CN115049023B - Civil air defense facility state monitoring method, device, equipment and storage medium - Google Patents

Civil air defense facility state monitoring method, device, equipment and storage medium Download PDF

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CN115049023B
CN115049023B CN202210971638.4A CN202210971638A CN115049023B CN 115049023 B CN115049023 B CN 115049023B CN 202210971638 A CN202210971638 A CN 202210971638A CN 115049023 B CN115049023 B CN 115049023B
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data
state
equipment
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air defense
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CN115049023A (en
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李燕
郏嘉
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Yunnan Zhidun Technology Co ltd
Shenzhen Zhaoxin Microelectronics Co ltd
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Yunnan Zhidun Technology Co ltd
Shenzhen Zhaoxin Microelectronics Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y40/00—IoT characterised by the purpose of the information processing
    • G16Y40/10—Detection; Monitoring
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention relates to the field of artificial intelligence, and discloses a method, a device, equipment and a storage medium for monitoring the state of a civil air defense facility, which are used for realizing the intellectualization of the state monitoring of the civil air defense facility and improving the accuracy of the state monitoring of the civil air defense facility. The method comprises the following steps: inputting the gas state data into a gas state simulation model for gas state detection to obtain a gas state detection result; performing data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and performing data segmentation on the equipment fusion data according to a plurality of equipment types to obtain target fusion data; respectively constructing equipment state matrixes according to the target fusion data to obtain target state matrixes; inputting the target state matrix into a device state detection model set to perform device state detection to obtain a device detection result; and carrying out comprehensive detection and analysis on the gas state detection result and the equipment detection result to obtain a civil air defense facility monitoring result.

Description

Civil air defense facility state monitoring method, device, equipment and storage medium
Technical Field
The invention relates to the field of artificial intelligence, in particular to a method, a device, equipment and a storage medium for monitoring the state of a civil air defense facility.
Background
At present, science and technology is continuously developed, industrial control equipment is changed day by day, and technologies such as networks, information, computers, human-computer interaction and the like are successfully applied to various industrial control fields, and good basis and technical means are provided for intelligent control of civil defense engineering. It is expected that the application of intelligent control systems in civil air defense engineering will become increasingly widespread. The intelligent civil air defense system takes an information network as a life pulse, information equipment as a carrier, information software as a soul and information resources as blood, constructs an intelligent civil air defense informatization system which integrates all services, multiple fields and all elements such as covering and organizing command, protection and rescue, communication alarm, engineering construction management, propaganda and education and the like, improves the system protection capability based on an information system, realizes the up-down communication, left-right interconnection, mutual support and information sharing of the civil air defense business system, and establishes a platform, intelligent and integrated civil air defense business innovation mode of unified management, unified command and unified scheduling.
The mode of patrolling and examining through the manual work is monitored people's air defense facility for knowing people's air defense real-time running information to current scheme can not realize that intelligence monitors people's air defense facility, because the control deviation appears in the manual work easily moreover, leads to the people's air defense facility state monitoring rate of accuracy of current scheme to be low.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for monitoring the state of a civil air defense facility, which are used for realizing the intellectualization of the state monitoring of the civil air defense facility and improving the accuracy of the state monitoring of the civil air defense facility.
The invention provides a civil air defense facility state monitoring method, which comprises the following steps: the method comprises the steps of obtaining monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, carrying out data classification extraction on the monitoring data, and obtaining a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data; performing parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result; performing data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and performing data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type; respectively constructing the equipment state matrixes of the multiple equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type; respectively inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain an equipment detection result corresponding to each equipment type; and carrying out comprehensive detection analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
Optionally, in a first implementation manner of the first aspect of the present invention, the performing parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the plurality of parameter values into a preset gas state simulation model to perform gas state detection to obtain a gas state detection result, includes: performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting the plurality of parameter values into a preset gas state simulation model to perform gas state curve fitting to obtain a target gas state curve; and carrying out curve analysis on the target gas state curve to obtain a gas state detection result.
Optionally, in a second implementation manner of the first aspect of the present invention, the performing data fusion on the device state data and the power supply state data to obtain device fusion data, and performing data segmentation on the device fusion data according to a plurality of preset device types to obtain target fusion data corresponding to each device type includes: establishing a data association relation between the equipment state data and the power supply state data; performing data fusion on the equipment state data and the power supply state data based on the data association relation to obtain equipment fusion data; inquiring the device attributes of a plurality of preset device types to obtain the device attribute corresponding to each device type; and performing data segmentation on the device fusion data based on the device attribute corresponding to each device type to obtain target fusion data corresponding to each device type.
