A building safety performance evaluation method and system

Abstract

The present application relates to the technical field of building safety evaluation, in particular to a building safety performance evaluation method and system, comprising the following steps: collecting displacement and acceleration data of the building, using optical fiber sensors to measure in real time, checking the quality of the data, combining time series analysis and recording data changes to obtain real-time monitoring data.In the present application, by real-time monitoring of building displacement and acceleration data, combined with time series analysis and recording data changes, the building safety performance evaluation provides significant improvement in real-time and accuracy, by identifying abnormal patterns and potential weaknesses in building structures, potential safety hazards can be detected at an early stage, reducing the risk of accidents, through quantitative evaluation of risk areas, not only enhancing the ability of buildings to resist natural and man-made threats, but also providing important reference data for future design and construction, improving the scientificity and advancement of building safety evaluation.

Description

Technical Field

[0001] This invention relates to the field of building safety assessment technology, and in particular to a method and system for assessing building safety performance. Background Technology

[0002] The field of building safety assessment technology focuses on analyzing and evaluating the safety performance of buildings during design, construction, and use. This includes assessing the physical and mechanical properties of building structures to ensure structural safety and functional integrity under normal use conditions and various extreme circumstances (such as earthquakes, storms, and fires). Assessment methods involve static and dynamic structural analysis, material fatigue testing, and long-term monitoring of the durability and reliability of various building components. Building safety assessment also emphasizes the development of preventative and improvement measures to enhance the building's resistance to natural and man-made threats.

[0003] Building safety performance assessment methods refer to a specific set of techniques or procedures designed to systematically evaluate the safety performance of buildings. This involves using advanced technologies and tools, such as digital simulation, physical testing, and Building Information Modeling (BIM) technology, to identify weaknesses that threaten the structural safety of buildings. Its primary purpose is to help architects, engineers, and maintenance managers understand the current safety status of buildings, develop corresponding reinforcement and improvement measures, and provide a reference for future design and construction. It can significantly improve building safety, reduce the risk of accidents, and ensure the safety of people and property.

[0004] Existing building safety assessment technologies primarily rely on traditional methods such as static and dynamic structural analysis, material fatigue testing, and long-term observation. While historically widely used, these methods have significant shortcomings in real-time data processing and immediate response capabilities under extreme conditions. Particularly during extreme natural events like earthquakes and storms, the inability to capture critical data in real time leads to assessment results lagging behind actual needs, failing to effectively support rapid response in emergency situations. Traditional assessment methods also often exhibit limitations in data integration and processing, such as low data update frequency and difficulty in achieving comprehensive real-time monitoring, directly impacting the comprehensiveness and accuracy of the assessment and resulting in the inability to provide necessary safety guarantees at critical moments. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method and system for evaluating the safety performance of buildings.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for assessing the safety performance of a building, comprising the following steps:

[0007] S1: Collect displacement and acceleration data of the building, measure them in real time using fiber optic sensors, check the quality of the data, and obtain real-time monitoring data by combining time series analysis and recording data changes.

[0008] S2: Using the real-time monitoring data, optimize the damping and mechanical response of the building's support structure, adjust and match changes in external and internal loads in real time, and obtain adjustment response records;

[0009] S3: Based on the adjusted response records, identify the building response characteristics under extreme weather and earthquake conditions, assess the building's safety performance, configure emergency modes, and establish emergency response strategies;

[0010] S4: Implement the emergency response strategy, perform recursive pattern analysis on the building structure, evaluate the frequency and impact of repeating patterns through relationship diagrams and node analysis, identify abnormal patterns and potential weaknesses, and obtain structural behavior patterns.

[0011] S5: Based on the structural behavior pattern, perform a quantitative assessment of the risk area, compare and analyze the standard design data and the real-time performance of the building, and generate potential risk identification results by calculating deviations and potential risk points;

[0012] S6: Based on the potential risk identification results, calculate the entropy value of the building structure, analyze the trend of entropy value change over time, identify the degradation and damage of the building's safety performance structure, and obtain the health status assessment results.

[0013] As a further aspect of the present invention, the real-time monitoring data includes time stamps, amplitude and frequency changes of the data; the adjustment response record includes response time, changes in mechanical properties and matching degree with load changes; the emergency response strategy includes the configuration of the building's safety performance assessment results and emergency modes under extreme weather and earthquake conditions; the structural behavior patterns include repetitive loading response patterns, abnormal structural behavior and potential structural weaknesses; the potential risk identification results include structural deviation values, key risk points and potential damage areas; and the health status assessment results include time series analysis of entropy values ​​and trend identification of building structural degradation and damage.

[0014] As a further aspect of the present invention, the steps of collecting displacement and acceleration data of buildings, measuring them in real time using fiber optic sensors, verifying the quality of the data, and combining time series analysis and recording data changes to obtain real-time monitoring data are as follows:

[0015] S101: Collects displacement and acceleration data of buildings, deploys fiber optic sensors at key points of the building structure, including columns, beams and foundations, extracts information from key areas of structural performance, and generates raw monitoring data.

[0016] S102: Based on the original monitoring data, perform data quality inspection, eliminate noise and errors, adjust the sensitivity of the fiber optic sensor and the data collection frequency, check the consistency of the data, and obtain the corrected data;

[0017] S103: Using the corrected data, record and analyze the data change trends, including periodic changes and emergency response. By analyzing the time series of the data, identify the behavioral characteristics of the building under differentiated conditions and obtain real-time monitoring data.

