Intelligent nuclear power fire-fighting monitoring method and system

Abstract

The invention provides an intelligent nuclear power fire-fighting monitoring method and system. The method comprises the following steps: acquiring equipment data of fire detection equipment and fire-fighting linkage equipment; cleaning the equipment data to obtain equipment processing data; the current equipment processing data and a normal reference value of the current equipment processing data are compared and analyzed, equipment health degree prediction is obtained, and the normal reference value is obtained through calculation according to historical statistical equipment processing data; and sending the position information of the corresponding fire detection equipment and the fire-fighting linkage equipment and the equipment health degree prediction information to a display screen for display. Therefore, equipment health degree prediction information is obtained through a digital technology, the health state of the equipment can be effectively predicted through an analysis method combining current equipment data and historical data, potential problems can be found in advance, proper measures are taken to ensure that the equipment can work normally when a fire occurs, and the safety of the equipment is improved. And loss of personnel and property is reduced to the greatest extent.

Description

Technical Field

[0001] The present invention relates to the technical field of fire early warning, and in particular to an intelligent nuclear power fire monitoring method and system. Background Art

[0002] The structure of a nuclear power plant is complex, involving multiple systems and equipment. Fires may affect key safety facilities such as cooling systems, power supply, and control systems, thereby increasing the risk of accidents. There are a large number of radioactive materials inside a nuclear power plant, and any fire may cause radioactive material leakage. If the fire is not controlled in time, it may cause a larger-scale accident, causing a chain reaction and aggravating the severity of the accident. Timely and effective fire warnings can ensure that personnel can be evacuated quickly and take appropriate countermeasures to ensure the safety of personnel and property. Therefore, nuclear power plants need to pay special attention to the construction and maintenance of fire protection systems to ensure efficient and reliable response capabilities and reduce potential risks.

[0003] The existing nuclear power fire protection system mainly includes various types of fire detectors, relay modules, input / output modules, and manual fire alarms, which mainly play the role of fire alarm and alarm information transmission. Each link is mainly completed manually, including the overall status and performance of equipment such as fire detection equipment and fire linkage equipment during operation, which also requires manual judgment. That is, manual information collection, manual analysis and decision-making, and manual execution have not fully utilized the role of digital technology in nuclear power fire protection. Therefore, it is necessary to design an intelligent nuclear power fire monitoring method and system to solve the current problems of insufficient intelligence and safety of nuclear power fire protection. Summary of the invention

[0004] In view of some of the shortcomings of the above-mentioned prior art, the present invention provides an intelligent nuclear power fire monitoring method and system, which uses digital technology to predict the health of fire-fighting equipment, ensures effective detection of fire situations and timely implementation of rescue measures, and reduces casualties and property losses.

[0005] To achieve the above-mentioned purpose and other related purposes, the present invention provides an intelligent nuclear power fire monitoring method, comprising:

[0006] Obtain equipment data of fire detection equipment and fire linkage equipment;

[0007] Clean the equipment data to obtain equipment processing data;

[0008] Compare and analyze the current equipment processing data with its normal reference value to obtain equipment health prediction, where the normal reference value is calculated based on historical statistical equipment processing data;

[0009] The location information of the corresponding fire detection equipment and fire linkage equipment and their equipment health prediction information are sent to the display screen for display.

[0010] As one embodiment of the present invention, the calculation formula of the normal reference value is:

[0011] Among them, x1 is the initial value of the device, that is, the set value, x2 is the average value of the historical statistical device processing data, w1 and w2 are the weights of x1 and x2 respectively.

[0012] As one embodiment of the present invention, the calculation of the weight w2 includes:

[0013]

[0014] Among them, e -kx is an exponential decay term, where k is a positive constant.

