Ground monitoring system and method for verifying the risk status of infrastructure

Abstract

This invention relates to the field of infrastructure safety monitoring technology, specifically to a ground monitoring system and method for verifying the risk status of infrastructure. The method includes: acquiring the risk level, risk type, and status confidence level of the infrastructure, and integrating them into risk status information; dividing key risk areas and collecting infrastructure monitoring data in these areas in real time; mapping the infrastructure monitoring data to real-time operating status, performing consistency analysis between the real-time operating status and the risk status information, generating risk status verification results, and dynamically adjusting the monitoring strategy. The system includes: a risk status information acquisition module, a ground monitoring data acquisition module, a risk status verification module, and a monitoring strategy dynamic adjustment module. Through the above methods, the degree of matching between the risk status information and the actual operating status reflected by the on-site monitoring data is quantitatively judged from multiple dimensions, thereby improving the scientific nature, accuracy, and effectiveness of infrastructure safety risk management.

Description

Technical Field

[0001] This invention relates to the field of infrastructure safety monitoring technology, and in particular to a ground monitoring system and method for verifying the risk status of infrastructure. Background Technology

[0002] In the field of safety risk management for infrastructure and engineering structures such as highway slopes, bridges, tunnels, water conservancy projects, and municipal facilities, the rapid development and widespread application of remote sensing monitoring, IoT technology, and intelligent sensing methods have made the identification of infrastructure risk status and on-site entity monitoring a crucial support for engineering decision-making and risk prevention, providing key data and technical guarantees for the safe operation of infrastructure throughout its entire lifecycle. Currently, the industry has established a basic application system for infrastructure risk status identification methods and ground entity monitoring, capable of determining the risk level and type of infrastructure, as well as collecting data on on-site displacement, deformation, and environmental conditions. However, existing technologies still have the following problems in risk status identification results and on-site ground monitoring: The lack of a consistency verification mechanism between risk status and actual operational status makes it impossible to verify and correct risk assessment conclusions in a timely manner. Existing technologies lack a systematic analysis and verification framework between risk status information obtained from infrastructure risk assessment and the actual operational status reflected in on-site monitoring data. They cannot quantify the degree of matching between the two from multiple dimensions. When deviations exist between risk assessment conclusions and the actual on-site operational status of infrastructure, these deviations cannot be detected or identified in a timely manner, nor can the risk assessment conclusions be corrected based on actual on-site data. This easily leads to errors in risk assessment, thereby affecting the scientific validity of subsequent risk prevention and control engineering decisions. Summary of the Invention

[0003] The purpose of this invention is to provide a ground monitoring system and method for verifying the risk status of infrastructure. It aims to solve the technical problem in the prior art that when there is a deviation between the risk assessment conclusion and the actual operating status of the infrastructure on site, the deviation cannot be detected and identified in a timely manner, and the risk assessment conclusion cannot be corrected based on the actual on-site data. This can easily lead to errors in risk assessment and affect the scientific nature of subsequent risk prevention and control engineering decisions.

[0004] To achieve the above objectives, the present invention employs a ground monitoring method for verifying the risk status of infrastructure, comprising the following steps: Based on spatiotemporal state modeling and risk identification, risk assessment is performed on infrastructure to obtain the risk level, risk type, and state confidence of the infrastructure, and integrate them into risk state information; Define key risk areas, collect and output real-time infrastructure monitoring data in these areas; The infrastructure monitoring data is mapped to the real-time operating status, and the consistency analysis between the real-time operating status and the risk status information is performed to obtain the degree of matching and generate a risk status verification result containing the core indicators of the matching degree. Based on the risk status verification results, the monitoring strategy for key risk areas is dynamically adjusted.

[0005] Among them, in the steps of assessing the risks of infrastructure based on spatiotemporal state modeling and risk identification, obtaining the risk level, risk type, and state confidence of the infrastructure, and integrating them into risk state information: Collect basic information on the infrastructure's structural attributes, geographical distribution, historical operational data, and surrounding environmental data, and define the analytical boundaries for time series and spatial dimensions; Establish a logical correlation between infrastructure spatiotemporal state parameters and the probability of risk occurrence and the degree of risk impact; Collect current spatiotemporal status data of infrastructure; the spatiotemporal status data includes the operational status of different spatial locations and dynamic change data at different time points; Perform full-dimensional calculations on the current spatiotemporal state data, analyze the current state characteristics of the infrastructure, combine with preset risk assessment criteria, complete the preliminary risk assessment of the infrastructure, and output the assessment results.