[0018] As a further aspect of the present invention, the steps of using the real-time monitoring data to optimize the damping and mechanical response of the building's support structure, and to adjust and match changes in external and internal loads in real time to obtain the adjustment response record are as follows:

[0019] S201: Based on the real-time monitoring data, evaluate the structural behavior of the building, identify key load points and pressure distribution, identify the locations of damping and support structures that need to be optimized, and generate structural behavior evaluation results;

[0020] S202: Based on the structural behavior assessment results, calculate the required damping adjustment and support strength, adjust the structural parameters of the building to match the detected load changes, verify the structural response to match the real-time load, and generate parameter adjustment records;

[0021] S203: Using the parameters to adjust the record, monitor the response effect of the adjusted structure, track the performance of the damping and support structure, verify the matching degree between the adjustment effect and the expectation, evaluate the complete adjustment effect, and obtain the adjustment response record.

[0022] As a further aspect of the present invention, the steps of identifying building response characteristics under extreme weather and earthquake conditions, assessing building safety performance, configuring emergency modes, and establishing emergency response strategies based on the adjusted response records are as follows:

[0023] S301: Analyze the adjustment response records, identify data under emergency conditions such as extreme weather and earthquakes, calibrate key performance indicators, including displacement and stress response, identify the behavior of building structures under high pressure, and generate key performance data;

[0024] S302: Based on the aforementioned key performance data, conduct a safety performance assessment of the building, analyze the building's safety level by comparing it with industry safety standards, identify potential risk points, and generate a safety assessment result;

[0025] S303: Based on the safety assessment results, configure emergency measures for automatic damping adjustment and support reinforcement. If an extreme event is detected, the emergency measures will be automatically activated to optimize the safety performance of the building and establish an emergency response strategy.

[0026] As a further aspect of the present invention, the steps of implementing the emergency response strategy, performing recursive pattern analysis on the building structure, evaluating the frequency and impact of recurring patterns through relationship diagrams and node analysis, identifying anomalous patterns and potential weaknesses, and obtaining structural behavior patterns are as follows:

[0027] S401: Implement the emergency response strategy to monitor the structural safety performance of the building in real time, including collecting structural response data of the building during weather warnings and seismic activity, and generating target monitoring data;

[0028] S402: Based on the target monitoring data, construct a relationship diagram of structural behavior, evaluate the repetitive behavior patterns and influences in the building's safety performance structure through node and edge analysis, identify stress distribution and displacement patterns, and generate pattern analysis results;

[0029] S403: Using the pattern analysis results, perform abnormal pattern detection, identify structural responses that deviate from the normal behavior pattern, identify potential weaknesses and causes of failure in the building's safety performance structure, and obtain the structural behavior pattern.

[0030] As a further aspect of the present invention, based on the structural behavior pattern, a quantitative assessment of the risk area is performed, and the standard design data and the real-time performance of the building are compared and analyzed. The specific steps for generating potential risk identification results by calculating deviations and potential risk points are as follows:

[0031] S501: Using the aforementioned structural behavior pattern, quantitatively assess the key areas of the building's safety performance structure, identify areas subjected to stress and displacement, mark them as risk points, and generate risk area data;

[0032] S502: Based on the risk area data, compare the building's design parameters and real-time monitoring results, calculate the deviation between the design parameters and real-time monitoring results, analyze the difference between real-time performance and design standards, and generate deviation analysis results;

[0033] S503: Using the deviation analysis results, iteratively analyze and calculate potential risk points in the building's safety performance structure, including stress concentration and structural fatigue signs, and extract key information to obtain potential risk identification results.

[0034] As a further aspect of the present invention, the steps of calculating the entropy value of the building structure based on the potential risk identification results, analyzing the trend of entropy value changes over time, identifying the degradation and damage of the building's safety performance structure, and obtaining the health status assessment results are as follows:

[0035] S601: Using the potential risk identification results, the Monte Carlo method is used to quantitatively analyze the structural safety performance of the building. By calculating the entropy value of the structure, the overall stability of the structural safety performance of the building is analyzed, and initial entropy value data is generated.

[0036] S602: Based on the initial entropy value data, analyze the trend of entropy value change over time, identify the fluctuation of structural entropy value of building safety performance by analyzing the time series, record the changes in structural stability, and generate entropy value trend analysis results;

[0037] S603: Using the entropy trend analysis results, identify the degradation and damage development trends in the building's safety performance structure, identify and analyze safety hazards and problem areas that need to be addressed first, and obtain the health status assessment results.

[0038] As a further aspect of the present invention, the formula of the Monte Carlo method is as follows:

[0039]

[0040] Where H is the weighted entropy value, p i Let w be the probability of the state. i Let f be the weighting coefficient for state i, β be the risk adjustment coefficient, and f be the weighting coefficient for state i. j For the weights of the risk factors, d j This is a distance metric for risk factors, where n is the total number of states and m is the total number of risk factors.

[0041] A building safety performance assessment system, the building safety performance assessment system being used to execute the above-described building safety performance assessment method, the system comprising:

[0042] The data collection module collects building displacement and acceleration data, uses fiber optic sensors to measure the data in real time, and combines time series analysis to record data changes and obtain real-time monitoring data.

