Building facility operation and maintenance monitoring method, equipment, medium and product

Abstract

The invention relates to the technical field of building operation and maintenance, in particular to a building facility operation and maintenance monitoring method and device, a medium and a product. The method comprises the following steps: constructing a scene template library, wherein each scene template in the scene template library is associated with a plurality of monitoring indexes and an initial early warning threshold value; obtaining attribute information of a to-be-monitored building, matching the attribute information with the scene template library, and determining an adaptive monitoring index set; dynamically correcting an initial early warning threshold value of the monitoring index set based on the attribute information and the prediction environment information, and generating a current early warning threshold value; acquiring real-time monitoring data of the to-be-monitored building, comparing the real-time monitoring data with a current early warning threshold value, and identifying an over-standard index and an associated index of the over-standard index; and generating risk early warning information based on the standard exceeding index and the association index, and pushing the risk early warning information to the operation and maintenance terminal. According to the invention, operation and maintenance personnel can be assisted to quickly position core risks and potential extension risks, and building operation and maintenance safety is guaranteed.

Description

Technical Field

[0001] This application relates to the field of building operation and maintenance technology, and in particular to a method, equipment, medium and product for monitoring the operation and maintenance of building facilities. Background Technology

[0002] In the field of building operation and maintenance monitoring, with the acceleration of urbanization, the number of buildings has surged and their service life has gradually increased, making building structural safety and stable operation and maintenance crucial to ensuring public safety. Existing technologies mostly employ monitoring methods with preset fixed early warning thresholds. This involves pre-setting uniform or single-dimensional monitoring indicator thresholds for different types of buildings, and achieving risk warnings by comparing real-time monitoring data with these fixed thresholds. However, the attribute information of different buildings varies significantly, and the environmental conditions of the areas where buildings are located are constantly changing. Fixed early warning thresholds cannot match the individual characteristics of buildings with dynamic environmental changes, easily leading to inaccurate warnings and making it difficult to effectively ensure building operation and maintenance safety. Summary of the Invention

[0003] To address the problem that existing technologies using fixed detection thresholds cannot guarantee the safety of building operation and maintenance, this application provides a method, equipment, medium, and product for monitoring the operation and maintenance of building facilities.

[0004] Firstly, this application provides a method for monitoring the operation and maintenance of building facilities, employing the following technical solution: A method for monitoring the operation and maintenance of building facilities, comprising: Construct a scenario template library, in which each scenario template is associated with multiple monitoring indicators and an initial early warning threshold; Obtain the attribute information of the building to be monitored, match the attribute information with the scene template library, and determine the appropriate set of monitoring indicators; Obtain the predicted environmental information of the area where the building to be monitored is located, and dynamically correct the initial warning threshold of the monitoring index set based on the attribute information and the predicted environmental information to generate the current warning threshold; The real-time monitoring data of the building to be monitored is obtained, and the real-time monitoring data is compared with the current early warning threshold to identify the indicators exceeding the standard and the related indicators of the indicators exceeding the standard. Risk warning information is generated based on the exceeded indicators and the related indicators, and the risk warning information is pushed to the operation and maintenance terminal.

[0005] By adopting the above technical solutions, a scenario template library of associated monitoring indicators and initial early warning thresholds is constructed. This library is then combined with the attributes of the buildings to be monitored to match and adapt the indicator set. The thresholds are then dynamically adjusted based on building attributes and regional predicted environmental information. Finally, real-time data comparison identifies exceeding and associated indicators and pushes early warning information, achieving precise adaptation of monitoring indicators and avoiding redundancy or omissions of general indicators. Dynamic threshold adjustment ensures that early warning standards align with individual building characteristics and environmental changes, improving the scientific validity of the thresholds. The identification of associated indicators and precise early warning push help maintenance personnel quickly locate core risks and potential extended risks, improving maintenance response efficiency and decision-making accuracy, and ensuring building maintenance safety.

[0006] In a preferred embodiment, this application can be further configured as follows: The step of dynamically correcting the initial warning threshold of the monitoring indicator set based on the attribute information and the prediction environment information to generate the current warning threshold includes: The monitoring indicator set is divided into fixed threshold indicators and dynamic threshold indicators; Based on the attribute information and the prediction environment information, the initial warning threshold of the dynamic threshold indicator is corrected to obtain the current warning threshold of the dynamic threshold indicator. The initial warning threshold of the fixed threshold indicator is used as the current warning threshold, and the current warning thresholds of the fixed threshold indicator and the dynamic threshold indicator constitute the current warning threshold of the monitoring indicator set.