[0006] The process includes the steps of performing full-dimensional calculations on the current spatiotemporal state data, analyzing the current state characteristics of the infrastructure, combining this with preset risk assessment criteria, completing a preliminary risk assessment of the infrastructure, and outputting the assessment results: The risk level and risk type of the infrastructure are extracted from the output judgment results, and the state confidence of the judgment results is calculated. Risk level, risk type, and status confidence are integrated into risk status information.

[0007] Among the steps, the following steps are involved: identifying critical risk areas, collecting real-time infrastructure monitoring data within these areas, and outputting the data: Based on the risk status information of the infrastructure, the scope of the risk-critical area is delineated, and ground monitoring equipment is deployed in the risk-critical area, and the monitoring points and basic monitoring frequencies are determined. Ground-based monitoring equipment is used to collect real-time data on the displacement, deformation, and environmental conditions of infrastructure in critical risk areas.

[0008] After acquiring monitoring data by using ground-based monitoring equipment to collect real-time data on the displacement, deformation, and environmental conditions of infrastructure in critical risk areas: The collected monitoring data undergoes preliminary noise reduction and deduplication preprocessing, and is then standardized and output in a unified format.

[0009] Among the steps, the following steps are involved: mapping infrastructure monitoring data to real-time operational status, performing consistency analysis between real-time operational status and risk status information, obtaining the degree of matching, and generating risk status verification results containing core indicators of the matching degree: Transform infrastructure monitoring data into quantifiable real-time infrastructure operational status; We extract corresponding analysis dimensions from risk status information and real-time operational status, and conduct multi-dimensional consistency comparison analysis.

[0010] After extracting corresponding analysis dimensions from risk status information and real-time operational status, and conducting multi-dimensional consistency comparison analysis: Based on the analysis results, the overall matching degree between risk status information and real-time operating status is calculated, and a complete risk status verification result is generated with the matching degree as the core indicator.

[0011] Among them, the step of dynamically adjusting the monitoring strategy for key risk areas based on the risk status verification results is as follows: Preset the adjustment rules for monitoring strategies corresponding to the risk status verification results, and divide the adjustment direction and magnitude into different matching degree ranges; The generated risk status verification results are matched with preset adjustment rules to determine the corresponding monitoring strategy adjustment plan; The adjustment plan will be implemented to adjust the monitoring locations, monitoring frequency, and monitoring scope in key risk areas.

[0012] After adjusting the monitoring locations, frequency, and scope of key risk areas according to the adjustment plan: Synchronously update and execute the operating parameters of the monitoring equipment.

[0013] This invention also provides a ground monitoring system for verifying the risk status of infrastructure, comprising a risk status information acquisition module, a ground monitoring data acquisition module, a risk status verification module, and a monitoring strategy dynamic adjustment module; wherein: The risk status information acquisition module is used to assess the risks of infrastructure based on spatiotemporal state modeling and risk discrimination, acquire the risk level, risk type, and status confidence of the infrastructure, and integrate them into risk status information. The ground monitoring data acquisition module is used to delineate key risk areas, collect infrastructure monitoring data in the key risk areas in real time, and output the data. The risk status verification module is used to map infrastructure monitoring data to real-time operating status, perform consistency analysis between real-time operating status and risk status information, obtain the degree of matching, and generate risk status verification results containing core indicators of matching degree. The monitoring strategy dynamic adjustment module is used to dynamically adjust the monitoring strategy for key risk areas based on the risk status verification results.