[0043] Based on the real-time monitoring data, the data processing module analyzes the mechanical properties of the data, adjusts the damping and support structure of the building in real time, matches the changes in external and internal loads, and obtains adjustment response records.

[0044] The strategy construction module assesses the building's response characteristics under extreme weather and earthquake conditions by adjusting the response records, and constructs emergency modes to establish emergency response strategies.

[0045] The pattern recognition module executes the emergency response strategy, performs recursive pattern analysis on the building structure, analyzes and evaluates the frequency and impact of differentiated patterns, identifies abnormal patterns, and generates structural behavior patterns.

[0046] The risk assessment module uses the structural behavior pattern to quantitatively assess the risk area, compares and analyzes standard design data and the real-time performance of the building, calculates the entropy value of the building structure, records changes in structural stability, and obtains the health status assessment results.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0048] This invention employs fiber optic sensors to monitor building displacement and acceleration data in real time, combined with time-series analysis to record data changes, significantly improving the real-time performance and accuracy of building safety performance assessments. Real-time monitoring data enables safety assessments to respond promptly to the building's actual condition, effectively optimizing damping and support structures, matching internal and external load changes, and ensuring structural stability under extreme conditions. Recursive pattern analysis and relational graph node analysis identify abnormal patterns and potential weaknesses in the building structure, allowing for the discovery of potential safety hazards at an early stage and reducing the risk of accidents. Quantitative assessment of risk areas, comparing design data with real-time performance, not only enhances the building's resistance to natural and man-made threats but also provides crucial reference data for future design and construction, improving the scientific rigor and sophistication of building safety assessments. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flowchart of S1 of the present invention;

[0051] Figure 3 This is a detailed flowchart of the S2 process of the present invention;

[0052] Figure 4 This is a detailed flowchart of the S3 process of the present invention;

[0053] Figure 5 This is a detailed flowchart of the S4 process of the present invention;

[0054] Figure 6 This is a detailed flowchart of S5 of the present invention;

[0055] Figure 7 This is a detailed flowchart of S6 of the present invention;

[0056] Figure 8 This is a system flowchart of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0059] Please see Figure 1 This invention provides a technical solution, a method for assessing the safety performance of buildings, comprising the following steps:

[0060] S1: Collect displacement and acceleration data of the building, measure them in real time using fiber optic sensors, check the quality of the data, and obtain real-time monitoring data by combining time series analysis and recording data changes.

[0061] S2: Using real-time monitoring data, by adjusting the proportional, integral, and derivative parameters of the controller, the mechanical response of the building's damping and support structure is optimized, and the adjustment response record is obtained by adjusting and matching changes in external and internal loads in real time.

[0062] S3: Based on the adjustment response records, identify the building response characteristics under extreme weather and earthquake conditions, assess the building's safety performance by adjusting damping and stiffness, configure emergency modes to optimize the building structure's disaster resistance, and establish emergency response strategies;

[0063] S4: Implement emergency response strategies, conduct recursive pattern analysis on building structures, extract repeating patterns from structural response data, evaluate the frequency and impact of repeating patterns through relationship diagrams and node analysis, identify anomalous patterns and potential weaknesses, and obtain structural behavior patterns.

[0064] S5: Based on structural behavior patterns, quantitative assessment of risk areas is conducted, and the standard design data and the real-time performance of the building are compared and analyzed. By calculating deviations and potential risk points, the stability and safety of the structure are assessed, and potential risk identification results are generated.

[0065] S6: Based on the results of potential risk identification, calculate the entropy value of the building structure, analyze the trend of entropy value change over time, identify the degradation and damage of the building's safety performance structure, and obtain the health status assessment results.

[0066] Real-time monitoring data includes time stamps, amplitude, and frequency changes; response adjustment records include response time, changes in mechanical properties, and matching degree with load changes; emergency response strategies include the configuration of building safety performance assessment results and emergency modes under extreme weather and earthquake conditions; structural behavior patterns include repetitive loading response patterns, abnormal structural behavior, and potential structural weaknesses; potential risk identification results include structural deviation values, key risk points, and potential damage areas; health status assessment results include time series analysis of entropy values ​​and trend identification of building structural degradation and damage.

[0067] Please see Figure 2 The specific steps for collecting displacement and acceleration data of buildings, measuring them in real time using fiber optic sensors, verifying data quality, and combining time series analysis with recording data changes to obtain real-time monitoring data are as follows:

[0068] S101: The execution flow for collecting displacement and acceleration data of the building, deploying fiber optic sensors at key points of the building structure, including columns, beams and foundations, extracting information from key areas of structural performance, and generating raw monitoring data is as follows;

[0069] Substep S101 collects displacement and acceleration data of the building to assess structural safety and performance. The system deploys fiber optic sensors at key points in the building structure, including columns, beams, and the foundation. Due to their high sensitivity and accuracy, fiber optic sensors are particularly suitable for data acquisition in critical areas. Through these sensors, the system extracts displacement and acceleration information from key areas of the building's structural performance, forming raw monitoring data, expressed using the following formula:

[0070]

[0071] Among them, D original a represents the sum of the original monitoring data. i d is the acceleration measurement value of the i-th sensor. i is the corresponding displacement measurement value, and n is the total number of sensors.

