Automatic control system for low-pressure carbon dioxide fire extinguishing

Abstract

The invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, and relates to the technical field of fire fighting, and the system comprises a data monitoring module which is used for obtaining gas data in a monitoring area in real time, and outputting first data in combination with obtained real-time operation data of a fire extinguishing system; the preprocessing module is used for preprocessing the first data to obtain to-be-analyzed data; the early warning module is used for performing feature extraction on the to-be-analyzed data to construct a first feature set, and selecting an early warning model from the model database to perform early warning analysis on the to-be-analyzed data to obtain a first result; and the control module is used for analyzing the first result, selecting a control strategy and a control instruction from a strategy-instruction database to control the fire extinguishing equipment, and optimizing the control strategy in combination with a preset optimization method. According to the invention, the fire protection area in the power plant can be monitored in real time, early warning analysis is carried out on the monitoring data, corresponding fire protection measures are taken in time, and the loss caused by a fire disaster is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of fire fighting, and in particular to a low-pressure carbon dioxide fire extinguishing automatic control system. Background Art

[0002] A fire extinguishing system in which carbon dioxide fire extinguishing agent is stored at a temperature of -18℃ to -20℃ is called a low-pressure carbon dioxide fire extinguishing system. It mainly uses a refrigeration system to reduce the storage pressure of the fire extinguishing agent to increase the storage capacity of the container. It is suitable for places where fires need to be extinguished quickly, effectively and cleanly, such as machine rooms, substations, computer rooms, etc.

[0003] At present, although the low-pressure carbon dioxide fire extinguishing system has advantages in many aspects, it also has some shortcomings. For example, if the release amount of carbon dioxide in the fire extinguishing area cannot be controlled, excessive release may cause suffocation of people in the fire extinguishing area, resulting in casualties. In addition, the low-pressure carbon dioxide fire extinguishing system often performs fire extinguishing operations in the fire area only after the fire occurs, and there is a certain lag, which may cause the fire to spread due to untimely fire extinguishing and expand the fire loss.

[0004] Therefore, the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system. Summary of the invention

[0005] The present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, which is used to monitor the fire prevention area in the power plant in real time, and through early warning analysis of the monitoring data, timely perform fine fire extinguishing operations on the fire area and the potential fire areas around the fire area, so as to achieve early detection, early treatment, early prevention, reduce the possibility of fire spread, and thus reduce the losses suffered by the power plant due to fire.

[0006] The present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, comprising:

[0007] A data monitoring module, used to obtain gas data in the monitoring area in real time through a plurality of preset monitoring devices arranged in the monitoring area, and output first data in combination with the obtained real-time operation data of the fire extinguishing system;

[0008] A preprocessing module, used for preprocessing the first data by a preset preprocessing method to obtain data to be analyzed;

[0009] An early warning module is used to extract features from the data to be analyzed, construct a first feature set, and select a matching early warning model from a model database based on the first feature set to perform early warning analysis on the data to be analyzed, to obtain a first result;

[0010] A control module is used to parse the first result, select matching control strategies and control instructions from a strategy-instruction database based on the parsed content, control corresponding fire extinguishing equipment based on the control strategies and control instructions, and optimize the control strategies in combination with a preset optimization method.

[0011] Preferably, the data monitoring module includes:

[0012] The location information acquisition submodule is used to obtain the location information of each fire zone in the monitoring area and obtain the fire zone location data;

[0013] The first monitoring submodule is used to obtain the gas data of each fire zone in real time through the preset monitoring equipment set in each fire zone in the monitoring area, and summarize the gas monitoring data;

[0014] The second monitoring submodule is used to obtain the operating data of each fire-fighting equipment in the low-pressure carbon dioxide fire extinguishing system in real time to obtain the system operating data;

[0015] The data summary submodule is used to obtain the first data through comprehensive output based on the fire zone location data, gas monitoring data and system operation data.

[0016] Preferably, the first monitoring submodule includes:

[0017] A demand acquisition unit is used to acquire the fire demand data of each fire zone in the monitoring area and summarize the regional demand information;

[0018] The equipment matching unit is used to match the preset monitoring equipment corresponding to each fire zone with the fire demand data of the fire zone and the preset demand-equipment comparison table, and construct a monitoring equipment list;

[0019] The data acquisition unit is used to acquire the gas data of each fire zone in real time based on each preset monitoring device in the monitoring device list, and summarize the gas monitoring data.

[0020] Preferably, the preprocessing module comprises:

[0021] an abnormal feature identification submodule, configured to extract features from the first data, and perform feature matching in an abnormal feature database based on the extracted features to obtain an abnormal feature set;

[0022] The preprocessing submodule is used to select a matching preprocessing method in a method database based on the abnormal feature set, and preprocess the first data based on the preprocessing method to obtain data to be analyzed.

[0023] Preferably, the preprocessing submodule includes:

[0024] A factor acquisition unit, used to acquire a matching factor matching each abnormal feature in the abnormal feature set in combination with a preset feature-factor comparison table;

[0025] A method matching unit, used for selecting a matching preprocessing method in a method database based on the matching factor;

[0026] A preprocessing unit is used to preprocess the first data based on the preprocessing method to obtain data to be analyzed.

