Big data-based electrical fireproof safety assessment system for water conservancy and hydropower engineering construction

Abstract

The invention provides a water conservancy and hydropower engineering building electrical fireproof safety assessment system based on big data, and the system comprises a data acquisition module which is used for crawling historical building electrical fire data corresponding to water conservancy and hydropower engineering based on the big data, analyzing the historical electrical fire data of the building to determine the electrical operation state quantity when the electrical fire occurs in the building; the evaluation system construction module is used for determining an electrical fireproof safety evaluation index based on the electrical operation state quantity, and constructing an electrical fireproof safety evaluation system based on the electrical fireproof safety evaluation index; and the safety evaluation module is used for monitoring operation data of each electrical operation project in the building, inputting the operation data into the electrical fireproof safety evaluation system for safety evaluation to obtain a safety evaluation value of each electrical operation project, and performing emergency response on an abnormal electrical operation project in the water conservancy and hydropower project based on the safety evaluation value. The accuracy of potential safety hazard discovery is improved, and the operation safety of water conservancy and hydropower buildings is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction. Background Technology

[0002] Water conservancy and hydropower projects are an important material foundation for water conservancy, flood control, and people's livelihood, and an important component of the national economic infrastructure. Therefore, electrical fire safety in the construction of water conservancy and hydropower projects is of particular importance.

[0003] In national fire statistics, electrical fires caused by various factors have consistently ranked first among all fire causes. Water conservancy and hydropower facilities are important projects related to the national economy and people's livelihood, and electrical fire safety management in engineering projects is a crucial part of water conservancy and hydropower projects. However, in practice, electrical fire safety often becomes a "weak link" in the safety management of water conservancy and hydropower projects. Most electrical fire prevention systems on the market now only use monitoring equipment to monitor electrical equipment, and can only play an alarm role when a fire occurs. They cannot predict and assess potential electrical safety hazards in advance based on the operating data of electrical equipment, nor can they provide timely and effective emergency response to electrical fires, thus reducing the monitoring effect of electrical fire safety.

[0004] Therefore, in order to overcome the above-mentioned defects, the present invention provides an electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data. Summary of the Invention

[0005] This invention provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering buildings. It uses big data technology to crawl historical electrical fire data corresponding to water conservancy and hydropower engineering buildings, and analyzes this data to accurately and effectively obtain electrical operating status quantities when electrical fires occur in water conservancy and hydropower engineering buildings. This provides convenience and assurance for determining electrical fire safety assessment indicators and constructing an electrical fire safety assessment system. Finally, by analyzing the operational data of various electrical operation items in water conservancy and hydropower engineering buildings through the constructed electrical fire safety assessment system, it enables timely and effective prediction and detection of abnormal electrical operation items in water conservancy and hydropower engineering buildings. This improves the accuracy, reliability, and timeliness of safety hazard detection, thereby facilitating timely implementation of corresponding emergency measures and ensuring the operational safety of water conservancy and hydropower engineering buildings.

[0006] This invention provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, comprising:

[0007] The data acquisition module is used to crawl historical electrical fire data of water conservancy and hydropower projects based on big data, and to analyze the historical electrical fire data of buildings to determine the electrical operating status quantities when an electrical fire occurs in a building.

[0008] The assessment system construction module is used to determine electrical fire safety assessment indicators based on electrical operating status quantities, and to construct an electrical fire safety assessment system based on these indicators.

[0009] The safety assessment module is used to monitor the operational data of various electrical operation items in the building in real time, and input the operational data into the electrical fire safety assessment system for safety assessment, to obtain the safety assessment value of each electrical operation item, and to carry out emergency response to abnormal electrical operation items in water conservancy and hydropower projects based on the safety assessment value.

[0010] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes a data acquisition module comprising:

[0011] The tag determination unit is used to obtain the electrical fire prevention tasks of buildings and analyze the electrical fire prevention tasks of buildings and determine the target electrical fire prevention projects in water conservancy and hydropower buildings. At the same time, it extracts the project attributes of the target electrical fire prevention projects and configures project tags for each target electrical fire prevention project based on the project attributes. The target electrical fire prevention project is at least one type.

[0012] The data access unit is used to traverse the preset database in the server based on big data and project tags, and obtain the sub-building electrical fire data set corresponding to each project tag based on the traversal results.

[0013] The data feedback unit is used to perform a first encapsulation on the electrical fire data set of each sub-building to obtain a first data packet, and then perform a second encapsulation after adding the project tag to the header of the corresponding first data packet to obtain a second data packet, and feed the second data packet back to the data acquisition terminal to complete the crawling of historical building electrical fire data.

[0014] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes a data feedback unit comprising:

[0015] The data retrieval subunit is used to obtain the historical building electrical fire data corresponding to the water conservancy and hydropower project, and to discretize the historical building electrical fire data and map the discretized historical building electrical fire data to a two-dimensional coordinate system.

[0016] The abnormal data determination subunit is used to determine the value range of historical building electrical fire data based on the mapping result, and to determine the average value of historical building electrical fire data based on the value range. At the same time, the target value of each discretized historical building electrical fire data is subtracted from the average value, and historical building electrical fire data with a difference greater than a preset difference threshold is judged as abnormal data.

[0017] The data cleaning subunit is used to match target data cleaning rules from a preset data cleaning rule library based on the project tags corresponding to the abnormal data, and clean the abnormal data based on the target data cleaning rules to obtain the final historical building electrical fire data.

[0018] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes a data acquisition module comprising:

[0019] The data acquisition unit is used to acquire historical building electrical fire data corresponding to water conservancy and hydropower projects, and to use the preset building electrical fire prevention dimension as the status assessment index, and to perform clustering processing on the historical building electrical fire data based on the status assessment index.

[0020] The data preprocessing unit is used to obtain the sub-historical building electrical fire data corresponding to each preset building electrical fire prevention dimension based on the clustering processing results, and to convert the sub-historical building electrical fire data into the target curve based on the values ​​of the sub-historical building electrical fire data.