[0072] S102: Based on the original monitoring data, perform data quality inspection, eliminate noise and errors, adjust the sensitivity of the fiber optic sensor and the data collection frequency, check the consistency of the data, and obtain the corrected data. The execution process is as follows:

[0073] Sub-step S102, based on the raw monitoring data, performs quality inspection. The system eliminates noise and errors in the data, involving filtering and statistical analysis to remove unstructured vibrations and environmental interference. The sensitivity of the fiber optic sensor and the data collection frequency are adjusted to ensure data accuracy and consistency, resulting in corrected data using the following formula:

[0074]

[0075] Among them, D corrected This represents the corrected data, d i These are the original data values ​​before correction. is the average value of the original data, and n is the total number of data points.

[0076] S103: Using the corrected data, record and analyze the data change trends, including periodic changes and emergency response. By analyzing the time series of the data, identify the behavioral characteristics of buildings under differentiated conditions. The execution process for real-time monitoring data is as follows.

[0077] Substep S103 utilizes the corrected data to record and analyze data trends, monitor and analyze periodic fluctuations and emergency response, which is crucial for assessing a building's response to natural disasters such as earthquakes or strong winds. Through time-series analysis, the system identifies the building's behavioral characteristics under different environmental and load conditions, obtaining real-time monitoring data using the following formula:

[0078]

[0079] Among them, T trend Indicates the trend of data change, v t It is the measurement value at time point t. It is the average of all measured values. It is the average of the points in time, and T is the total number of points in time.

[0080] Please see Figure 3 The specific steps for optimizing the building's damping and support structure mechanical response using real-time monitoring data, adjusting and matching changes in external and internal loads in real time, and obtaining adjustment response records are as follows:

[0081] S201: Based on real-time monitoring data, the following execution flow is used to evaluate the structural behavior of the building, identify key load points and pressure distribution, identify the locations of damping and support structures that need optimization, and generate structural behavior evaluation results.

[0082] Substep S201 assesses the structural behavior of the building based on real-time monitoring data, paying particular attention to critical load points and pressure distribution. It analyzes data collected from critical structural points to identify areas bearing the greatest pressure. The data identifies weak points and areas of excessive stress in the structure, which are potential risk points requiring special attention or reinforcement. It also identifies areas where damping and bracing structure placement need optimization to improve the building's responsiveness to dynamic loads, generating a structural behavior assessment result using the following formula:

[0083]

[0084] Among them, B eval p represents the structural behavior assessment result. i It is the pressure at the i-th measurement point, a i is the stress coefficient, A is the area of ​​influence, and n is the total number of measurement points.

[0085] S202: Based on the structural behavior assessment results, calculate the required damping adjustment and support strength, adjust the structural parameters of the building to match the detected load changes, check the structural response to match the real-time load, and generate parameter adjustment records. The execution process is as follows:

[0086] Substep S202, based on the structural behavior assessment results, calculates the required damping adjustment and brace strength. This involves using dynamic analysis and simulation techniques to calculate the ideal response state of each structural component under different load conditions. Based on detected load changes, structural parameters of the building, such as damping ratio and brace stiffness, are adjusted to match actual structural response requirements. These adjustments ensure the building structure maintains performance and safety under varying environmental and load conditions, generating parameter adjustment records using the following formula:

[0087]

[0088] Among them, P adjust This indicates the parameter adjustment record, d j It is the adjustment amount of the j-th structural component, l j is the load factor of the component, L is the total load, and m is the total number of components.

[0089] S203: By using parameter adjustment records, monitor the response effect of the adjusted structure, track the performance of damping and support structures, verify the matching degree between the adjustment effect and the expectation, evaluate the complete adjustment effect, and obtain the following execution flow of adjustment response records;

[0090] Sub-step S203 utilizes parameter adjustment records to monitor the structural response after adjustment, track the performance of damping and support structures, and analyze whether the actual response matches expectations. The effectiveness of the adjustment measures is evaluated through regular structural performance testing and real-time data analysis. This includes monitoring the structure's performance under various load and environmental conditions to ensure the adjustment measures achieve the expected improvement, resulting in adjustment response records using the following formula:

[0091]

[0092] Among them, R response This indicates adjusting the response record, r k R is the response value after adjustment of the k-th structural component. k K is the expected response value, and K is the total number of components.

[0093] Please see Figure 4 Based on the adjustment response records, the steps for identifying the building's response characteristics under extreme weather and earthquake conditions, assessing the building's safety performance, configuring emergency modes, and establishing an emergency response strategy are as follows:

[0094] S301: The execution flow for analyzing and adjusting response records, identifying data under emergency conditions such as extreme weather and earthquakes, calibrating key performance indicators, including displacement and stress response, identifying the behavior of building structures under high pressure, and generating key performance data is as follows;

[0095] The S301 sub-step analyzes and adjusts response records, paying particular attention to data under emergency conditions such as extreme weather and earthquakes. It filters data points related to extreme events from batch monitoring data, such as high-stress responses during earthquakes or displacement data during strong winds. Key performance indicators, such as displacement, stress response rate, and duration, are calibrated. These indicators reflect the behavioral characteristics of the building structure under high pressure. Key performance data is generated using the following formula:

[0096]

[0097] Among them, K performance This represents key performance data, β. i s is the weight coefficient of the i-th event. i It is the stress response value, u i is the displacement, and n is the total number of events.