[0027] Preferably, the early warning module includes:

[0028] A feature extraction submodule, used for extracting features from the data to be analyzed, and constructing a first feature set based on the extracted features;

[0029] A model matching submodule, configured to select a matching early warning model from a model database based on the first feature set and in combination with a preset feature-model mapping table;

[0030] A format conversion submodule, used to convert the data to be analyzed into data to be processed in a preset format in combination with the format requirement information of the early warning model;

[0031] A data verification submodule, used to verify the data to be processed, and output the data to be processed that meets the preset verification conditions as second data;

[0032] The early warning analysis submodule is used to perform early warning analysis on the second data through the early warning model to obtain a first result.

[0033] Preferably, the control module comprises:

[0034] An analysis submodule, used to analyze the first result and obtain a sub-result corresponding to each fire zone in the monitoring area;

[0035] A demand matching submodule, used for matching the fire demand data of each fire zone in the regional demand information with the corresponding sub-result, outputting the demand matching result of each fire zone, and summarizing to obtain a first matching result;

[0036] A level determination submodule, configured to obtain the fire protection level of each fire protection zone based on the first matching result and in combination with a preset result-level mapping table, and output a level ranking table based on the priority corresponding to the fire protection level;

[0037] A model building submodule is used to build a three-dimensional fire model corresponding to the monitoring area by combining the fire zone location data and the operation data of the fire-fighting equipment installed in the corresponding area;

[0038] An information labeling submodule, for labeling the fire protection level of each fire protection zone in the three-dimensional fire protection model based on the level ranking table, and outputting a fire protection distribution map;

[0039] A strategy matching submodule, for selecting a matching control strategy from a strategy-instruction database based on the sub-results and the fire distribution map;

[0040] An instruction acquisition submodule, used for selecting corresponding control instructions from the strategy-instruction database based on the control strategy;

[0041] An instruction execution submodule is used to control the corresponding fire extinguishing equipment in the fire extinguishing system based on the control strategy and the control instruction, perform fire extinguishing operations on the corresponding areas in the fire protection zone where there is a fire, and perform pre-fire extinguishing operations on the fire protection zone where there is a potential fire;

[0042] The process data monitoring submodule is used to obtain the environmental data of each fire zone and the operation data of the fire extinguishing system in real time during the execution of the control instruction, and output the process data;

[0043] An optimization analysis submodule, used to optimize and analyze the process data in combination with preset optimization indicators, and select a matching preset optimization method from a method database based on the optimization analysis results;

[0044] The strategy optimization submodule is used to optimize the control strategy based on the preset optimization method.

[0045] Preferably, the optimization analysis submodule includes:

[0046] A first parsing unit, configured to parse the process data to obtain first process data corresponding to the environmental change data in the fire zone corresponding to the control instruction;

[0047] A second parsing unit is used to parse the process data, obtain the operation process data of the corresponding fire-fighting equipment in the fire protection zone corresponding to the control instruction in the fire extinguishing system, and output second process data;

[0048] A feature extraction unit, used to extract features from the first process data and the second process data, and construct a second feature set and a third feature set respectively;

[0049] An indicator acquisition unit, configured to select, from an indicator database, first indicators corresponding to each feature in the second feature set and second indicators corresponding to each feature in the third feature set based on a preset feature-indicator comparison table, and construct a first indicator set and a second indicator set respectively;

[0050] an optimization analysis unit, configured to perform optimization analysis on the first process data based on the first indicator set, and at the same time, perform optimization analysis on the second process data based on the second indicator set, and perform comprehensive analysis on the analysis results to obtain an optimization analysis result;

[0051]

[0052] Where r represents the optimization analysis result; σ1 represents the correlation coefficient between the first indicator set and the second indicator set; σ2 represents the correlation coefficient between the fire area and the potential fire area; ε1 represents the calculation weight corresponding to the first process data; n represents the total number of the first indicators in the first indicator set; p i1 represents the environmental parameter value under the first index of the i-th fire area; t i1 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the fire area; L i1 represents the evaluation coefficient corresponding to the first index of the i-th fire area; p i2 represents the environmental parameter value under the first index of the i-th potential fire area; t i2 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the potential fire area; L i2 represents the evaluation coefficient corresponding to the i-th first indicator of the potential fire area; ε2 represents the calculation weight corresponding to the second process data; m represents the total number of second indicators in the second indicator set; p j1 represents the equipment operating parameter value under the jth second index in the fire area; t j1 represents the expected target value of the operating parameter corresponding to the jth second indicator in the fire area; L j1 represents the evaluation coefficient corresponding to the jth first indicator of the fire area; p j2 represents the equipment operating parameter value under the jth second index in the potential fire area; t j2 represents the expected target value of the operating parameter corresponding to the jth second indicator in the potential fire area; L j2 represents the evaluation coefficient corresponding to the jth first indicator of the potential fire area;

[0053] The method matching unit is used to select a matching preset optimization method in a method database based on the optimization analysis result and in combination with a preset result-method comparison table.

