CN115187069A - Fire safety system evaluation regulation and control system and method - Google Patents
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Abstract
The application discloses a fire safety system evaluation regulation and control system and a method. According to the invention, by using the technical means of big data image analysis, semantic analysis, intelligent evaluation and the like, a uniform and transparent information intercommunication interface is formed between the relevant units and the fire service organization, comprehensive, automatic, normalized and sustainable intelligent analysis and evaluation are carried out aiming at the actual operation state of the fire safety system of the relevant units, and regulation and control intervention are carried out in time, so that a perfect fire safety system is formed, and the relevant units are ensured to fulfill fire safety duties.
Description
Technical Field
The application relates to the technical field of fire safety system management, in particular to a fire safety system evaluation regulation system and a fire safety system evaluation regulation method.
Background
The fire safety is related to the life and property safety of the masses, and for any unit, the construction of a fire safety system is a central place. In recent years, with innovation of a fire safety related management system, main responsibilities of fire safety start to migrate to the side of an owner unit, and the initiative of the owner unit on fire safety construction is strengthened through responsibility transfer; meanwhile, a professional fire service organization provides support for a fire safety system of a business unit.
With the adoption of the method as a power, more and more units begin to construct a software and hardware framework for fire safety through informatization and intellectualization technical means such as the Internet of things, big data, cloud platforms and artificial intelligence. However, the existing fire safety architecture still focuses on the aspect of "things", for example, an automatic detection system for various fires is additionally installed, an alarm and emergency communication system is provided, and a fire hydrant, a water spray pipeline, a foam fire extinguisher and the like with an automatic function are arranged.
However, there are a number of cases in fire safety practice that show that, despite the large investment in construction and maintenance in these areas, they have not finally achieved the effects of disaster prevention and reduction. For example, in the aspect of fire safety, many units have the phenomena that the efficiency of the units cannot be guaranteed due to the fact that software and hardware facilities are complete, potential troubleshooting hazards cannot be found due to data detection and safety inspection, and the units cannot respond quickly and effectively due to the fact that an alarm can be given. This indicates that the relevant units lack the effective means of normalization at the level of responsibility of fire safety. On the other hand, a fault also exists between the fire service organization and the related units, so that accurate and timely state information of the owner units in the aspect of fire safety cannot be fully mastered, and services in the aspects of evaluation, detection, supervision, training and the like cannot be pertinently developed.
The reason is that although the relevant units establish a software and hardware architecture for fire safety on the aspect of 'object', a system mechanism cannot be further established on the aspects and links of detection and maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and object management and control, emergency plans, drill training and the like, and a uniform and transparent interface is not established with a fire service organization, so that a reliable fire safety system cannot be formed.
Disclosure of Invention
Object of the application
In view of the above problems, the present invention provides a fire safety system evaluation and control system and method. The invention utilizes the technical means of big data analysis image, semantic analysis, intelligent evaluation and the like to form a uniform and transparent information intercommunication interface between related units and the fire service organization, carries out comprehensive, automatic, normalized and sustainable intelligent analysis and evaluation aiming at the actual running state of the fire safety system of the related units, and carries out regulation and control intervention in time, thereby forming a perfect fire safety system and ensuring that the related units can fulfill the fire safety duty.
Disclosure of the invention
The invention provides a fire safety system evaluation regulation and control system, which is characterized by comprising the following components: the system comprises an equipment internet of things acquisition end, a fire-fighting main unit user end, a fire-fighting safety data center and a fire-fighting service mechanism end;
the equipment internet of things acquisition end is used for acquiring fire protection detection data and fire protection equipment state data through an equipment internet of things deployed by a fire protection main body unit and providing the acquired data to a fire protection main body unit user end, a fire protection service mechanism end and a fire protection safety data center;
the user side of the fire-fighting main body unit is used for the fire-fighting main body unit to generate fire-fighting safety mechanism information including detection maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plans and drill training, and the fire-fighting safety mechanism information is uploaded to the fire-fighting safety data center and the fire-fighting service institution side;
the fire safety data center is used for storing basic data, building space data, fire detection data, fire facility state data and fire safety mechanism information related to a fire main body unit, and the basic data, the building space data, the fire detection data, the fire facility state data and the fire safety mechanism information are called by the fire service institution; the evaluation analysis data and the regulation and control feedback data related to the fire-fighting main body unit are obtained and stored from the fire-fighting service institution end;
the fire service mechanism side is used for accessing fire detection data and fire fighting equipment state data of the equipment internet of things acquisition side, receiving fire safety mechanism information uploaded by the user side of the fire main unit, and calling fire main unit related data stored in the fire safety data center; based on the data and the information, carrying out multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and carrying out regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
Preferably, the fire service end includes: the system comprises a fire-fighting main body unit portrait unit, a multi-dimensional comprehensive analysis unit and a fire-fighting main body regulation and control feedback unit;
the fire-fighting main unit image unit is used for quantitatively generating image information representing state characteristics of the fire-fighting main unit in multiple dimensions of a fire-fighting safety system according to basic data, building space data, fire-fighting equipment third-party detection and evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main unit;
the multi-dimensional comprehensive analysis unit is used for combining the portrait information to execute multi-dimensional intelligent analysis and evaluation on a fire safety mechanism of a fire main unit;
and the fire-fighting main body regulation and control feedback unit carries out targeted regulation and control feedback on the user side of the fire-fighting main body unit according to the evaluation index of each dimension obtained by the multi-dimension comprehensive analysis unit, and the regulation and control feedback feeds the fire-fighting safety mechanism standard corresponding to the dimension of which the evaluation index is lower than a set threshold value back to the user side of the fire-fighting main body unit on the basis of the fire-fighting safety mechanism standard applicable to the standard main body model.
Preferably, the portrait information of the fire-fighting subject unit includes portrait dimensions including, but not limited to: the fire fighting equipment comprises a unit population number, population mobility, a building area, a building layer number, a building unit number, a space connectivity index, building structure fire resistance, a fire fighting channel number, a fire fighting elevator number, an escape path connectivity index, a total number of fire fighting facilities, a fire fighting facility coverage rate, a fire fighting facility effective rate, a fire fighting facility maintenance rate and a fire fighting data exception rate; the portrait unit of the fire-fighting main body unit extracts data indexes related to portrait dimensions from basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit, and assigns values to the portrait dimensions after conversion or deduction is carried out on the basis of the related data indexes; will be the main unit of fire controlThe image information is represented by Y = { Y = 1 、Y 2 ...Y i ...Y n In which Y is i A data index value representing the ith portrait dimension;
let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models, and the 1 st, 2 nd, 8230l, L \8230andL standard main body model portraits are represented as YN 1 、YN 2 ...YN l ...YN L ；
Calculating the portrait information Y of main body unit and No. 1, 2, 8230l, L, standard model portrait YN 1 、YN 2 ...YN l ...YN L The respective matching degrees.