[0098] S302: The execution process for conducting a safety performance assessment of a building based on key performance data, analyzing the building's safety level by comparing it with industry safety standards, identifying potential risk points, and generating safety assessment results is as follows;

[0099] The S302 sub-step, based on critical performance data, analyzes the building's safety level by comparing it with industry safety standards, such as seismic safety performance levels and wind load standards. It identifies potential risks in the building structure, such as safety hazards caused by material fatigue or design deficiencies, and provides a detailed report on the overall safety status of the building. This helps decision-makers take appropriate maintenance or reinforcement measures and generates a safety assessment result using the following formula:

[0100]

[0101] Among them, S assessment Indicates the safety assessment results, α j r is the risk coefficient of the j-th risk point. j R is the response indicator for risk points, R is the baseline indicator for risk response, and m is the total number of risk points.

[0102] S303: Based on the safety assessment results, configure emergency measures for automatic damping adjustment and support reinforcement. If an extreme event is detected, the emergency measures will be automatically activated to optimize the safety performance of the building. The execution process of the emergency response strategy is as follows:

[0103] Sub-step S303, based on the safety assessment results, establishes an emergency response mechanism for automatic damping adjustment and support reinforcement, enabling automatic activation upon detection of extreme events. This includes enhancing the responsiveness of the damping system and reinforcing key support structures to optimize building safety performance. The building can rapidly adjust its structural behavior to minimize damage during natural disasters, establishing an emergency response strategy using the following formula:

[0104]

[0105] Among them, E response Indicates the effectiveness of emergency response strategies, γ k δ is the effectiveness coefficient of the k-th adjustment measure. k 'p' represents the depth of the adjustment of the measures, and 'p' represents the total number of measures.

[0106] Please see Figure 5 The specific steps for implementing an emergency response strategy, conducting recursive pattern analysis on the building structure, assessing the frequency and impact of repeating patterns through relationship diagrams and node analysis, identifying anomalous patterns and potential weaknesses, and obtaining structural behavior patterns are as follows:

[0107] S401: Implement emergency response strategies and monitor the structural safety performance of buildings in real time, including collecting structural response data of buildings during weather warnings and seismic activity. The execution process for generating target monitoring data is as follows:

[0108] The S401 sub-step implements an emergency response strategy, monitoring the structural safety performance of buildings in real time during warning weather and seismic activity. It deploys high-precision monitoring equipment, such as accelerometers and displacement sensors, to collect key data on building response. This monitoring equipment records the building's structural response under different environmental pressures, such as displacement, vibration frequency, and stress changes. This data forms the basis for understanding the building's performance under actual environmental conditions and is used for further analysis and safety assessments, generating target monitoring data using the following formula:

[0109]

[0110] Among them, M data Represents target monitoring data, θ i v is the sensitivity coefficient of the i-th sensor. i It's vibration data, s i This is stress data, and n is the number of sensors.

[0111] S402: Based on target monitoring data, construct a relationship diagram of structural behavior, evaluate the repetitive behavior patterns and influences in the building's safety performance structure through node and edge analysis, identify stress distribution and displacement patterns, and generate pattern analysis results. The execution flow is as follows:

[0112] Substep S402, based on target monitoring data, constructs a structural relationship diagram of the building's safety performance. Using graph theory analysis, it assesses recurring behavioral patterns and their impact within the building. This includes analyzing and identifying key stress distributions and displacement patterns through nodes (critical structural points) and edges (stress or displacement relationships between structural points), revealing the building's behavioral trends under specific loads. This is crucial for preventing structural failures. The resulting pattern analysis results are generated using the following formula:

[0113]

[0114] Among them, P analysis Indicating the results of pattern analysis, λ j σ is the importance coefficient of the j-th node. jk It is the degree of association between nodes j and k, K j It is the set of nodes directly connected to node j, and m is the total number of nodes.

[0115] S403: Using the pattern analysis results, perform abnormal pattern detection, identify structural responses that deviate from the normal behavior pattern, identify potential weaknesses and causes of failure in the building's safety performance structure, and obtain the following execution flow of the structural behavior pattern;

[0116] The S403 sub-step utilizes the pattern analysis results to perform anomaly pattern detection, identifying structural responses that deviate from normal behavior patterns, including abnormal stress distributions or abnormal displacement patterns. Through analysis, the system can identify potential weaknesses and causes of failure in the building's structural safety performance. This is crucial for maintaining the long-term stability and safety of buildings, guiding future maintenance work and structural reinforcement measures, and yielding the structural behavior pattern using the following formula:

[0117]

[0118] Among them, A behavior μ represents the structural behavior pattern. l It is the anomaly index of the l-th pattern, δ l It represents the degree to which the pattern deviates from the norm, and p is the total number of patterns.