[0015] As one embodiment of the present invention, the calculation of the average value of the device processing data includes the following steps:

[0016] Step 1: Create a first data set and a second data set, the first data set is used to accumulate the sum of all added data points, and the second data set is used to record the number of added data points; wherein the data of the data point is the device processing data;

[0017] Step 2: Add new data points to the current first data set and second data set;

[0018] Step 3: Check whether the second data set is 0. When the second data set is 0, end the current operation; otherwise, divide the first data set by the second data set to obtain the current average value, that is, the average value of the device processing data.

[0019] As one embodiment of the present invention, the step of sending the location information of the corresponding fire detection equipment and fire linkage equipment and the equipment health prediction information thereof to the display screen for display includes:

[0020] Obtain building structure data;

[0021] Fuse the equipment data of fire detection equipment and fire linkage equipment with the building structure data, and establish a 3D visualization model;

[0022] The location information of the corresponding fire detection equipment and fire linkage equipment and their equipment health prediction information are displayed in the 3D visualization model.

[0023] As one of the embodiments of the present invention, a method for fusing equipment data of fire detection equipment and fire linkage equipment with building structure data is a coordinate system mapping method, including: converting the regional location information of the fire detection equipment and the fire linkage equipment into a coordinate system in the building structure so that the equipment and its corresponding regional location information match.

[0024] As one embodiment of the present invention, the method further includes:

[0025] Obtain equipment data of temperature and humidity sensors in key areas;

[0026] Compare the environmental monitoring data of the temperature and humidity sensor with its normal environmental reference value to obtain regional fire warning information of the key areas monitored by the temperature and humidity sensor;

[0027] Among them, the normal environmental reference value is calculated based on historical statistical environmental monitoring data.

[0028] As one embodiment of the present invention, the key area includes a hazardous material storage area, and its location information can be obtained by manually entering or acquiring the material storage information in the nuclear power warehouse management system and displayed in a 3D visualization model.

[0029] As one embodiment of the present invention, the method further includes: based on the input inspection signal, calling the historical device processing data of the corresponding device to inspect the device.

[0030] To achieve the above-mentioned purpose and other related purposes, the present invention also includes an intelligent nuclear power fire monitoring system, including:

[0031] Data acquisition module, which obtains the equipment data of fire detection equipment and fire linkage equipment;

[0032] The data processing module cleans the device data to obtain device processing data;

[0033] The analysis module calculates the normal reference value based on the historical statistical equipment processing data; compares and analyzes the current equipment processing data with its normal reference value to obtain the equipment health prediction;

[0034] The visualization module displays the location information of the device and its device health prediction information.

[0035] The present invention has at least the following beneficial technical effects:

[0036] (1) An intelligent nuclear power fire monitoring method and system of the present invention includes obtaining equipment data of fire detection equipment and fire linkage equipment; cleaning the equipment data to obtain equipment processing data; calculating its normal reference value based on historical statistical equipment processing data; comparing the current equipment processing data with its normal reference value to obtain equipment health prediction; displaying the location information of the equipment and its equipment health prediction information. By obtaining the equipment health prediction information through digital technology and combining the analysis method of current equipment data with historical data, the health status of the equipment can be effectively predicted, potential problems can be discovered in advance, and appropriate measures can be taken to ensure that it can work normally when a fire occurs, and to ensure that the nuclear power fire protection system can accurately and timely discover and handle fires, thereby minimizing the loss of personnel and property.

[0037] (2) The equipment health prediction of the present invention is to use the historical statistical data of the equipment to calculate its corresponding normal reference value, and compare the current equipment processing data with its normal reference value. In addition, as the equipment is running, the historical statistical data is continuously updated, so that the obtained equipment health is updated in real time, achieving the purpose of real-time monitoring of fire protection system equipment. The operating conditions, use environment and operation mode of each device are different. The historical statistical data can capture these individual differences, so that the reference value can be better adapted to the specific device. This helps to ensure the accuracy of the results and ensure that the equipment operates in the best condition.