[0007] By adopting the above technical solution, the monitoring indicators are divided into two categories: fixed and dynamic. Dynamic threshold indicators are corrected by combining building attributes and predicted environmental information, while fixed threshold indicators directly use the initial thresholds and are integrated to form a complete current warning threshold. A clear distinction is made between mandatory standard indicators and flexible adjustment indicators, which not only follows industry legal norms to ensure compliance, but also focuses on the accurate correction of dynamic indicators and avoids erroneous adjustments to fixed thresholds. The classification, correction and integration method takes into account both the standardization and adaptability of the thresholds, and improves the rationality of the thresholds.

[0008] In a preferred embodiment, this application can be further configured as follows: The step of correcting the initial warning threshold of the dynamic threshold indicator based on the attribute information and the prediction environment information to obtain the current warning threshold of the dynamic threshold indicator includes: Based on the structural information in the attribute information, a simulation model matching the building to be monitored is constructed; The predicted environmental information is input as a load into the simulation model, and the theoretical response values ​​of each monitoring index of the simulation model are received. For each dynamic threshold indicator, the theoretical response value of the dynamic threshold indicator is compared with the initial warning threshold, and the larger value is taken as the warning benchmark value. Based on the attribute information and the predicted environment information, a dynamic safety factor is determined; The product of the warning baseline value and the dynamic safety coefficient is calculated and used as the current warning threshold of the dynamic threshold index.

[0009] By adopting the above technical solutions, the construction of the simulation model achieves accurate simulation of the building structure response, and the theoretical response value provides a scientific basis for threshold correction; the determination of the early warning benchmark value ensures that the threshold is not lower than the expected building response under environmental load, avoiding missed reports; the dynamic safety factor incorporates building health and environmental risk considerations, further reserving a safety margin, so that the dynamic threshold is both scientific and safe, effectively reducing safety hazards caused by structural degradation or sudden environmental changes.

[0010] In a preferred embodiment, this application can be further configured such that determining the dynamic safety factor based on the attribute information and the predicted environment information includes: Multi-dimensional features are extracted from the attribute information, and each dimension feature is scored. Based on the predicted environment information, determine the dimensional weight distribution; Based on the aforementioned dimensional weight distribution, the scores of the multi-dimensional features are weighted and summed to obtain the overall building health score. The building health comprehensive score is mapped to the dynamic safety factor.

[0011] By adopting the above technical solutions, multi-dimensional features cover the core influencing factors of building health, enabling a comprehensive assessment of building status; the environmental information-driven weight distribution allows the assessment to focus on environmentally sensitive dimensions, improving the relevance of the comprehensive score; the precise mapping between the score and the safety factor quantifies the building health status and environmental risks into parameters that can be directly used for threshold correction, ensuring the rationality of the dynamic safety factor.

[0012] In a preferred embodiment, this application can be further configured as follows: comparing the real-time monitoring data with the current warning threshold to identify the exceeding indicators and the related indicators of the exceeding indicators includes: Mark the indicators in the set of monitoring indicators whose real-time monitoring data exceeds the current warning threshold as exceeding indicators; Obtain historical operation and maintenance data of the scene to which the building to be monitored belongs, and mine the correlation rules between monitoring indicators based on the historical operation and maintenance data; Query the indicators that have the association rule with the exceeded indicator to form a candidate indicator set; For any set of candidate indicators and out-of-standard indicators that have the association rule, calculate the association confidence, environmental similarity and historical co-occurrence frequency of the candidate indicators and the out-of-standard indicators, and calculate the association strength based on the association confidence, environmental similarity and historical co-occurrence frequency; Candidate indicators whose correlation strength exceeds a preset strength threshold are selected from the candidate indicator set and used as the correlation indicators of the over-standard indicators.

[0013] By adopting the above technical solutions, the association rule mining based on historical data ensures the objectivity and reliability of the correlation between indicators; the multi-dimensional correlation strength calculation avoids the one-sidedness of single-dimensional judgment and improves the accuracy of correlation indicator identification; and effectively filters out potential risk indicators that are strongly correlated with the indicators exceeding the standard, helping operation and maintenance personnel to fully grasp the risk chain and avoid overlooking risks caused by viewing a single indicator exceeding the standard in isolation.