[0021] The operating status quantity determination unit is used to determine the amplitude characteristics of the electrical fire data of sub-historical buildings under each preset building electrical fire prevention dimension based on the target curve diagram, and to obtain the electrical operating status quantity corresponding to the occurrence of an electrical fire in a water conservancy and hydropower building based on the amplitude characteristics.

[0022] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes an assessment system construction module comprising:

[0023] Indicator quantification unit, used for:

[0024] The historical electrical fire data of water conservancy and hydropower projects were analyzed to obtain the electrical fire factors and characteristics corresponding to the historical electrical fire data. Based on the preset electrical fire prevention requirements, the initial electrical fire safety assessment index was determined, and the electrical fire factors were correlated with the initial electrical fire safety assessment index based on the preset causal relationship.

[0025] The electrical operating status quantities are obtained, and the influence ratio of different electrical fire factors in electrical fires is determined based on the electrical operating status quantities and electrical fire characteristics. Based on the influence ratio, the initial electrical fire safety assessment index is assigned a target quantitative value to obtain the target electrical fire safety assessment index.

[0026] The weight determination unit is used to determine the evaluation weights of different target electrical fire safety evaluation indicators based on the target quantification value, and obtain the electrical fire safety evaluation indicators based on the evaluation weights. At the same time, it determines the correlation characteristics between the electrical fire safety evaluation indicators based on electrical fire factors, and corrects the electrical fire safety evaluation indicators based on the correlation characteristics to obtain the final electrical fire safety evaluation indicators.

[0027] The assessment system construction unit is used to determine the topological structure between the final electrical fire safety assessment indicators based on the correlation characteristics, and to construct the electrical fire safety assessment system corresponding to the final electrical fire safety assessment indicators based on the topological structure.

[0028] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes assessment system construction units comprising:

[0029] The data acquisition subunit is used to generate a data access request based on the data acquisition terminal, access the target electrical fire data in the server based on the data access request, and retrieve the target electrical fire test data based on the access result. The target electrical fire data has known electrical fire cause, electrical fire level and electrical fire type.

[0030] The system testing subunit is used to input the target electrical fire test data into the constructed electrical fire safety assessment system for analysis and testing, and to obtain the target test results, which include the theoretical electrical fire cause, theoretical electrical fire level, and theoretical electrical fire type.

[0031] The system optimization subunit is used to compare the target test results with the benchmark results. If the target test results and the benchmark results are consistent, the constructed electrical fire safety assessment system is deemed qualified. Otherwise, the electrical fire safety assessment system is deemed unqualified, and the electrical fire safety assessment system is reconstructed.

[0032] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes assessment system construction units comprising:

[0033] The data crawling subunit is used to determine the data crawling interval, configure the clock generator based on the data crawling interval, and generate periodic data crawling instructions based on the configuration results. At the same time, based on the periodic data crawling instructions, it controls the preset data crawling program to crawl real-time building electrical fire data of water conservancy and hydropower projects according to big data, compares the differences between real-time building electrical fire data of adjacent periods, and retains the building electrical fire data with differences when there are differences.

[0034] The system is improved by sub-units, which are used for:

[0035] The electrical fire data of different buildings is analyzed to determine the structural characteristics of the electrical fire data of different buildings, and the correlation nodes between the electrical fire data of different buildings and the electrical fire safety assessment system are determined based on the structural characteristics.

[0036] Construct electrical fire safety assessment branches corresponding to the differential building electrical fire data, and link these branches with the electrical fire safety assessment system based on associated nodes to improve the electrical fire safety assessment system.

[0037] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes a safety assessment module comprising:

[0038] The structural analysis unit is used to acquire three-dimensional data of water conservancy and hydropower constructions, and to analyze the three-dimensional data to determine the distribution characteristics of electrical equipment in water conservancy and hydropower constructions.

[0039] The monitoring point determination unit is used to determine key electrical equipment based on distribution characteristics, configure target monitoring points for the key electrical equipment, and set the target monitoring points as the installation locations of the monitoring devices. There is at least one key electrical equipment and one target monitoring point.

[0040] The data monitoring unit is used to monitor the corresponding key electrical equipment based on the monitoring device installed at the monitoring device installation location, and to obtain the operation data of various electrical operation items in the water conservancy and hydropower construction based on the monitoring results. It also marks the operation data of various electrical operation items based on the equipment identification of key electrical equipment, thus completing the monitoring and collection of operation data of various electrical operation items.

[0041] Preferably, a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction includes a safety assessment module comprising:

[0042] The data evaluation unit is used to acquire the operational data of various electrical operation items, and input the operational data of various electrical operation items into the electrical fire safety evaluation system for analysis to obtain the safety evaluation value of each electrical operation item.

[0043] The abnormal electrical operation item determination unit is used to compare the safety assessment value of each electrical operation item with the corresponding preset benchmark threshold, and to determine the electrical operation item whose safety assessment value is lower than the corresponding preset benchmark threshold as an abnormal electrical operation item.

[0044] The emergency response unit is used to extract project tags for abnormal electrical operation items, search the preset emergency measures library based on the project tags, obtain target emergency measures based on the search results, and perform emergency response for abnormal electrical operation items based on the target emergency measures.

[0045] Preferably, an electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data, including an emergency response unit, comprises:

[0046] The result acquisition subunit is used to acquire the project tags of the abnormal electrical operation items, generate an emergency response report based on the project tags, establish a wireless communication link between the emergency response terminal and the management terminal, and transmit the emergency response report to the management terminal for the first alarm notification.