[0014] This invention discloses a ground monitoring system and method for verifying the risk status of infrastructure. The system comprises a risk status information acquisition module, a ground monitoring data acquisition module, a risk status verification module, and a monitoring strategy dynamic adjustment module, comprising the following steps: Risk assessment of infrastructure based on spatiotemporal state modeling and risk discrimination; acquisition of the infrastructure's risk level, risk type, and status confidence level, integrated into risk status information; division of key risk areas; real-time acquisition and output of infrastructure monitoring data within these areas; mapping of the infrastructure monitoring data to real-time operational status; consistency analysis of the real-time operational status and risk status information; obtaining the degree of matching; and generating a risk status verification result containing core indicators of the matching degree. Based on the risk status verification result, the monitoring strategy for the key risk areas is dynamically adjusted. Through these methods, the degree of matching between the risk status information and the actual operational status reflected by the on-site monitoring data is quantitatively assessed from multiple dimensions, thereby improving the scientific, accurate, and effective nature of infrastructure safety risk management. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the steps of the ground monitoring method for verifying the risk status of infrastructure according to the present invention.

[0017] Figure 2 This is a flowchart of steps S100 of the present invention.

[0018] Figure 3 This is a flowchart of steps S200 of the present invention.

[0019] Figure 4 This is a flowchart of steps S300 of the present invention.

[0020] Figure 5 This is a flowchart of steps S400 of the present invention.

[0021] Figure 6 This is a schematic diagram of the ground monitoring system for verifying the risk status of infrastructure according to the present invention.

[0022] Figure 7This is a schematic diagram of the electronic device of the present invention.

[0023] 501-Risk status information acquisition module, 502-Ground monitoring data acquisition module, 503-Risk status verification module, 504-Monitoring strategy dynamic adjustment module. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0025] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0026] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0027] Please see Figures 1-5 This invention provides a ground monitoring method for verifying the risk status of infrastructure, comprising the following steps: S100: Based on spatiotemporal state modeling and risk identification, risk assessment is performed on infrastructure to obtain the risk level, risk type, and state confidence of the infrastructure, and integrate them into risk state information.

[0028] In this embodiment, risk assessment of infrastructure is performed based on spatiotemporal state modeling and risk discrimination to obtain the infrastructure's risk level, risk type, and state confidence level, which are then integrated into risk state information. The specific process is as follows: S101: Collect basic information on the structural attributes, geographical distribution, historical operation data, and surrounding environment data of infrastructure, and delineate the analysis boundaries of time series and spatial dimensions; S102: Establish the logic linking infrastructure spatiotemporal state parameters with the probability of risk occurrence and the degree of risk impact; S103: Collect current spatiotemporal status data of infrastructure; the spatiotemporal status data includes the operational status of different spatial locations and dynamic change data at different time points; S104: Perform full-dimensional calculations on the current spatiotemporal state data, analyze the current state characteristics of the infrastructure, combine with preset risk assessment criteria, complete the preliminary risk assessment of the infrastructure, and output the assessment results; S105: Extract the risk level and risk type of the infrastructure from the output judgment results, and calculate the state confidence of the judgment results; S106: Integrate risk level, risk type, and status confidence into risk status information.

[0029] In the above process, comprehensive multi-dimensional basic information of infrastructure is collected, covering structural attributes (such as material, specifications, construction years, and structural form), geographical distribution (such as latitude and longitude, topography, and regional location), historical operation data (such as past deformation, displacement records, fault maintenance information, and risk occurrence cases), and surrounding environmental data (such as meteorological conditions, geological conditions, hydrological data, and distribution of surrounding buildings). Subsequently, in combination with the type of infrastructure (highway slopes, bridges, tunnels, water conservancy projects, etc.) and risk prevention and control needs, the time series analysis boundaries (such as the time intervals for short-term real-time monitoring, medium-term operation analysis, and long-term aging assessment) and the spatial dimension analysis boundaries (such as key structural parts of infrastructure, different geographical zones, and surrounding impact range) are defined to determine the core scope and indicator dimensions of spatiotemporal state analysis.

