CN116882773A - Emergency risk avoiding method and system for intelligent power plant - Google Patents
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Abstract
The application discloses an emergency risk avoiding method and system for an intelligent power plant, wherein the method comprises the steps of collecting historical accident data of the intelligent power plant, wherein the historical accident data at least comprises accident starting place positions, accident influence ranges, accident duration time and escape paths; establishing a first prediction model according to the building structure of the intelligent power plant and the influence weights of different positions in the building, and optimizing and testing the first prediction model according to the historical accident data to obtain a second prediction model; and acquiring real-time accident data of the intelligent power plant, and acquiring an emergency risk avoiding path by combining the second prediction model. When the escape route is generated and displayed through the light guide unit, people can escape timely according to the light guide unit, and meanwhile, people who escape can be prompted and guided through the voice guide unit, so that escape efficiency is greatly improved.
Description
Technical Field
The application relates to the technical field of intelligent power plants, in particular to an emergency risk avoiding method and system for an intelligent power plant.
Background
The intelligent power plant is built for establishing a modern energy power system to realize safe, efficient, green and low-carbon power generation, and is characterized in that the production process can be optimized autonomously, and related systems can collect, analyze, judge and plan own behaviors; at present, a large amount of combustible dangerous substances such as coal exist in an intelligent power plant, so that dangerous accidents such as fire disaster and the like are easy to occur in the power plant, and although an emergency danger avoiding system is arranged in the power plant, staff are panicked due to lack of guidance and accidents, so that internal staff cannot quickly avoid danger and escape.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present application has been made in view of the above-described problems occurring in the prior art.
Therefore, the application provides an emergency risk avoiding method and system for an intelligent power plant, which can solve the problems in the background technology.
In order to solve the technical problems, the application provides the following technical scheme that the emergency risk avoiding method for the intelligent power plant comprises the following steps:
collecting historical accident data of the intelligent power plant, wherein the historical accident data at least comprises accident starting place positions, accident influence ranges, accident duration time and escape paths;
establishing a first prediction model according to the building structure of the intelligent power plant and the influence weights of different positions in the building, and optimizing and testing the first prediction model according to the historical accident data to obtain a second prediction model;
and acquiring real-time accident data of the intelligent power plant, and acquiring an emergency risk avoiding path by combining the second prediction model.
An urgent danger prevention system for an intelligent power plant is characterized in that: comprises a data collection unit, an analog prediction unit, an early warning unit, a guiding unit and a control terminal unit,
the data collection unit is used for acquiring working condition data, monitoring data and data acquired by a sensor, which are generated in real time in the intelligent power plant, collecting historical accident data of the intelligent power plant and classifying the historical accident data;
the simulation prediction unit is used for establishing a prediction model and carrying out optimization updating on the prediction model according to the data acquired by the data collection unit;
the early warning unit is used for sending early warning to personnel in the intelligent power plant according to the data acquired by the data acquisition unit and the result predicted by the simulation prediction unit;
the guiding unit is used for carrying out physical guiding according to the prediction result of the simulation prediction unit and displaying the prediction result in a grading and classification manner;
and the control terminal unit is used for maintaining the data transmission of all the units and transmitting early warning information to the user terminal.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the simulation prediction unit comprises a building structure acquisition and classification module, a model building module and a model analysis module,
the building structure acquisition and classification module classifies the intelligent power plant buildings, any gate of the intelligent power plant is selected as an origin to establish a rectangular coordinate system, the direction of an enclosing wall where the selected gate is located is taken as a transverse axis, a vertical axis is established in the direction perpendicular to the transverse axis and passes through the origin to obtain the building coordinates inside the intelligent power plant and the straight line distance between the corresponding building and the origin, the building coordinates are named as building 1, building 2 and the number of the building n, and the building n is the total sum of all the buildings in the intelligent power plant;
and selecting any positive direction, and carrying out secondary classification naming on the interior of the building n according to the number of floors and rooms, wherein the secondary classification naming is named as building n-floor m-room k.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the analog prediction unit further comprises,
the model building module obtains the secondary classification naming of the building by the building structure obtaining and classifying module, and inputs the secondary classification naming into the built prediction model, and the prediction model is as follows:
wherein ,in order to predict escape route of accident point building n-layer m-room k after accident, t is evacuation time of non-accident building personnel, f (x) J ,y J ) For the length function of a path between one-layer escape door of accident building and a gate of intelligent power plant, x J Is the abscissa of the accident point, y J For the ordinate of the accident point, L (n, m, k) is the path length function of one-layer escape door of the floor where the accident point is located and the accident building, C (n, m, k) is the path length function of the escape door at the optimal position and distance when people in the room where the accident is located escape from the room where the accident is located, G min (n, m, k) is a path length function between the room in which the accident is located and the nearest escape door from the accident point;
the primary influence area is an accident room;
the secondary influence areas are a building n-layer m-room k-1 and a building n-layer m-room k+1, and if the building n-layer m-room k is an inflection point room, the secondary influence areas are the building n-layer m-room k-1 and the escape door with the smallest distance.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the analog prediction unit further comprises,
the model building module acquires the historical accident data acquired by the data collecting unit, divides the historical accident data into an optimized data set and a test data set according to the proportion of 2:1, and optimizes the prediction model, the primary influence area and the secondary influence area according to the position of an originating place in the historical accident data, the accident influence range, the accident duration and the escape path;
the optimized prediction model is as follows:
wherein, delta is the damage coefficient of the escape door at the optimal position, if the escape door at the optimal position is damaged, the delta is 1, if the escape door at the optimal position is not damaged, the delta is 0, and Z (n, m, k) is the path length function between different escape doors of the floor where the accident is located;
the primary influence area is optimized to be an accident occurrence room, a building n-layer m-room k-1 and a building n-layer m-room k+1, and if the building n-layer m-room k is an inflection point room, the primary influence area is the building n-layer m-room k-1 and an escape door with the minimum distance;
the secondary influence area is optimized to be a building n-layer m-room k-1, a building n-layer m-room k+1 and a building n-layer m+1-room k, if the building n-layer m-room k is an inflection point room, the secondary influence area is a building n-layer m+1-room k and an escape door with the minimum distance.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the early warning unit comprises a data acquisition module, a grading module, an alarm notification module and a data transmission module,
the data acquisition module is used for collecting the data acquired by the data acquisition unit and the result data predicted by the simulation prediction unit, carrying out structural processing, transmitting the processed data to the grading module, grading the alarm information by the grading module, dividing the primary influence area into first-class alarm information, dividing the secondary influence area into second-class alarm information, dividing the non-accident building into third-class alarm information, transmitting the alarm information of different grades to the guiding unit through the data transmission module, and carrying out corresponding grade alarm notification by the alarm notification module according to the grading result of the grading module;
when the warning situation is an first warning situation, the control terminal unit sends the optimal escape route diagram obtained by the simulation prediction unit to the user terminal, sounds an alarm corresponding to the building, flashes an alarm lamp in the first-level influence area and sounds a buzzer in the first-level influence area;
when the warning situation is a second warning situation, sending the optimal escape route map obtained by the simulation prediction unit to a user terminal through the control terminal unit, and sounding an alarm corresponding to the floor;
when the alarm condition is three-class alarm condition, accident warning information is directly sent to the user terminal, and an alarm corresponding to the building is sounded.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the guiding unit comprises a display screen module, a light control module and a voice notification module,
the guiding unit acquires the result data predicted by the simulation prediction unit, performs safety division on all escape paths, divides the paths into a safest path, a general safety path and a dangerous path according to escape time, escape safety and escape path length, and intelligently guides escape personnel according to the alarm condition notification state of the alarm condition notification module;
when the path is the safest path, the display screen module displays green arrows on all display screens on the safest path to point to escape directions, the light management module displays all lights on the safest path as green normally-on states, and the voice notification module notifies all voice notification modules on the safest path of the safety path;
when the path is a general safety path, the display screen module directs yellow arrows displayed by all display screens on the general safety path to the direction of the safest path, the lamplight management and control module displays all lamplight on the general safety path to be in a yellow normally-bright state, and all voice notification modules on the general safety path carry out notification of withdrawing from the place as soon as possible;
when the path is a dangerous path, the display screen module displays red cross numbers on all display screens on the safest path and flashes, the lamplight management and control module displays all lamplights on the safest path in a red normally-on state, and the voice notification module does not notify.