Optionally, in a third implementation manner of the first aspect of the present invention, the respectively constructing the device state matrices of the multiple device types according to the target fusion data corresponding to each device type to obtain the target state matrix corresponding to each device type includes: performing data alignment on the target fusion data corresponding to each equipment type to obtain standard data corresponding to each equipment type; performing data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type; and performing matrix conversion on a plurality of data pairs corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the respectively inputting the target state matrix corresponding to each device type into a preset device state detection model set for device state detection to obtain a device detection result corresponding to each device type includes: inquiring the detection requirement of each equipment type from a preset state monitoring cloud platform; selecting a target detection model from a preset equipment state detection model set according to the detection requirement of each equipment type, wherein the equipment state detection model set comprises: a deformation detection model, a working state detection model and a performance detection model; and respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, and obtaining an equipment detection result corresponding to each equipment type.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the performing comprehensive detection analysis on the gas state detection result and the device detection result corresponding to each device type to obtain a civil air defense facility monitoring result, and generating the safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result includes: traversing the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a traversal result; extracting an abnormal detection result in the traversal result, and generating a civil air defense facility monitoring result according to the abnormal detection result; and carrying out abnormity type analysis on the monitoring result of the civil air defense facility to obtain a target abnormity type, and generating safety alarm information of the target civil air defense facility according to the target abnormity type.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the method for monitoring the state of the civil air defense facility further includes: visually displaying the safety alarm information, and analyzing the safety alarm information to obtain an alarm information analysis result; generating a remote maintenance strategy corresponding to the target civil air defense facility according to the alarm information analysis result; and generating a target maintenance work order according to the remote maintenance strategy, and dispatching the target maintenance work order to a target maintenance terminal.
A second aspect of the present invention provides a civil air defense facility status monitoring apparatus, comprising: the acquisition module is used for acquiring monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, and performing data classification and extraction on the monitoring data to obtain a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data; the detection module is used for carrying out parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the parameter values into a preset gas state simulation model to carry out gas state detection to obtain a gas state detection result; the fusion module is used for carrying out data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and carrying out data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type; the building module is used for respectively building the equipment state matrixes of the multiple equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type; the processing module is used for inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain an equipment detection result corresponding to each equipment type; and the generating module is used for carrying out comprehensive detection analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
Optionally, in a first implementation manner of the second aspect of the present invention, the detection module is specifically configured to: performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting the plurality of parameter values into a preset gas state simulation model for gas state curve fitting to obtain a target gas state curve; and carrying out curve analysis on the target gas state curve to obtain a gas state detection result.
Optionally, in a second implementation manner of the second aspect of the present invention, the fusion module is specifically configured to: establishing a data association relation between the equipment state data and the power supply state data; performing data fusion on the equipment state data and the power supply state data based on the data association relation to obtain equipment fusion data; inquiring the device attributes of a plurality of preset device types to obtain the device attribute corresponding to each device type; and performing data segmentation on the device fusion data based on the device attribute corresponding to each device type to obtain target fusion data corresponding to each device type.
Optionally, in a third implementation manner of the second aspect of the present invention, the building module is specifically configured to: performing data alignment on the target fusion data corresponding to each equipment type to obtain standard data corresponding to each equipment type; performing data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type; and performing matrix conversion on a plurality of data pairs corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the processing module is specifically configured to: inquiring the detection requirement of each equipment type from a preset state monitoring cloud platform; selecting a target detection model from a preset equipment state detection model set according to the detection requirement of each equipment type, wherein the equipment state detection model set comprises: a deformation detection model, a working state detection model and a performance detection model; and respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, thereby obtaining an equipment detection result corresponding to each equipment type.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the generating module is specifically configured to: traversing the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a traversal result; extracting an abnormal detection result in the traversal result, and generating a civil air defense facility monitoring result according to the abnormal detection result; and analyzing the abnormity type of the monitoring result of the civil air defense facility to obtain a target abnormity type, and generating safety alarm information of the target civil air defense facility according to the target abnormity type.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the civil air defense facility status monitoring apparatus further includes: the maintenance module is used for visually displaying the safety alarm information and analyzing the safety alarm information to obtain an alarm information analysis result; generating a remote maintenance strategy corresponding to the target civil air defense facility according to the alarm information analysis result; and generating a target maintenance work order according to the remote maintenance strategy, and dispatching the target maintenance work order to a target maintenance terminal.
A third aspect of the present invention provides a civil air defense facility condition monitoring apparatus, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the civil air defense status monitoring apparatus to perform the civil air defense status monitoring method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which when run on a computer, cause the computer to execute the above-described civil air defense facility status monitoring method.