[0047] The monitoring subunit is used to monitor the emergency response progress of the emergency response terminal for abnormal electrical operation items in real time based on the alarm notification results, and to transmit the emergency response progress to the management terminal for a second alarm notification via a wireless communication link.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0049] 1. By crawling historical electrical fire data of water conservancy and hydropower projects using big data technology, and analyzing the crawled historical electrical fire data, the electrical operating status of water conservancy and hydropower projects during electrical fires can be accurately and effectively obtained. This provides convenience and guarantee for determining electrical fire safety assessment indicators and constructing an electrical fire safety assessment system. Finally, by analyzing the operating data of various electrical operation items in water conservancy and hydropower projects through the constructed electrical fire safety assessment system, abnormal electrical operation items in water conservancy and hydropower projects can be predicted and detected in a timely and effective manner. This improves the accuracy, reliability, and timeliness of safety hazard detection, thereby facilitating timely implementation of corresponding emergency measures and ensuring the operational safety of water conservancy and hydropower projects.

[0050] 2. By analyzing electrical fire data, the system identifies the corresponding electrical fire factors and characteristics. Secondly, it accurately determines the correlation between different electrical fire safety assessment indicators based on these factors and characteristics. Finally, it accurately and effectively quantifies different initial electrical fire safety assessment indicators and determines their assessment weights based on electrical operating status quantities. Ultimately, this leads to the accurate and reliable construction of an electrical fire safety assessment system, facilitating electrical fire safety assessments of water conservancy and hydropower engineering projects. This ensures the accuracy and reliability of electrical fire safety assessments for water conservancy and hydropower engineering projects, enabling timely detection of anomalies and prompt implementation of appropriate emergency measures, thus guaranteeing the operational safety of water conservancy and hydropower engineering projects.

[0051] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0052] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0053] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0054] Figure 1 This is a structural diagram of a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, as described in an embodiment of the present invention.

[0055] Figure 2 This is a structural diagram of a data acquisition module in a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, as described in an embodiment of the present invention.

[0056] Figure 3 This is a structural diagram of the assessment system construction module in a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, as described in an embodiment of the present invention. Detailed Implementation

[0057] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0058] Example 1:

[0059] This embodiment provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, such as... Figure 1 As shown, it includes:

[0060] The data acquisition module is used to crawl historical electrical fire data of water conservancy and hydropower projects based on big data, and to analyze the historical electrical fire data of buildings to determine the electrical operating status quantities when an electrical fire occurs in a building.

[0061] The assessment system construction module is used to determine electrical fire safety assessment indicators based on electrical operating status quantities, and to construct an electrical fire safety assessment system based on these indicators.

[0062] The safety assessment module is used to monitor the operational data of various electrical operation items in the building in real time, and input the operational data into the electrical fire safety assessment system for safety assessment, to obtain the safety assessment value of each electrical operation item, and to carry out emergency response to abnormal electrical operation items in water conservancy and hydropower projects based on the safety assessment value.

[0063] In this embodiment, "buildings" is a general term for buildings and structures. Among them, houses used for people to study, work, live, and engage in production and various cultural and social activities are called "buildings," such as schools, shops, residences, theaters, etc. Buildings set up for engineering and technical needs, where people do not produce or live, are called "structures," such as bridges, dams, water towers, monuments, etc. The purpose is to achieve effective electrical and fire safety assessments of water conservancy and hydropower projects in different structures, and to ensure the comprehensiveness of the safety assessment.

[0064] In this embodiment, the historical building electrical fire data is known in advance, is stored in the server, and the causes and types of electrical fires corresponding to the historical building electrical fire data are known.

[0065] In this embodiment, the electrical operating status quantity refers to the actual status of electrical fire data corresponding to different electrical equipment in a water conservancy and hydropower project when a fire occurs, including the data type and the corresponding value.

[0066] In this embodiment, electrical operation items refer to all electrical equipment included in the construction of water conservancy and hydropower projects, as well as power lines related to water conservancy and hydropower.

[0067] In this embodiment, the safety assessment value is used to characterize the current operational safety status of each electrical operation item. The higher the value, the safer the electrical operation item is.

[0068] In this embodiment, emergency response to abnormal electrical operation items in water conservancy and hydropower projects based on safety assessment values ​​refers to comparing the safety assessment values ​​of each electrical operation item with the corresponding preset safety thresholds, and determining that the safety assessment value is less than the preset safety threshold as an abnormal electrical operation item. Abnormal electrical operation items are electrical equipment or power lines with potential safety hazards.

[0069] In this embodiment, emergency response refers to responding to an emergency by adopting preset emergency measures, that is, resolving the current security problem through preset emergency measures.

[0070] The beneficial effects of the above technical solution are as follows: By crawling historical electrical fire data of water conservancy and hydropower projects using big data technology and analyzing the crawled historical electrical fire data, the electrical operating status of water conservancy and hydropower projects during electrical fires can be accurately and effectively obtained. This provides convenience and guarantee for determining electrical fire safety assessment indicators and constructing an electrical fire safety assessment system. Finally, by analyzing the operating data of various electrical operation items in water conservancy and hydropower projects through the constructed electrical fire safety assessment system, abnormal electrical operation items in water conservancy and hydropower projects can be predicted and discovered in a timely and effective manner. This improves the accuracy, reliability, and timeliness of safety hazard detection, thereby facilitating timely implementation of corresponding emergency measures and ensuring the operational safety of water conservancy and hydropower projects.

[0071] Example 2:

[0072] Based on Example 1, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, such as... Figure 2 As shown, the data acquisition module includes:

[0073] The tag determination unit is used to obtain the electrical fire prevention tasks of buildings and analyze the electrical fire prevention tasks of buildings and determine the target electrical fire prevention projects in water conservancy and hydropower buildings. At the same time, it extracts the project attributes of the target electrical fire prevention projects and configures project tags for each target electrical fire prevention project based on the project attributes. The target electrical fire prevention project is at least one type.

[0074] The data access unit is used to traverse the preset database in the server based on big data and project tags, and obtain the sub-building electrical fire data set corresponding to each project tag based on the traversal results.