Wherein the portrait information Y of the fire-fighting subject unit and the first kind standard subject model portrait YN l The matching degree calculation method comprises the following steps: first computing Y of the image information Y in the ith image dimension i Drawing YN with the first kind standard main body model l Is/are as follows
Degree of dimensional matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of rho is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The maximum value of the value; further, the image information Y and the first type standard subject model image YN are calculated from the 1 st to nth dimensions l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e i A weighted weighting factor for the ith image dimension, an
The weighting factors for each dimension may be set according to the degree of importance of the 1 st to nth portrait dimensions.
Preferably, the multidimensional comprehensive analysis unit extracts fire safety mechanism information of each type as a dimension from a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety conference record, a fire safety system file, a fire safety event log, an emergency fire-extinguishing plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety patrol log, a fire safety maintenance log, a fire safety filing record, a fire safety exercise log, a fire safety mission log, a fire safety hidden danger log, a flammable and explosive management file, a dynamic and dynamic management file, a large-scale activity management file and a fire safety report file of the fire main body unitThe set of thematic tags corresponding to this dimension is denoted as E 1 ，E 2 ，...E m (ii) a Furthermore, for the standard main body model with the highest matching degree with the portrait information of the fire-fighting main body unit, the theme label set of the standard main body model and the corresponding fire-fighting safety mechanism template is expressed as Z;
subject label set E of fire safety mechanism information for fire-fighting principal unit s Wherein the included tag entity is denoted as e s For the label entity corresponding to the label content in the subject label set Z, the label entity is represented as Z t (ii) a A fire safety-related knowledge graph semantic network is predefined, in which an entity e is linked s And z t Is expressed as L (s，t) Are respectively marked as
The length of each relationship path is expressed as
Where the length of the relationship path is defined as the number of entities on the path, entity e s And z t The degree of correlation of (d) is defined as:
then each subject label set E of fire safety mechanism information of the fire-fighting principal unit s Relevancy C (E) of topic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s (iv) the average of the correlation degrees generated by pairwise combination of each tag entity in Z and each tag entity in Z; further, the correlation C (E) between each topic tag set of the fire safety mechanism information of the fire main body unit and the topic tag set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension is as follows:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, 0 ≦ w (Q) s ) 1 or less, which represents an evaluation index corresponding to fire safety mechanism information of the fire-fighting subject unit.
The invention provides a fire safety system evaluation regulation and control method, which comprises the following steps:
acquiring data, namely acquiring fire fighting detection data and fire fighting equipment state data through an equipment Internet of things deployed by a fire fighting main body unit;
generating fire safety mechanism information, namely generating the fire safety mechanism information comprising detection maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plan and drill training;
a fire fighting data access calling step, which is used for storing basic data, building space data, fire fighting detection data, fire fighting facility state data and fire fighting safety mechanism information related to a fire fighting main body unit for the fire fighting service mechanism end to call;
accessing fire protection detection data and fire protection facility state data of the equipment internet of things acquisition end, receiving fire protection safety mechanism information uploaded by a user end of the fire protection main unit, and calling data related to the fire protection main unit stored in the fire protection safety data center; and based on the data and the information, executing multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and performing regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
Specifically, the method for executing multi-dimensional intelligent analysis and evaluation on the fire safety mechanism of a fire main body unit comprises the following steps:
quantitatively generating image information representing state characteristics of the fire-fighting main body unit in multiple dimensions of a fire-fighting safety system according to the basic data, the building space data, the third-party detection and evaluation information of the fire-fighting equipment, the maintenance information of the fire-fighting equipment, the fire-fighting detection data and the state data of the fire-fighting equipment, which are related to the fire-fighting main body unit;
according to the portrait information of the fire-fighting main body unit, matching with a predefined standard main body model portrait to obtain a standard main body model with the highest portrait information matching degree with the fire-fighting main body unit;
calculating the matching degree of the portrait information of the fire-fighting main body unit and the standard main body model portrait;
acquiring fire safety mechanism information of a fire main unit generated by a user side of the fire main unit, calling a fire safety mechanism template corresponding to a standard main model with the highest matching degree, and performing multi-dimensional intelligent analysis and evaluation on the fire safety mechanism information of the fire main unit to acquire a multi-dimensional comprehensive evaluation index;
and performing targeted regulation and control feedback on the user side of the fire-fighting main unit according to the evaluation index of each dimension, wherein the regulation and control feedback is based on the fire safety mechanism standard applicable to the standard main model, and the fire safety mechanism standard corresponding to the dimension with the evaluation index lower than the set threshold value is fed back to the user side of the fire-fighting main unit.
Specifically, the portrait information of the fire-fighting subject unit includes portrait dimensions including, but not limited to: the fire fighting equipment comprises a unit population number, population mobility, a building area, a building layer number, a building unit number, a space connectivity index, building structure fire resistance, a fire fighting channel number, a fire fighting elevator number, an escape path connectivity index, a total number of fire fighting facilities, a fire fighting facility coverage rate, a fire fighting facility effective rate, a fire fighting facility maintenance rate and a fire fighting data exception rate; the portrait unit of the fire-fighting main body unit extracts data indexes related to portrait dimensions from basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit, and assigns values to the portrait dimensions after conversion or deduction is carried out on the basis of the related data indexes; representing the image information of a fire-fighting subject unit as Y = { Y 1 、Y 2 ...Y i ...Y n In which Y is i A data index value representing the ith portrait dimension;
let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models in total, and the portrait of the 1 st, 2 nd, 8230l \, 8230l standard main body models is represented as YN 1 、YN 2 ...YN l ...YN L ；
Calculating the portrait information Y of main body unit and No. 1, 2, 8230l, L, standard model portrait YN 1 、YN 2 ...YN l ...YN L The respective degree of match.
Wherein the portrait information Y of the fire-fighting main body unit and the first kind standard main body model portrait YN l The matching degree calculation method comprises the following steps: first computing Y of the image information Y in the ith image dimension i Drawing YN with the first kind standard main body model l Is
Degree of dimensional matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of rho is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in a range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. I.ltoreq.nInside the enclosure
The maximum value of the values; further, the image information Y and the first type standard subject model image YN are calculated from the 1 st to nth dimensions l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e is i A weighted weighting factor for the ith image dimension, and
the weighting factors for each dimension may be set according to the degree of importance of the 1 st to nth portrait dimensions.