[0030] Based on the collected basic information and the defined spatiotemporal analysis boundaries, the core spatiotemporal state parameters of the infrastructure are identified (such as displacement rates at different spatial locations, deformation at different time points, and environmental factors changing over time). Through statistical analysis, machine learning modeling, and engineering experience summarization, a quantitative and qualitative correlation logic between each spatiotemporal state parameter and the probability and degree of risk occurrence is established. This clarifies the likelihood of risk occurrence corresponding to different parameter variation ranges, as well as the impact of parameter anomalies on the structural safety and operational functions of the infrastructure, laying a logical foundation for subsequent risk assessment.

[0031] Relying on IoT monitoring equipment, on-site inspection and data collection, and remote sensing monitoring, real-time spatiotemporal status data of infrastructure is collected. Spatial data includes the real-time operating status of different key parts and locations of the infrastructure (such as the displacement of bridge bearings, soil stress in different sections of slopes, and deformation of tunnel walls). Temporal data includes dynamic changes of the infrastructure at continuous time points (such as hourly displacement changes, daily environmental parameter fluctuations, and phased structural aging data). During the collection process, the data is ensured to accurately correspond to the preset spatiotemporal analysis boundaries, and traceability information such as data collection time, collection point, and collection equipment is recorded.

[0032] Based on the established correlation logic between spatiotemporal state parameters and risks, the data is analyzed in all dimensions to extract the core state characteristics of the infrastructure (such as whether the parameters are abnormal, the magnitude of the abnormality, the trend of change, spatiotemporal coupling characteristics, etc.). At the same time, combined with the risk judgment standards preset by engineering specifications, industry standards and actual prevention and control needs (such as the threshold range of different parameters, the basis for risk level classification, and the conditions for risk type judgment), the state characteristics obtained from the analysis are matched with the risk judgment standards one by one to complete the preliminary risk judgment of the infrastructure and output the judgment results including preliminary risk conclusions, judgment basis and data support.

[0033] From the preliminary risk assessment results, the risk level (such as standardized classification of high, medium, low, and no risk) and risk type (such as slope slippage, bridge bearing aging, tunnel wall deformation, and water conservancy project leakage) corresponding to the infrastructure are accurately extracted according to the preset extraction rules. Then, by calculating the completeness of the data, the accuracy of parameter matching, and the applicability of the correlation logic in the assessment process, the state confidence of this risk assessment result is quantitatively calculated. The confidence is presented in the form of percentage or decimal, which intuitively reflects the reliability of the risk assessment result. At the same time, the calculation process and basis are recorded.

[0034] Standardized integration rules for risk status information are established to unify the expression and data format of risk levels, risk types, and status confidence levels. Subsequently, the extracted risk levels, risk types, and calculated status confidence levels are standardized and organized, while supplementing basic traceability information such as unique identifiers of infrastructures, analysis time and space range, and data collection periods. Finally, the above information is integrated according to a pre-set structured framework (such as information tables with fixed fields and standardized messages) to generate complete, standardized risk status information that can be directly used in subsequent stages, ensuring the integrity, relevance, and standardization of the information.

[0035] S200: Define risk-critical areas, collect infrastructure monitoring data in these areas in real time, and output the data.

[0036] In this implementation, risk-critical areas are defined, and infrastructure monitoring data within these areas is collected and output in real time. The specific process is as follows: S201: Based on the risk status information of the infrastructure, delineate the scope of the risk-critical area, deploy ground monitoring equipment within the risk-critical area, and divide the monitoring points and basic monitoring frequency. S202: Use ground monitoring equipment to collect real-time data on the displacement, deformation, and environmental conditions of infrastructure in critical risk areas to obtain monitoring data; S203: Perform preliminary noise reduction and deduplication preprocessing on the collected monitoring data, unify the format, and output in a standardized manner.

[0037] In the above process, based on the risk status information generated in step S100, and combined with the structural characteristics, spatial distribution, and risk assessment conclusions of the infrastructure, the scope of the critical risk areas is delineated. Priority is given to designating infrastructure parts with high risk levels and clearly defined risk types, as well as their surrounding affected areas, as core critical areas, and areas with medium risk levels as secondary critical areas. Within the designated critical risk areas, ground monitoring equipment (such as displacement monitors, deformation sensors, rain gauges, stress monitoring equipment, etc.) is deployed according to the risk type and monitoring needs. At the same time, based on the regional risk level and the complexity of the infrastructure structure, monitoring points are scientifically divided (such as dense deployment in core critical areas and routine deployment in secondary critical areas), and the basic monitoring frequency of each monitoring point is determined (such as real-time monitoring in high-risk areas and timed monitoring in medium-risk areas), forming a complete monitoring deployment and basic rule scheme.