[0038] (3) The present invention obtains building structure data, fuses the equipment data of fire detection equipment and fire linkage equipment with the building structure data, and establishes a 3D visualization model; the location information of the corresponding fire detection equipment and fire linkage equipment and its equipment health prediction information are displayed in the 3D visualization model. When the fire detection equipment sends out a fire alarm or the equipment health predicts that the equipment has a problem and needs maintenance, the regional location information of the equipment can be displayed through the 3D visualization model, allowing firefighters to arrive in time and improve work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 This is a flow chart of an intelligent nuclear power fire monitoring method in one embodiment of the present invention;

[0041] Figure 2 A system diagram of an intelligent nuclear power fire monitoring system in one embodiment of the present invention;

[0042] Figure 3 The figure is a working principle diagram of an intelligent nuclear power fire monitoring system in one embodiment of the present invention.

[0043] Among them, there are a data acquisition module 10, a data processing module 20, an analysis module 30, and a visualization module 40. DETAILED DESCRIPTION

[0044] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0045] It should be noted that the illustrations provided in the following embodiments are only used to illustrate the basic concept of the present invention in a schematic manner, and thus the illustrations only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0046] See also Figure 1 and Figure 2 To achieve the above-mentioned purpose and other related purposes, the present invention provides an intelligent nuclear power fire monitoring method, comprising the following steps: S1, obtaining equipment data of fire detection equipment and fire linkage equipment; S2, cleaning the equipment data to obtain equipment processing data; S3, comparing and analyzing the current equipment processing data with its normal reference value to obtain equipment health prediction, wherein the normal reference value is calculated based on historical statistical equipment processing data; S4, sending the location information of the corresponding fire detection equipment and fire linkage equipment and its equipment health prediction information to the display screen for display.

[0047] It should be noted that the fire linkage equipment can be equipped with sensors as needed to sense its status and obtain equipment data of the fire linkage equipment.

[0048] Furthermore, cleaning the device data can improve the quality and reliability of the data, making subsequent analysis and decision-making more accurate. Cleaning can include removing duplicate data: you can use the drop_duplicates() function of pandas. Identify and delete duplicate records to ensure that each record is unique; fill or delete missing values: use the mean, median, or interpolation method to fill; directly delete rows or columns with missing values. Denoising: use smoothing techniques (such as moving average) to remove noise in the data. Handling outliers: determine the upper and lower limits of the values ​​and filter out outliers.

[0049] Furthermore, the current device processing data is compared with its normal reference value to obtain a prediction of the device health. For example, methods such as Z-score and IQR can be used to identify deviations. Health score: Based on the difference, a health score can be generated. This score may be a percentage, indicating how close the current state of the device is to the ideal state, or a classification, such as normal, warning, abnormal state, etc. Normal state: If the current data is not significantly different from the normal reference value, the health score is within the normal range, indicating that the device is operating well. Warning state: If the current data deviates from the normal reference value, but is still within an acceptable range, attention may be required. At this point, the health score may be in the warning range, and monitoring is recommended. Abnormal state: If the current indicator is significantly lower or higher than the normal reference value, the device may be faulty or about to fail. The health score may be displayed as abnormal, requiring immediate inspection and maintenance.

[0050] It should be noted that fire detection equipment may include smoke and temperature detectors, flame detectors and combustible gas detectors. A microcontroller is integrated on the smoke and temperature detector, which is generally implemented through a built-in smart chip. It has strong computing power and sufficient memory, and can execute complex algorithms and real-time data processing. The smoke and temperature detector can immediately determine whether an alarm signal is generated during the signal acquisition process. The smoke and temperature detector can analyze the dust accumulation information in the environment. For example, it can determine whether long-term dust accumulation affects the accuracy of the signal through the "dust accumulation algorithm", and can even determine the possible existence of a fire based on the change pattern of the dust. The flame detector uses a higher-performance infrared flame detector and utilizes more advanced infrared sensors, spectral analysis and data processing technology, which significantly improves its sensitivity, accuracy and anti-interference ability. The above-mentioned fire detection equipment can send an alarm signal when a fire is detected. The alarm signal can be displayed synchronously on the display end of the visualization module 40.