Taking the fire safety mechanism information of each type as a dimension, respectively extracting a subject label set corresponding to the dimension to express as an E in a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety meeting record, a fire safety system file, a fire safety event log, an emergency fire-fighting plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety patrol log, a fire safety maintenance log, a fire safety filing record, a fire safety drilling log, a fire safety task log, a fire safety hidden danger log, a flammable explosive article management file, an electric dynamic fire management file, a large-scale activity management file and a fire safety report file of the fire main body unit, taking the fire safety mechanism information of each type as a dimension, and respectively extracting a subject label set corresponding to the dimension 1 ，E 2 ，...E m (ii) a Further, for a standard body model having the highest matching degree with the image information of the fire-fighting body unit, the standard body model and the corresponding fire-fighting safetyThe thematic label set of the mechanism template is denoted as Z;
subject label set E of fire safety mechanism information for fire-fighting principal unit s Wherein the included tag entity is denoted as e s For the label content in the subject label set Z, the corresponding label entity is represented as Z t (ii) a A fire safety-related knowledge graph semantic network is predefined, in which an entity e is linked s And z t Is expressed as L (s，t) Are respectively marked as
The length of each relationship path is expressed as
Where the length of the relationship path is defined as the number of entities on the path, entity e s And z t The degree of correlation of (c) is defined as:
then each subject label set E of fire safety mechanism information of the fire-fighting principal unit s Relevancy C (E) of topic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s (iv) the average of the correlation degrees generated by pairwise combination of each tag entity in Z and each tag entity in Z; further, the correlation C (E) between each topic tag set of the fire safety mechanism information of the fire main body unit and the topic tag set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, w (Q) is more than or equal to 0 s ) 1 or less, which represents an evaluation index corresponding to fire safety mechanism information of the fire-fighting subject unit.
Therefore, the invention uses the technical means of big data analysis image, semantic analysis, intelligent evaluation and the like to form a uniform and transparent information intercommunication interface between the relevant units and the fire service organization, carries out comprehensive, automatic, normalized and sustainable intelligent analysis and evaluation aiming at the actual operation state of the fire safety system of the relevant units, and carries out regulation and control intervention in time, thereby forming a perfect fire safety system and ensuring that the relevant units can well fulfill fire safety duties.
Drawings
The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining and illustrating the present application and should not be construed as limiting the scope of protection of the present application.
Fig. 1 is a schematic diagram of an overall architecture of a fire safety system evaluation regulation and control system disclosed in an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a fire service end disclosed in an embodiment of the present application.
Fig. 3 is a flowchart of a fire safety system evaluation and regulation method disclosed in the embodiment of the present application.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.
The invention provides a fire safety system evaluation regulation and control system and a method. The invention utilizes the technical means of big data analysis image, semantic analysis, intelligent evaluation and the like to form a uniform and transparent information intercommunication interface between related units and the fire service organization, carries out comprehensive, automatic, normalized and sustainable intelligent analysis and evaluation aiming at the actual running state of the fire safety system of the related units, and carries out regulation and control intervention in time, thereby forming a perfect fire safety system and ensuring that the related units can fulfill the fire safety duty.
An embodiment of the fire safety system evaluation regulation system disclosed in the present application is described in detail below with reference to fig. 1. This fire safety system aassessment regulation and control system includes: the system comprises an equipment internet of things acquisition end, a fire-fighting main unit user end, a fire-fighting safety data center and a fire-fighting service mechanism end;
the equipment internet of things acquisition end is used for acquiring fire fighting detection data and fire fighting equipment state data through an equipment internet of things deployed by a fire fighting main body unit and providing the acquired data to a user end of the fire fighting main body unit, a fire fighting service mechanism end and a fire fighting safety data center;
the user side of the fire-fighting main body unit is used for the fire-fighting main body unit to generate fire-fighting safety mechanism information including detection maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plans and drill training, and the fire-fighting safety mechanism information is uploaded to the fire-fighting safety data center and the fire-fighting service institution side;
the fire safety data center is used for storing basic data, building space data, fire detection data, fire facility state data and fire safety mechanism information related to a fire main body unit, and the basic data, the building space data, the fire detection data, the fire facility state data and the fire safety mechanism information are called by the fire service institution; the evaluation analysis data and the regulation and control feedback data related to the fire-fighting main body unit are obtained and stored from the fire-fighting service institution end;
the fire-fighting service mechanism side is used for accessing fire-fighting detection data and fire-fighting equipment state data of the equipment Internet of things acquisition side, receiving fire-fighting safety mechanism information uploaded by a user side of the fire-fighting main unit, and calling data related to the fire-fighting main unit stored in the fire-fighting safety data center; and based on the data and the information, executing multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and performing regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
The operation and function of the various components of the system are described in detail below.
The equipment internet of things deployed by a fire-fighting main body unit specifically comprises at least one of the following facilities: the fire disaster automatic detection system, the electric fire monitoring system, the combustible gas detection alarm system, the independent fire detector, the fire-fighting linkage controller, the indoor fire hydrant system, the outdoor fire hydrant system, the automatic water-spraying fire extinguishing system, the mechanical smoke-proof and smoke-discharging system, the foam fire extinguishing system, the water mist fire extinguishing system, the dry powder fire extinguishing system, the gas fire extinguishing system, the fire elevator system, the fire-fighting special telephone system, the emergency broadcasting system, the emergency lighting and evacuation indicating system, the fire separation facility, the fire-fighting equipment power supply monitoring system, the access control system and the fire-fighting video monitoring system. Moreover, the facilities in the equipment Internet of things can realize uplink and downlink communication of data based on NB-IOT, LORA and other Internet of things communication protocols. Therefore, the above facilities in the equipment internet of things can transmit the fire detection data acquired by the facilities to the equipment internet of things acquisition end of the invention based on the internet of things communication protocol, for example, the sensing data of smoke concentration, high temperature, open fire and the like detected by the automatic fire detection system, the combustible gas component and concentration data detected by the combustible gas detection alarm system, the abnormal current value, the abnormal voltage value and the open circuit data detected by the electrical fire monitoring system, and the like. The above facilities in the equipment internet of things can also transmit fire protection facility state data reflecting the actual parameters, working state, self-checking state, error reporting records and the like of the facilities to the equipment internet of things collection end based on the internet of things communication protocol. The equipment internet of things acquisition end is used as an interface unit of the equipment internet of things deployed by the fire safety system evaluation regulation and control system and the fire main body unit, and can collect the fire detection data and the fire facility state data, and after necessary data cleaning, format normalization, simplification and other processing, the data are synchronously provided for the user end of the fire main body unit, the fire service mechanism end and the fire safety data center.
The user side of the fire-fighting main body unit is a terminal unit for the fire-fighting main body unit to realize various information interaction and user operation. The user side of the fire-fighting main body unit is used for the fire-fighting main body unit to generate fire-fighting safety mechanism information including detection maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plans and drill training, and uploads the fire-fighting safety mechanism information to the fire-fighting safety data center and the fire-fighting service institution side. The user side of the fire-fighting main body unit can also obtain the fire-fighting detection data and the fire-fighting equipment state data from the equipment internet of things acquisition end, and provides visual display, viewing, statistics, overrun alarm and other functions of the data for the fire-fighting main body unit.