[0054] The present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, which realizes automatic monitoring and control of the fire extinguishing system by combining the gas data in the monitoring area and the real-time operation data of the fire extinguishing system with the early warning model and the control strategy, and finally optimizes the control strategy through the optimization method, thereby realizing the intelligent control of the system. The present invention can realize the functions of real-time monitoring and early warning, intelligent control, and optimization strategy, thereby improving the efficiency and reliability of the fire extinguishing system. Through the application of the early warning model and the optimization method, the present invention can respond to fire risks more accurately, improve the fire extinguishing effect, and reduce the possibility of misjudgment of the fire situation due to human factors and causing the fire to spread, thereby ensuring the safety of personnel and equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0056] Figure 1 It is a schematic diagram of the framework of a low-pressure carbon dioxide fire extinguishing automatic control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, comprising:

[0059] A data monitoring module, used to obtain gas data in the monitoring area in real time through a plurality of preset monitoring devices arranged in the monitoring area, and output first data in combination with the obtained real-time operation data of the fire extinguishing system;

[0060] A preprocessing module, used to preprocess the first data by a preset preprocessing method to obtain data to be analyzed;

[0061] The early warning module is used to extract features of the data to be analyzed, construct a first feature set, and select a matching early warning model from the model database based on the first feature set to perform early warning analysis on the data to be analyzed, thereby obtaining a first result;

[0062] The control module is used to parse the first result, select matching control strategies and control instructions from the strategy-instruction database based on the parsed content, control the corresponding fire extinguishing equipment based on the control strategies and control instructions, and optimize the control strategies in combination with a preset optimization method.

[0063] In this embodiment, monitoring area: refers to the area in the power plant that is monitored;

[0064] In this embodiment, the preset monitoring device: a device preset for monitoring gas data, such as a carbon dioxide concentration sensor, etc.;

[0065] In this embodiment, gas data: gas-related data monitored in the monitoring area, such as carbon dioxide concentration, temperature, etc.;

[0066] In this embodiment, real-time operation data: that is, the current operation status and data of each fire extinguishing device in the fire extinguishing system;

[0067] In this embodiment, the first data: that is, data obtained according to the gas data and the real-time operation data;

[0068] In this embodiment, the preset preprocessing method: a preset method for processing the first data, including but not limited to data filtering, correction or other processing methods;

[0069] In this embodiment, the data to be analyzed: that is, the data obtained after preprocessing;

[0070] In this embodiment, the first feature set: a feature set extracted from the data to be analyzed;

[0071] In this embodiment, the early warning model: a model used for early warning analysis of the data to be analyzed, which is a model constructed based on machine learning or statistical methods;

[0072] In this embodiment, the first result: that is, the early warning analysis result;

[0073] In this embodiment, the strategy-instruction database: a database storing control strategies and control instructions for different fire situations;

[0074] In this embodiment, the control strategy: a strategy for controlling the fire extinguishing equipment selected according to the first result;

[0075] In this embodiment, control instructions: specific control instructions used to control the operation of each fire extinguishing device in the fire extinguishing system;

[0076] In this embodiment, the preset optimization method is a pre-set method for optimizing the control strategy, which may include algorithm optimization, parameter adjustment, etc.

[0077] The implementation principle and beneficial effects of this embodiment: The present invention realizes automatic monitoring and control of the fire extinguishing system by combining the gas data in the monitoring area and the real-time operation data of the fire extinguishing system with the early warning model and the control strategy, and finally optimizes the control strategy through the optimization method, thereby realizing intelligent control of the system. The present invention can realize the functions of real-time monitoring and early warning, intelligent control, and optimization strategy, thereby improving the efficiency and reliability of the fire extinguishing system. Through the application of early warning models and optimization methods, the present invention can respond to fire risks more accurately, improve fire extinguishing effects, and reduce the possibility of fire spread caused by misjudgment of fire conditions due to human factors, thereby ensuring the safety of personnel and equipment.

[0078] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, a data monitoring module, comprising:

[0079] The location information acquisition submodule is used to obtain the location information of each fire zone in the monitoring area and obtain the fire zone location data;

[0080] The first monitoring submodule is used to obtain the gas data of each fire zone in real time through the preset monitoring equipment set in each fire zone in the monitoring area, and summarize the gas monitoring data;

[0081] The second monitoring submodule is used to obtain the operating data of each fire-fighting equipment in the low-pressure carbon dioxide fire extinguishing system in real time to obtain the system operating data;

[0082] The data summary submodule is used to obtain the first data through comprehensive output based on the fire zone location data, gas monitoring data and system operation data.

[0083] In this embodiment, fire prevention area refers to each specific area divided within the monitoring area for monitoring and controlling fire risks;

[0084] In this embodiment, the location information refers to the location coordinates or location description of the fire zone, which is used to determine the specific location of each fire zone in the monitoring area;

[0085] In this embodiment, the fire zone location data is obtained by summarizing the location data of each fire zone acquired by the location information acquisition submodule, and is used to identify the location of each fire zone;

[0086] In this embodiment, gas monitoring data: gas data of each fire zone acquired in real time by the first monitoring submodule, including gas concentration, temperature and other related data;

[0087] In this embodiment, the system operation data refers to the operation data of each fire-fighting equipment in the low-pressure carbon dioxide fire-extinguishing system acquired in real time by the second monitoring submodule, including information such as equipment status and working status.