As a preferable scheme of the emergency risk avoiding system for the intelligent power plant, the application comprises the following steps: the control terminal unit transmits early warning information to the user terminal in real time, and transmits the changed path map to the user terminal if the escape route is changed, wherein the connection mode of the control terminal unit and the user terminal is wireless broadband network and short-distance wireless communication.
A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method as described above when executing the computer program.
A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method as described above.
The application has the beneficial effects that: the application provides an emergency risk avoiding method and system for an intelligent power plant, wherein the emergency risk avoiding method and system for the intelligent power plant are matched with units, when a fire disaster occurs in the power plant, the temperature sensing module and the smoke sensing module in the data acquisition unit can timely find out the fire disaster, the data acquisition unit transmits information to a control terminal, the control terminal transmits escape information to a user terminal, the escape route is simulated through a simulation prediction unit according to the position of the fire disaster, the simulation prediction unit is matched with the user terminal, the escape route is generated after the simulation prediction is completed, and the escape route is displayed through a light guide unit, so that people can escape timely according to the light guide unit, and meanwhile, the voice guide unit can prompt and guide people for escape, so that the escape efficiency is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a flow chart of a method and system for emergency risk avoidance for an intelligent power plant according to an embodiment of the present application;
fig. 2 is an internal structure diagram of a computer device of an emergency risk avoidance method and system for an intelligent power plant according to an embodiment of the present application.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1-2, a first embodiment of the present application provides an emergency risk avoidance method and system for an intelligent power plant, including:
collecting historical accident data of the intelligent power plant, wherein the historical accident data at least comprises accident starting place positions, accident influence ranges, accident duration time and escape paths;
furthermore, a first prediction model is established according to the building structure of the intelligent power plant and the influence weights of different positions in the building, and the first prediction model is optimized and tested according to the historical accident data to obtain a second prediction model;
furthermore, the real-time accident data of the intelligent power plant is obtained, and the emergency risk avoiding path is obtained by combining the second prediction model.
In one embodiment, an emergency risk avoidance system for an intelligent power plant includes a data collection unit 100, a simulation prediction unit 200, an early warning unit 300, a guidance unit 400, and a control terminal unit 500,
the data collection unit 100 is used for acquiring working condition data, monitoring data and data acquired by sensors, which are generated in real time in the intelligent power plant, collecting historical accident data of the intelligent power plant, and classifying the historical accident data;
the simulation prediction unit 200 is configured to establish a prediction model, and perform optimization update on the prediction model according to the data acquired by the data collection unit 100;
the early warning unit 300 is used for sending early warning to personnel in the intelligent power plant according to the data acquired by the data collecting unit 100 and the result predicted by the simulation predicting unit 200;
the guiding unit 400 is configured to perform physical guiding according to the prediction result of the simulation prediction unit 200, and stage and display the prediction result in a classified manner;
and the control terminal unit 500 is used for maintaining the data transmission of all units and transmitting the early warning information to the user terminal.
The simulation prediction unit 200 includes a building structure acquisition and classification module 201, a model building module 202, and a model analysis module 203.