[0075] The data feedback unit is used to perform a first encapsulation on the electrical fire data set of each sub-building to obtain a first data packet, and then perform a second encapsulation after adding the project tag to the header of the corresponding first data packet to obtain a second data packet, and feed the second data packet back to the data acquisition terminal to complete the crawling of historical building electrical fire data.

[0076] In this embodiment, the building electrical fire prevention task is known in advance and is used to characterize the items that require safety assessment and monitoring of the building electrical system, as well as the safety assessment requirements for each item.

[0077] In this embodiment, the target electrical fire protection project refers to electrical equipment and power lines that require safety protection in current water conservancy and hydropower construction.

[0078] In this embodiment, project attributes refer to parameters that can characterize the project type, operation mode, or operating environment of the target electrical fire protection project.

[0079] In this embodiment, the project label refers to a marking symbol that can distinguish different target electrical fire protection projects.

[0080] In this embodiment, the preset database is pre-set and used to store different electrical fire data.

[0081] In this embodiment, the sub-building electrical fire data set refers to all electrical fire data corresponding to each project tag retrieved from a preset database.

[0082] In this embodiment, the first encapsulation refers to encapsulating the electrical fire data of each sub-building, with the aim of effectively distinguishing different types of electrical fire data. The first data package is the data set obtained after encapsulating the electrical fire data of different sub-buildings.

[0083] In this embodiment, the second encapsulation refers to encapsulating the first data packet containing the item tag, that is, summarizing all the first data packets containing the item tag. The second data packet is the data packet obtained after summarizing all the first data packets containing the item tag.

[0084] The beneficial effects of the above technical solution are as follows: By analyzing the acquired electrical fire prevention tasks, the target electrical fire prevention projects and their corresponding project attributes can be accurately and effectively determined. Secondly, based on the project attributes, the corresponding electrical fire data set is retrieved from the preset database and encapsulated to facilitate the feedback of the retrieved electrical fire data. Finally, the encapsulated electrical fire data is transmitted to the data acquisition terminal, enabling accurate and effective crawling of historical electrical fire data of water conservancy and hydropower constructions, providing a basis and convenience for the electrical fire safety assessment of water conservancy and hydropower engineering constructions.

[0085] Example 3:

[0086] Based on Example 2, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, including a data feedback unit:

[0087] The data retrieval subunit is used to obtain the historical building electrical fire data corresponding to the water conservancy and hydropower project, and to discretize the historical building electrical fire data and map the discretized historical building electrical fire data to a two-dimensional coordinate system.

[0088] The abnormal data determination subunit is used to determine the value range of historical building electrical fire data based on the mapping result, and to determine the average value of historical building electrical fire data based on the value range. At the same time, the target value of each discretized historical building electrical fire data is subtracted from the average value, and historical building electrical fire data with a difference greater than a preset difference threshold is judged as abnormal data.

[0089] The data cleaning subunit is used to match target data cleaning rules from a preset data cleaning rule library based on the project tags corresponding to the abnormal data, and clean the abnormal data based on the target data cleaning rules to obtain the final historical building electrical fire data.

[0090] In this embodiment, discretization refers to splitting historical building electrical fire data into independent data units, with the aim of facilitating the determination of the changing trends of historical building electrical fire data in a coordinate system.

[0091] In this embodiment, the target value refers to the specific value of historical building electrical fire data.

[0092] In this embodiment, the preset difference threshold is set in advance and is used to measure whether the historical building electrical fire data is qualified.

[0093] In this embodiment, abnormal data refers to building electrical fire data where the difference is greater than a preset difference threshold.

[0094] In this embodiment, the preset data cleaning rule library is pre-set and used to store different data cleaning rules.

[0095] In this embodiment, the target data cleaning rule refers to the rule applicable to cleaning the current abnormal data.

[0096] The beneficial effects of the above technical solution are as follows: by discretizing the obtained historical building electrical fire data and mapping the discretized historical building electrical fire data in a two-dimensional coordinate system, the abnormal data in the historical building electrical fire data can be accurately and effectively identified based on the mapping results. Finally, the corresponding target data cleaning rules are retrieved to clean the abnormal data, ensuring the accuracy and reliability of the final obtained historical building electrical fire data.

[0097] Example 4:

[0098] Based on Example 1, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, including a data acquisition module:

[0099] The data acquisition unit is used to acquire historical building electrical fire data corresponding to water conservancy and hydropower projects, and to use the preset building electrical fire prevention dimension as the status assessment index, and to perform clustering processing on the historical building electrical fire data based on the status assessment index.

[0100] The data preprocessing unit is used to obtain the sub-historical building electrical fire data corresponding to each preset building electrical fire prevention dimension based on the clustering processing results, and to convert the sub-historical building electrical fire data into the target curve based on the values ​​of the sub-historical building electrical fire data.

[0101] The operating status quantity determination unit is used to determine the amplitude characteristics of the electrical fire data of sub-historical buildings under each preset building electrical fire prevention dimension based on the target curve diagram, and to obtain the electrical operating status quantity corresponding to the occurrence of an electrical fire in a water conservancy and hydropower building based on the amplitude characteristics.

[0102] In this embodiment, the electrical fire protection dimensions of the building are known in advance, that is, the types of electrical fire protection that need to be carried out, such as fires caused by excessive voltage or current.

[0103] In this embodiment, the status assessment index is determined based on the preset building electrical fire prevention dimensions, and serves as the basis for classifying historical building electrical fire data.

[0104] In this embodiment, the sub-historical building electrical fire data refers to the historical building electrical fire data corresponding to each preset building electrical fire prevention dimension.

[0105] In this embodiment, the target curve graph refers to the graph obtained by displaying the electrical fire data of the sub-historical building in the form of a curve.

[0106] In this embodiment, amplitude characteristics refer to parameters that can characterize the changes in the values ​​of electrical fire data of sub-historical buildings.