[0014] In a preferred embodiment, this application can be further configured such that: the generation of risk warning information based on the exceeding indicator and the related indicator includes: Obtain the historical operation and maintenance records of the building to be monitored; Extract the historical damage locations and damage frequencies corresponding to the out-of-standard indicators and the associated indicators from the historical operation and maintenance records; Based on the historical damage locations and the damage frequency, calculate the potential risk value for each location; Based on the potential risk value, the risk location is determined, and risk warning information including the risk location, the exceeding indicator, and the related indicator is generated.

[0015] By adopting the above technical solutions and combining historical operation and maintenance data, the precise correlation between risks and building components is achieved, making early warning information more concrete. The calculation of potential risk values ​​quantifies the risk level of each component, helping to quickly identify core high-risk components. Early warning information containing key risk elements provides operation and maintenance personnel with clear risk positioning and handling directions, improving the pertinence and effectiveness of operation and maintenance measures and reducing the cost of blind operation and maintenance.

[0016] Secondly, this application provides an electronic device that adopts the following technical solution: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform the building facility operation and maintenance monitoring method as described in any of the first aspects.

[0017] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the building facility operation and maintenance monitoring method as described in any of the first aspects.

[0018] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the building facility operation and maintenance monitoring method as described in any of the first aspects.

[0019] In summary, this application includes the following beneficial technical effects: This application constructs a scenario template library of associated monitoring indicators and initial early warning thresholds, matches the appropriate indicator set with the attributes of the building to be monitored, and then dynamically corrects the thresholds based on building attributes and regional predicted environmental information. Finally, it identifies exceeding and associated indicators through real-time data comparison and pushes early warning information, achieving accurate adaptation of monitoring indicators and avoiding redundancy or missing general indicators. Dynamic threshold correction makes the early warning standards fit the individual characteristics of the building and environmental changes, improving the scientific nature of the thresholds. The identification of associated indicators and accurate early warning push help operation and maintenance personnel quickly locate core risks and potential extended risks, improve operation and maintenance response efficiency and decision-making accuracy, and ensure building operation and maintenance safety. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for monitoring the operation and maintenance of building facilities provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] The following is in conjunction with the appendix Figure 1 To be continued Figure 2 This application will be described in further detail.

[0022] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0025] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0026] This application provides a method for monitoring the operation and maintenance of building facilities, such as... Figure 1 As shown, the method provided in this application embodiment is executed by an electronic device, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication. This application embodiment does not impose any limitations on this connection. The method includes steps S101-S105, wherein: S101. Construct a scenario template library. Each scenario template in the scenario template library is associated with multiple monitoring indicators and an initial early warning threshold.

[0027] Specifically, scene templates can be categorized according to building function, including: hospitals, schools, stadiums, residential buildings, bridges, etc. For each building scene template, specific monitoring indicators are configured. For example, for the residential building scene, monitoring indicators may include inter-floor displacement angle, beam-column joint strain, wall crack width, and foundation horizontal displacement. Initial warning thresholds are set for each monitoring indicator according to national standards and industry specifications. The category tags of each scene, associated monitoring indicators, and initial warning thresholds for each indicator are bound to scene templates and stored in a database to form a scene template library.

[0028] S102. Obtain the attribute information of the building to be monitored, match the attribute information with the scene template library, and determine the appropriate set of monitoring indicators.

[0029] Specifically, the building to be monitored is the building that currently needs to be monitored, and its attribute information includes building type, structural data, construction year, material type, historical maintenance records, etc. A scene template of the same type is retrieved from the scene template library according to the building type of the building to be monitored, and the monitoring indicators of that scene template are used as the set of monitoring indicators for the building to be monitored.

[0030] S103. Obtain the predicted environmental information of the area where the building to be monitored is located. Based on the attribute information and the predicted environmental information, dynamically correct the initial warning threshold of the monitoring indicator set and generate the current warning threshold.

[0031] Specifically, the system connects with meteorological forecasting platforms, geological monitoring systems, and environmental monitoring stations to obtain predicted environmental information for the area where the building to be monitored is located over a future period, including: temperature, precipitation intensity, wind speed and direction, and earthquake early warning level. Each monitoring indicator in the scenario template library is labeled with its type, including fixed threshold indicators and dynamic threshold indicators. Fixed threshold indicators are unaffected by differences in building attributes or short-term environmental changes, and must strictly adhere to national and industry mandatory standards and design specifications. Their thresholds are clearly defined by law or technical specifications, with no room for adjustment. Dynamic threshold indicators are significantly affected by individual building attributes (such as structural age and material condition) or dynamic environmental factors (such as wind speed, rainfall, and earthquake risk), requiring adjustments to the warning threshold based on actual conditions. Based on attribute information and predicted environmental information, the initial warning threshold of the dynamic threshold indicator is corrected to obtain the current warning threshold. The initial warning threshold of the fixed threshold indicator is used as the current warning threshold. The current warning thresholds of the fixed and dynamic threshold indicators constitute the current warning threshold of the monitoring indicator set.