Specifically, the building structure acquiring and classifying module 201 classifies the intelligent power plant building, selects any gate of the intelligent power plant as an origin to establish a rectangular coordinate system, uses the enclosure direction of the selected gate as a transverse axis, establishes a vertical axis perpendicular to the transverse axis direction and passing through the origin to acquire the building coordinates inside the intelligent power plant and the straight line distance between the corresponding building and the origin, and names the building 1, the building 2, the number of the building n and the number of the building n are the total sum of all the buildings in the intelligent power plant according to the order from small to large;
further, any positive direction is selected, and the interior of the building n is named as the building n-layer m-room k by carrying out secondary classification naming according to the number of floors and rooms.
Further, the model building module 202 obtains the secondary classification naming of the building by the building structure obtaining and classifying module 201, and inputs the secondary classification naming into the built prediction model, and the prediction model is:
wherein ,in order to predict escape route of accident point building n-layer m-room k after accident, t is evacuation time of non-accident building personnel, f (x) J ,y J ) For the length function of a path between one-layer escape door of accident building and a gate of intelligent power plant, x J Is the abscissa of the accident point, y J For the ordinate of the accident point, L (n, m, k) is the path length function of one-layer escape door of the floor where the accident point is located and the accident building, C (n, m, k) is the path length function of the escape door at the optimal position and distance when people in the room where the accident is located escape from the room where the accident is located, G min (n, m, k) is a path length function between the room in which the accident is located and the nearest escape door from the accident point;
it should be noted that the primary impact area is an accident occurrence room;
it should be noted that, the secondary influence areas are the building n-layer m-room k-1 and the building n-layer m-room k+1, and if the building n-layer m-room k is the inflection point room, the secondary influence areas are the building n-layer m-room k-1 and the escape door with the smallest distance.
Further, the model building module 202 obtains the historical accident data obtained by the data collecting unit 100, and divides the historical accident data into an optimized data set and a test data set according to the ratio of 2:1, and optimizes the prediction model, the primary influence area and the secondary influence area according to the position of the originating place in the historical accident data, the accident influence range, the accident duration and the escape route;
further, the optimized prediction model is as follows:
wherein, delta is the damage coefficient of the escape door at the optimal position, if the escape door at the optimal position is damaged, the delta is 1, if the escape door at the optimal position is not damaged, the delta is 0, and Z (n, m, k) is the path length function between different escape doors of the floor where the accident is located;
it should be noted that, the primary influence area is optimized as the accident occurrence room, the building n-layer m-room k-1 and the building n-layer m-room k+1, if the building n-layer m-room k is the inflection point room, the primary influence area is the building n-layer m-room k-1 and the escape door with the minimum distance;
it should be noted that the secondary influence area is optimized as building n-layer m-room k-1, building n-layer m-room k+1, and building n-layer m+1-room k if building n-layer m-room k is an inflection point room, and the secondary influence area is building n-layer m+1-room k and escape door with the smallest distance.
Further, the early warning unit 300 includes a data acquisition module 301, a classification module 302, an alarm notification module 303, and a data transmission module 304;
specifically, the data acquisition module 301 collects the data acquired by the data collection unit 100 and the result data predicted by the simulation prediction unit 200, performs structural processing, and transmits the processed data to the classification module 302, the classification module 302 classifies the warning information, the primary influence area is classified into an first warning condition, the secondary influence area is classified into a second warning condition, the non-accident building is classified into a third warning condition, and the warning information of different grades is transmitted to the guide unit 400 through the data transmission module 304, and the warning notification module 303 performs corresponding grade warning notification according to the classification result of the classification module 302;
further, when the alarm condition is an first alarm condition, the control terminal unit 500 sends the optimal escape route map obtained by the simulation prediction unit 200 to the user terminal, sounds an alarm corresponding to the building, blinks an alarm lamp in the first-level influence area, and sounds a buzzer in the first-level influence area;
further, when the warning situation is the second warning situation, the control terminal unit 500 sends the optimal escape route map obtained by the simulation prediction unit 200 to the user terminal, and sounds the alarm corresponding to the floor;
furthermore, when the alarm condition is three-class alarm condition, accident warning information is directly sent to the user terminal, and an alarm corresponding to the building is sounded.