[0088] The implementation principle and beneficial effects of this embodiment are as follows: the location information of the fire zone is obtained through the location information acquisition submodule, the first monitoring submodule obtains the gas data of the fire zone in real time, the second monitoring submodule obtains the operation data of the fire-fighting equipment in the system in real time, and then the data summary submodule combines these data and comprehensively outputs the first data to achieve comprehensive monitoring and control of the fire risk in the monitoring area. The present invention can monitor the gas data and system operation data of different fire zones in the power plant in real time, which is helpful to timely discover potential fire risks and improve the response speed and accuracy of the fire extinguishing system. Then, by comprehensively analyzing the data of each fire zone, the system can more accurately judge the degree of fire risk, thereby taking corresponding control measures, improving the efficiency and reliability of the fire extinguishing system, and ensuring the safety of personnel and equipment in the monitoring area.

[0089] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, wherein the first monitoring submodule comprises:

[0090] A demand acquisition unit is used to acquire the fire demand data of each fire zone in the monitoring area and summarize the regional demand information;

[0091] The equipment matching unit is used to match the preset monitoring equipment corresponding to each fire zone with the fire demand data of the fire zone and the preset demand-equipment comparison table, and construct a monitoring equipment list;

[0092] The data acquisition unit is used to acquire the gas data of each fire zone in real time based on each preset monitoring device in the monitoring device list, and summarize the gas monitoring data.

[0093] In this embodiment, fire protection demand data refers to the fire protection demand information of each fire zone in the monitoring area, including the fire risk level, special demand and other data of each fire zone;

[0094] In this embodiment, the regional demand information: the fire demand information of the entire monitoring area obtained by the demand acquisition unit, which is used to represent the comprehensive fire demand situation of the entire monitoring area;

[0095] In this embodiment, the preset demand-equipment comparison table is used to record the corresponding relationship between the fire protection demand of each fire protection zone and the preset monitoring equipment, that is, to determine the monitoring equipment to be used according to the fire protection demand;

[0096] In this embodiment, the monitoring equipment list: the monitoring equipment list obtained by the equipment matching unit in combination with the fire demand data and the preset demand-equipment comparison table, is used to represent the list of monitoring equipment required for each fire zone.

[0097] The implementation principle and beneficial effects of this embodiment: The present invention obtains the fire demand data of each fire zone through the demand acquisition unit, summarizes the regional demand information, and then obtains the monitoring equipment list through the equipment matching unit, and then obtains the gas data of each fire zone in real time through the data acquisition unit, summarizes the gas monitoring data, thereby realizing the gas monitoring of each fire zone. The present invention matches the preset monitoring equipment according to the fire demand, and can more accurately monitor the gas data of each fire zone, improve the accuracy and effectiveness of monitoring. At the same time, the monitoring equipment list is customized according to the fire demand, which can not only better meet the monitoring needs of different fire zones and improve the flexibility and applicability of the system, but also help the system better adapt to the characteristics of different monitoring areas and improve the response speed and sensitivity of the fire extinguishing system.

[0098] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, a pre-processing module, comprising:

[0099] An abnormal feature identification submodule, used to extract features from the first data, and perform feature matching in an abnormal feature database based on the extracted features to obtain an abnormal feature set;

[0100] The preprocessing submodule is used to select a matching preprocessing method in a method database based on the abnormal feature set, and preprocess the first data based on the preprocessing method to obtain data to be analyzed.

[0101] In this embodiment, the abnormal feature database: a database storing various possible abnormal features, used to match the features extracted from the first data to identify possible abnormal situations, so as to pre-process the first data later;

[0102] In this embodiment, abnormal feature set: an abnormal feature set obtained after extraction and matching by the abnormal feature recognition submodule, used to represent abnormal features that may exist in the first data;

[0103] In this embodiment, the method database: a database storing various preprocessing methods, used to select a matching preprocessing method according to the abnormal feature set to further process the first data;

[0104] In this embodiment, preprocessing: a data processing method used to improve the data quality of the first data and provide a convenient data processing method for subsequent data analysis, including operations such as data cleaning, data conversion, and data normalization.

[0105] The implementation principle and beneficial effects of this embodiment are as follows: the first data is feature extracted through the abnormal feature recognition submodule, and feature matching is performed in the abnormal feature database to obtain an abnormal feature set, and then a matching preprocessing method is selected in the method database, and the first data is preprocessed based on these preprocessing methods to obtain the data to be analyzed, providing a more accurate data basis for subsequent analysis. The present invention can timely discover and process abnormal situations in the first data through abnormal feature recognition and preprocessing, improve the quality and reliability of the data, and then eliminate noise, missing values ​​or abnormal values ​​in the data by selecting the obtained preprocessing method, making the data more standardized and easy to analyze, which helps to improve the accuracy and effectiveness of subsequent data analysis.