[0032] S104. Obtain real-time monitoring data of the building to be monitored, compare the real-time monitoring data with the current warning threshold, and identify the indicators that exceed the standard and the related indicators of the indicators that exceed the standard.

[0033] Specifically, real-time monitoring data is compared one by one with the current warning threshold. If the real-time value of a certain indicator exceeds its current warning threshold, it is marked as an exceeding indicator. For example, if the real-time value of the inter-floor displacement angle is 1 / 500, exceeding the current warning threshold of 1 / 550, it is determined to be an exceeding indicator. Historical operation and maintenance data of the scenario to which the building to be monitored belongs is retrieved, that is, historical operation and maintenance data of the same type as the building to be monitored is retrieved. Historical operation and maintenance data includes monitoring indicator data and fault records. An association rule mining algorithm is used to analyze the correlation between indicators in the historical operation and maintenance data. For example, excessive wall crack width is often accompanied by excessive foundation settlement. All indicators that have association rules with the exceeding indicators are included in the candidate indicator set.

[0034] For each candidate indicator in the candidate indicator set, the correlation strength between the candidate indicator and its associated exceeding indicators is calculated. If the candidate indicator is correlated with multiple exceeding indicators, the one with the highest correlation strength is taken as the final determined correlation strength. Candidate indicators whose correlation strength exceeds a preset strength threshold are selected from the candidate indicator set as the associated indicators of the exceeding indicators. The preset strength threshold can be flexibly set according to actual experience, and this embodiment does not impose specific limitations.

[0035] S105. Generate risk warning information based on the exceeding indicators and related indicators, and push the risk warning information to the operation and maintenance terminal.

[0036] Specifically, risk areas with potential risks are identified based on exceeding and related indicators. Risk warning information includes the risk area, the exceeding indicator, and related indicators. Maintenance terminals can be maintenance personnel's mobile phones, monitoring center screens, etc.

[0037] This embodiment constructs a scenario template library of associated monitoring indicators and initial early warning thresholds, matches the set of indicators with the attributes of the building to be monitored, and then dynamically corrects the thresholds based on building attributes and regional predicted environmental information. Finally, it identifies exceeding and associated indicators through real-time data comparison and pushes early warning information, achieving accurate adaptation of monitoring indicators and avoiding redundancy or missing general indicators. Dynamic threshold correction makes the early warning standards fit the individual characteristics of the building and environmental changes, improving the scientific nature of the thresholds. The identification of associated indicators and accurate early warning push help operation and maintenance personnel quickly locate core risks and potential extended risks, improve operation and maintenance response efficiency and decision-making accuracy, and ensure the safety of building operation and maintenance.

[0038] One possible implementation of this application embodiment involves dynamically correcting the initial warning threshold of the monitoring indicator set based on attribute information and prediction environment information to generate the current warning threshold, including: The monitoring indicator set is divided into fixed threshold indicators and dynamic threshold indicators; Based on attribute information and prediction environment information, the initial warning threshold of the dynamic threshold indicator is corrected to obtain the current warning threshold of the dynamic threshold indicator. The initial warning threshold of the fixed threshold indicator is used as the current warning threshold. The current warning thresholds of the fixed threshold indicator and the dynamic threshold indicator constitute the current warning threshold of the monitoring indicator set.

[0039] This embodiment divides monitoring indicators into two categories: fixed and dynamic. Dynamic threshold indicators are corrected by combining building attributes and predicted environmental information, while fixed threshold indicators directly use the initial thresholds and integrate them to form a complete current warning threshold. It clearly distinguishes between mandatory standard indicators and flexible adjustment indicators, which not only follows industry legal norms to ensure compliance, but also focuses on the accurate correction of dynamic indicators to avoid erroneous adjustments to fixed thresholds. The classification, correction and integration method takes into account both the standardization and adaptability of thresholds, and improves the rationality of thresholds.

[0040] One possible implementation of this application embodiment involves correcting the initial warning threshold of a dynamic threshold indicator based on attribute information and prediction environment information to obtain the current warning threshold of the dynamic threshold indicator, including: Based on the structural information in the attribute information, a simulation model matching the building to be monitored is constructed. The predicted environmental information is used as the load input to the simulation model, and the theoretical response values ​​of each monitoring index of the simulation model are received. For each dynamic threshold indicator, the theoretical response value of the dynamic threshold indicator is compared with the initial warning threshold, and the larger value is taken as the warning benchmark value. The dynamic safety factor is determined based on attribute information and predicted environment information; Calculate the product of the early warning baseline value and the dynamic safety factor, and use it as the current early warning threshold for the dynamic threshold indicator.