[0051] It should be noted that fire linkage equipment may include fire sprinkler heads, fire doors, fire dampers and smoke exhaust systems. It is crucial to ensure that these facilities can function effectively in critical situations. For example, smart sensors are used to monitor whether fire doors are closed to ensure that they can prevent the spread of fire when a fire occurs. In the event of a fire, the fire door can be automatically closed (equipped with smart sensors) to ensure that it remains closed at critical moments to prevent the spread of smoke and flames. The main function of the smoke exhaust system is to promptly exhaust the smoke and harmful gases generated at the fire scene, improve the escape environment, and increase the chance of escape of personnel. Through smoke exhaust, the temperature at the fire scene can be effectively reduced, thereby slowing down the development and spread of the fire. The smoke exhaust system is usually linked with the building's ventilation system to ensure that effective air flow can be quickly organized to help evacuate smoke when a fire occurs.

[0052] As one embodiment of the present invention, the calculation formula of the normal reference value is: Formula (1)

[0053] Among them, x1 is the initial value of the device, that is, the set value, x2 is the average value of the historical statistical device processing data, and w1 and w2 are the weights of x1 and x2 respectively.

[0054] The calculation of weight w2 includes:

[0055]

[0056] Among them, e -kx is an exponential decay term, where k is a positive constant and x is an independent variable, usually representing time or distance.

[0057] The above formulas (1) and (2) combine the initial value of the device and the average value of historical statistical data, and adjust the weight through the exponential decay term so that the normal reference value can reflect the current state of the device.

[0058] Using weight functions with initial values ​​and asymptotic properties, many situations in actual problems can be simulated. For example, as time goes by and data changes, the updated data may be more important than the set value. In this case, dynamic weights can reflect such actual situations. The use of weighted averages can also help simplify complex data analysis processes, especially when dealing with multiple data sources or multi-stage statistics. Weighted averages can be conveniently used for fitting models, predictive analysis, etc., and weight allocation can more easily form a comprehensive result. Combining set values ​​with new statistical data and using dynamic weights to calculate weighted averages can provide decision makers with more accurate and real-time information assistance to help make more informed decisions.

[0059] In summary, by using adjustable weights to calculate the weighted average, this method not only improves the flexibility and adaptability of the analysis, but also effectively deals with complexity and uncertainty, providing strong support for decision-making.

[0060] As one embodiment of the present invention, the calculation of the average value of the device processing data includes the following steps:

[0061] Step 1: Create a first data set and a second data set, the first data set is used to accumulate the sum of all added data points, and the second data set is used to record the number of added data points; wherein the data of the data point is the device processing data;

[0062] Step 2: Add new data points to the current first data set and second data set;

[0063] Step 3: Check whether the second data set is 0. When the second data set is 0, end the current operation; otherwise, divide the first data set by the second data set to obtain the current average value, that is, the average value of the device processing data.

[0064] The present invention realizes intelligent data processing, uses historical statistical data to calculate the corresponding normal reference value, compares the current equipment processing data with its normal reference value, and obtains the equipment health. (1) Historical statistical data provides real performance information of the equipment under normal operating conditions. This information serves as a benchmark to help define the "normal" state. Using real data rather than assumptions or theoretical models can more accurately reflect the actual situation. (2) The operating conditions, usage environment and operating methods of each device are different. Historical statistical data can capture these individual differences, so that the reference value can be better adapted to the specific device. This helps to avoid inaccuracies caused by overly general models. (3) Analysis of historical data can reveal long-term trends and periodic changes in equipment performance, such as wear, aging and other phenomena. This trend identification can help formulate more optimized maintenance strategies to ensure that the equipment operates in the best condition.

[0065] Therefore, the fire protection system of the present invention obtains equipment health prediction by continuously monitoring the status of fire detection equipment and fire linkage equipment. Monitoring the operating status of fire detection equipment can ensure its sensitivity and accuracy, improve the timeliness and accuracy of fire warning, and reduce the losses caused by fire. At the same time, it ensures that the fire detector can accurately and timely detect the fire source when a fire occurs, and quickly send alarm information, and the response time will not be delayed due to equipment failure. Detecting the operating status of fire linkage equipment can ensure that emergency measures are taken in time when a fire occurs, reducing the loss of personnel and property.