[0106] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, a preprocessing submodule, including:

[0107] A factor acquisition unit, used to acquire a matching factor matching each abnormal feature in the abnormal feature set in combination with a preset feature-factor comparison table;

[0108] A method matching unit, used for selecting a matching preprocessing method in a method database based on a matching factor;

[0109] The preprocessing unit is used to preprocess the first data based on the preprocessing method to obtain data to be analyzed.

[0110] In this embodiment, a feature-factor comparison table is preset: a table storing the correspondence between abnormal features and matching factors, and a corresponding matching factor can be obtained according to each abnormal feature in the input abnormal feature set, so as to facilitate the subsequent method selection;

[0111] In this embodiment, the matching factor is a factor corresponding to each abnormal feature in the abnormal feature set, which can help the system select an adapted preprocessing method for different abnormal features.

[0112] The implementation principle and beneficial effects of this embodiment: The present invention selects a matching preprocessing method in a method database according to the obtained matching factor, and processes the first data by the preprocessing method to obtain the data to be analyzed. The present invention can accurately match the corresponding factors and preprocessing methods according to the specific abnormal features in the abnormal feature set, thereby improving the accuracy and efficiency of data processing, so as to better adapt to the processing requirements of different abnormal situations, optimize the data processing process, and provide a more reliable data basis for subsequent data analysis.

[0113] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system and an early warning module, comprising:

[0114] A feature extraction submodule is used to extract features from the data to be analyzed and obtain a first feature set based on the extracted features;

[0115] A model matching submodule, used to select a matching early warning model in the model database based on the first feature set and in combination with a preset feature-model mapping table;

[0116] The format conversion submodule is used to convert the data to be analyzed into the data to be processed in a preset format according to the format requirement information of the early warning model;

[0117] A data verification submodule, used to verify the data to be processed, and output the data to be processed that meets the preset verification conditions as the second data;

[0118] The early warning analysis submodule is used to perform early warning analysis on the second data through the early warning model to obtain a first result.

[0119] In this embodiment, the first feature set is a feature set obtained by extracting features from the data to be analyzed by the feature extraction submodule;

[0120] In this embodiment, the preset feature-model mapping table: a table storing the mapping relationship between data features and early warning models, used to select an early warning model matching the first feature set in the model database;

[0121] In this embodiment, the model database: a database storing various data analysis models, including but not limited to prediction models, early warning models, etc.;

[0122] In this embodiment, the format requirement information: that is, the format requirement information of the early warning model for the data to be processed;

[0123] In this embodiment, the preset format is the data format required by the early warning model. The format conversion submodule needs to convert the data to be analyzed into data that conforms to the preset format and then input it into the early warning model for early warning analysis.

[0124] In this embodiment, data verification: an operation of verifying and analyzing the integrity and accuracy of the data to be analyzed to ensure the accuracy of subsequent data analysis;

[0125] In this embodiment, preset verification conditions: preset data verification conditions, through which the data to be processed that meet the conditions can be screened out, reducing the interference of invalid or irrelevant data on subsequent data analysis;

[0126] In this embodiment, the second data refers to the data to be processed that meets the preset verification conditions.

[0127] The implementation principle and beneficial effects of this embodiment: Through the steps of feature extraction, model matching, data conversion, verification and early warning analysis, the present invention can comprehensively process and analyze data and provide timely and effective early warning information. At the same time, it can help the system to quickly and accurately identify potential dangerous situations, improve the response speed and accuracy of the automatic control system, thereby enhancing the overall safety and reliability of the fire extinguishing system.

[0128] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, a control module, including:

[0129] An analysis submodule, used to analyze the first result and obtain a sub-result corresponding to each fire zone in the monitoring area;

[0130] The demand matching submodule is used to match the fire demand data of each fire zone in the regional demand information with the corresponding sub-results, output the demand matching results of each fire zone, and summarize them to obtain the first matching result;

[0131] A level determination submodule, for obtaining the fire protection level of each fire zone based on the first matching result and in combination with a preset result-level mapping table, and outputting a level ranking table based on the priority corresponding to the fire protection level;

[0132] The model building submodule is used to build a three-dimensional fire model corresponding to the monitoring area by combining the fire zone location data and the operation data of the fire-fighting equipment installed in the corresponding area;

[0133] The information labeling submodule is used to label the fire protection level of each fire protection zone in the fire protection three-dimensional model based on the level ranking table and output the fire protection distribution map;

[0134] A strategy matching submodule is used to select a matching control strategy from the strategy-instruction database based on the sub-results and the fire distribution map;

[0135] The instruction acquisition submodule is used to select and obtain corresponding control instructions from the strategy-instruction database based on the control strategy;

[0136] The instruction execution submodule is used to control the corresponding fire extinguishing equipment in the fire extinguishing system based on the control strategy and control instructions, perform fire extinguishing operations on the corresponding areas in the fire protection zone where there is a fire, and perform pre-fire extinguishing operations on the fire protection zone where there is a potential fire;

[0137] The process data monitoring submodule is used to obtain the environmental data of each fire zone and the operation data of the fire extinguishing system in real time during the execution of the control instructions, and output the process data;

[0138] The optimization analysis submodule is used to optimize and analyze the process data in combination with the preset optimization index, and select a matching preset optimization method from the method database based on the optimization analysis result;

[0139] The strategy optimization submodule is used to optimize the control strategy based on the preset optimization method.