[0041] In this embodiment, structural information includes structural type (frame, shear wall, steel structure, etc.), component dimensions (beam / column cross-sectional dimensions, wall thickness), material parameters (concrete strength grade, steel grade, masonry strength), node connection method, foundation type (raft foundation, pile foundation, etc.), and design load values ​​(dead load, live load). The process of building the simulation model includes: creating a geometric model; drawing the geometric outlines of beams, columns, shear walls, foundations, etc., in the software based on the component dimensions and positional relationships in the structural information, ensuring that the component connection nodes are consistent with reality, such as rigid connections in frame nodes and hinged connections between infill walls and the main structure; assigning material properties and allocating corresponding material parameters to each component; setting boundary conditions to simulate the actual constraint state of the building, for example, setting the bottom of the pile foundation as a fixed constraint with zero displacement, the connection between the shear wall and the foundation as a rigid constraint, and the connection between the infill wall and the frame as an elastic connection; and applying design loads, distributing dead loads, live loads, and other design loads to the components according to specifications.

[0042] The predicted environmental information is converted into a load format recognizable by the simulation model to obtain the environmental loads. A new load case is then created in the simulation model, and the standardized environmental loads are superimposed onto the design loads. The simulation model is then run, and the theoretical response data from the simulation model is received.

[0043] By comparing the theoretical response value (the actual expected response of the building under the predicted environment) with the initial warning threshold (the basic threshold in the scenario template library), the larger value is taken as the warning benchmark. This ensures that the threshold covers the structural response under environmental loads while retaining the safety baseline of the initial threshold. For each dynamic threshold index, the product of its warning benchmark value and dynamic safety factor is calculated as the current warning threshold for that index.

[0044] The simulation model in this embodiment achieves accurate simulation of the building structure response, and the theoretical response value provides a scientific basis for threshold correction. The determination of the early warning benchmark value ensures that the threshold is not lower than the expected building response under environmental load, avoiding missed reports. The dynamic safety factor incorporates building health and environmental risk considerations, further reserving a safety margin, so that the dynamic threshold is both scientific and safe, effectively reducing safety hazards caused by structural degradation or sudden environmental changes.

[0045] One possible implementation of this application embodiment, determining the dynamic security factor based on attribute information and predicted environment information, includes: Extract multi-dimensional features from attribute information and score each feature. Determine the dimensional weight distribution based on the predicted environmental information; Based on the dimensional weight distribution, the scores of multi-dimensional features are weighted and summed to obtain the comprehensive building health score; The overall building health score is mapped to a dynamic safety factor.

[0046] Specifically, feature dimensions can be set for each scenario template based on practical experience; this embodiment does not limit the feature dimensions. For example, feature dimensions include structural age, damage history, maintenance records, design standards, and material condition. Structural age can be extracted from building completion filing documents and property registration archives to accurately determine the construction year, i.e., the difference between the current year and the completion year. Damage history can be extracted from building operation and maintenance records and third-party inspection reports, including damage type, damage location, damage extent, and repair status. Maintenance records can be obtained from property operation and maintenance ledgers, including maintenance type and frequency. Design standards are extracted from structural design drawings and design specifications, including design service life and seismic strength. Material condition can be extracted from material testing reports, on-site sampling and testing data, and performance parameters of new materials, including concrete strength and steel yield strength.

[0047] The pre-defined scoring rules are as follows: For structural age, the structure can be divided into age groups, each with a corresponding score; the shorter the service life, the higher the score. For damage history, the structure can be categorized into types, including no damage, minor damage and repaired, moderate damage and repaired, minor damage not repaired, moderate damage not repaired (corresponding to a score of 30), and severe damage (regardless of repair status). Each type corresponds to a score, with scores decreasing sequentially according to type. For maintenance records, the system is categorized into regular inspections and maintenance, irregular inspections and maintenance, and no maintenance, with each type corresponding to a score, decreasing sequentially according to type. For design standards, the newer the standard version and the higher the protection level, the higher the corresponding score. Pre-defined scores can be set for each combination of standard version and protection level. For material condition, a corresponding score can be pre-set for the performance parameter range of each material. The maximum score for a single material is consistent with the maximum score for the feature dimension. The average score of all materials is calculated as the score for the material condition feature dimension. Specific feature dimensions and scoring rules can be set by maintenance personnel based on practical experience; this embodiment does not impose specific limitations.