In the technical scheme provided by the invention, the state monitoring cloud platform is constructed to carry out all-dimensional monitoring on the civil defense facility, the monitoring data of the target civil defense facility is acquired, the data monitoring of the state monitoring cloud platform on the civil defense facility is realized, the gas state data, the equipment state data and the power supply state data of the civil defense facility are acquired in real time, the remote monitoring on the civil defense facility, the gas state detection and the equipment detection result are realized, the unattended management requirement is met, and the management efficiency is improved; the system and the method have the advantages that the cost of civil air defense information construction and long-term operation and maintenance is reduced, the civil air defense service efficiency and the civil air defense service capacity are comprehensively improved, the gas state detection result and the equipment detection result corresponding to each equipment type are comprehensively detected and analyzed, the civil air defense facility monitoring result is obtained, the safety warning information of the target civil air defense facility is generated according to the civil air defense facility monitoring result, the intellectualization of the civil air defense facility state monitoring is realized, and the accuracy of the civil air defense facility state monitoring is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a civil air defense facility state monitoring method in an embodiment of the invention;
FIG. 2 is a schematic diagram of another embodiment of a civil air defense facility state monitoring method in an embodiment of the invention;
FIG. 3 is a schematic diagram of an embodiment of a civil air defense facility status monitoring device in an embodiment of the invention;
FIG. 4 is a schematic diagram of another embodiment of a civil air defense facility status monitoring device in an embodiment of the invention;
fig. 5 is a schematic diagram of an embodiment of a state monitoring device of a civil air defense facility in the embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for monitoring the state of a civil air defense facility, which are used for realizing the intellectualization of the state monitoring of the civil air defense facility and improving the accuracy of the state monitoring of the civil air defense facility. The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of an embodiment of the present invention is described below, and referring to fig. 1, an embodiment of a method for monitoring a state of a civil air defense facility in an embodiment of the present invention includes:
101. the method comprises the steps of obtaining monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, carrying out data classification extraction on the monitoring data, and obtaining a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data;
it is to be understood that the executing subject of the present invention may be a civil defense facility status monitoring apparatus, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
Specifically, the server may receive monitoring data acquisition information sent by a user through the state monitoring cloud platform, after receiving a monitoring data acquisition signal sent by the user through the state monitoring cloud platform, the browser determines monitoring data to be acquired according to the monitoring data acquisition information, optionally, the monitoring data acquisition signal of the user may include a data type of the monitoring data to be acquired, a time interval for acquiring the monitoring data to be acquired, and a time identifier of the monitoring data to be acquired, the monitoring data to be acquired may be determined according to the data type of the monitoring data to be acquired and the time identifier of the monitoring data to be acquired, the browser may be controlled to send a data acquisition instruction frequency to the server according to the time interval for acquiring the monitoring data to be acquired, and then the server performs data classification extraction on the monitoring data to obtain a plurality of state data, wherein the plurality of state data include: the gas state data, the equipment state data and the power supply state data are used for facilitating the follow-up improvement of the accuracy of the state monitoring of the civil air defense facility.
In this embodiment, data acquisition is performed on the target civil air defense facility based on a preset sensor group to obtain monitoring data, wherein the sensor group includes but is not limited to: the system comprises a security door sensor, a fan sensor, a gas sensor, a current voltage sensor and the like, wherein the security door sensor is used for acquiring inclination angle data of a security door of the target civil air defense facility and acquiring air flow data of a fan, and the inclination angle data and the air flow data are used as equipment state data and transmitted to a monitoring cloud platform; and acquiring gas state data of the target civil air defense facility through the gas sensor, and monitoring power supply state data through the current voltage sensor. Further, the server respectively constructs a real-time database and a historical database, and continuously stores data in the production process of the target civil air defense facility; and carrying out automatic data calling on the continuous data according to a preset data format. The security door sensor is a double-shaft tilt angle sensor, shares two sensitive shafts, namely an X shaft and a Y shaft. When the sensitive shaft and the gravity direction form an angle of 90 degrees, the angle change value output in each inclination is larger; when the sensitive axis forms an angle of 45 degrees with the gravity direction, the angle change value caused each time is small, and when the two are close to parallel, the output change is hardly caused any more by each deviation. In addition, a state monitoring cloud platform is constructed, multi-service field, multi-level, multi-dimension and multi-form information organization, correlation analysis and trend prediction are realized through deep mining, data modeling and fusion analysis of all civil air defense full service and all element data, important information support is provided for scientific planning management of all protection elements of civil air defense, combat readiness resources and efficient organization and command of civil air defense during combat, through the actual conditions of civil air defense, on the basis of an intelligent gateway, the data monitoring of the civil air defense system of each building by a civil air defense unit monitoring center is realized through the communication technology of the internet of things, the information of a safety door, basement gas concentration, a safety fan system and the like of the civil air defense is obtained in real time, the remote monitoring of the civil air defense is realized, the unattended management requirement is met, and the management efficiency is improved.
102. Performing parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the plurality of parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result;
it should be noted that, the server performs parameter separation on the gas state data to obtain a plurality of parameter values, where the parameter values include a gas constant (also called a general or ideal gas constant, and generally denoted by symbol R) which is a physical constant linking each thermodynamic function in the physical state equation. (the ratio of the gas constant to the avogalois constant is the boltzmann constant.) this is a constant that characterizes the properties of an ideal gas, the gas constant corresponding to the boltzmann constant but expressed in units of energy per mole per temperature increment (rather than energy per particle per temperature increment) (i.e., the pressure-volume product). The constants are also the constant combination of Boyle law, charles method, avogadro law and Gay-Lussac law, and then the server inputs a plurality of parameter values into a preset gas state simulation model to carry out gas state detection, so that a gas state detection result is obtained, and the gas state monitoring is carried out through a gas state policy model, so that the accuracy of the gas state monitoring can be improved.
Specifically, in this embodiment, whether the air flow of the target civil air defense facility reaches the standard is determined according to the gas state data, so as to obtain an air flow standard analysis result; storing the air flow data and the air flow standard-reaching analysis result; performing gas content index analysis on the target civil air defense facility according to the gas state data to obtain a gas content index analysis result; and storing the gas data and the gas content index analysis result so as to generate a gas state detection result.
103. Performing data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and performing data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type;
specifically, the server performs data fusion on the device status data and the power supply status data, wherein each data source may be data from different acquisition channels, and an acquisition channel may be a website, a data platform, or a created database, and the like.