[0119] Please see Figure 6 Based on structural behavior patterns, the quantitative assessment of risk areas is conducted. This involves comparing and analyzing standard design data with the building's real-time performance, and generating potential risk identification results by calculating deviations and potential risk points. The specific steps are as follows:

[0120] S501: The execution flow for quantitatively assessing the key areas of a building's structural safety performance using structural behavior patterns, identifying areas subjected to stress and displacement, marking them as risk points, and generating risk area data is as follows;

[0121] The S501 sub-step employs a structural behavior model to quantitatively assess critical areas of a building's structural safety performance. It identifies areas subjected to high stress and displacement and marks them as risk points. Using the structural behavior model, the system precisely locates structural areas exhibiting high stress or abnormal displacement behavior under simulated or actual loading conditions. These structural areas are the focus of structural safety assessment because they represent potential points of failure or malfunction. Marking risk points is for preventing structural failures and taking remedial measures in advance. Risk area data is generated using the following formula:

[0122]

[0123] Among them, R areas Represents risk area data, φ i s is the risk coefficient of the i-th region. i It is the stress value, d i is the displacement value, and n is the total number of monitored areas.

[0124] S502: Based on risk area data, compare the building's design parameters and real-time monitoring results, calculate the deviation between the design parameters and real-time monitoring results, analyze the difference between real-time performance and design standards, and generate deviation analysis results. The execution process is as follows:

[0125] The S502 sub-step, based on risk area data, compares the building's design parameters with real-time monitoring results. By calculating the deviation between the design parameters and real-time monitoring results, it analyzes the difference between real-time performance and design standards. This helps engineers assess whether the building's actual performance meets safety standards and whether adjustments or enhancements to the design are needed to cope with unforeseen loads or environmental conditions, generating deviation analysis results using the following formula:

[0126]

[0127] Among them, D deviation p represents the results of the deviation analysis. j It is the parameter value monitored in real time, q j These are the design parameter values, and m is the total number of parameters.

[0128] S503: The execution flow for using deviation analysis results to iteratively analyze and calculate potential risk points in the building's safety performance structure, including stress concentration and structural fatigue signs, and extracting key information to obtain potential risk identification results is as follows;

[0129] The S503 sub-step utilizes the deviation analysis results to iteratively analyze and calculate potential risk points in the building's structural safety performance, including the identification of stress concentration points and signs of structural fatigue, both crucial aspects of preventing structural failures. Through continuous monitoring and data analysis, relevant information on key risk points is extracted. This information is essential for developing maintenance plans and taking preventative measures, resulting in potential risk identification using the following formula:

[0130]

[0131] Among them, P risks Indicates the results of potential risk identification, ψ k v is the severity coefficient of the k-th risk point. k It is the monitoring value, t k 'o' is the threshold, and 'o' is the total number of risk points.

[0132] Please see Figure 7 The specific steps for obtaining a health status assessment result are as follows: Based on the potential risk identification results, the entropy value of the building structure is calculated, and the trend of entropy value change over time is analyzed to identify the degradation and damage to the building's safety performance structure.

[0133] S601: Using the results of potential risk identification, the Monte Carlo method is used to quantitatively analyze the structural safety performance of the building. The execution flow for generating initial entropy value data is as follows:

[0134] Substep S601 uses the potential risk identification results to quantitatively analyze the structural safety performance of the building using the Monte Carlo method. The Monte Carlo method is a statistical simulation technique used to evaluate the behavior and performance of a system. It simulates the response of the building structure under different loading and environmental conditions, calculating the structure's entropy value. The entropy value is used to assess the overall stability of the building, reflecting the volatility and disorder of the system state. Higher entropy values ​​indicate instability and a high-risk state of the structural system, generating initial entropy value data.

[0135] The formula for the Monte Carlo method is as follows:

[0136]

[0137] Where H is the weighted entropy value, p i Let w be the probability of the state. i Let f be the weighting coefficient for state i, β be the risk adjustment coefficient, and f be the weighting coefficient for state i. j For the weights of the risk factors, d j This is a distance metric for risk factors, where n is the total number of states and m is the total number of risk factors.

[0138] The execution process is as follows:

[0139] The probability p of each state is obtained using Monte Carlo simulation. i Assign a weight w to each state i The weights reflect the importance of each state in the building safety performance assessment. The information entropy of each state is calculated, and a risk adjustment coefficient β is used to adjust the influence of different risk factors on the entropy. The coefficient is determined based on expert evaluation. Each risk factor f j Based on the weighted average of their impact on building safety, d j It represents the distance from the ideal safe state and can be a measure of the difference between the actual state and the ideal state. After integrating all information, the entropy value is calculated to enhance the stability index.

[0140] S602: Based on the initial entropy value data, analyze the trend of entropy value change over time. By analyzing the time series, identify the fluctuation of structural entropy value of building safety performance, record the changes in structural stability, and generate entropy value trend analysis results. The execution process is as follows:

[0141] Substep S602, based on initial entropy data, analyzes the trend of entropy changes over time. By constructing a time series model, it tracks the fluctuations and changes in the structural entropy of the building's safety performance, which helps monitor the dynamic changes in structural stability. Time series analysis allows the identification of patterns of structural performance fluctuations over time, such as periodic changes or declining trends. These patterns predict potential structural problems and generate entropy trend analysis results using the following formula:

[0142]

[0143] Among them, H trend H represents the entropy trend analysis results. t It is the entropy value at time t. It is the average entropy value, and T is the total number of time periods.