Specifically, the user side of the fire-fighting main body unit generates the fire-fighting safety mechanism information of the contents in the aspects of detection maintenance, supervision patrol, assessment early warning, hidden danger investigation, key events and article management and control, emergency plans and exercise training and supports the operations of managing, updating, deleting and the like of the fire-fighting safety mechanism information by means of a menu and a form page supporting man-machine interaction operation and information editing, supporting file uploading, supporting connection to a database or a data interface, executing various structured or unstructured data records or data table importing, supporting video and audio data loading, supporting log record generation and the like. The fire safety mechanism information generated by the user side of the fire main unit comprises at least one of the following specific types: the system comprises a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety meeting record, a fire safety system file, a fire safety event log, an emergency fire-fighting plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety patrol log, a fire safety maintenance log, a fire safety filing record, a fire safety exercise log, a fire safety task log, a fire safety hidden danger log, an inflammable explosive management file, an dynamic and dynamic electric management file, a large-scale activity management file and a fire safety report file. The information of the fire safety mechanism in the text format can be edited on the terminal equipment of the user and then uploaded to the user side of the fire main unit; related data tables or log files can be exported from a registration management system or a database related to functions of fire-fighting equipment, flammable and explosive articles, electric appliances, pipelines, personnel and the like, and then imported to the user side of the fire-fighting main body unit; the information of the corresponding column can also be input by utilizing a menu and a form page provided by the user side of the fire-fighting main body unit; and then, the user side of the fire-fighting main body unit generates the fire-fighting safety mechanism information. And the user side of the fire-fighting main body unit further uploads the local fire-fighting safety mechanism information to the fire-fighting safety data center and the fire-fighting service mechanism side.
The fire safety data center is used as a data center of the fire safety system evaluation regulation and control system and provides functions of data collection, storage, management and calling. The fire safety data center is communicated with the equipment internet of things acquisition end through a special data interface, so that fire detection data and fire facility state data of the equipment internet of things are received and stored. And the fire safety data center is communicated with the user side of the fire main unit through a special data interface, so that fire safety mechanism information is obtained. In addition, the fire safety data center is also provided with a special data interface facing to a building management mechanism end, a technical service mechanism end or other third party mechanism ends, so that relevant data representing building space information, fire protection facility third party detection and evaluation information and fire protection facility maintenance information are obtained. The fire-fighting safety data center stores basic data, building space data, fire-fighting detection data, fire-fighting equipment state data, fire-fighting safety mechanism information, fire-fighting equipment third-party detection evaluation information and fire-fighting equipment maintenance information related to a fire-fighting main body unit, and the basic data, the building space data, the fire-fighting detection data, the fire-fighting equipment state data, the fire-fighting safety mechanism information, the fire-fighting equipment third-party detection evaluation information and the fire-fighting equipment maintenance information are called by the fire-fighting service institution end. And the fire safety data center can obtain and store the related evaluation analysis data and the regulation and control feedback data of the fire main body unit from the fire service institution.
The fire service organization end is an intelligent terminal located on one side of a professional fire service organization. The fire service mechanism end is used for accessing fire detection data and fire fighting equipment state data of the equipment internet of things acquisition end, receiving fire safety mechanism information uploaded by a user end of a fire main unit, and calling data related to the fire main unit stored in the fire safety data center, wherein the data called from the fire safety data center include but are not limited to: basic data, building space data, fire-fighting equipment third-party detection and evaluation information and fire-fighting equipment maintenance information related to the fire-fighting main body unit.
Based on the data and the information, the fire-fighting service mechanism end can generate portrait information of the fire-fighting main body unit, and executes multi-dimensional intelligent analysis and evaluation on a fire-fighting safety mechanism of the fire-fighting main body unit by combining the portrait information, and performs targeted regulation and control feedback on a user side of the fire-fighting main body unit according to a multi-dimensional intelligent analysis and evaluation result. Therefore, the fire-fighting service mechanism end can comprehensively, automatically, normally and continuously analyze, evaluate and regulate the actual operation state of the fire-fighting safety system of the fire-fighting main body unit, the fire-fighting facilities are used as main objects for construction and management in the prior art, the evaluation and regulation of the actual operation state of the whole fire-fighting safety software and hardware system are changed into the evaluation and regulation of the actual operation state of the whole fire-fighting safety software and hardware system, the specialized capability of the fire-fighting service mechanism is exerted to enable the majority of the fire-fighting main body units, and the relevant units are guaranteed to fulfill the fire-fighting safety duty.
Specifically, referring to fig. 2, the fire service side includes: a fire-fighting main body unit portrait unit, a multi-dimensional comprehensive analysis unit and a fire-fighting main body regulation and control feedback unit.
The fire-fighting main body unit portrait unit is used for quantitatively generating portrait information representing state characteristics of the fire-fighting main body unit in multiple dimensions of a fire-fighting safety system according to basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit. Specifically, the portrait information of the fire-fighting subject unit includes portrait dimensions including, but not limited to: the number of unit population, population mobility, building area, number of building layers, number of building units, space connectivity index, building structure fire resistance, number of fire fighting channels, number of fire fighting elevators, escape path connectivity index, total number of fire fighting facilities, fire fighting facility coverage rate, fire fighting facility efficiency rate, fire fighting facility maintenance rate, fire fighting data anomaly rate, and the like. The portrait unit of the fire-fighting main body unit detects and evaluates information, maintenance information and maintenance information of the fire-fighting equipment from basic data, building space data, third party detection and evaluation information of the fire-fighting equipment, and information of the fire-fighting equipmentAnd extracting data indexes related to the portrait dimensions from the detection data and the fire fighting equipment state data, and assigning values to the portrait dimensions after conversion or deduction is performed on the basis of the related data indexes. Representing the image information of a fire-fighting subject unit as Y = { Y = { (Y) } 1 、Y 2 ...Y i ...Y n In which Y is i The value of the data index representing the ith image dimension.
And the multidimensional comprehensive analysis unit is used for combining the portrait information to execute multidimensional intelligent analysis and evaluation on a fire safety mechanism of a fire main body unit.
Specifically, first, the multidimensional integrated analysis unit matches a predefined standard subject model image based on image information of a fire-fighting subject unit, and obtains a standard subject model having the highest degree of matching with the image information of the fire-fighting subject unit.