It should be noted that, the guiding unit 400 includes a display screen module 401, a light management module 402, and a voice notification module 403;
furthermore, the guiding unit 400 obtains the result data predicted by the simulation prediction unit 200, performs security division on all escape paths, divides the paths into a safest path, a normal safe path and a dangerous path according to the escape time, the escape security and the escape path length, and performs intelligent guiding on the evacuee according to the alarm notification state of the alarm notification module 303;
it should be noted that, when the path is the safest path, the display screen module 401 directs all display screens on the safest path to display green arrows in the escape direction, the light management module 402 displays all lights on the safest path as green normally-on status, and the voice notification module 403 notifies all voice notification modules on the safest path of the safe path;
it should be noted that, when the path is a general safety path, the display screen module 401 directs all display screens on the general safety path to display yellow arrows in the direction of the safest path, the light management module 402 displays all lights on the general safety path as yellow normally-on status, and the voice notification module 403 performs a prompt evacuation notification from the place on the general safety path;
it should be noted that, when the path is a dangerous path, the display screen module 401 displays red cross numbers on all display screens on the safest path and blinks, the light management module 402 displays all lights on the safest path as red normally-on states, and the voice notification module 403 does not notify.
It should be noted that, the control terminal unit 500 includes transmitting early warning information to the user terminal in real time, and if the escape route is changed, the control terminal unit 500 transmits the changed path map to the user terminal, and the connection mode between the control terminal unit 500 and the user terminal is wireless broadband network and short-distance wireless communication.
The above unit modules may be embedded in hardware or independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above units.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 2. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program when executed by the processor implements an emergency risk avoidance method for an intelligent power plant. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
collecting historical accident data of the intelligent power plant, wherein the historical accident data at least comprises accident starting place positions, accident influence ranges, accident duration time and escape paths;
establishing a first prediction model according to the building structure of the intelligent power plant and the influence weights of different positions in the building, and optimizing and testing the first prediction model according to the historical accident data to obtain a second prediction model;
and acquiring real-time accident data of the intelligent power plant, and acquiring an emergency risk avoiding path by combining the second prediction model.
Example 2
Referring to fig. 1-2, for one embodiment of the present application, an emergency risk avoidance method and system for an intelligent power plant are provided, and in order to verify the beneficial effects of the present application, a scientific demonstration is performed through a comparative experiment.
TABLE 1 Emergency danger avoidance data for a building 2-floor 5-Room 1 in a Smart Power plant at an Accident floor
Table 1 shows the data obtained when an accident exercise is performed in a smart power plant, only one person is injured at the end of the accident exercise, and the rest of the people are evacuated to the safety zone outside the smart power plant according to the paths on time. According to the emergency risk avoiding method and system for the intelligent power plant, through cooperation among units, when a fire disaster occurs in the power plant, the temperature sensing module and the smoke sensing module in the data acquisition unit can be found in time, information is transmitted to the control terminal through the data collection unit, escape information is sent to the user terminal through the control terminal, the escape route is simulated through the simulation prediction unit according to the position where the fire disaster occurs, the unit cooperation is performed after the simulation prediction is completed, the escape route is generated and displayed through the light guide unit, people can escape timely according to the light guide unit, meanwhile, the voice guide unit can prompt and guide people who escape, and escape efficiency is greatly improved.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered in the scope of the claims of the present application.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be realized by adopting various computer languages, such as object-oriented programming language Java, an transliteration script language JavaScript and the like.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. An emergency risk avoiding method for an intelligent power plant is characterized by comprising the following steps of: comprising the steps of (a) a step of,
collecting historical accident data of the intelligent power plant, wherein the historical accident data at least comprises accident starting place positions, accident influence ranges, accident duration time and escape paths;
establishing a first prediction model according to the building structure of the intelligent power plant and the influence weights of different positions in the building, and optimizing and testing the first prediction model according to the historical accident data to obtain a second prediction model;
and acquiring real-time accident data of the intelligent power plant, and acquiring an emergency risk avoiding path by combining the second prediction model.