[0107] The beneficial effects of the above technical solution are as follows: by determining the preset building electrical fire prevention dimensions for historical building electrical fire data corresponding to water conservancy and hydropower projects, the historical building electrical fire data can be classified according to the preset building electrical fire prevention dimensions. Based on the classification results, each sub-historical building electrical fire data is converted into a corresponding target curve. Finally, the amplitude characteristics of the sub-historical building electrical fire data are determined based on the target curve, thereby accurately obtaining electrical operating status quantities based on amplitude characteristics. This provides convenience and basis for determining electrical fire safety assessment indicators and ensures the accuracy and reliability of the constructed electrical fire safety assessment system.

[0108] Example 5:

[0109] Based on Example 1, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, such as... Figure 2 As shown, the evaluation system construction module includes:

[0110] Indicator quantification unit, used for:

[0111] The historical electrical fire data of water conservancy and hydropower projects were analyzed to obtain the electrical fire factors and characteristics corresponding to the historical electrical fire data. Based on the preset electrical fire prevention requirements, the initial electrical fire safety assessment index was determined, and the electrical fire factors were correlated with the initial electrical fire safety assessment index based on the preset causal relationship.

[0112] The electrical operating status quantities are obtained, and the influence ratio of different electrical fire factors in electrical fires is determined based on the electrical operating status quantities and electrical fire characteristics. Based on the influence ratio, the initial electrical fire safety assessment index is assigned a target quantitative value to obtain the target electrical fire safety assessment index.

[0113] The weight determination unit is used to determine the evaluation weights of different target electrical fire safety evaluation indicators based on the target quantification value, and obtain the electrical fire safety evaluation indicators based on the evaluation weights. At the same time, it determines the correlation characteristics between the electrical fire safety evaluation indicators based on electrical fire factors, and corrects the electrical fire safety evaluation indicators based on the correlation characteristics to obtain the final electrical fire safety evaluation indicators.

[0114] The assessment system construction unit is used to determine the topological structure between the final electrical fire safety assessment indicators based on the correlation characteristics, and to construct the electrical fire safety assessment system corresponding to the final electrical fire safety assessment indicators based on the topological structure.

[0115] In this embodiment, electrical fire factors refer to external influencing factors that cause electrical fires in water conservancy and hydropower engineering structures.

[0116] In this embodiment, electrical fire characteristics refer to the type of electrical fire and the severity of the electrical fire that occurs when an electrical fire occurs in a water conservancy and hydropower project.

[0117] In this embodiment, the preset electrical fire protection requirements are pre-set and are used to characterize the standards for protecting against different electrical fires.

[0118] In this embodiment, the initial electrical fire safety assessment index refers to an index whose type is known only, such as the name of the index, such as current, voltage, and power.

[0119] In this embodiment, the pre-defined causal relationship is known in advance and is used to characterize the correspondence between electrical fire factors and electrical fire types, as well as the relationship between electrical fire factors and initial electrical fire safety assessment indicators.

[0120] In this embodiment, the influence ratio is used to characterize the proportion of different electrical fire factors in an electrical fire. For example, fires caused by excessive current may account for 30%.

[0121] In this embodiment, the target quantification value is used to characterize the proportion of different initial electrical fire safety assessment indicators in the electrical fire safety assessment of water conservancy and hydropower engineering construction, thereby facilitating the accuracy and reliability of the final assessment results.

[0122] In this embodiment, the target electrical fire safety assessment index refers to the index obtained by assigning specific quantitative values ​​to the initial electrical fire safety assessment index. For example, when conducting an electrical fire safety assessment of water conservancy and hydropower engineering construction, the current index accounts for 30%, the voltage index accounts for 10%, the power index accounts for 10%, the line layout accounts for 30%, and the equipment performance accounts for 20%, etc.

[0123] In this embodiment, the evaluation weight is used to characterize the importance of different target electrical fire safety evaluation indicators when conducting electrical fire safety evaluation. The larger the value, the greater the role.

[0124] In this embodiment, the correlation feature is used to characterize the correlation between electrical flood safety assessment indicators and the interaction between electrical fire safety assessment indicators, such as how current and voltage can cause changes in equipment power.

[0125] In this embodiment, the topology is used to characterize the interaction between different electrical fire safety assessment indicators, thereby facilitating the construction of a corresponding electrical fire safety assessment system based on the topology.

[0126] The beneficial effects of the above technical solution are as follows: First, by analyzing electrical fire data, the electrical fire factors and characteristics corresponding to the electrical fire data can be determined. Second, the correlation between different electrical fire safety assessment indicators can be accurately determined based on electrical fire factors and characteristics. Finally, based on electrical operating status quantities, different initial electrical fire safety assessment indicators can be accurately and effectively quantified, and the assessment weights of different electrical fire safety assessment indicators can be effectively determined. Ultimately, an accurate and reliable electrical fire safety assessment system can be constructed, which facilitates the assessment of electrical fire safety in water conservancy and hydropower engineering constructions and ensures the accuracy and reliability of electrical fire safety assessments for water conservancy and hydropower engineering constructions. This facilitates the timely detection of abnormal situations and the timely implementation of corresponding emergency measures for safety response, thus ensuring the operational safety of water conservancy and hydropower engineering constructions.

[0127] Example 6:

[0128] Based on Example 5, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction. The assessment system construction unit includes:

[0129] The data acquisition subunit is used to generate a data access request based on the data acquisition terminal, access the target electrical fire data in the server based on the data access request, and retrieve the target electrical fire test data based on the access result. The target electrical fire data has known electrical fire cause, electrical fire level and electrical fire type.

[0130] The system testing subunit is used to input the target electrical fire test data into the constructed electrical fire safety assessment system for analysis and testing, and to obtain the target test results, which include the theoretical electrical fire cause, theoretical electrical fire level, and theoretical electrical fire type.

[0131] The system optimization subunit is used to compare the target test results with the benchmark results. If the target test results and the benchmark results are consistent, the constructed electrical fire safety assessment system is deemed qualified. Otherwise, the electrical fire safety assessment system is deemed unqualified, and the electrical fire safety assessment system is reconstructed.