[0038] According to the preset monitoring rules, all ground monitoring equipment in the risk-critical area is activated to continuously and in real time collect data on infrastructure displacement (such as horizontal and vertical displacement), deformation (such as structural strain, deformation amount, and deformation rate), and environmental data (such as temperature, humidity, rainfall, wind speed, and geological moisture content). During the collection process, the normal operation of the equipment is ensured, the collected data is transmitted in real time, and the collected data is initially recorded in real time, with the time, location, and equipment number of the data collection marked to ensure the real-time nature, continuity, and traceability of the data and to avoid data loss or interruption.

[0039] The collected raw monitoring data undergoes preliminary preprocessing. Duplicate data from the same monitoring location and time, as well as redundant data caused by equipment malfunctions or signal interference, are removed using pre-defined deduplication rules. Noise reduction methods adapted to infrastructure monitoring data are employed to identify and correct abnormal noise data caused by environmental interference and equipment operational fluctuations, eliminating invalid data that significantly deviates from the normal data range and restoring the true characteristics of the data. Subsequently, the data is standardized according to a pre-defined standardized format, unifying the units of measurement, numerical precision, timestamp representation, and location coding, thus achieving unified data format standardization. Finally, the preprocessed standardized data is output in a standardized manner according to the receiving requirements of subsequent stages, in the form of structured data tables, standardized data messages, and specified database formats. Data backups are also maintained to ensure that the output data can be directly recognized and used by subsequent stages.

[0040] S300: Maps infrastructure monitoring data to real-time operating status, performs consistency analysis between real-time operating status and risk status information, obtains the degree of matching, and generates risk status verification results containing core indicators of matching degree.

[0041] In this embodiment, infrastructure monitoring data is mapped to real-time operational status, and a consistency analysis is performed between the real-time operational status and risk status information to obtain the degree of matching, generating a risk status verification result containing core indicators of the matching degree. The specific process is as follows: S301: Convert infrastructure monitoring data into quantifiable real-time infrastructure operating status; S302: Extract corresponding analysis dimensions from risk status information and real-time operating status, and conduct multi-dimensional consistency comparison analysis; S303: Calculate the overall matching degree between risk status information and real-time operating status based on the analysis results, and generate complete risk status verification results with matching degree as the core indicator.

[0042] In the above process, mapping rules between infrastructure monitoring data and operational status are formulated. Combining the engineering characteristics and operational standards of different types of infrastructure, the operational status levels (such as normal, minor anomaly, moderate anomaly, and severe anomaly) corresponding to different monitoring data ranges and data change trends are clarified. Each operational status is then quantified and assigned a value to achieve quantifiable analysis of the operational status. Subsequently, the standardized monitoring data output by S203 is substituted into the mapping rules. Through data matching, trend analysis, threshold comparison, and other methods, the specific monitoring data is converted into corresponding quantitative values ​​to form the real-time operational status of the infrastructure that can be directly used for analysis. At the same time, the core characteristics and anomalies of the real-time operational status are identified.

[0043] From the risk status information generated in step S100, key analytical dimensions such as risk level, risk type, and core spatiotemporal parameters associated with the risk are extracted. Simultaneously, from the real-time operating status obtained in step S301, corresponding matching analytical dimensions such as operating status level, anomaly type, and changes in core monitoring parameters are extracted to ensure that the analytical dimensions of the two are one-to-one and accurately matched. Subsequently, for each pair of corresponding dimensions, a multi-dimensional consistency comparison analysis is carried out, including qualitative comparison (such as whether the risk type and anomaly type are consistent, and whether the risk level and operating status level match) and quantitative comparison (such as the numerical deviation and trend deviation between the risk-related parameters and the actual monitoring parameters). The comparison analysis results, degree of deviation, and judgment basis of each dimension are recorded one by one.