104. Respectively constructing equipment state matrixes of a plurality of equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type;
it should be noted that, the matrix conversion performed by the server is to calculate the tag characteristics of the device types through a preset device state tag library to obtain a tag matrix, and then the server performs device type matching according to the state matrix to determine a target state matrix corresponding to each device type, optionally, the server calculates the tag characteristic coefficients of multiple device types according to target fusion data corresponding to each device type, and the server performs matrix conversion on the tag characteristics according to the tag characteristic coefficients to obtain a target state matrix, so that the accuracy of state monitoring performed on the civil defense facility by the subsequent server is facilitated through the construction of the target state matrix.
105. Respectively inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain an equipment detection result corresponding to each equipment type;
the server reevaluates the parameters to form a reconstructed hidden Markov model, an observation sequence is obtained through prediction, the observed quantities are compared, when the observed quantities are different, the second step is repeated after the hidden Markov model parameters are mutated, when the observed quantities are the same, a target detection model is generated and trained to be converged, precision value measurement, recall rate measurement and parameter quantity calculation are carried out, the result is judged, when a preset condition is met, the searched model is judged, when the preset condition is not met, all the target detection models are reordered to obtain the observation sequence, and the steps are repeated after the original observation sequence is replaced. The invention solves the problem that the target detection model in the prior art has poor practicability because the trained target detection model has large load on the memory and GPU of the terminal equipment in use due to large band-containing parameter quantity, thereby causing the execution difficulty of the terminal equipment. And respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, so as to obtain an equipment detection result corresponding to each equipment type, and improving the accuracy of data determination by reconstructing the hidden Markov model.
106. And carrying out comprehensive detection and analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
Specifically, each detection result is obtained, the detection result is detected based on a preset detection condition to obtain detection data, the detection data is traversed, clustering analysis is performed on the detection data to obtain a plurality of result clusters, anomaly analysis is performed on the detection data contained in each of the result clusters to obtain an anomaly analysis result of each result cluster, and a user to be detected corresponding to feature data contained in the result cluster of which the anomaly analysis result meets the preset anomaly condition is determined as an anomalous user. According to the method and the device, the cluster analysis and the anomaly detection are combined, so that the identification of the abnormal data can be effectively promoted while the fast iteration is ensured.
In this embodiment, the user may also be set to a usage right, where the usage right includes: adding and deleting users, modifying information of registered users, providing different operation authorities without users, and enabling non-users not to log in the monitoring cloud platform; generating a target report according to a preset civil air defense operation requirement, and visually displaying the target report; and adopting various alarm forms to carry out safety alarm on the target civil air defense facility; and displaying the alarm information in a flashing manner and displaying the operation parameters based on the preset graphical interface.
In the embodiment of the invention, the state monitoring cloud platform is constructed to carry out all-dimensional monitoring on the civil defense facilities, the monitoring data of the target civil defense facilities are collected, the data monitoring of the state monitoring cloud platform on the civil defense facilities is realized, the gas state data, the equipment state data and the power supply state data of the civil defense facilities are obtained in real time, the remote monitoring on the civil defense, the gas state detection and the equipment detection result are realized, the unattended management requirement is met, and the management efficiency is improved; the system and the method have the advantages that the cost of civil air defense information construction and long-term operation and maintenance is reduced, the civil air defense service efficiency and the civil air defense service capacity are comprehensively improved, the gas state detection result and the equipment detection result corresponding to each equipment type are comprehensively detected and analyzed, the civil air defense facility monitoring result is obtained, the safety warning information of the target civil air defense facility is generated according to the civil air defense facility monitoring result, the intellectualization of the civil air defense facility state monitoring is realized, and the accuracy of the civil air defense facility state monitoring is improved.
Referring to fig. 2, another embodiment of the method for monitoring the state of the civil air defense facility in the embodiment of the invention includes:
201. the method comprises the steps of obtaining monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, carrying out data classification extraction on the monitoring data, and obtaining a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data;
specifically, in this embodiment, the specific implementation of step 201 is similar to that of step 101, and is not described herein again.
202. Performing parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the plurality of parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result;
specifically, performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting a plurality of parameter values into a preset gas state simulation model to perform gas state curve fitting to obtain a target gas state curve; and carrying out curve analysis on the target gas state curve to obtain a gas state detection result.
The server performs data tagging on the gas state data to obtain a gas state tag, extracts parameter data from the gas state data based on a preset monitoring period and the gas state tag, further performs air flow analysis according to the air flow data, and judges whether the air flow data reaches the standard, wherein the standard air flow is defined as follows: at absolute pressure of 1 standard atmospheric pressure 1.0133bar, temperature of 0 ℃ and relative humidity of 0% of dry air flow, generally expressed in Nm3/min, content index analysis in the gas data is performed according to the air flow standard analysis result, wherein the air quality data comprises types of data such as total suspended particulate matters, fluorides, particulate matters with particle sizes smaller than or equal to 10 micrometers, particulate matters with particle sizes smaller than or equal to 2.5 micrometers and the like, analysis is performed to finally obtain a corresponding gas content index analysis result, and then the server inputs a plurality of parameter values into a preset gas state simulation model to perform gas state curve fitting to obtain a target gas state curve; and carrying out curve analysis on the target gas state curve to obtain a gas state detection result.