[0048] The sum of the weights of each feature dimension is 1, representing the proportion of importance of each feature dimension in the comprehensive assessment of building health. Different types of environmental risks have different degrees of impact on each dimension of the building. For example, structural age and material condition are more critical in strong wind environments, while damage history and design standards are more critical in earthquake environments. By predicting environmental information to drive the allocation of dimension weights, the comprehensive score is made more in line with the building safety needs under the current environment.

[0049] The predicted environmental information is converted into environmental risk types and risk levels. Risk types include strong wind risk, rainstorm risk, and earthquake risk, while risk levels are divided into low, medium, and high risks. The conversion process can be achieved through a pre-trained environmental risk prediction model, which is trained from environmental information data labeled with risk types and risk levels.

[0050] The default weights for each feature dimension are the same. Based on industry experience, environmental risk types and feature dimensions are pre-associated. When the model identifies an environmental risk type based on predicted environmental information, the weight of the feature dimension corresponding to the identified environmental risk type is increased. The increase can be set according to the risk level; for example, a 10% increase for low risk, a 20% increase for medium risk, and a 30% increase for high risk. After determining the increase, the weights of feature dimensions without risk are uniformly reduced, with the sum of the reductions equal to the increase, ensuring that the sum of the weights of all feature dimensions remains 1.

[0051] A mapping rule is pre-set, which follows the principle that the lower the building health comprehensive score, the higher the corresponding dynamic safety factor. The dynamic safety factor corresponding to each score segment is pre-set, and the specific mapping relationship is not limited in this embodiment.

[0052] This embodiment achieves a comprehensive assessment of building status by covering the core influencing factors of building health through multi-dimensional features; the weight distribution driven by environmental information enables the assessment to focus on environmentally sensitive dimensions, improving the pertinence of the comprehensive score; the precise mapping between the score and the safety factor quantifies the building health status and environmental risk into parameters that can be directly used for threshold correction, ensuring the rationality of the dynamic safety factor.

[0053] One possible implementation of this application involves comparing real-time monitoring data with the current warning threshold to identify exceeding indicators and related indicators, including: Mark the indicators in the monitoring indicator set whose real-time monitoring data exceeds the current warning threshold as exceeding the standard indicators; Obtain historical operation and maintenance data of the scene to which the building to be monitored belongs, and mine the correlation rules between monitoring indicators based on the historical operation and maintenance data; Query indicators that have association rules with the indicators that exceed the standard, and form a candidate indicator set; For any set of candidate indicators and out-of-standard indicators with association rules, calculate the association confidence, environmental similarity, and historical co-occurrence frequency of the candidate indicators and out-of-standard indicators, and calculate the association strength based on the association confidence, environmental similarity, and historical co-occurrence frequency. Candidate indicators whose correlation strength exceeds a preset strength threshold are selected from the candidate indicator set and used as the correlation indicators of the out-of-standard indicators.

[0054] In this embodiment, the Apriori algorithm is used to mine association rules. The algorithm identifies the support and confidence between two monitoring indicators that are related. Association rules that meet the minimum support and minimum confidence are considered valid association rules. Support represents the frequency of rule occurrence, and confidence represents the probability of rule validity. The mined valid association rules are stored in an association rule database. New historical data is periodically added, and the mining algorithm is re-executed to update the association rules. Indices with valid associations with the out-of-standard indicators are retrieved from the association rule database to obtain a candidate indicator set. The candidate indicator set is deduplicated. If multiple out-of-standard indicators are associated with the same indicator, only one association is retained, and the source of the association is marked, i.e., the associated out-of-standard indicator.

[0055] For any set of candidate and out-of-target indicators with association rules, the confidence level determined by the mining algorithm is used as the association confidence level for that set. Historical environmental conditions at the time the association rules were formed are retrieved, and the average environmental conditions over the period between the current and predicted environmental information are determined. The similarity between the average environmental conditions and the historical environmental conditions is calculated. The historical co-occurrence frequency represents the proportion of times that the out-of-target indicator and the candidate indicator in the set of historical operation and maintenance data are simultaneously abnormal, out of the total number of abnormalities, reflecting the co-occurrence stability between the indicators. The association confidence level, environmental similarity, and historical co-occurrence frequency are weighted and summed based on preset weights. These preset weights are set by expert experience, with the association confidence level having the highest weight.