[0044] Based on the weight of each analytical dimension in determining infrastructure risk, a corresponding weight coefficient is assigned to each comparative analysis dimension (e.g., the weight of core risk parameter dimensions is higher than that of auxiliary dimensions). Simultaneously, the quantitative standards for the comparison results of each dimension are clarified, converting qualitative and quantitative comparison results into dimension matching scores of 0-100%. Subsequently, based on the comparative analysis results of each dimension, the individual matching score of each dimension is calculated. Through weighted summation, the overall comprehensive matching score between real-time operational status and risk status information is calculated; this score is the core indicator of the risk status verification result. Next, according to the preset matching score level classification standards, the overall comprehensive matching score is graded (e.g., perfect match, basic match, significant deviation, severe discrepancy). Finally, the overall comprehensive matching score, matching score level, individual matching scores of each dimension, comparative analysis details, and abnormal dimension annotations are structured and integrated. After supplementing the source information, a complete risk status verification result containing the core matching score indicator is generated, providing a comprehensive basis for subsequent monitoring strategy adjustments.

[0045] S400: Based on the risk status verification results, dynamically adjust the monitoring strategy for key risk areas.

[0046] In this implementation, the monitoring strategy for key risk areas is dynamically adjusted based on the risk status verification results. The specific process is as follows: S401: Preset the adjustment rules for monitoring strategies corresponding to the risk status verification results, and divide the adjustment direction and magnitude into different matching degree intervals; S402: Match the generated risk status verification results with the preset adjustment rules to determine the corresponding monitoring strategy adjustment plan; S403: Adjust the monitoring points, monitoring frequency, and monitoring range of the risk-critical areas according to the adjustment plan, and update and execute the operating parameters of the monitoring equipment simultaneously.

[0047] In the above process, based on the actual needs of infrastructure risk management and the allocation of monitoring resources, pre-set corresponding rules for risk status verification results and monitoring strategy adjustments are established. According to the core matching index generated by S303, different matching degree ranges are divided (e.g., 90% and above is a complete match, 70%~89% is a basic match, 40%~69% is a large deviation, and below 40% is a serious mismatch). At the same time, the direction and magnitude of monitoring strategy adjustments corresponding to each matching degree range are clearly defined, including specific adjustment requirements such as adding / removing monitoring points, increasing / decreasing monitoring frequency, and expanding / shrinking the monitoring scope, to ensure the scientific, operable, and targeted nature of the adjustment rules.

[0048] The overall comprehensive matching degree, matching degree level, and anomaly dimension labeling in the risk status verification results generated in step S303 are precisely matched with the preset monitoring strategy adjustment rules. Based on the matching results and the actual situation of the key risk areas (such as infrastructure structure, distribution of monitoring equipment, and monitoring resources), a specific monitoring strategy adjustment plan is formulated, which clarifies the key risk areas that need to be adjusted, the specific adjustment content (such as which points to add equipment, which areas to increase the monitoring frequency, and the specific boundaries of the expanded monitoring range), the priority of the adjustment implementation, and the required monitoring resources. At the same time, the rationality and feasibility of the adjustment plan are preliminarily verified to ensure that the plan can effectively solve the deviation problems found in the verification results.

[0049] According to the established monitoring strategy adjustment plan, specific adjustment operations are organized and implemented, including adding, deleting, or optimizing the location of monitoring points in key risk areas, resetting the monitoring frequency of each monitoring point, and expanding or shrinking the monitoring range. Simultaneously, the adjusted monitoring rules (such as monitoring frequency, monitoring range, and data transmission requirements) are updated to the operating parameters of all ground monitoring equipment to ensure that the equipment operates normally according to the new monitoring strategy. After the adjustment is implemented, the operating status of the monitoring equipment and the data collection status are verified in real time to confirm that the adjusted monitoring strategy can be implemented, forming a closed loop of dynamic adjustment of the monitoring strategy and ensuring that the monitoring data can accurately match the actual risk status of the infrastructure.

[0050] Corresponding to the aforementioned embodiments of ground monitoring methods for verifying the risk status of infrastructure, this application also provides embodiments of ground monitoring systems for verifying the risk status of infrastructure.