203. Performing data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and performing data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type;
specifically, a data association relation between equipment state data and power supply state data is established; performing data fusion on the equipment state data and the power supply state data based on the data association relation to obtain equipment fusion data; inquiring the device attributes of a plurality of preset device types to obtain the device attribute corresponding to each device type; and performing data segmentation on the device fusion data based on the device attribute corresponding to each device type to obtain target fusion data corresponding to each device type.
The entities summarized in the multi-level entity model are entities having incidence relation in a specific scene, and fusion basis is provided for data fusion. Because entities in the same-level entity model have parallel association types and entities between adjacent-level entity models have dependent association types, data fusion of entity description information in entity models with different levels can be realized by setting different fusion conditions, for example, setting description information of entities in adjacent 3 levels for data fusion, setting description information of entities in the same level for data fusion, and specifically, after a server obtains device fusion data, inquiring device attributes of a plurality of preset device types to obtain device attributes corresponding to each device type; the method comprises the steps of carrying out data segmentation on equipment fusion data based on equipment attributes corresponding to each equipment type to obtain target fusion data corresponding to each equipment type, extracting association relations among entities from description information of the entities in each data source, summarizing the entities with the association relations to generate an entity set, wherein the entity set considers the commonality among the entities and the association among the entities, further establishes a multi-level entity model according to the association types among the entities in the entity set, carries out data fusion on the entity description information in each data source through the multi-level entity model, can realize the fusion of data in different levels according to different preset fusion conditions, and can improve the flexibility of the data fusion so as to ensure the accuracy of the fusion data.
204. Respectively constructing equipment state matrixes of a plurality of equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type;
specifically, data alignment is performed on target fusion data corresponding to each device type to obtain standard data corresponding to each device type; performing data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type; and performing matrix conversion on a plurality of data pairs corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type.
The method comprises the steps of carrying out data alignment on target fusion data corresponding to each equipment type to obtain standard data corresponding to each equipment type, carrying out data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type, further extracting matrix elements in a template matrix by a server, and taking the matrix elements as characteristic elements. The server performs feature encoding processing by encoding feature elements and parameter matrixes through an attention head mechanism. It should be noted that the template matrix is a matrix describing network parameters, the attention head mechanism performs sequence-to-sequence conversion in an "encoding-decoding" manner, that is, the problem of information loss in long-distance information transmission during encoding and decoding is solved, by introducing the attention head mechanism, information at each position in the matrix is stored, when each target state matrix is generated during matrix conversion, relevant information is directly selected from the information of the matrix as assistance through the attention mechanism, and finally the server performs matrix conversion on a plurality of data pairs corresponding to each device type to obtain a target state matrix corresponding to each device type.
205. Inquiring the detection requirement of each equipment type from a preset state monitoring cloud platform;
206. selecting a target detection model from a preset equipment state detection model set according to the detection requirement of each equipment type, wherein the equipment state detection model set comprises: a deformation detection model, a working state detection model and a performance detection model;
207. respectively inputting the target state matrix corresponding to each equipment type into a target detection model to carry out equipment state detection, and obtaining an equipment detection result corresponding to each equipment type;
specifically, the server queries the detection requirement of each device type from a preset state monitoring cloud platform, and it is noted that the detection requirement takes at least one requirement keyword for representing the service detection requirement and at least one piece of detection data corresponding to the detection requirement and related to the service detection requirement in a preset time period, determines a detection rule for analyzing a detection target indicated by the service detection requirement according to the at least one requirement keyword, determines a detection data group corresponding to the detection requirement and corresponding to the detection data corresponding to the detection requirement according to the detection rule for each piece of detection data corresponding to the detection requirement, screens out a target session data group from the determined at least one detection data group corresponding to the detection requirement according to the detection rule, and determines a service detection result of the service detection requirement in the preset time period based on the number of the target session data groups. By the determining method and the determining device, the service detection result can be determined more accurately. Establishing a hidden Markov model, reestimating parameters of the hidden Markov model to form a reconstructed hidden Markov model, predicting to obtain an observation sequence of the reconstructed hidden Markov model, comparing observed quantities, repeating the second step after parameter variation of the hidden Markov model, generating a target detection model and training until convergence, then carrying out precision value measurement, recall rate measurement and parameter quantity calculation, judging results, judging the searched model when a preset condition is met, reordering all target detection models to obtain the observation sequence when the preset condition is not met, and repeating the steps after replacing the original observation sequence. The method and the device solve the problem that the target detection model in the prior art has poor practicability because the trained target detection model has large load on the memory and the GPU of the terminal equipment in use due to large band-containing parameter quantity, and the execution of the terminal equipment is difficult. And respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, and obtaining an equipment detection result corresponding to each equipment type.
208. And carrying out comprehensive detection and analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
Specifically, the server traverses the detection result of the gas state detection result and the detection result of the equipment corresponding to each equipment type to obtain a traversal result, extracts the abnormal detection result in the traversal result, and then the server obtains the monitoring result of the civil air defense facility and generates the safety alarm information of the target civil air defense facility according to the monitoring result of the civil air defense facility.