2. An urgent danger prevention system for an intelligent power plant is characterized in that: comprises a data collection unit (100), an analog prediction unit (200), an early warning unit (300), a guiding unit (400) and a control terminal unit (500),
the data collection unit (100) is used for acquiring working condition data, monitoring data and data acquired by a sensor, which are generated in real time in the intelligent power plant, collecting historical accident data of the intelligent power plant and classifying the historical accident data;
the simulation prediction unit (200) is used for establishing a prediction model and carrying out optimization updating on the prediction model according to the data acquired by the data collection unit (100);
the early warning unit (300) is used for sending early warning to personnel in the intelligent power plant according to the data acquired by the data acquisition unit (100) and the result predicted by the simulation prediction unit (200);
the guiding unit (400) is used for carrying out physical guiding according to the prediction result of the simulation prediction unit (200) and displaying the prediction result in a grading and classification manner;
and the control terminal unit (500) is used for maintaining data transmission of all units and transmitting early warning information to the user terminal.
3. The emergency evacuation system for an intelligent power plant of claim 2, wherein: the simulation prediction unit (200) comprises a building structure acquisition and classification module (201), a model establishment module (202) and a model analysis module (203),
the building structure acquisition and classification module (201) classifies the intelligent power plant buildings, any gate of the intelligent power plant is selected as an origin to establish a rectangular coordinate system, the direction of a wall where the selected gate is located is taken as a transverse axis, a vertical axis is established in the direction perpendicular to the transverse axis and passing through the origin, the building coordinates inside the intelligent power plant and the straight line distance between the corresponding building and the origin are obtained, the building is named as building 1, building 2, the number of the building n is the total number of all the buildings in the intelligent power plant according to the sorting naming from small to large;
and selecting any positive direction, and carrying out secondary classification naming on the interior of the building n according to the number of floors and rooms, wherein the secondary classification naming is named as building n-floor m-room k.
4. An emergency evacuation system for an intelligent power plant as claimed in claim 3, wherein: the analog prediction unit (200) further comprises,
the model building module (202) obtains the secondary classification naming of the building by the building structure obtaining and classifying module (201), and inputs the secondary classification naming into the built prediction model, wherein the prediction model is as follows:
wherein ,in order to predict escape route of accident point building n-layer m-room k after accident, t is evacuation time of non-accident building personnel, f (x) J ,y J ) For the length function of a path between one-layer escape door of accident building and a gate of intelligent power plant, x J Is the abscissa of the accident point, y J For the ordinate of the accident point, L (n, m, k) is the path length function of one-layer escape door of the floor where the accident point is located and the accident building, C (n, m, k) is the path length function of the escape door at the optimal position and distance when people in the room where the accident is located escape from the room where the accident is located, G min (n, m, k) is a path length function between the room in which the accident is located and the nearest escape door from the accident point;
the primary influence area is an accident room;
the secondary influence areas are a building n-layer m-room k-1 and a building n-layer m-room k+1, and if the building n-layer m-room k is an inflection point room, the secondary influence areas are the building n-layer m-room k-1 and the escape door with the smallest distance.