[0051] Figure 6 This is a block diagram illustrating a ground monitoring system for verifying the risk status of infrastructure, according to an exemplary embodiment. (Refer to...) Figure 6 The system may include: a risk status information acquisition module 501, a ground monitoring data acquisition module 502, a risk status verification module 503, and a monitoring strategy dynamic adjustment module 504; wherein: The risk status information acquisition module 501 is used to perform risk assessment on the infrastructure based on spatiotemporal state modeling and risk discrimination, acquire the risk level, risk type, and status confidence of the infrastructure, and integrate them into risk status information. The ground monitoring data acquisition module 502 is used to divide the risk-critical areas, collect infrastructure monitoring data in the risk-critical areas in real time, and output the data. The risk status verification module 503 is used to map infrastructure monitoring data to real-time operating status, perform consistency analysis on real-time operating status and risk status information, obtain the degree of matching, and generate a risk status verification result containing core indicators of matching degree. The monitoring strategy dynamic adjustment module 504 is used to dynamically adjust the monitoring strategy for key risk areas based on the risk status verification results.

[0052] In this embodiment, the risk status information acquisition module 501 assesses the risks of infrastructure based on spatiotemporal state modeling and risk discrimination, acquiring the risk level, risk type, and status confidence of the infrastructure, and integrating them into risk status information. The ground monitoring data acquisition module 502 divides key risk areas, collects infrastructure monitoring data in these areas in real time, and outputs the data. The risk status verification module 503 maps the infrastructure monitoring data to real-time operating status and performs consistency analysis between the real-time operating status and the risk status information to obtain the degree of matching, generating a risk status verification result containing core indicators of the degree of matching. The monitoring strategy dynamic adjustment module 504 dynamically adjusts the monitoring strategy for key risk areas based on the risk status verification result. Through the above methods, the degree of matching between the risk status information and the actual operating status reflected by the on-site monitoring data is quantitatively judged from multiple dimensions, thereby improving the scientific, accurate, and effective nature of infrastructure safety risk management.

[0053] Regarding the system in the above embodiments, the specific manner in which each module performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0054] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0055] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the ground monitoring method for verifying the infrastructure risk status as described above. Figure 7 The diagram shown is a hardware structure diagram of any data processing-capable device within a ground monitoring system for verifying the risk status of infrastructure, as provided in an embodiment of the present invention. (Except for...) Figure 7 In addition to the processor, memory, and network interface shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0056] Accordingly, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the ground monitoring method for verifying the risk status of infrastructure as described above. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.

[0057] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0058] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A ground-based monitoring method for verifying the risk status of infrastructure, characterized in that, Includes the following steps: Based on spatiotemporal state modeling and risk identification, risk assessment is performed on infrastructure to obtain the risk level, risk type, and state confidence of the infrastructure, and integrate them into risk state information; Define key risk areas, collect and output real-time infrastructure monitoring data in these areas; The infrastructure monitoring data is mapped to the real-time operating status, and the consistency analysis between the real-time operating status and the risk status information is performed to obtain the degree of matching and generate a risk status verification result containing the core indicators of the matching degree. Based on the risk status verification results, the monitoring strategy for key risk areas is dynamically adjusted.

2. The ground monitoring method for verifying the risk status of infrastructure as described in claim 1, characterized in that, In the steps of assessing infrastructure risk based on spatiotemporal state modeling and risk identification, obtaining the infrastructure's risk level, risk type, and state confidence level, and integrating them into risk state information: Collect basic information on the infrastructure's structural attributes, geographical distribution, historical operational data, and surrounding environmental data, and define the analytical boundaries for time series and spatial dimensions; Establish a logical correlation between infrastructure spatiotemporal state parameters and the probability of risk occurrence and the degree of risk impact; Collect current spatiotemporal status data of infrastructure; The spatiotemporal state data includes the operational status at different spatial locations and the dynamic change data at different time points; Perform full-dimensional calculations on the current spatiotemporal state data, analyze the current state characteristics of the infrastructure, combine with preset risk assessment criteria, complete the preliminary risk assessment of the infrastructure, and output the assessment results.