The method comprises the steps of obtaining each detection result, carrying out detection processing on the detection results based on preset detection conditions, obtaining detection data, traversing the detection data, carrying out cluster analysis on the detection data, obtaining a plurality of result clusters, carrying out abnormity analysis on the detection data contained in each result cluster in the plurality of result clusters, obtaining abnormity analysis results of each result cluster, and determining a user to be detected corresponding to characteristic data contained in the result cluster of which the abnormity analysis results meet the preset abnormity conditions as an abnormal user. According to the method and the device, the cluster analysis and the anomaly detection are combined, so that the identification of the abnormal data can be effectively promoted while the fast iteration is ensured.
Optionally, visually displaying the safety alarm information, and analyzing the safety alarm information to obtain an alarm information analysis result; generating a remote maintenance strategy corresponding to the target civil air defense facility according to the analysis result of the alarm information; and generating a target maintenance work order according to the remote maintenance strategy, and dispatching the target maintenance work order to a target maintenance terminal.
The server realizes information organization, association analysis and trend prediction in multiple service fields, multiple levels, multiple dimensions and multiple forms by deep mining, data modeling and fusion analysis of civil air defense full services and full element data, provides important information support for scientific planning management of various protective elements and combat readiness resources of civil air defense at ordinary times and organization and command of civil air defense high efficiency in wartime, and specifically generates a remote maintenance strategy corresponding to a target civil air defense facility according to an alarm information analysis result; and generating a target maintenance work order according to the remote maintenance strategy, sending the target maintenance work order to the target maintenance terminal, visually displaying the safety alarm information by the server, and visually monitoring the equipment state, so that the monitoring accuracy of the personnel defense facility is improved.
In the embodiment of the invention, the state monitoring cloud platform is constructed to carry out all-around monitoring on the civil air defense facilities, the monitoring data of the target civil air defense facilities are collected, the data monitoring of the state monitoring cloud platform on the civil air defense facilities is realized, the gas state data, the equipment state data and the power supply state data of the civil air defense facilities are acquired in real time, the remote monitoring on the civil air defense, the gas state detection and the equipment detection result are realized, the unattended management requirement is met, and the management efficiency is improved; the system and the method have the advantages that the cost of civil air defense information construction and long-term operation and maintenance is reduced, the civil air defense service efficiency and the civil air defense service capacity are comprehensively improved, the gas state detection result and the equipment detection result corresponding to each equipment type are comprehensively detected and analyzed, the civil air defense facility monitoring result is obtained, the safety warning information of the target civil air defense facility is generated according to the civil air defense facility monitoring result, the intellectualization of the civil air defense facility state monitoring is realized, and the accuracy of the civil air defense facility state monitoring is improved.
With reference to fig. 3, the method for monitoring the state of the civil air defense facility in the embodiment of the present invention is described above, and a device for monitoring the state of the civil air defense facility in the embodiment of the present invention is described below, where one embodiment of the device for monitoring the state of the civil air defense facility in the embodiment of the present invention includes:
an obtaining module 301, configured to obtain monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, and perform data classification and extraction on the monitoring data to obtain multiple pieces of state data, where the multiple pieces of state data include: gas state data, equipment state data and power supply state data;
the detection module 302 is configured to perform parameter separation on the gas state data to obtain a plurality of parameter values, and input the plurality of parameter values into a preset gas state simulation model to perform gas state detection to obtain a gas state detection result;
the fusion module 303 is configured to perform data fusion on the device state data and the power supply state data to obtain device fusion data, and perform data segmentation on the device fusion data according to a plurality of preset device types to obtain target fusion data corresponding to each device type;
a constructing module 304, configured to respectively construct device state matrices of the multiple device types according to the target fusion data corresponding to each device type, so as to obtain a target state matrix corresponding to each device type;
a processing module 305, configured to input the target state matrix corresponding to each device type into a preset device state detection model set for device state detection, so as to obtain a device detection result corresponding to each device type;
a generating module 306, configured to perform comprehensive detection and analysis on the gas state detection result and the device detection result corresponding to each device type to obtain a civil air defense facility monitoring result, and generate safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
In the embodiment of the invention, the state monitoring cloud platform is constructed to carry out all-around monitoring on the civil air defense facilities, the monitoring data of the target civil air defense facilities are collected, the data monitoring of the state monitoring cloud platform on the civil air defense facilities is realized, the gas state data, the equipment state data and the power supply state data of the civil air defense facilities are acquired in real time, the remote monitoring on the civil air defense, the gas state detection and the equipment detection result are realized, the unattended management requirement is met, and the management efficiency is improved; the system and the method have the advantages that the cost of civil air defense information construction and long-term operation and maintenance is reduced, the civil air defense service efficiency and the civil air defense service capacity are comprehensively improved, the gas state detection result and the equipment detection result corresponding to each equipment type are comprehensively detected and analyzed, the civil air defense facility monitoring result is obtained, the safety warning information of the target civil air defense facility is generated according to the civil air defense facility monitoring result, the intellectualization of the civil air defense facility state monitoring is realized, and the accuracy of the civil air defense facility state monitoring is improved.