Due to the diversity of the fire-fighting main body units in the aspects of basic information, building space, fire-fighting facility configuration, fire-fighting data state and the like, the applicable fire-fighting safety mechanism obviously has larger difference. Therefore, in order to regularly perform subsequent multidimensional intelligent analysis and evaluation on the fire safety mechanisms of the fire main units, the multidimensional comprehensive analysis unit predefines a plurality of typical standard main body models, and each standard main body model corresponds to the fire main units with different characteristics in terms of basic information, building space, fire protection facility configuration, fire protection data state and the like. Also, portrait information is established for each standard subject model, and standard subject model portraits include portrait dimensions, similar to the above, including but not limited to: the number of unit population, population mobility, building area, number of building layers, number of building units, space connectivity index, building structure fire resistance, number of fire fighting channels, number of fire fighting elevators, escape path connectivity index, total number of fire fighting facilities, fire fighting facility coverage rate, fire fighting facility efficiency rate, fire fighting facility maintenance rate, fire fighting data anomaly rate, and the like. Let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models, and the 1 st, 2 nd, 8230l, L \8230andL standard main body model portraits are represented as YN 1 、YN 2 ...YN l ...YN L 。
The multi-dimensional comprehensive analysis unit calculates the portrait information Y of the fire-fighting main body unit and the 1 st and the 2 nd (8230); L (8230); L standard main body model portrait YN 1 、YN 2 ...YN l ...YN L The respective degree of match. Wherein the portrait information Y of the fire-fighting subject unit and the first kind standard subject model portrait YN l The matching degree calculation method comprises the following steps: first calculating Y of the portrait information Y in the ith portrait dimension i Drawing YN with the first kind standard main body model l Is
Degree of dimensional matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of rho is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. I.ltoreq.n
The maximum value of the value; further, according to 1 toThe image information Y and the standard model image YN of the first kind in the nth dimension l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e i A weighted weighting factor for the ith image dimension, an
The weighting factors for each dimension may be set according to the degree of importance of the 1 st to nth portrait dimensions. Therefore, the multi-dimensional comprehensive analysis unit calculates the portrait information Y of the fire-fighting main body unit and the 1 st, 2 nd, 8230l \ 8230l L standard main body model portrait YN 1 、YN 2 ...YN l ...YN L Respective degree of matching δ 1 、δ 2 、…δ 1 …δ L And determining a standard main body model with the highest matching degree with the portrait information of the fire-fighting main body unit.
And then, the multidimensional comprehensive analysis unit obtains the fire safety mechanism information of the fire main body unit generated by the user side of the fire main body unit, calls a fire safety mechanism template corresponding to the standard main body model with the highest matching degree, and carries out multidimensional intelligent analysis and evaluation on the fire safety mechanism information of the fire main body unit to obtain a multidimensional comprehensive evaluation index.
As described above, the fire safety mechanism information of the fire-fighting principal unit obtained by the multidimensional comprehensive analysis unit includes at least one of the following specific types: the system comprises a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety conference record, a fire safety system file, a fire safety event log, an emergency fire-extinguishing plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety inspection log, a fire safety maintenance log, a fire safety filing record, a fire safety rehearsal log, a fire safety task log, a fire safety hidden danger log, a flammable explosive management file, an dynamic and dynamic management file, a large-scale activity management file and a fire safety report file.
And for the predefined several standard main body models, each standard main body model has a corresponding fire safety mechanism template, the fire safety mechanism template defines a fire safety mechanism standard applicable to the standard main body model, and the type of the fire safety mechanism standard also corresponds to the type of the fire safety mechanism information of the fire main body unit, that is, the fire safety mechanism template includes: fire safety manual standard, fire safety ability self-evaluation standard, fire safety knowledge self-examination standard, fire safety personnel standard, fire safety knowledge training standard, fire safety conference ratio standard, fire safety system standard, fire safety event standard, emergency fire-fighting plan standard, emergency evacuation plan standard, fire safety duty standard, fire safety detection standard, fire safety inspection standard, fire safety maintenance standard, fire safety construction standard, fire safety drilling standard, fire safety mission standard, fire safety hidden danger standard, inflammable explosive management standard, dynamic and dynamic power management standard, large-scale activity management standard, and fire safety report standard.
The multi-dimensional comprehensive analysis unit extracts the subject labels of multiple dimensions from the obtained fire safety mechanism information of the fire main body unit; specifically, the multidimensional comprehensive analysis unit is selected from a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety meeting record, a fire safety system file, a fire safety event log, an emergency fire-fighting plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety patrol log, a fire safety maintenance log, a fire safety assessment log of the fire main body unitTaking the fire safety mechanism information of each type as a dimension in a safety maintenance log, a fire safety filing record, a fire safety drilling log, a fire safety task log, a fire safety hidden danger log, a flammable and explosive management file, an dynamic and dynamic management file, a large-scale activity management file and a fire safety report file, respectively extracting a theme label set corresponding to the dimension to represent the theme label set as E 1 ，E 2 ，...E m (ii) a Further, for a standard body model that has the highest matching degree with the image information of the fire-fighting body unit, a subject label set of the standard body model and the fire-fighting safety mechanism template corresponding thereto is represented as Z.
Thematic taggant set of fire safety mechanism information for fire-fighting principal units, e.g. E s Wherein the included tag entity is denoted as e s For the label entity corresponding to the label content in the subject label set Z, the label entity is represented as Z t (ii) a The multi-dimensional comprehensive analysis unit predefines a fire safety-related knowledge-graph semantic network in which an entity e is linked s And z t The relationship path (linkage, i.e., "entity 1-relationship 1-entity 2-relationship 2-entity 3", for example), where the first and last entities 1 and 3 are entity e s And z t ) Is expressed as L (s，t) I.e. total L (s，t) The bar relationship paths are respectively recorded as
The length of each relationship path is expressed as
Where the length of the relationship path is defined as the number of entities on the path (e.g., path length of 3 in the "entity 1-relationship 1-entity 2-relationship 2-entity 3" example above), entity e s And z t The degree of correlation of (c) is defined as:
then each subject label set (e.g., E) of the fire safety mechanism information of the fire-fighting principal unit s ) Relevancy C (E) of thematic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s And Z and each tag entity in Z are combined pairwise to produce an average value of the correlation.
In turn, each thematic tag set (e.g., E) according to the fire safety mechanism information of the fire main body unit s ) Correlation C (E) with the topic tag set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension is as follows:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, w (Q) is more than or equal to 0 s ) 1, which represents an evaluation index corresponding to the fire safety mechanism information of the fire-fighting subject unit.
The fire-fighting main body regulation and control feedback unit carries out targeted regulation and control feedback on the user sides of the fire-fighting main body units according to the evaluation index of each dimension obtained by the multi-dimension comprehensive analysis unit, and the regulation and control feedback feeds the fire-fighting safety mechanism standard corresponding to the dimension of which the evaluation index is lower than the set threshold value back to the user sides of the fire-fighting main body units on the basis of the fire-fighting safety mechanism standard applicable to the standard main body model.