[0140] In this embodiment, sub-results: that is, the content corresponding to each fire zone in the analysis result, which is used for subsequent demand matching and control decision-making;

[0141] In this embodiment, the demand matching result is the result obtained by matching the fire demand data of each fire zone in the regional demand information with the corresponding sub-result;

[0142] In this embodiment, the first matching result: a result obtained by summarizing the matching results of the requirements corresponding to each fire zone;

[0143] In this embodiment, the preset result-level mapping table: a table storing a mapping relationship between the first matching result and the fire protection level, used to obtain the fire protection level of each fire protection zone based on the first matching result;

[0144] In this embodiment, the fire protection level is the level information used to characterize the importance of each fire protection zone in the fire protection process;

[0145] In this embodiment, the ranking table: based on the priority corresponding to the fire protection level, a ranking table corresponding to the fire protection level of each fire protection zone is output. The higher the level, the more important the fire protection zone is, and the higher the monitoring accuracy and fire extinguishing priority are generally;

[0146] In this embodiment, the fire protection three-dimensional model: that is, the three-dimensional model is established by combining the fire protection zone location data and the fire protection equipment operation data, so that personnel can intuitively observe the real-time status of each fire protection zone in the monitoring area;

[0147] In this embodiment, the fire distribution map is a distribution map obtained by marking the fire level of the three-dimensional fire model, which is used to characterize the fire level corresponding to each fire zone, so as to facilitate intuitive observation of the fire status and fire situation of each fire zone when a fire occurs;

[0148] In this embodiment, the pre-fire extinguishing operation is a pre-set fire extinguishing operation performed in a fire zone where a potential fire exists, so as to reduce the risk of fire spreading and causing a fire in the fire zone surrounding the fire zone where the fire exists, such as firewall isolation, temperature reduction, etc.;

[0149] In this embodiment, environmental data refers to environmental change data in each fire zone during the execution of the control instruction, such as temperature, humidity, gas concentration, etc.;

[0150] In this embodiment, process data refers to the operational change data of the firefighting equipment in each fire zone during the execution of the control instruction, for example, the opening data of various valves, the flow data of the pipeline, and the usage data of carbon dioxide in the storage tank, etc.;

[0151] In this embodiment, the preset optimization index is an evaluation index used for optimizing the process data, for example, carbon dioxide utilization rate, temperature change rate, temperature change amount, etc.;

[0152] In this embodiment, the optimization analysis result refers to the optimization result obtained after analyzing the process data based on the preset optimization index.

[0153] The implementation principle and beneficial effects of this embodiment: The system realizes comprehensive control and optimization of the fire extinguishing system through the collaborative work of sub-modules such as analysis, demand matching, level determination, model building, information labeling, strategy matching, instruction acquisition, instruction execution, process data monitoring, optimization analysis and strategy optimization. The present invention can improve the response speed and flexibility of the fire extinguishing system, perform intelligent fire control and optimization according to real-time data and demand information, improve the efficiency and safety of the fire extinguishing system, and at the same time, through real-time monitoring and optimization analysis, the system can timely discover problems and take corresponding measures, thereby improving the overall fire extinguishing effect and system reliability.

[0154] An embodiment of the present invention provides a low-pressure carbon dioxide fire extinguishing automatic control system, an optimization analysis submodule, including:

[0155] A first parsing unit, used to parse the process data to obtain first process data corresponding to the environmental change data in the fire zone corresponding to the control instruction;

[0156] A second parsing unit is used to parse the process data, obtain the operation process data of the corresponding fire-fighting equipment in the fire protection zone corresponding to the control instruction in the fire extinguishing system, and output the second process data;

[0157] A feature extraction unit, used to extract features from the first process data and the second process data, and construct a second feature set and a third feature set respectively;

[0158] An indicator acquisition unit is used to select, based on a preset feature-indicator comparison table, first indicators corresponding to each feature in the second feature set and second indicators corresponding to each feature in the third feature set from the indicator database, and respectively construct a first indicator set and a second indicator set;

[0159] An optimization analysis unit, configured to perform optimization analysis on the first process data based on the first indicator set, and at the same time, perform optimization analysis on the second process data based on the second indicator set, and perform comprehensive analysis on the analysis results to obtain an optimization analysis result;

[0160]

[0161] Where r represents the optimization analysis result; σ1 represents the correlation coefficient between the first indicator set and the second indicator set; σ2 represents the correlation coefficient between the fire area and the potential fire area; ε1 represents the calculation weight corresponding to the first process data; n represents the total number of the first indicator in the first indicator set; p i1 represents the environmental parameter value under the first index of the i-th fire area; t i1 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the fire area; L i1 represents the evaluation coefficient corresponding to the first index of the i-th fire area; p i2 represents the environmental parameter value under the first index of the i-th potential fire area; t i2 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the potential fire area; L i2 represents the evaluation coefficient corresponding to the i-th first indicator of the potential fire area; ε2 represents the calculation weight corresponding to the second process data; m represents the total number of second indicators in the second indicator set; p j1 represents the equipment operating parameter value under the jth second index in the fire area; t j1 represents the expected target value of the operating parameter corresponding to the jth second indicator in the fire area; L j1 represents the evaluation coefficient corresponding to the jth first indicator of the fire area; p j2 represents the equipment operating parameter value under the jth second index in the potential fire area; t j2 represents the expected target value of the operating parameter corresponding to the jth second indicator in the potential fire area; L j2 represents the evaluation coefficient corresponding to the jth first indicator of the potential fire area;

[0162] The method matching unit is used to select a matching preset optimization method in the method database based on the optimization analysis result and in combination with the preset result-method comparison table.