[0066] It should be noted that the equipment data of fire detection equipment and fire linkage equipment includes equipment status data, equipment operation data and equipment fault data. Equipment status data generally includes the current status information of the equipment, such as operating status, stop status, warning status, etc. Status data can reflect the immediate health status of the equipment and help identify whether the equipment is in normal operation. Equipment operation data includes performance indicators of the equipment within a specific time period, such as operating time, load, current, temperature, vibration, etc. Operation data can provide the performance of the equipment under normal working conditions, help determine whether the equipment is operating within the normal range, and its performance under different workloads. Equipment fault data includes historical fault information, such as the time, type, severity, maintenance record, etc. of the fault. Fault data can provide historical performance records of the equipment, help identify potential patterns and causes of failures, and thus perform trend analysis and prediction.

[0067] For example, the health prediction of fire detection equipment:

[0068] Current equipment data for fire detection equipment includes:

[0069] Status data: Current status: Normal operation (no alarm)

[0070] Operation data: Current temperature: 24°C (ambient temperature), Current humidity: 50% (relative humidity), Current smoke concentration: 0.5% (lower than the alarm threshold)

[0071] Fault data: Current fault status: No fault; Last fault alarm record: An overtemperature fault was reported 6 months ago and has been repaired after inspection.

[0072] Normal reference values ​​(past 7 days):

[0073] Temperature: 25℃, humidity: 48%, smoke concentration: 0.3%;

[0074] Last self-inspection pass rate: All the past 30 self-inspections have passed;

[0075] Compare the current equipment data with its normal reference value:

[0076] Temperature comparison: The current temperature of 24°C is close to the average temperature of 25°C, indicating that the working environment of the fire detector is within the normal range.

[0077] Humidity comparison: The current humidity of 50% is slightly higher than the average humidity of 48%. The increase in humidity may affect the sensitivity of the detector, so you need to pay attention to environmental changes.

[0078] Smoke density comparison: The current smoke density of 0.5% is higher than the historical average of 0.3%, but still below the alarm threshold. It shows normal working status. It is necessary to continue to monitor the changes in smoke density to prevent fire.

[0079] Fault status: There is no fault at present and the self-test result is normal, indicating that the detector is in good equipment health.

[0080] The health prediction results of the fire detection equipment are obtained: Combined with the above comparative analysis, the fire detector is in good health under the current situation and no abnormalities are found. However, it should be noted that if the temperature and smoke concentration continue to rise in the following monitoring data, it should be a cause of alarm. Through this analysis method that combines current equipment data with normal parameters, the health status of the fire detector can be effectively predicted, potential problems can be discovered in advance, and appropriate measures can be taken to ensure that it can work normally when a fire occurs.

[0081] As one embodiment of the present invention, the step of sending the location information of the corresponding fire detection equipment and fire linkage equipment and the equipment health prediction information thereof to the display screen for display includes:

[0082] Obtain building structure data;

[0083] (1) Fuse the equipment data of fire detection equipment and fire linkage equipment with the building structure data and establish a 3D visualization model;

[0084] (2) Display the location information of the corresponding fire detection equipment and fire linkage equipment and their equipment health prediction information in the 3D visualization model.

[0085] Among them, the method of fusing the equipment data of fire detection equipment and fire linkage equipment with the building structure data is a coordinate system mapping method, including: converting the regional location information of fire detection equipment and fire linkage equipment into a coordinate system in the building structure so that the equipment and its corresponding regional location information match.