[0056] This embodiment ensures the objectivity and reliability of indicator correlation by mining association rules based on historical data; multi-dimensional correlation strength calculation avoids the one-sidedness of single-dimensional judgment and improves the accuracy of correlation indicator identification; it effectively filters out potential risk indicators that are strongly correlated with the indicators exceeding the standard, helping operation and maintenance personnel to fully grasp the risk chain and avoid overlooking risks caused by viewing a single indicator exceeding the standard in isolation.

[0057] One possible implementation of this application's embodiments, generating risk warning information based on exceeding indicators and related indicators, includes: Obtain the historical operation and maintenance records of the building to be monitored; Extract the historical damage locations and damage frequencies corresponding to the out-of-standard indicators and related indicators from historical operation and maintenance records; Calculate the potential risk value for each site based on historical injury locations and frequency of injury; Based on the potential risk value, the risk location is determined, and risk warning information including the risk location, the exceeding indicator, and related indicators is generated.

[0058] Historical maintenance records include information such as maintenance time, abnormal indicators, and actual damage locations. Damage location indicates the specific structural component or location where physical damage actually occurred. Damage frequency indicates the number of times the same location was recorded as damaged in the historical maintenance records; the higher the frequency, the more likely that location is weak.

[0059] For each identified historical damage location, the record in the historical operation and maintenance data where the abnormal indicator type includes any indicator exceeding the standard or related indicator is considered a damage record. For damage locations with only one damage record, that damage record is considered a valid damage record. For damage locations with multiple damage records, the damage record most recent to the current time is considered a valid damage record. The number of damage records can be used as the damage frequency, or the damage frequency can be calculated directly from all damage counts of the historical damage location in the historical operation and maintenance records, regardless of the abnormal indicator type.

[0060] Furthermore, based on valid injury records and injury frequency, a potential risk value is calculated. For each historical injury site, the abnormal indicators and related indicators included in its abnormal indicators are identified and recorded as: Indicator A, Indicator B, ... The sum of the indicator weights is calculated. Specifically, for the abnormal indicators, the weight is set as the first weight; for the related indicators, the weight is set as the second weight, with the first weight being greater than the second weight. The product of the sum of indicator weights, injury frequency, severity, and time decay factor is calculated as the potential risk value for that site. The severity value can be preset, with higher values ​​corresponding to more severe injuries. The time decay factor t is calculated as follows: Where λ is the attenuation coefficient, which can be 0.3, and Δt represents the time difference between the current moment and the effective damage record. The larger the time difference, the smaller the attenuation factor.

[0061] Each damaged part is sorted from high to low according to its potential risk value to obtain a list of risky parts, which can guide maintenance personnel to inspect them in sequence.

[0062] This embodiment combines historical operation and maintenance data to achieve a precise correlation between risks and building components, making early warning information more concrete; the calculation of potential risk values ​​quantifies the risk level of each component, helping to quickly identify core high-risk components; early warning information containing key risk elements provides operation and maintenance personnel with clear risk positioning and handling directions, improving the pertinence and effectiveness of operation and maintenance measures, and reducing the cost of blind operation and maintenance.

[0063] This application provides an electronic device, such as... Figure 2 As shown, Figure 2 The illustrated electronic device 200 includes a processor 201 and a memory 203. The processor 201 and the memory 203 are connected, for example, via a bus 202. Optionally, the electronic device 200 may also include a transceiver 204. It should be noted that in practical applications, the transceiver 204 is not limited to one type, and the structure of this electronic device 200 does not constitute a limitation on the embodiments of this application.

[0064] Processor 201 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 201 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0065] Bus 202 may include a pathway for transmitting information between the aforementioned components. Bus 202 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 202 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 2 The symbol is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0066] The memory 203 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0067] The memory 203 stores the application code that executes the solution of this application, and its execution is controlled by the processor 201. The processor 201 executes the application code stored in the memory 203 to implement the content shown in the aforementioned embodiment of the building facility operation and maintenance monitoring method.

[0068] Figure 2 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0069] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the contents shown in the aforementioned embodiments of the building facility operation and maintenance monitoring method.

[0070] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0071] This application provides a computer program product, including a computer program, which, when executed by a processor, implements the content shown in the aforementioned embodiment of the building facility operation and maintenance monitoring method.