[0132] In this embodiment, the target electrical fire test data refers to the data used to verify the constructed electrical fire safety assessment system.

[0133] In this embodiment, the target test result refers to the result obtained after inputting the target electrical fire test data into the electrical fire safety assessment system for analysis.

[0134] In this embodiment, the theoretical causes of electrical fires, the theoretical levels of electrical fires, and the theoretical types of electrical fires refer to the results obtained after analysis and do not represent the actual results.

[0135] In this embodiment, the baseline result is the actual result corresponding to the target fire test data, which is known in advance.

[0136] The beneficial effects of the above technical solution are: by retrieving target fire test data to test the analytical performance of the electrical fire safety assessment system, the analytical accuracy of the electrical fire safety assessment system can be effectively verified. It also facilitates timely adjustment and improvement of the electrical fire safety assessment system when the analytical effect is unqualified, thus ensuring the accuracy and reliability of the final electrical fire safety assessment results for water conservancy and hydropower engineering construction.

[0137] Example 7:

[0138] Based on Example 5, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction. The assessment system construction unit includes:

[0139] The data crawling subunit is used to determine the data crawling interval, configure the clock generator based on the data crawling interval, and generate periodic data crawling instructions based on the configuration results. At the same time, based on the periodic data crawling instructions, it controls the preset data crawling program to crawl real-time building electrical fire data of water conservancy and hydropower projects according to big data, compares the differences between real-time building electrical fire data of adjacent periods, and retains the building electrical fire data with differences when there are differences.

[0140] The system is improved by sub-units, which are used for:

[0141] The electrical fire data of different buildings is analyzed to determine the structural characteristics of the electrical fire data of different buildings, and the correlation nodes between the electrical fire data of different buildings and the electrical fire safety assessment system are determined based on the structural characteristics.

[0142] Construct electrical fire safety assessment branches corresponding to the differential building electrical fire data, and link these branches with the electrical fire safety assessment system based on associated nodes to improve the electrical fire safety assessment system.

[0143] In this embodiment, the data crawling interval is used to characterize the time interval for obtaining data from the server, thereby ensuring the comprehensiveness and reliability of the crawled electrical fire data.

[0144] In this embodiment, the periodic data crawling instruction refers to the instruction generated by the clock generator according to the data crawling interval, which is used to obtain real-time updated electrical fire data from the server.

[0145] In this embodiment, the preset data crawling program is pre-set and is a tool used to obtain electrical fire data of water conservancy and hydropower construction.

[0146] In this embodiment, differential building electrical fire data refers to data that is different between real-time building electrical fire data in adjacent periods.

[0147] In this embodiment, the structural features are used to characterize the range of values ​​for electrical fire data in different buildings and the correlation between the data.

[0148] In this embodiment, the associated node refers to the location where there is a correlation between the differential building electrical fire data and the currently constructed electrical fire safety assessment system.

[0149] In this embodiment, the electrical fire safety assessment branch refers to the assessment system built based on the differential electrical fire data.

[0150] The beneficial effects of the above technical solution are as follows: First, by crawling real-time building electrical fire data based on big data and comparing the differences between real-time building electrical fire data in adjacent periods, accurate and effective confirmation of the differences in building electrical fire data can be achieved. Second, by analyzing the differences in building electrical fire data, the correlation nodes between the differences in building electrical fire data and the current electrical fire safety assessment system can be confirmed. Finally, by linking the electrical fire safety assessment branches corresponding to the differences in building electrical fire data with the electrical fire safety assessment system through the correlation nodes, the comprehensive reliability of the constructed electrical fire safety assessment system can be ensured, and it is also convenient to conduct a comprehensive and effective analysis of the electrical fire safety of water conservancy and hydropower buildings.

[0151] Example 8:

[0152] Based on Example 1, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, including a safety assessment module:

[0153] The structural analysis unit is used to acquire three-dimensional data of water conservancy and hydropower constructions, and to analyze the three-dimensional data to determine the distribution characteristics of electrical equipment in water conservancy and hydropower constructions.

[0154] The monitoring point determination unit is used to determine key electrical equipment based on distribution characteristics, configure target monitoring points for the key electrical equipment, and set the target monitoring points as the installation locations of the monitoring devices. There is at least one key electrical equipment and one target monitoring point.

[0155] The data monitoring unit is used to monitor the corresponding key electrical equipment based on the monitoring device installed at the monitoring device installation location, and to obtain the operation data of various electrical operation items in the water conservancy and hydropower construction based on the monitoring results. It also marks the operation data of various electrical operation items based on the equipment identification of key electrical equipment, thus completing the monitoring and collection of operation data of various electrical operation items.

[0156] In this embodiment, the distribution characteristics refer to the spatial distribution of electrical equipment in water conservancy and hydropower construction.

[0157] In this embodiment, critical electrical equipment refers to equipment that requires electrical protection testing in water conservancy and hydropower construction based on the spatial distribution of electrical equipment.

[0158] In this embodiment, the target monitoring point refers to the location point used to monitor key electrical equipment.

[0159] In this embodiment, the equipment identifier of the critical electrical equipment is a pre-set identifier based on the model of the critical electrical equipment, used to distinguish different critical electrical equipment.

[0160] In this embodiment, marking the operating data of each electrical operation item based on the equipment identifier of the key electrical equipment is to determine which key electrical equipment the operating data of each electrical operation item corresponds to.

[0161] The beneficial effects of the above technical solution are: by determining the three-dimensional data of water conservancy and hydropower construction, the distribution characteristics of electrical equipment in water conservancy and hydropower construction can be effectively determined, thereby confirming the key electrical equipment. This effectively ensures the monitoring of key electrical equipment for various electrical operation projects in water conservancy and hydropower construction, improves the effectiveness and accuracy of water conservancy and hydropower construction monitoring, and thus ensures the operational safety of water conservancy and hydropower construction.