[0144] S603: The execution process for using entropy trend analysis results to identify the degradation and damage development trends in the structural safety performance of buildings, identify and analyze safety hazards and problem areas that need to be addressed first, and obtain health status assessment results is as follows;

[0145] The S603 sub-step utilizes entropy trend analysis results to identify degradation and damage development trends in the building's structural safety performance. Through in-depth analysis of entropy data and monitoring indicators, it can identify potential degradation areas and damage development patterns within the structure. This includes analyzing areas where entropy values ​​show abnormal increases or fluctuations, prioritizing degradation areas, providing a detailed description of the building's current structural health, and identifying key areas requiring attention or intervention. The resulting health status assessment is achieved using the formula:

[0146]

[0147] Among them, S health Indicates the health status assessment result, ξ k It is the sensitivity coefficient of the k-th region, ΔH k is the change in regional entropy, and m is the total number of monitored areas.

[0148] Please see Figure 8 A building safety performance assessment system, used to perform the above-mentioned building safety performance assessment method, the system comprising:

[0149] The data collection module collects building displacement and acceleration data, uses fiber optic sensors to measure the data in real time, and combines time series analysis to record data changes and obtain real-time monitoring data.

[0150] The data processing module analyzes the mechanical properties of the data based on real-time monitoring data, adjusts the damping and support structure of the building in real time, matches changes in external and internal loads, and obtains adjustment response records.

[0151] The strategy building module assesses the building's response characteristics under extreme weather and earthquake conditions by adjusting response records, and builds emergency modes to establish emergency response strategies.

[0152] The pattern recognition module executes emergency response strategies, performs recursive pattern analysis on the building structure, analyzes and evaluates the frequency and impact of differentiated patterns, identifies abnormal patterns, and generates structural behavior patterns.

[0153] The risk assessment module uses structural behavior patterns to quantitatively assess risk areas, compares and analyzes standard design data and the real-time performance of buildings, calculates the entropy value of building structures, records changes in structural stability, and obtains health status assessment results.

[0154] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for assessing the safety performance of a building, characterized in that, Includes the following steps: The displacement and acceleration data of the building are collected, measured in real time using fiber optic sensors, the quality of the data is checked, and real-time monitoring data is obtained by combining time series analysis and recording data changes. Using the real-time monitoring data, the damping and mechanical response of the building's support structure are optimized, and the external and internal load changes are adjusted in real time to obtain the adjustment response record; Based on the adjusted response records, identify the building response characteristics under extreme weather and earthquake conditions, assess the building's safety performance, configure emergency modes, and establish emergency response strategies. Implement the aforementioned emergency response strategy, perform recursive pattern analysis on the building structure, evaluate the frequency and impact of repeating patterns through relationship diagrams and node analysis, identify anomalous patterns and potential weaknesses, and obtain structural behavior patterns. Based on the structural behavior pattern, a quantitative assessment of the risk area is conducted, and the standard design data and the real-time performance of the building are compared and analyzed. By calculating the deviation and potential risk points, potential risk identification results are generated. Based on the potential risk identification results, the entropy value of the building structure is calculated, and the trend of entropy value change over time is analyzed to identify the degradation and damage of the building's safety performance structure and obtain the health status assessment results.

2. The building safety performance assessment method according to claim 1, characterized in that, The real-time monitoring data includes data time stamps, amplitude and frequency changes; the adjustment response record includes response time, changes in mechanical properties and matching degree with load changes; the emergency response strategy includes the configuration of building safety performance assessment results and emergency modes under extreme weather and earthquake conditions; the structural behavior patterns include repetitive loading response patterns, abnormal structural behavior and potential structural weaknesses; the potential risk identification results include structural deviation values, key risk points and potential damage areas; and the health status assessment results include time series analysis of entropy values ​​and trend identification of building structural degradation and damage.

3. The building safety performance assessment method according to claim 1, characterized in that, The specific steps for collecting displacement and acceleration data of buildings, measuring them in real time using fiber optic sensors, verifying the quality of the data, and combining time series analysis with recording data changes to obtain real-time monitoring data are as follows: Collect displacement and acceleration data of buildings, deploy fiber optic sensors at key points of the building structure, including columns, beams and foundations, extract information from key areas of structural performance, and generate raw monitoring data; Based on the original monitoring data, a data quality check is performed to eliminate noise and errors, adjust the sensitivity of the fiber optic sensor and the data collection frequency, check the consistency of the data, and obtain the corrected data. Using the corrected data, the changing trends of the data are recorded and analyzed, including periodic changes and responses to emergencies. By analyzing the time series of the data, the behavioral characteristics of buildings under different conditions are identified, and real-time monitoring data is obtained.

4. The building safety performance assessment method according to claim 1, characterized in that, The specific steps for optimizing the building's damping and support structure's mechanical response using the real-time monitoring data, and adjusting and matching changes in external and internal loads in real time to obtain the adjustment response record are as follows: Based on the real-time monitoring data, the structural behavior of the building is evaluated, key load points and pressure distribution are identified, the locations of damping and support structures that need to be optimized are identified, and structural behavior evaluation results are generated. Based on the structural behavior assessment results, the required damping adjustment and support strength are calculated. By adjusting the structural parameters of the building to match the detected load changes, the structural response is checked to verify the match with the real-time load, and a parameter adjustment record is generated. By using the parameter adjustment records, the response effect of the adjusted structure is monitored, the performance of the damping and support structures is tracked, the matching degree between the adjustment effect and the expectation is verified, the complete adjustment effect is evaluated, and the adjustment response record is obtained.