Referring to fig. 3, the invention provides a fire safety system evaluation regulation method, which comprises the following steps:
acquiring data, namely acquiring fire fighting detection data and fire fighting equipment state data through an equipment Internet of things deployed by a fire fighting main body unit;
generating fire safety mechanism information, namely generating the fire safety mechanism information comprising the contents in the aspects of detection, maintenance, supervision and patrol, assessment and early warning, hidden danger investigation, key event and article management and control, emergency plan and drill training;
a fire protection data access calling step, which is to store basic data, building space data, fire protection detection data, fire protection facility state data and fire protection safety mechanism information related to a fire protection main body unit for the fire protection service mechanism end to call;
accessing fire protection detection data and fire protection facility state data of the equipment internet of things acquisition end, receiving fire protection safety mechanism information uploaded by a user end of the fire protection main unit, and calling data related to the fire protection main unit stored in the fire protection safety data center; and based on the data and the information, executing multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and performing regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
Specifically, the method for executing multi-dimensional intelligent analysis and evaluation on the fire safety mechanism of a fire main unit comprises the following steps:
quantitatively generating image information representing state characteristics of the fire-fighting main body unit in multiple dimensions of a fire-fighting safety system according to the basic data, the building space data, the third-party detection and evaluation information of the fire-fighting equipment, the maintenance information of the fire-fighting equipment, the fire-fighting detection data and the state data of the fire-fighting equipment, which are related to the fire-fighting main body unit;
according to the portrait information of the fire-fighting main body unit, matching with a predefined standard main body model portrait to obtain a standard main body model with the highest portrait information matching degree with the fire-fighting main body unit;
calculating the matching degree of the portrait information of the fire-fighting main body unit and the standard main body model portrait;
acquiring fire safety mechanism information of a fire main unit generated by a user side of the fire main unit, calling a fire safety mechanism template corresponding to a standard main model with the highest matching degree, and performing multi-dimensional intelligent analysis and evaluation on the fire safety mechanism information of the fire main unit to acquire a multi-dimensional comprehensive evaluation index;
and performing targeted regulation and control feedback on the user side of the fire-fighting main body unit according to the evaluation index of each dimension, wherein the regulation and control feedback is based on the fire safety mechanism standard applicable to the standard main body model, and the fire safety mechanism standard corresponding to the dimension with the evaluation index lower than a set threshold value is fed back to the user side of the fire-fighting main body unit.
Specifically, the portrait information of the fire-fighting subject unit includes portrait dimensions including, but not limited to: the fire fighting equipment comprises a unit population number, population mobility, a building area, a building layer number, a building unit number, a space connectivity index, building structure fire resistance, a fire fighting channel number, a fire fighting elevator number, an escape path connectivity index, a total number of fire fighting facilities, a fire fighting facility coverage rate, a fire fighting facility effective rate, a fire fighting facility maintenance rate and a fire fighting data exception rate; the portrait unit of the fire-fighting main body unit extracts data indexes related to portrait dimensions from basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit, and assigns values to the portrait dimensions after conversion or deduction is carried out on the basis of the related data indexes; representing the image information of a fire-fighting subject unit as Y = { Y 1 、Y 2 ...Y i ...Y n In which Y is i A data index value representing the ith portrait dimension;
let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models in total, and the portrait of the 1 st, 2 nd, 8230l \, 8230l standard main body models is represented as YN 1 、YN 2 ...YN l ...YN L ；
Calculating the portrait information Y of main body unit and No. 1, 2, 8230l, L, standard model portrait YN 1 、YN 2 ...YN l ...YN L The respective matching degrees.
Wherein the portrait information Y of the fire-fighting main body unit and the first kind standard main body model portrait YN l The matching degree calculation method of (2) is as follows: first computing Y of the image information Y in the ith image dimension i Drawing YN with the first kind standard main body model l Is/are as follows
Degree of dimensional matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of p is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The maximum value of the value; further, based on the image information Y in the 1 st to nth dimensions and the standard subject model image YN of the first kind l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e i A weighted weighting factor for the ith image dimension, an
The weighting factors for each dimension may be set according to the degree of importance of the 1 st to nth portrait dimensions.
Taking the fire safety mechanism information of each type as a dimension, extracting a subject label set corresponding to the dimension respectively from a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel name record, a fire safety knowledge training record, a fire safety conference record, a fire safety system file, a fire safety event log, an emergency fire-fighting plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety inspection log, a fire safety maintenance log, a fire safety filing record, a fire safety drilling log, a fire safety task log, a fire safety hidden danger log, a flammable explosive management file, an dynamic and dynamic management file, a large-scale activity management file and a fire safety report file of the fire main body unit, and expressing the fire safety mechanism information as E 1 ，E 2 ，...E m (ii) a Furthermore, for the standard main body model which has the highest matching degree with the portrait information of the fire-fighting main body unit, the theme label set of the standard main body model and the corresponding fire-fighting safety mechanism template is represented as Z;
subject label set E of fire safety mechanism information for fire-fighting principal unit s Wherein the included tag entity is denoted as e s For the label entity corresponding to the label content in the subject label set Z, the label entity is represented as Z t (ii) a A fire safety-related knowledge graph semantic network is predefined, in which an entity e is linked s And z t Is expressed as L (s，t) Are respectively marked as
The length of each relationship path is expressed as
Wherein the length of the relationship path is defined as the number of entities on the path, entity e s And z t The degree of correlation of (c) is defined as:
then each subject label set E of fire safety mechanism information of the fire-fighting principal unit s Relevancy C (E) of thematic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s (iv) the average of the correlation degrees generated by pairwise combination of each tag entity in Z and each tag entity in Z; further, the correlation C (E) between each topic tag set of the fire safety mechanism information of the fire main body unit and the topic tag set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension is as follows:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, 0 ≦ w (Q) s ) 1 or less, which represents an evaluation index corresponding to fire safety mechanism information of the fire-fighting subject unit.
According to the invention, by using the technical means of big data image analysis, semantic analysis, intelligent evaluation and the like, a uniform and transparent information intercommunication interface is formed between the relevant units and the fire service organization, comprehensive, automatic, normalized and sustainable intelligent analysis and evaluation are carried out aiming at the actual operation state of the fire safety system of the relevant units, and regulation and control intervention are carried out in time, so that a perfect fire safety system is formed, and the relevant units are ensured to fulfill fire safety duties.