[0072] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for monitoring the operation and maintenance of building facilities, characterized in that, include: Construct a scenario template library, in which each scenario template is associated with multiple monitoring indicators and an initial early warning threshold; Obtain the attribute information of the building to be monitored, match the attribute information with the scene template library, and determine the appropriate set of monitoring indicators; Obtain the predicted environmental information of the area where the building to be monitored is located, and dynamically correct the initial warning threshold of the monitoring index set based on the attribute information and the predicted environmental information to generate the current warning threshold; The real-time monitoring data of the building to be monitored is obtained, and the real-time monitoring data is compared with the current early warning threshold to identify the indicators exceeding the standard and the related indicators of the indicators exceeding the standard. Risk warning information is generated based on the exceeded indicators and the related indicators, and the risk warning information is pushed to the operation and maintenance terminal.

2. The building facility operation and maintenance monitoring method according to claim 1, characterized in that, The step of dynamically correcting the initial warning threshold of the monitoring indicator set based on the attribute information and the prediction environment information to generate the current warning threshold includes: The monitoring indicator set is divided into fixed threshold indicators and dynamic threshold indicators; Based on the attribute information and the prediction environment information, the initial warning threshold of the dynamic threshold indicator is corrected to obtain the current warning threshold of the dynamic threshold indicator. The initial warning threshold of the fixed threshold indicator is used as the current warning threshold, and the current warning thresholds of the fixed threshold indicator and the dynamic threshold indicator constitute the current warning threshold of the monitoring indicator set.

3. The building facility operation and maintenance monitoring method according to claim 2, characterized in that, The step of correcting the initial warning threshold of the dynamic threshold indicator based on the attribute information and the prediction environment information to obtain the current warning threshold of the dynamic threshold indicator includes: Based on the structural information in the attribute information, a simulation model matching the building to be monitored is constructed; The predicted environmental information is input as a load into the simulation model, and the theoretical response values ​​of each monitoring index of the simulation model are received. For each dynamic threshold indicator, the theoretical response value of the dynamic threshold indicator is compared with the initial warning threshold, and the larger value is taken as the warning benchmark value. Based on the attribute information and the predicted environment information, a dynamic safety factor is determined; The product of the warning baseline value and the dynamic safety coefficient is calculated and used as the current warning threshold of the dynamic threshold index.

4. The building facility operation and maintenance monitoring method according to claim 3, characterized in that, The determination of the dynamic safety factor based on the attribute information and the predicted environment information includes: Multi-dimensional features are extracted from the attribute information, and each dimension feature is scored. Based on the predicted environment information, determine the dimensional weight distribution; Based on the aforementioned dimensional weight distribution, the scores of the multi-dimensional features are weighted and summed to obtain the overall building health score. The building health comprehensive score is mapped to the dynamic safety factor.

5. The building facility operation and maintenance monitoring method according to claim 1, characterized in that, The step of comparing the real-time monitoring data with the current warning threshold to identify the exceeding indicators and the related indicators of the exceeding indicators includes: Mark the indicators in the set of monitoring indicators whose real-time monitoring data exceeds the current warning threshold as exceeding indicators; Obtain historical operation and maintenance data of the scene to which the building to be monitored belongs, and mine the correlation rules between monitoring indicators based on the historical operation and maintenance data; Query the indicators that have the association rule with the exceeded indicator to form a candidate indicator set; For any set of candidate indicators and out-of-standard indicators that have the association rule, calculate the association confidence, environmental similarity and historical co-occurrence frequency of the candidate indicators and the out-of-standard indicators, and calculate the association strength based on the association confidence, environmental similarity and historical co-occurrence frequency; Candidate indicators whose correlation strength exceeds a preset strength threshold are selected from the candidate indicator set and used as the correlation indicators of the over-standard indicators.

6. The building facility operation and maintenance monitoring method according to claim 1, characterized in that, The generation of risk warning information based on the exceeding indicators and the related indicators includes: Obtain the historical operation and maintenance records of the building to be monitored; Extract the historical damage locations and damage frequencies corresponding to the out-of-standard indicators and the associated indicators from the historical operation and maintenance records; Based on the historical damage locations and the damage frequency, calculate the potential risk value for each location; Based on the potential risk value, the risk location is determined, and risk warning information including the risk location, the exceeding indicator, and the related indicator is generated.

7. An electronic device, characterized in that, include: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: perform the building facility operation and maintenance monitoring method according to any one of claims 1-6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed in the computer, the computer is instructed to perform the building facility operation and maintenance monitoring method according to any one of claims 1-6.

9. A computer program product, characterized in that, It includes a computer program, which, when executed by a processor, implements the steps of the building facility operation and maintenance monitoring method according to any one of claims 1-6.

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