3. The ground monitoring method for verifying the risk status of infrastructure as described in claim 2, characterized in that, After performing full-dimensional calculations on the current spatiotemporal state data, analyzing the current state characteristics of the infrastructure, combining it with preset risk assessment criteria, completing the preliminary risk assessment of the infrastructure, and outputting the assessment results: The risk level and risk type of the infrastructure are extracted from the output judgment results, and the state confidence of the judgment results is calculated. Risk level, risk type, and status confidence are integrated into risk status information.

4. The ground monitoring method for verifying the risk status of infrastructure as described in claim 1, characterized in that, In the steps of delineating risk-critical areas, collecting real-time infrastructure monitoring data within these areas, and outputting the data: Based on the risk status information of the infrastructure, the scope of the risk-critical area is delineated, and ground monitoring equipment is deployed in the risk-critical area, and the monitoring points and basic monitoring frequencies are determined. Ground-based monitoring equipment is used to collect real-time data on the displacement, deformation, and environmental conditions of infrastructure in critical risk areas.

5. The ground monitoring method for verifying the risk status of infrastructure as described in claim 4, characterized in that, After acquiring monitoring data by using ground-based monitoring equipment to collect real-time data on the displacement, deformation, and environmental conditions of infrastructure in critical risk areas: The collected monitoring data undergoes preliminary noise reduction and deduplication preprocessing, and is then standardized and output in a unified format.

6. The ground monitoring method for verifying the risk status of infrastructure as described in claim 1, characterized in that, In the steps of mapping infrastructure monitoring data to real-time operational status, performing consistency analysis between real-time operational status and risk status information, obtaining the degree of matching, and generating risk status verification results containing core indicators of the matching degree: Transform infrastructure monitoring data into quantifiable real-time infrastructure operational status; We extract corresponding analysis dimensions from risk status information and real-time operational status, and conduct multi-dimensional consistency comparison analysis.

7. The ground monitoring method for verifying the risk status of infrastructure as described in claim 6, characterized in that, After extracting corresponding analytical dimensions from risk status information and real-time operational status, and performing multi-dimensional consistency comparison analysis: Based on the analysis results, the overall matching degree between risk status information and real-time operating status is calculated, and a complete risk status verification result is generated with the matching degree as the core indicator.

8. The ground monitoring method for verifying the risk status of infrastructure as described in claim 1, characterized in that, In the step of dynamically adjusting the monitoring strategy for key risk areas based on the risk status verification results: Preset the adjustment rules for monitoring strategies corresponding to the risk status verification results, and divide the adjustment direction and magnitude into different matching degree ranges; The generated risk status verification results are matched with preset adjustment rules to determine the corresponding monitoring strategy adjustment plan; The adjustment plan will be implemented to adjust the monitoring locations, monitoring frequency, and monitoring scope in key risk areas.

9. The ground monitoring method for verifying the risk status of infrastructure as described in claim 8, characterized in that, After adjusting the monitoring locations, monitoring frequency, and monitoring scope of key risk areas according to the adjustment plan: Synchronously update and execute the operating parameters of the monitoring equipment.

10. A ground monitoring system for verifying the risk status of infrastructure, employing the ground monitoring method for verifying the risk status of infrastructure as described in claim 1, characterized in that, It includes a risk status information acquisition module, a ground monitoring data acquisition module, a risk status verification module, and a monitoring strategy dynamic adjustment module; among which: The risk status information acquisition module is used to assess the risks of infrastructure based on spatiotemporal state modeling and risk discrimination, acquire the risk level, risk type, and status confidence of the infrastructure, and integrate them into risk status information. The ground monitoring data acquisition module is used to delineate key risk areas, collect infrastructure monitoring data in the key risk areas in real time, and output the data. The risk status verification module is used to map infrastructure monitoring data to real-time operating status, perform consistency analysis between real-time operating status and risk status information, obtain the degree of matching, and generate risk status verification results containing core indicators of matching degree. The monitoring strategy dynamic adjustment module is used to dynamically adjust the monitoring strategy for key risk areas based on the risk status verification results.

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