and generate several decision-making plans; The optimization module is used to evaluate, verify and optimize decision-making plans and determine the target plan for risk failure information of infrastructure.

[0058] The present invention also provides a holographic sensing and control platform for infrastructure multi-source heterogeneous data fusion security situation. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control platform provided by the present invention is described below. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control platform described below and the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method described above can be referenced to each other. Figure 6 This is a structural block diagram of the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control platform provided by the present invention, such as Figure 6 As shown, the platform includes a perception module, a data transmission and management module, a data analysis module, a knowledge base module and an application module.

[0059] Among them, the perception module is used to obtain risk fault information of the infrastructure in the target area; the data transmission and management module is used to transmit and cloud store the risk fault information; the data analysis module is used to clean and verify the risk fault information, as well as to correct the data; the knowledge base module is used to store basic knowledge and historical data related to the operation of the infrastructure; the application module is used to evaluate and verify the decision-making plan and optimize the plan, and determine the target plan for the risk fault information of the infrastructure.

[0060] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor 701, a communications interface 702, a memory 703 and a communication bus 704, wherein the processor 701, the communications interface 702 and the memory 703 communicate with each other through the communication bus 704. The processor 701 may call the logic instructions in the memory 703 to execute the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method, the method comprising: Obtain risk failure information of infrastructure in the target area; Clean and verify the risk failure information of the infrastructure, and make data corrections to the risk failure information; Combined with the pre-built knowledge base, it conducts security situation awareness of infrastructure risk failure information and generates several decision-making plans; Evaluate, verify and optimize decision-making plans to determine target plans for infrastructure risk failure information.

[0061] In addition, the logic instructions in the above-mentioned memory 703 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0062] On the other hand, the present invention further provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method provided by the above methods, and the method includes: Obtain risk failure information of infrastructure in the target area; Clean and verify the risk failure information of the infrastructure, and make data corrections to the risk failure information; Combined with the pre-built knowledge base, it conducts security situation awareness of infrastructure risk failure information and generates several decision-making plans; Evaluate, verify and optimize decision-making plans to determine target plans for infrastructure risk failure information.

[0063] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method provided by the above methods, the method comprising: Obtain risk failure information of infrastructure in the target area; Clean and verify the risk failure information of the infrastructure, and make data corrections to the risk failure information; Combined with the pre-built knowledge base, it conducts security situation awareness of infrastructure risk failure information and generates several decision-making plans; Evaluate, verify and optimize decision-making plans to determine target plans for infrastructure risk failure information.

[0064] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0065] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A holographic sensing and control method for infrastructure multi-source heterogeneous data fusion security situation, characterized in that: include: Obtain risk failure information of infrastructure in the target area; Performing data cleaning and verification processing on the risk failure information of the infrastructure, and performing data correction on the risk failure information; Combined with the pre-built knowledge base, security situation awareness of risk failure information of the infrastructure is performed, and several decision-making plans are generated; The decision-making plan is evaluated, verified and optimized to determine a target plan for the risk failure information of the infrastructure.

2. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: Obtain risk failure information of infrastructure in the target area, including: The dynamic timing information and static discrete information of the infrastructure in the target area are sensed and captured in real time through pre-arranged sensing devices.

3. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: After obtaining the risk failure information of the infrastructure in the target area, it also includes: The risk failure information is stored in a database through a cloud storage solution.

4. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: Perform data cleaning and verification on the risk failure information of the infrastructure, including: filtering incomplete data in the risk failure information of the infrastructure; filtering erroneous data in the risk failure information of the infrastructure; Find and remove duplicate data in risk failure information for the infrastructure.

5. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: The risk fault information is corrected, including: An automatic spatial alignment algorithm for monitoring and inspection time series data is used to correct the inherent deviation of multi-channel data in the risk fault information; the basic model of the automatic spatial alignment algorithm for monitoring and inspection time series data includes a minimum space-time deviation estimation-double interpolation correction model and a multi-channel time series signal feature data matching model.

6. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 5 is characterized in that: An automatic spatial alignment algorithm for monitoring and inspection time series data is used to correct the inherent deviation of multi-channel data in the risk fault information, including: Based on the minimum spatiotemporal deviation estimation-double interpolation correction model, determining the minimum spatiotemporal deviation of the risk fault information, and performing deviation correction on the risk fault information; Based on the multi-channel time series signal feature data matching model, representative features are extracted from the time series signals of multiple channels of the risk fault information, and the representative features are compared and matched with pre-set target features to perform feature alignment processing.

7. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: Building the knowledge base includes: Based on the characteristics of the research results on the disaster mechanism of the infrastructure in the target area, basic knowledge is obtained and classified; Based on the basic knowledge, the knowledge base is constructed in combination with the disaster scenario type and disaster risk event type of the infrastructure.

8. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: Conduct security situation awareness of risk failure information of the infrastructure and generate several decision-making plans, including: Establishing a neural network model based on the monitoring time sequence of the infrastructure and the risk failure information of the infrastructure to predict the operation change trend of the infrastructure; Performing a safety assessment on the infrastructure based on the risk failure information of the infrastructure to obtain an assessment result; Generate a monitoring and analysis report for the infrastructure in combination with the operation change trend and evaluation results of the infrastructure; A pre-configured decision support system is called to generate several decision plans based on the monitoring and analysis report.

9. The infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control method according to claim 1 is characterized in that: Evaluate and verify the decision-making plan, including: Determine the evaluation criteria based on the specific application scenarios of the infrastructure; According to the evaluation criteria, each of the decision-making options is evaluated and preliminarily screened; Conduct simulation verification on the decision-making schemes initially screened out to optimize the screening results; Optimizing the decision-making plan to determine a target plan for the risk failure information of the infrastructure, including: On the basis of evaluation and verification, the parameters and strategies of the decision-making scheme are adjusted to obtain the target scheme.

10. An infrastructure multi-source heterogeneous data fusion security situation holographic sensing and control system, characterized by: include: An acquisition module, used to acquire risk failure information of infrastructure in a target area; A processing module, used for performing data cleaning and verification processing on the risk failure information of the infrastructure, and performing data correction on the risk failure information; A perception module, used to combine a pre-built knowledge base to conduct security situation perception of risk failure information of the infrastructure and generate a number of decision-making solutions; The optimization module is used to evaluate and verify the decision-making plan and optimize the plan to determine the target plan for the risk failure information of the infrastructure.

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