The division of modules, sub-modules and/or units herein is merely a division of logical functions, and other divisions may be possible in actual implementation, for example, a plurality of modules, sub-modules and/or units may be combined or integrated in another system. Modules, sub-modules, units described as separate parts may or may not be physically separate. The components displayed as cells may or may not be physical cells, and may be located in a specific place or distributed in grid cells. Therefore, some or all of the units can be selected according to actual needs to implement the scheme of the embodiment.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A fire safety system assesses regulation system, comprising: the system comprises an equipment internet of things acquisition end, a fire-fighting main unit user end, a fire-fighting safety data center and a fire-fighting service mechanism end;
the equipment internet of things acquisition end is used for acquiring fire protection detection data and fire protection equipment state data through an equipment internet of things deployed by a fire protection main body unit and providing the acquired data to a fire protection main body unit user end, a fire protection service mechanism end and a fire protection safety data center;
the user side of the fire-fighting main body unit is used for the fire-fighting main body unit to generate fire-fighting safety mechanism information including contents in aspects of detection maintenance, supervision and patrol, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plans and drill training, and the fire-fighting safety mechanism information is uploaded to the fire-fighting safety data center and the fire-fighting service institution side;
the fire safety data center is used for storing basic data, building space data, fire detection data, fire facility state data and fire safety mechanism information related to a fire main body unit, and the basic data, the building space data, the fire detection data, the fire facility state data and the fire safety mechanism information are called by the fire service institution; acquiring and storing relevant evaluation analysis data and regulation and control feedback data of a fire-fighting main body unit from the fire-fighting service institution terminal;
the fire-fighting service mechanism side is used for accessing fire-fighting detection data and fire-fighting equipment state data of the equipment Internet of things acquisition side, receiving fire-fighting safety mechanism information uploaded by a user side of the fire-fighting main unit, and calling data related to the fire-fighting main unit stored in the fire-fighting safety data center; and based on the data and the information, executing multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and performing regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
2. The fire safety system assessment regulation system of claim 1, wherein the fire service authority side comprises: the system comprises a fire-fighting main body unit portrait unit, a multi-dimensional comprehensive analysis unit and a fire-fighting main body regulation and control feedback unit;
the fire-fighting main unit image unit is used for quantitatively generating image information representing state characteristics of the fire-fighting main unit in multiple dimensions of a fire-fighting safety system according to basic data, building space data, fire-fighting equipment third-party detection and evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main unit;
the multi-dimensional comprehensive analysis unit is used for combining the portrait information to execute multi-dimensional intelligent analysis and evaluation on a fire safety mechanism of a fire main unit;
and the fire-fighting main body regulation and control feedback unit carries out targeted regulation and control feedback on the user side of the fire-fighting main body unit according to the evaluation index of each dimension obtained by the multi-dimension comprehensive analysis unit, and the regulation and control feedback feeds the fire-fighting safety mechanism standard corresponding to the dimension of which the evaluation index is lower than a set threshold value back to the user side of the fire-fighting main body unit on the basis of the fire-fighting safety mechanism standard applicable to the standard main body model.
3. A fire safety system assessment regulation system as claimed in claim 2 wherein the portrait information of the fire-fighting subject unit includes portrait dimensions including but not limited to: unit population number, population mobility, building area, building layer number, building unit number, space connectivity index, building structure fire resistance, fire fighting channel number, fire fighting elevator number and escape routeThe fire fighting data comprises a path connectivity index, a total number of fire fighting facilities, a fire fighting facility coverage rate, a fire fighting facility effective rate, a fire fighting facility maintenance rate and a fire fighting data abnormal rate; the portrait unit of the fire-fighting main body unit extracts data indexes related to portrait dimensions from basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit, and assigns values to the portrait dimensions after conversion or deduction is carried out on the basis of the related data indexes; representing the image information of a fire-fighting subject unit as Y = { Y 1 、Y 2 ...Y i ...Y n In which Y is i A data index value representing the ith portrait dimension;
let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models in total, and the portrait of the 1 st, 2 nd, 8230l \, 8230l standard main body models is represented as YN 1 、YN 2 ...YN l ...YN L ；
Calculating the portrait information Y of main body unit and No. 1, 2, 8230l, L, standard model portrait YN 1 、YN 2 ...YN l ...YN L The respective degree of match.
4. The fire safety system assessment and control system according to claim 3, wherein the portrait information Y of the fire-fighting subject unit and the standard subject model portrait YN of the first kind l The matching degree calculation method comprises the following steps: first calculating Y of the portrait information Y in the ith portrait dimension i Drawing YN with the first kind standard main body model l Is/are as follows
Degree of dimension matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of rho is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The maximum value of the values; further, based on the image information Y in the 1 st to nth dimensions and the standard subject model image YN of the first kind l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e i A weighted weighting factor for the ith image dimension, an
The weighting factor of each dimension can be set according to the importance degree of the 1 st to nth portrait dimensions.
5. The fire safety system assessment and control system according to claim 4, wherein the multidimensional comprehensive analysis unit extracts each type of fire safety mechanism information as a dimension from a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel directory, a fire safety knowledge training record, a fire safety conference record, a fire safety system file, a fire safety event log, an emergency fire-extinguishing plan, an emergency evacuation plan, a fire safety duty log, a fire safety detection log, a fire safety patrol log, a fire safety maintenance log, a fire safety filing record, a fire safety drilling log, a fire safety task log, a fire safety hidden danger log, a flammable and explosive management file, a dynamic and dynamic fire management file, a large-scale activity management file, and a fire safety report file of the fire main body unit, and respectively extracts a subject label set corresponding to the dimension and represents as E 1 ，E 2 ，...E m (ii) a Furthermore, for the standard main body model with the highest matching degree with the portrait information of the fire-fighting main body unit, the theme label set of the standard main body model and the corresponding fire-fighting safety mechanism template is expressed as Z;
subject label set E for fire safety mechanism information of fire-fighting principal unit s Wherein the included tag entity is denoted as e s For the label entity corresponding to the label content in the subject label set Z, the label entity is represented as Z t (ii) a Predefining a fire safety-related knowledgegraph semantic network in which the linking entity e s And z t Is expressed as L (s，t) Are respectively marked as
The length of each relationship path is expressed as
Wherein the length of a relationship path is defined as the entity on the pathNumber of bodies then entity e s And z t The degree of correlation of (d) is defined as:
then each topic tag set E of the fire safety mechanism information of the fire-fighting principal unit s Relevancy C (E) of topic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s (iv) the average of the correlation degrees generated by pairwise combination of each tag entity in Z and each tag entity in Z; further, according to the correlation degree C (E) between each theme label set of the fire safety mechanism information of the fire main body unit and the theme label set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, 0 ≦ w (Q) s ) 1 or less, which represents an evaluation index corresponding to fire safety mechanism information of the fire-fighting subject unit.
6. A fire safety system assessment regulation and control method is characterized by comprising the following steps:
a data acquisition step, wherein fire fighting detection data and fire fighting equipment state data are acquired through an equipment Internet of things deployed by a fire fighting main body unit;
generating fire safety mechanism information, namely generating the fire safety mechanism information comprising detection maintenance, supervision and inspection, assessment and early warning, hidden danger investigation, key events and article management and control, emergency plan and drill training;
a fire protection data access calling step, which is to store basic data, building space data, fire protection detection data, fire protection facility state data and fire protection safety mechanism information related to a fire protection main body unit for the fire protection service mechanism end to call;
accessing fire detection data and fire facility state data of an equipment internet of things acquisition end, receiving fire safety mechanism information uploaded by a user end of the fire main unit, and calling data related to the fire main unit stored in the fire safety data center; and based on the data and the information, executing multidimensional intelligent analysis and evaluation on a fire safety mechanism of the fire main body unit, and performing regulation and control feedback on the user side of the fire main body unit according to a multidimensional intelligent analysis and evaluation result.