[0162] Example 9:

[0163] Based on Example 1, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, including a safety assessment module:

[0164] The data evaluation unit is used to acquire the operational data of various electrical operation items, and input the operational data of various electrical operation items into the electrical fire safety evaluation system for analysis to obtain the safety evaluation value of each electrical operation item.

[0165] The abnormal electrical operation item determination unit is used to compare the safety assessment value of each electrical operation item with the corresponding preset benchmark threshold, and to determine the electrical operation item whose safety assessment value is lower than the corresponding preset benchmark threshold as an abnormal electrical operation item.

[0166] The emergency response unit is used to extract project tags for abnormal electrical operation items, search the preset emergency measures library based on the project tags, obtain target emergency measures based on the search results, and perform emergency response for abnormal electrical operation items based on the target emergency measures.

[0167] In this embodiment, the preset benchmark threshold refers to a pre-set threshold, and one electrical operation item corresponds to one benchmark threshold, which is used as a standard to measure whether there are any abnormal electrical operation items.

[0168] In this embodiment, the project labels are pre-set, and each electrical operation project corresponds to a different project label to distinguish different electrical operation projects.

[0169] In this embodiment, the preset emergency measures library is pre-set and contains emergency measures corresponding to different project tags. Therefore, the target emergency measures corresponding to the abnormal electrical operation project can be extracted from the preset emergency measures library by the project tag of the abnormal electrical operation project.

[0170] The beneficial effects of the above technical solution are: by determining the safety assessment value of each electrical operation item, it is possible to effectively assess abnormal electrical operation items based on preset benchmark thresholds, and then to achieve effective emergency response to abnormal electrical operation items through the item tags of abnormal electrical operation items, thereby ensuring the safety of electrical fire prevention in water conservancy and hydropower engineering construction.

[0171] Example 10:

[0172] Based on Example 9, this example provides a big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, including an emergency response unit:

[0173] The result acquisition subunit is used to acquire the project tags of the abnormal electrical operation items, generate an emergency response report based on the project tags, establish a wireless communication link between the emergency response terminal and the management terminal, and transmit the emergency response report to the management terminal for the first alarm notification.

[0174] The monitoring subunit is used to monitor the emergency response progress of the emergency response terminal for abnormal electrical operation items in real time based on the alarm notification results, and to transmit the emergency response progress to the management terminal for a second alarm notification via a wireless communication link.

[0175] In this embodiment, the emergency response report refers to a report generated based on the project tag of the abnormal electrical operation item, which can be notified to the management terminal.

[0176] In this embodiment, the first alarm notification refers to transmitting the obtained emergency response report to the management terminal to provide an alarm reminder, the purpose of which is to remind the management terminal to promptly confirm any abnormal electrical operation items.

[0177] In this embodiment, the second alarm notification refers to transmitting the emergency response progress to the management terminal in real time for notification.

[0178] The beneficial effects of the above technical solution are: by generating emergency response reports from project tags of abnormal electrical operation items and sending the first alarm notification to the management terminal, and then sending a second alarm notification based on the emergency response progress of the abnormal electrical operation items, accurate and comprehensive monitoring of electrical safety assessment of water conservancy and hydropower engineering construction is achieved, thereby improving the emergency response efficiency and effectiveness for electrical fires in water conservancy and hydropower engineering construction.

[0179] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, characterized in that, include: The data acquisition module is used to crawl historical electrical fire data of water conservancy and hydropower projects based on big data, and to analyze the historical electrical fire data of buildings to determine the electrical operating status quantities when an electrical fire occurs in a building. The assessment system construction module is used to determine electrical fire safety assessment indicators based on electrical operating status quantities, and to construct an electrical fire safety assessment system based on these indicators. The safety assessment module is used to monitor the operational data of various electrical operation items in the building in real time, and input the operational data into the electrical fire safety assessment system for safety assessment, to obtain the safety assessment value of each electrical operation item, and to carry out emergency response to abnormal electrical operation items in water conservancy and hydropower projects based on the safety assessment value.

2. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 1, characterized in that, The data acquisition module includes: The tag determination unit is used to obtain the electrical fire prevention tasks of buildings and analyze the electrical fire prevention tasks of buildings and determine the target electrical fire prevention projects in water conservancy and hydropower buildings. At the same time, it extracts the project attributes of the target electrical fire prevention projects and configures project tags for each target electrical fire prevention project based on the project attributes. The target electrical fire prevention project is at least one type. The data access unit is used to traverse the preset database in the server based on big data and project tags, and obtain the sub-building electrical fire data set corresponding to each project tag based on the traversal results. The data feedback unit is used to perform a first encapsulation on the electrical fire data set of each sub-building to obtain a first data packet, and then perform a second encapsulation after adding the project tag to the header of the corresponding first data packet to obtain a second data packet, and feed the second data packet back to the data acquisition terminal to complete the crawling of historical building electrical fire data.

3. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 2, characterized in that, The data feedback unit includes: The data retrieval subunit is used to obtain the historical building electrical fire data corresponding to the water conservancy and hydropower project, and to discretize the historical building electrical fire data and map the discretized historical building electrical fire data to a two-dimensional coordinate system. The abnormal data determination subunit is used to determine the value range of historical building electrical fire data based on the mapping result, and to determine the average value of historical building electrical fire data based on the value range. At the same time, the target value of each discretized historical building electrical fire data is subtracted from the average value, and historical building electrical fire data with a difference greater than a preset difference threshold is judged as abnormal data. The data cleaning subunit is used to match target data cleaning rules from a preset data cleaning rule library based on the project tags corresponding to the abnormal data, and clean the abnormal data based on the target data cleaning rules to obtain the final historical building electrical fire data.

4. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 1, characterized in that, The data acquisition module includes: The data acquisition unit is used to acquire historical building electrical fire data corresponding to water conservancy and hydropower projects, and to use the preset building electrical fire prevention dimension as the status assessment index, and to perform clustering processing on the historical building electrical fire data based on the status assessment index. The data preprocessing unit is used to obtain the sub-historical building electrical fire data corresponding to each preset building electrical fire prevention dimension based on the clustering processing results, and to convert the sub-historical building electrical fire data into the target curve based on the values ​​of the sub-historical building electrical fire data. The operating status quantity determination unit is used to determine the amplitude characteristics of the electrical fire data of sub-historical buildings under each preset building electrical fire prevention dimension based on the target curve diagram, and to obtain the electrical operating status quantity corresponding to the occurrence of electrical fire in water conservancy and hydropower buildings based on the amplitude characteristics.

5. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 1, characterized in that, The evaluation system construction module includes: Indicator quantification unit, used for: The historical electrical fire data of water conservancy and hydropower projects were analyzed to obtain the electrical fire factors and characteristics corresponding to the historical electrical fire data. Based on the preset electrical fire prevention requirements, the initial electrical fire safety assessment index was determined, and the electrical fire factors were correlated with the initial electrical fire safety assessment index based on the preset causal relationship. The electrical operating status quantities are obtained, and the influence ratio of different electrical fire factors in electrical fires is determined based on the electrical operating status quantities and electrical fire characteristics. Based on the influence ratio, the initial electrical fire safety assessment index is assigned a target quantitative value to obtain the target electrical fire safety assessment index. The weight determination unit is used to determine the evaluation weights of different target electrical fire safety evaluation indicators based on the target quantification value, and obtain the electrical fire safety evaluation indicators based on the evaluation weights. At the same time, it determines the correlation characteristics between the electrical fire safety evaluation indicators based on electrical fire factors, and corrects the electrical fire safety evaluation indicators based on the correlation characteristics to obtain the final electrical fire safety evaluation indicators. The assessment system construction unit is used to determine the topological structure between the final electrical fire safety assessment indicators based on the correlation characteristics, and to construct the electrical fire safety assessment system corresponding to the final electrical fire safety assessment indicators based on the topological structure.

6. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 5, characterized in that, The evaluation system construction units include: The data acquisition subunit is used to generate a data access request based on the data acquisition terminal, access the target electrical fire data in the server based on the data access request, and retrieve the target electrical fire test data based on the access result. The target electrical fire data has known electrical fire cause, electrical fire level and electrical fire type. The system testing subunit is used to input the target electrical fire test data into the constructed electrical fire safety assessment system for analysis and testing, and to obtain the target test results, which include the theoretical electrical fire cause, theoretical electrical fire level, and theoretical electrical fire type. The system optimization subunit is used to compare the target test results with the benchmark results. If the target test results and the benchmark results are consistent, the constructed electrical fire safety assessment system is deemed qualified. Otherwise, the electrical fire safety assessment system is deemed unqualified, and the electrical fire safety assessment system is reconstructed.

7. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 5, characterized in that, The evaluation system construction units include: The data crawling subunit is used to determine the data crawling interval, configure the clock generator based on the data crawling interval, and generate periodic data crawling instructions based on the configuration results. At the same time, based on the periodic data crawling instructions, it controls the preset data crawling program to crawl real-time building electrical fire data of water conservancy and hydropower projects according to big data, compares the differences between real-time building electrical fire data of adjacent periods, and retains the building electrical fire data with differences when there are differences. The system is improved by sub-units, which are used for: The electrical fire data of different buildings is analyzed to determine the structural characteristics of the electrical fire data of different buildings, and the correlation nodes between the electrical fire data of different buildings and the electrical fire safety assessment system are determined based on the structural characteristics. Construct electrical fire safety assessment branches corresponding to the differential building electrical fire data, and link these branches with the electrical fire safety assessment system based on associated nodes to improve the electrical fire safety assessment system.

8. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 1, characterized in that, The security assessment module includes: The structural analysis unit is used to acquire three-dimensional data of water conservancy and hydropower constructions, and to analyze the three-dimensional data to determine the distribution characteristics of electrical equipment in water conservancy and hydropower constructions. The monitoring point determination unit is used to determine key electrical equipment based on distribution characteristics, configure target monitoring points for the key electrical equipment, and set the target monitoring points as the installation locations of the monitoring devices. There is at least one key electrical equipment and one target monitoring point. The data monitoring unit is used to monitor the corresponding key electrical equipment based on the monitoring device installed at the monitoring device installation location, and to obtain the operation data of various electrical operation items in the water conservancy and hydropower construction based on the monitoring results. It also marks the operation data of various electrical operation items based on the equipment identification of key electrical equipment, thus completing the monitoring and collection of operation data of various electrical operation items.

9. The electrical fire safety assessment system for water conservancy and hydropower engineering construction based on big data as described in claim 1, characterized in that, The security assessment module includes: The data evaluation unit is used to acquire the operational data of various electrical operation items, and input the operational data of various electrical operation items into the electrical fire safety evaluation system for analysis to obtain the safety evaluation value of each electrical operation item. The abnormal electrical operation item determination unit is used to compare the safety assessment value of each electrical operation item with the corresponding preset benchmark threshold, and to determine the electrical operation item whose safety assessment value is lower than the corresponding preset benchmark threshold as an abnormal electrical operation item. The emergency response unit is used to extract project tags for abnormal electrical operation items, search the preset emergency measures library based on the project tags, obtain target emergency measures based on the search results, and perform emergency response for abnormal electrical operation items based on the target emergency measures.

10. A big data-based electrical fire safety assessment system for water conservancy and hydropower engineering construction, as described in claim 9, is characterized in that... Emergency response unit, including: The result acquisition subunit is used to acquire the project tags of the abnormal electrical operation items, generate an emergency response report based on the project tags, establish a wireless communication link between the emergency response terminal and the management terminal, and transmit the emergency response report to the management terminal for the first alarm notification. The monitoring subunit is used to monitor the emergency response progress of the emergency response terminal for abnormal electrical operation items in real time based on the alarm notification results, and to transmit the emergency response progress to the management terminal for a second alarm notification via a wireless communication link.

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