5. The emergency evacuation system for an intelligent power plant of claim 4, wherein: the analog prediction unit (200) further comprises,
the model building module (202) acquires the historical accident data acquired by the data collecting unit (100), divides the historical accident data into an optimized data set and a test data set according to the proportion of 2:1, and optimizes the prediction model, the primary influence area and the secondary influence area according to the starting place position, the accident influence range, the accident duration and the escape path in the historical accident data;
the optimized prediction model is as follows:
wherein, delta is the damage coefficient of the escape door at the optimal position, if the escape door at the optimal position is damaged, the delta is 1, if the escape door at the optimal position is not damaged, the delta is 0, and Z (n, m, k) is the path length function between different escape doors of the floor where the accident is located;
the primary influence area is optimized to be an accident occurrence room, a building n-layer m-room k-1 and a building n-layer m-room k+1, and if the building n-layer m-room k is an inflection point room, the primary influence area is the building n-layer m-room k-1 and an escape door with the minimum distance;
the secondary influence area is optimized to be a building n-layer m-room k-1, a building n-layer m-room k+1 and a building n-layer m+1-room k, if the building n-layer m-room k is an inflection point room, the secondary influence area is a building n-layer m+1-room k and an escape door with the minimum distance.
6. The emergency evacuation system for an intelligent power plant of claim 5, wherein: the early warning unit (300) comprises a data acquisition module (301), a grading module (302), an alarm notification module (303) and a data transmission module (304),
the data acquisition module (301) collects data acquired by the data collection unit (100) and result data predicted by the simulation prediction unit (200), performs structuring processing, transmits the processed data to the grading module (302), the grading module (302) grades alarm information, divides the primary influence area into a first class alarm, divides the secondary influence area into a second class alarm, divides a non-accident building into a third class alarm, and transmits alarm information of different grades to the guide unit (400) through the data transmission module (304), and the alarm notification module (303) performs corresponding grade alarm notification according to the grading result of the grading module (302);
when the warning situation is an first warning situation, the optimal escape route diagram obtained by the simulation prediction unit (200) is sent to a user terminal through the control terminal unit (500), an alarm corresponding to a building is sounded, an alarm lamp in the primary influence area is twinkled, and a buzzer in the primary influence area is sounded;
when the warning situation is a second warning situation, sending the optimal escape route map acquired by the simulation prediction unit (200) to a user terminal through the control terminal unit (500), and sounding an alarm of a corresponding floor;
when the alarm condition is three-class alarm condition, accident warning information is directly sent to the user terminal, and an alarm corresponding to the building is sounded.
7. The emergency evacuation system for an intelligent power plant of claim 6, wherein: the guiding unit (400) comprises a display screen module (401), a light management module (402) and a voice notification module (403),
the guiding unit (400) acquires the result data predicted by the simulation prediction unit (200), performs safety division on all escape paths, divides the paths into a safest path, a general safety path and a dangerous path according to escape time, escape safety and escape path length, and intelligently guides escape personnel according to the alarm notification state of the alarm notification module (303);
when the path is the safest path, the display screen module (401) displays all display screens on the safest path to point to the escape direction, the light management and control module (402) displays all lights on the safest path to be in a green normally-on state, and the voice notification module (403) notifies all voice notification modules on the safest path of the safe path;
when the path is a general safety path, the display screen module (401) displays yellow arrows on all display screens on the general safety path to point to the direction of the safest path, the light management and control module (402) displays all lights on the general safety path as yellow normally-bright state, and the voice notification module (403) performs a notification of a simple and rapid evacuation from the place by all voice notification modules on the general safety path;
when the path is a dangerous path, the display screen module (401) displays red cross numbers on all display screens on the safest path and flashes, the lamplight management module (402) displays all lamplights on the safest path in a red normally-on state, and the voice notification module (403) does not notify.
8. The emergency evacuation system for an intelligent power plant of claim 7, wherein: the control terminal unit (500) comprises the steps of transmitting early warning information to the user terminal in real time, and if the escape route is changed, the control terminal unit (500) transmits the changed path map to the user terminal, and the connection mode of the control terminal unit (500) and the user terminal is wireless broadband network and short-distance wireless communication.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method as claimed in claim 1 when executing the computer program.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method as claimed in claim 1.
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