7. The fire safety system assessment regulation and control method of claim 6, wherein performing multidimensional intelligent analysis and assessment on the fire safety mechanism of the fire main unit comprises:
quantitatively generating image information representing state characteristics of the fire-fighting main body unit in multiple dimensions of a fire-fighting safety system according to the basic data, the building space data, the third-party detection and evaluation information of the fire-fighting equipment, the maintenance information of the fire-fighting equipment, the fire-fighting detection data and the state data of the fire-fighting equipment, which are related to the fire-fighting main body unit;
matching with a predefined standard main body model image according to the image information of the fire-fighting main body unit to obtain a standard main body model with the highest matching degree with the image information of the fire-fighting main body unit;
calculating the matching degree of the portrait information of the fire-fighting main body unit and the standard main body model portrait;
acquiring fire safety mechanism information of a fire main unit generated by a user side of the fire main unit, calling a fire safety mechanism template corresponding to a standard main model with the highest matching degree, and performing multi-dimensional intelligent analysis and evaluation on the fire safety mechanism information of the fire main unit to acquire a multi-dimensional comprehensive evaluation index;
and performing targeted regulation and control feedback on the user side of the fire-fighting main unit according to the evaluation index of each dimension, wherein the regulation and control feedback is based on the fire safety mechanism standard applicable to the standard main model, and the fire safety mechanism standard corresponding to the dimension with the evaluation index lower than the set threshold value is fed back to the user side of the fire-fighting main unit.
8. The fire safety system assessment and control method according to claim 6, wherein the portrait information of the fire-fighting subject unit includes portrait dimensions including but not limited to: the fire fighting equipment comprises a unit population number, population mobility, a building area, a building layer number, a building unit number, a space connectivity index, building structure fire resistance, a fire fighting channel number, a fire fighting elevator number, an escape path connectivity index, a total number of fire fighting facilities, a fire fighting facility coverage rate, a fire fighting facility effective rate, a fire fighting facility maintenance rate and a fire fighting data exception rate; the portrait unit of the fire-fighting main body unit extracts data indexes related to portrait dimensions from basic data, building space data, fire-fighting equipment third-party detection evaluation information, fire-fighting equipment maintenance information, fire-fighting detection data and fire-fighting equipment state data related to the fire-fighting main body unit, and assigns values to the portrait dimensions after conversion or deduction is carried out on the basis of the related data indexes; representing the image information of a fire-fighting subject unit as Y = { Y 1 、Y 2 ...Y i ...Y n In which Y is i A data index value representing the ith portrait dimension;
let the first standard subject model image be expressed as
The data index value of the ith portrait dimension representing the portrait of the first standard main body model predefines L standard main body models, and the 1 st, 2 nd, 8230l, L \8230andL standard main body model portraits are represented as YN 1 、YN 2 ...YN l ...YN L ；
Calculating the portrait information Y of the fire-fighting main body unit and the 1 st, 2 nd, 8230l \ 8230l standard model portrait YN 1 、YN 2 ...YN l ...YN L The respective matching degrees.
9. The fire safety system assessment and control method according to claim 8, wherein the portrait information Y of the fire-fighting principal unit and the l-th standard principal model portrait YN l The matching degree calculation method of (2) is as follows: first computing Y of the image information Y in the ith image dimension i Drawing YN with the first kind of standard main body model l Is/are as follows
Degree of dimensional matching δ i l ：
Wherein rho is a predefined adjusting weight factor, and the value range of rho is more than or equal to 0 and less than or equal to 1;
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The minimum value of the values is selected,
expressed in the range of 1. Ltoreq. I.ltoreq.n, 1. Ltoreq. L.ltoreq.L
The maximum value of the value; further, based on the image information Y in the 1 st to nth dimensions and the standard subject model image YN of the first kind l Degree of dimension matching δ 1 l 、δ 2 l 、…δ i l …δ n l Calculating the image information Y and the first type standard subject model image YN by weighted summation l The matching degree of (2):
wherein e is i A weighted weighting factor for the ith image dimension, and
the weighting factor of each dimension can be set according to the importance degree of the 1 st to nth portrait dimensions.
10. The fire safety system assessment and control method according to claim 9, wherein each of the above fire safety mechanism information is taken as a dimension, and a subject label set corresponding to the dimension is extracted and expressed as E respectively from a fire safety manual, a fire safety capability self-evaluation record, a fire safety knowledge self-examination record, a fire safety personnel directory, a fire safety knowledge training record, a fire safety conference record, a fire safety system file, a fire safety event log, an emergency fire extinguishing plan, an emergency evacuation plan, a fire safety on duty log, a fire safety detection log, a fire safety inspection log, a fire safety maintenance log, a fire safety filing record, a fire safety exercise log, a fire safety mission log, a fire safety hidden danger log, a flammable explosive management file, an dynamic and dynamic management file, a large-scale activity management file, and a fire safety report file of the fire main body unit 1 ，E 2 ，...E m (ii) a Furthermore, for the standard main body model with the highest matching degree with the portrait information of the fire-fighting main body unit, the theme label set of the standard main body model and the corresponding fire-fighting safety mechanism template is expressed as Z;
subject label set E of fire safety mechanism information for fire-fighting principal unit s Wherein the included tag entity is denoted as e s For the label content in the subject label set Z, the corresponding label entity is represented as Z t (ii) a A fire safety-related knowledge graph semantic network is predefined, in which an entity e is linked s And z t Is expressed as L (s，t) Are respectively marked as
The length of each relationship path is expressed as
Wherein the length of the relationship path is defined as the number of entities on the path, entity e s And z t The degree of correlation of (d) is defined as:
then each subject label set E of fire safety mechanism information of the fire-fighting principal unit s Relevancy C (E) of topic tag set Z of fire safety mechanism template corresponding to standard principal model s And Z) is: e s (iv) the average of the correlation degrees generated by pairwise combination of each tag entity in Z and each tag entity in Z; further, the correlation C (E) between each topic tag set of the fire safety mechanism information of the fire main body unit and the topic tag set Z of the fire safety mechanism template s Z), calculating a multi-dimensional comprehensive evaluation index of the fire safety mechanism of the fire main unit, wherein the evaluation index of each dimension:
w(Q s )＝ρ*C(E s ，Z)
wherein rho is a normalization coefficient, w (Q) is more than or equal to 0 s ) 1 or less, which represents an evaluation index corresponding to fire safety mechanism information of the fire-fighting subject unit.
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