5. The building safety performance assessment method according to claim 1, characterized in that, Based on the adjusted response records, the steps for identifying building response characteristics under extreme weather and earthquake conditions, assessing building safety performance, configuring emergency modes, and establishing emergency response strategies are as follows: Analyze the adjustment response records, identify data under emergency conditions such as extreme weather and earthquakes, calibrate key performance indicators, including displacement and stress response, identify the behavior of building structures under high pressure, and generate key performance data; Based on the aforementioned key performance data, a safety performance assessment of the building is conducted. By comparing the building with industry safety standards, the safety level of the building is analyzed, potential risk points are identified, and a safety assessment result is generated. Based on the safety assessment results, emergency measures such as automatic damping adjustment and support reinforcement are configured. If an extreme event is detected, the emergency measures are automatically activated to optimize the building's safety performance and establish an emergency response strategy.

6. The building safety performance assessment method according to claim 1, characterized in that, The specific steps for implementing the aforementioned emergency response strategy, including recursive pattern analysis of the building structure, evaluating the frequency and impact of recurring patterns through relationship diagrams and node analysis, identifying anomalous patterns and potential weaknesses, and obtaining structural behavior patterns, are as follows: Implement the aforementioned emergency response strategy to monitor the structural safety performance of buildings in real time, including collecting structural response data of buildings and generating target monitoring data during weather warnings and seismic activity. Based on the target monitoring data, a relationship diagram of structural behavior is constructed. Through the analysis of nodes and edges, the repetitive behavior patterns and influences in the building safety performance structure are evaluated, stress distribution and displacement patterns are identified, and pattern analysis results are generated. Using the pattern analysis results, abnormal pattern detection is performed to identify structural responses that deviate from the normal behavior patterns, identify potential weaknesses and causes of failure in the building's safety performance structure, and obtain the structural behavior patterns.

7. The building safety performance assessment method according to claim 1, characterized in that, Based on the aforementioned structural behavior pattern, the specific steps for quantitatively assessing risk areas, comparing and analyzing standard design data and the real-time performance of buildings, and generating potential risk identification results by calculating deviations and potential risk points are as follows: Using the aforementioned structural behavior pattern, the key areas of the building's safety performance structure are quantitatively assessed, areas subjected to stress and displacement are identified and marked as risk points, and risk area data is generated. Based on the risk area data, the design parameters of the building and the real-time monitoring results are compared, the deviation between the design parameters and the real-time monitoring results is calculated, the difference between the real-time performance and the design standard is analyzed, and the deviation analysis results are generated. Using the deviation analysis results, potential risk points in the building's safety performance structure are iteratively analyzed and calculated, including stress concentration and signs of structural fatigue, and key information is extracted to obtain potential risk identification results.

8. The building safety performance assessment method according to claim 1, characterized in that, Based on the potential risk identification results, the entropy value of the building structure is calculated, and the trend of entropy value change over time is analyzed to identify the degradation and damage of the building's safety performance structure and obtain the health status assessment results. The specific steps are as follows: Using the potential risk identification results, the Monte Carlo method is used to quantitatively analyze the structural safety performance of the building. By calculating the entropy value of the structure, the overall stability of the structural safety performance of the building is analyzed, and initial entropy value data is generated. Based on the initial entropy data, the trend of entropy change over time is analyzed. By analyzing the time series, the fluctuation of structural entropy in building safety performance is identified, the changes in structural stability are recorded, and entropy trend analysis results are generated. Using the entropy trend analysis results, the degradation and damage development trends in the building's safety performance structure are identified, safety hazards and problem areas that need to be addressed first are identified and analyzed, and health status assessment results are obtained.

9. The method for assessing the safety performance of buildings according to claim 8, characterized in that, The formula for the Monte Carlo method is as follows: Where H is the weighted entropy value, p i Let w be the probability of the state. i Let f be the weighting coefficient for state i, β be the risk adjustment coefficient, and f be the weighting coefficient for state i. j For the weights of the risk factors, d j This is a distance metric for risk factors, where n is the total number of states and m is the total number of risk factors.

10. A building safety performance assessment system, characterized in that, The building safety performance assessment method according to any one of claims 1-9, wherein the system comprises: The data collection module collects building displacement and acceleration data, uses fiber optic sensors to measure the data in real time, and combines time series analysis to record data changes and obtain real-time monitoring data. Based on the real-time monitoring data, the data processing module analyzes the mechanical properties of the data, adjusts the damping and support structure of the building in real time, matches the changes in external and internal loads, and obtains adjustment response records. The strategy construction module assesses the building's response characteristics under extreme weather and earthquake conditions by adjusting the response records, and constructs emergency modes to establish emergency response strategies. The pattern recognition module executes the emergency response strategy, performs recursive pattern analysis on the building structure, analyzes and evaluates the frequency and impact of differentiated patterns, identifies abnormal patterns, and generates structural behavior patterns. The risk assessment module uses the structural behavior pattern to quantitatively assess the risk area, compares and analyzes standard design data and the real-time performance of the building, calculates the entropy value of the building structure, records changes in structural stability, and obtains the health status assessment results.

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