Referring to fig. 4, another embodiment of the civil air defense facility state monitoring device in the embodiment of the present invention includes:
an obtaining module 301, configured to obtain monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, and perform data classification and extraction on the monitoring data to obtain multiple pieces of state data, where the multiple pieces of state data include: gas state data, equipment state data and power supply state data;
the detection module 302 is configured to perform parameter separation on the gas state data to obtain a plurality of parameter values, and input the plurality of parameter values into a preset gas state simulation model to perform gas state detection to obtain a gas state detection result;
the fusion module 303 is configured to perform data fusion on the device state data and the power supply state data to obtain device fusion data, and perform data segmentation on the device fusion data according to a plurality of preset device types to obtain target fusion data corresponding to each device type;
a constructing module 304, configured to respectively construct device state matrices of the multiple device types according to the target fusion data corresponding to each device type, so as to obtain a target state matrix corresponding to each device type;
a processing module 305, configured to input the target state matrix corresponding to each device type into a preset device state detection model set for device state detection, so as to obtain a device detection result corresponding to each device type;
a generating module 306, configured to perform comprehensive detection and analysis on the gas state detection result and the device detection result corresponding to each device type to obtain a civil air defense facility monitoring result, and generate safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
Optionally, the detection module 302 is specifically configured to: performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting the plurality of parameter values into a preset gas state simulation model for gas state curve fitting to obtain a target gas state curve; and carrying out curve analysis on the target gas state curve to obtain a gas state detection result.
Optionally, the fusion module 303 is specifically configured to: establishing a data association relation between the equipment state data and the power supply state data; performing data fusion on the equipment state data and the power supply state data based on the data association relation to obtain equipment fusion data; inquiring the device attributes of a plurality of preset device types to obtain the device attribute corresponding to each device type; and performing data segmentation on the device fusion data based on the device attribute corresponding to each device type to obtain target fusion data corresponding to each device type.
Optionally, the building module 304 is specifically configured to: performing data alignment on the target fusion data corresponding to each equipment type to obtain standard data corresponding to each equipment type; performing data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type; and performing matrix conversion on a plurality of data pairs corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type.
Optionally, the processing module 305 is specifically configured to: inquiring the detection requirement of each equipment type from a preset state monitoring cloud platform; selecting a target detection model from a preset equipment state detection model set according to the detection requirement of each equipment type, wherein the equipment state detection model set comprises: a deformation detection model, a working state detection model and a performance detection model; and respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, and obtaining an equipment detection result corresponding to each equipment type.
Optionally, the generating module 306 is specifically configured to: traversing the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a traversal result; extracting an abnormal detection result in the traversal result, and generating a civil air defense facility monitoring result according to the abnormal detection result; and analyzing the abnormity type of the monitoring result of the civil air defense facility to obtain a target abnormity type, and generating safety alarm information of the target civil air defense facility according to the target abnormity type.
Optionally, the civil air defense facility state monitoring device further comprises:
the maintenance module 307 is configured to visually display the safety warning information, and perform warning information analysis on the safety warning information to obtain a warning information analysis result; generating a remote maintenance strategy corresponding to the target civil air defense facility according to the alarm information analysis result; and generating a target maintenance work order according to the remote maintenance strategy, and dispatching the target maintenance work order to a target maintenance terminal.
In the embodiment of the invention, the state monitoring cloud platform is constructed to carry out all-around monitoring on the civil air defense facilities, the monitoring data of the target civil air defense facilities are collected, the data monitoring of the state monitoring cloud platform on the civil air defense facilities is realized, the gas state data, the equipment state data and the power supply state data of the civil air defense facilities are acquired in real time, the remote monitoring on the civil air defense, the gas state detection and the equipment detection result are realized, the unattended management requirement is met, and the management efficiency is improved; the method has the advantages that the civil air defense information construction and long-term operation and maintenance cost is reduced, the civil air defense service efficiency and the civil air defense service capacity are comprehensively improved, the gas state detection result and the equipment detection result corresponding to each equipment type are comprehensively detected and analyzed, the civil air defense facility monitoring result is obtained, the safety alarm information of the target civil air defense facility is generated according to the civil air defense facility monitoring result, the state monitoring intelligence of the civil air defense facility is realized, and the state monitoring accuracy of the civil air defense facility is improved.
Fig. 3 and fig. 4 describe the civil air defense facility status monitoring apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the civil air defense facility status monitoring device in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 5 is a schematic structural diagram of a civil air defense facility status monitoring device 500, which may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) for storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on storage medium 530 may include one or more modules (not shown), each of which may include a sequence of instructions operating on the air defense status monitoring apparatus 500. Still further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the personal air defense facility condition monitoring apparatus 500.
The personal protective equipment condition monitoring device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. Those skilled in the art will appreciate that the configuration of the figure 5 depicted in the form of a civil air defense status monitoring device does not constitute a limitation of the civil air defense status monitoring device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The invention also provides a state monitoring device of the civil air defense facility, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the state monitoring method of the civil air defense facility in the embodiments.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and which may also be a volatile computer readable storage medium, having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the method for monitoring the state of a personal protection arrangement.
Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. A civil air defense facility state monitoring method is characterized by comprising the following steps:
the method comprises the steps of obtaining monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, carrying out data classification extraction on the monitoring data, and obtaining a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data;
performing parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result; the parameter separation of the gas state data to obtain a plurality of parameter values, and the input of the plurality of parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result includes: performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting the plurality of parameter values into a preset gas state simulation model to perform gas state curve fitting to obtain a target gas state curve; carrying out curve analysis on the target gas state curve to obtain a gas state detection result;
performing data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and performing data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type;
respectively constructing the equipment state matrixes of the multiple equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type;
respectively inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain an equipment detection result corresponding to each equipment type;
and carrying out comprehensive detection analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
2. The civil air defense facility state monitoring method of claim 1, wherein the performing data fusion on the device state data and the power supply state data to obtain device fusion data, and performing data segmentation on the device fusion data according to a plurality of preset device types to obtain target fusion data corresponding to each device type comprises:
establishing a data association relation between the equipment state data and the power supply state data;
performing data fusion on the equipment state data and the power supply state data based on the data association relation to obtain equipment fusion data;
inquiring the device attributes of a plurality of preset device types to obtain the device attribute corresponding to each device type;
and performing data segmentation on the device fusion data based on the device attribute corresponding to each device type to obtain target fusion data corresponding to each device type.
3. The civil air defense facility state monitoring method of claim 1, wherein the step of respectively constructing the device state matrixes of the plurality of device types according to the target fusion data corresponding to each device type to obtain the target state matrix corresponding to each device type comprises the steps of:
performing data alignment on the target fusion data corresponding to each equipment type to obtain standard data corresponding to each equipment type;
performing data pair extraction on the standard data corresponding to each equipment type to obtain a plurality of data pairs corresponding to each equipment type;
and performing matrix conversion on a plurality of data pairs corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type.
4. The method for monitoring the state of the civil air defense facility according to claim 1, wherein the step of inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain the equipment detection result corresponding to each equipment type comprises the following steps:
inquiring the detection requirement of each equipment type from a preset state monitoring cloud platform;
selecting a target detection model from a preset equipment state detection model set according to the detection requirement of each equipment type, wherein the equipment state detection model set comprises: a deformation detection model, a working state detection model and a performance detection model;
and respectively inputting the target state matrix corresponding to each equipment type into the target detection model to carry out equipment state detection, and obtaining an equipment detection result corresponding to each equipment type.
5. The method for monitoring the state of the civil air defense facility according to claim 1, wherein the step of performing comprehensive detection analysis on the gas state detection result and the device detection result corresponding to each device type to obtain a civil air defense facility monitoring result, and generating the safety warning information of the target civil air defense facility according to the civil air defense facility monitoring result comprises the following steps:
traversing the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a traversal result;
extracting an abnormal detection result in the traversal result, and generating a civil air defense facility monitoring result according to the abnormal detection result;
and analyzing the abnormity type of the monitoring result of the civil air defense facility to obtain a target abnormity type, and generating safety alarm information of the target civil air defense facility according to the target abnormity type.
6. The civil air defense facility status monitoring method according to any of claims 1 to 5, characterized in that the civil air defense facility status monitoring method further comprises:
visually displaying the safety alarm information, and analyzing the safety alarm information to obtain an alarm information analysis result;
generating a remote maintenance strategy corresponding to the target civil air defense facility according to the alarm information analysis result;
and generating a target maintenance work order according to the remote maintenance strategy, and dispatching the target maintenance work order to a target maintenance terminal.
7. A civil air defense facility condition monitoring apparatus, characterized by comprising:
the acquisition module is used for acquiring monitoring data of a target civil air defense facility from a preset state monitoring cloud platform, and performing data classification and extraction on the monitoring data to obtain a plurality of state data, wherein the plurality of state data comprise: gas state data, equipment state data and power supply state data;
the detection module is used for carrying out parameter separation on the gas state data to obtain a plurality of parameter values, and inputting the parameter values into a preset gas state simulation model to carry out gas state detection to obtain a gas state detection result; the parameter separation of the gas state data to obtain a plurality of parameter values, and the input of the plurality of parameter values into a preset gas state simulation model for gas state detection to obtain a gas state detection result includes: performing data tagging processing on the gas state data to obtain a gas state tag; extracting parameter data from the gas state data based on a preset monitoring period and the gas state label to obtain a plurality of parameter values; inputting the plurality of parameter values into a preset gas state simulation model for gas state curve fitting to obtain a target gas state curve; carrying out curve analysis on the target gas state curve to obtain a gas state detection result;
the fusion module is used for carrying out data fusion on the equipment state data and the power supply state data to obtain equipment fusion data, and carrying out data segmentation on the equipment fusion data according to a plurality of preset equipment types to obtain target fusion data corresponding to each equipment type;
the building module is used for respectively building the equipment state matrixes of the multiple equipment types according to the target fusion data corresponding to each equipment type to obtain a target state matrix corresponding to each equipment type;
the processing module is used for inputting the target state matrix corresponding to each equipment type into a preset equipment state detection model set for equipment state detection to obtain an equipment detection result corresponding to each equipment type;
and the generating module is used for carrying out comprehensive detection analysis on the gas state detection result and the equipment detection result corresponding to each equipment type to obtain a civil air defense facility monitoring result, and generating safety alarm information of the target civil air defense facility according to the civil air defense facility monitoring result.
8. A civil air defense facility condition monitoring apparatus, characterized by comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invoking the instructions in the memory to cause the civil air defense status monitoring apparatus to perform the civil air defense status monitoring method of any of claims 1-6.
9. A computer readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement the personal protection device status monitoring method of any of claims 1-6.
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