[0163] In this embodiment, the first process data: that is, the environmental change data in the fire zone corresponding to the execution of the control instruction;

[0164] In this embodiment, the second process data: namely, the operation process data of the fire-fighting equipment in the fire protection zone corresponding to the execution of the control instruction;

[0165] In this embodiment, the second feature set: a feature set extracted from the first process data;

[0166] In this embodiment, the third feature set: a feature set extracted from the second process data;

[0167] In this embodiment, the preset feature-indicator comparison table: a comparison table containing mapping relationships between features and indicators, which is preset and used to match corresponding indicators according to input data features;

[0168] In this embodiment, the first indicator: that is, the optimization indicator corresponding to the first process data;

[0169] In this embodiment, the second index: that is, the optimization index corresponding to the second process data;

[0170] In this embodiment, the first indicator set: that is, the indicator set constructed according to the first indicator;

[0171] In this embodiment, the second indicator set: that is, the indicator set constructed according to the second indicator;

[0172] In this embodiment, the preset result-method comparison table, ie, a table of comparison between optimization analysis results and preset optimization methods, is preset.

[0173] The implementation principle and beneficial effects of this embodiment: The present invention conducts in-depth analysis and optimization of process data through the synergistic effect of units such as analysis, feature extraction, index acquisition, optimization analysis and method matching, extracts features based on environmental change data and fire equipment operation process data, and obtains corresponding indicators based on a preset index comparison table, obtains comprehensive optimization results through optimization analysis, and then selects appropriate optimization methods based on the preset result-method comparison table. The present invention can improve the intelligence and efficiency of the fire extinguishing system. Through in-depth analysis and optimization of process data, it can better understand environmental changes and the operation of fire equipment, thereby improving the response speed and accuracy of the fire extinguishing system. At the same time, the optimization analysis results can provide the system with more effective control strategies and optimization solutions, further improving the performance and reliability of the system, and ensuring that the fire extinguishing system can respond quickly and accurately and effectively extinguish fires when fires occur.

[0174] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A low-pressure carbon dioxide fire extinguishing automatic control system, characterized in that: include: A data monitoring module, used to obtain gas data in the monitoring area in real time through a plurality of preset monitoring devices arranged in the monitoring area, and output first data in combination with the obtained real-time operation data of the fire extinguishing system; A preprocessing module, used for preprocessing the first data by a preset preprocessing method to obtain data to be analyzed; An early warning module is used to extract features from the data to be analyzed, construct a first feature set, and select a matching early warning model from a model database based on the first feature set to perform early warning analysis on the data to be analyzed, to obtain a first result; A control module is used to parse the first result, select matching control strategies and control instructions from a strategy-instruction database based on the parsed content, control corresponding fire extinguishing equipment based on the control strategies and control instructions, and optimize the control strategies in combination with a preset optimization method.

2. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 1, characterized in that: The data monitoring module comprises: The location information acquisition submodule is used to obtain the location information of each fire zone in the monitoring area and obtain the fire zone location data; The first monitoring submodule is used to obtain the gas data of each fire zone in real time through the preset monitoring equipment set in each fire zone in the monitoring area, and summarize the gas monitoring data; The second monitoring submodule is used to obtain the operating data of each fire-fighting equipment in the low-pressure carbon dioxide fire extinguishing system in real time to obtain the system operating data; The data summary submodule is used to obtain the first data through comprehensive output based on the fire zone location data, gas monitoring data and system operation data.

3. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 2, characterized in that: The first monitoring submodule includes: A demand acquisition unit is used to acquire the fire demand data of each fire zone in the monitoring area and summarize the regional demand information; The equipment matching unit is used to match the preset monitoring equipment corresponding to each fire zone with the fire demand data of the fire zone and the preset demand-equipment comparison table, and construct a monitoring equipment list; The data acquisition unit is used to acquire the gas data of each fire zone in real time based on each preset monitoring device in the monitoring device list, and summarize the gas monitoring data.

4. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 1, characterized in that: The preprocessing module comprises: an abnormal feature identification submodule, configured to extract features from the first data, and perform feature matching in an abnormal feature database based on the extracted features to obtain an abnormal feature set; The preprocessing submodule is used to select a matching preprocessing method in a method database based on the abnormal feature set, and preprocess the first data based on the preprocessing method to obtain data to be analyzed.

5. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 4, characterized in that: The preprocessing submodule comprises: A factor acquisition unit, used to acquire a matching factor matching each abnormal feature in the abnormal feature set in combination with a preset feature-factor comparison table; A method matching unit, used for selecting a matching preprocessing method in a method database based on the matching factor; A preprocessing unit is used to preprocess the first data based on the preprocessing method to obtain data to be analyzed.

6. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 1, characterized in that: The early warning module comprises: A feature extraction submodule, used for extracting features from the data to be analyzed, and constructing a first feature set based on the extracted features; A model matching submodule, configured to select a matching early warning model from a model database based on the first feature set and in combination with a preset feature-model mapping table; A format conversion submodule, used to convert the data to be analyzed into data to be processed in a preset format in combination with the format requirement information of the early warning model; A data verification submodule, used to verify the data to be processed, and output the data to be processed that meets the preset verification conditions as second data; The early warning analysis submodule is used to perform early warning analysis on the second data through the early warning model to obtain a first result.

7. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 3, characterized in that: The control module comprises: An analysis submodule, used to analyze the first result and obtain a sub-result corresponding to each fire zone in the monitoring area; A demand matching submodule, used for matching the fire demand data of each fire zone in the regional demand information with the corresponding sub-result, outputting the demand matching result of each fire zone, and summarizing to obtain a first matching result; A level determination submodule, configured to obtain the fire protection level of each fire protection zone based on the first matching result and in combination with a preset result-level mapping table, and output a level ranking table based on the priority corresponding to the fire protection level; A model building submodule is used to build a three-dimensional fire model corresponding to the monitoring area by combining the fire zone location data and the operation data of the fire fighting equipment installed in the corresponding area; An information labeling submodule, for labeling the fire protection level of each fire protection zone in the three-dimensional fire protection model based on the level ranking table, and outputting a fire protection distribution map; A strategy matching submodule, for selecting a matching control strategy from a strategy-instruction database based on the sub-results and the fire distribution map; An instruction acquisition submodule, used for selecting corresponding control instructions from the strategy-instruction database based on the control strategy; An instruction execution submodule is used to control the corresponding fire extinguishing equipment in the fire extinguishing system based on the control strategy and the control instruction, perform fire extinguishing operations on the corresponding areas in the fire protection zone where there is a fire, and perform pre-fire extinguishing operations on the fire protection zone where there is a potential fire; The process data monitoring submodule is used to obtain the environmental data of each fire zone and the operation data of the fire extinguishing system in real time during the execution of the control instruction, and output the process data; An optimization analysis submodule, used to optimize and analyze the process data in combination with preset optimization indicators, and select a matching preset optimization method from a method database based on the optimization analysis results; The strategy optimization submodule is used to optimize the control strategy based on the preset optimization method.

8. A low-pressure carbon dioxide fire extinguishing automatic control system according to claim 7, characterized in that: The optimization analysis submodule includes: A first parsing unit, used to parse the process data to obtain first process data corresponding to the environmental change data in the fire zone corresponding to the control instruction; A second parsing unit is used to parse the process data, obtain the operation process data of the corresponding fire-fighting equipment in the fire protection zone corresponding to the control instruction in the fire extinguishing system, and output second process data; A feature extraction unit, used to extract features from the first process data and the second process data, and construct a second feature set and a third feature set respectively; An indicator acquisition unit, configured to select, from an indicator database, first indicators corresponding to each feature in the second feature set and second indicators corresponding to each feature in the third feature set based on a preset feature-indicator comparison table, and construct a first indicator set and a second indicator set respectively; an optimization analysis unit, configured to perform optimization analysis on the first process data based on the first indicator set, and at the same time, perform optimization analysis on the second process data based on the second indicator set, and perform comprehensive analysis on the analysis results to obtain an optimization analysis result; Where r represents the optimization analysis result; σ1 represents the correlation coefficient between the first indicator set and the second indicator set; σ2 represents the correlation coefficient between the fire area and the potential fire area; ε1 represents the calculation weight corresponding to the first process data; n represents the total number of the first indicators in the first indicator set; p i1 represents the environmental parameter value under the first index of the i-th fire area; t i1 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the fire area; L i1 represents the evaluation coefficient corresponding to the first index of the i-th fire area; p i2 represents the environmental parameter value under the first index of the i-th potential fire area; t i2 represents the expected target value of the environmental parameter corresponding to the i-th first indicator in the potential fire area; L i2 represents the evaluation coefficient corresponding to the i-th first indicator of the potential fire area; ε2 represents the calculation weight corresponding to the second process data; m represents the total number of second indicators in the second indicator set; p j1 represents the equipment operating parameter value under the jth second index in the fire area; t j1 represents the expected target value of the operating parameter corresponding to the jth second indicator in the fire area; L j1 represents the evaluation coefficient corresponding to the jth first indicator of the fire area; pj2 represents the equipment operating parameter value under the jth second indicator in the potential fire area; t j2 represents the expected target value of the operating parameter corresponding to the jth second indicator in the potential fire area; L j2 represents the evaluation coefficient corresponding to the jth first indicator of the potential fire area; The method matching unit is used to select a matching preset optimization method in a method database based on the optimization analysis result and in combination with a preset result-method comparison table.

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