[0086] It should be noted that the establishment of a 3D visualization model includes: (1) Using 3D modeling software (such as Blender, AutoCAD, SketchUp, etc.) to create a 3D model of the building. Game engines (such as Unity or Unreal Engine) can be used for more powerful visualization and interactive functions. (2) Creating a building structure model: Establish a building model according to the architectural design drawings, including walls, equipment locations, doors and windows and other structures. Make sure to align the model's coordinate system and define the origin and coordinate axes. (3) Import or integrate building information model (BIM) data: If there is an existing BIM model, you can import the building's 3D structure to reduce the modeling workload. (3) Set the coordinate system: Clarify the coordinate system inside the building (such as the lower left corner as the origin, the positive direction of the X, Y, and Z axes, etc.) to ensure that the subsequent equipment positions can accurately match the building model positions.

[0087] The data fusion of the equipment data of the fire detection equipment and the fire linkage equipment and the building structure data further includes: (1) Establishing a structural database compatible with the equipment data. (2) Coordinate system mapping: Developing a coordinate conversion algorithm to convert the equipment's location data (usually relative coordinates or absolute coordinates) into global coordinates in the building model. (3) Combining the equipment's status and health prediction information with its corresponding regional location information. Through mapping, ensure that the visualization information of each device in the 3D model is consistent with its actual location. (4) Use 3D visualization tools to dynamically draw the location and health status of the equipment in the model. For example, the equipment health information can be displayed through color changes, icon style changes, etc. For example: green represents normal, yellow represents warning, and red represents failure.

[0088] It should be noted that the 3D visualization model can associate data from different sources and provide a comprehensive view, such as building structure data, equipment health, and regional warning information for key areas. The display of the 3D visualization model can be divided into regions. Specifically, the 3D model can be divided into different functional areas (such as office areas, warehouses, production areas, public areas, etc.). Each area can display specific firefighting equipment and layouts. The location of fire linkage equipment, such as fire extinguishers, fire hydrants, alarms, sprinkler systems, and ventilation systems, is displayed in different areas. This allows relevant personnel to quickly find and check the equipment. Display the status (equipment health) of each device, and present it intuitively through color or marking. In the event of a fire, the alarm points of each fire detection equipment can be accurately displayed through the 3D visualization model, the scope of the fire can be accurately controlled, and the firefighting route and firefighting measures can be planned according to the scope of the fire.

[0089] As one embodiment of the present invention, the method further includes: (1) acquiring device data of a temperature and humidity sensor in a key area; (2) comparing the environmental monitoring data of the temperature and humidity sensor with its environmental normal reference value to obtain regional fire warning information of the key area monitored by the temperature and humidity sensor;

[0090] The environmental normal reference value is calculated based on historical environmental monitoring data. The key areas include hazardous material storage areas, whose location information can be obtained through manual entry or by obtaining material storage information in the nuclear power warehouse management system and displayed in the 3D visualization model.

[0091] Furthermore, the information of firefighters can also be connected to the 3D visualization model, so that when a fire occurs, firefighters in the area can be deployed in a timely manner. And according to the safety exits and evacuation routes clearly marked in the 3D model, it is ensured that when a fire occurs, personnel can quickly find a safe evacuation route.

[0092] As one embodiment of the present invention, the method further includes: based on the input inspection signal, calling the historical device processing data of the corresponding device to inspect the device.

[0093] It should be noted that equipment inspection is a crucial link in equipment management, maintenance and emergency response. Through regular inspections, abnormal conditions of equipment, such as failures, wear and tear or aging, can be discovered in time to ensure that the equipment can work normally and reduce the risk of failure and downtime. Monitor the performance indicators of the equipment to ensure that the equipment operates within the specified performance range. If performance degradation is found, timely measures can be taken for maintenance or replacement. At the same time, due to the special nature of nuclear power, the activation of fire linkage equipment must take into account nuclear power safety requirements. The fire linkage equipment cannot be directly controlled by the fire alarm. For example, if a smoke detector alarms in an area, the fire sprinkler head in the area will not be opened directly, but requires manual confirmation to start normally. The firefighters in the area are deployed in time through the 3D visualization model for confirmation.

[0094] To achieve the above-mentioned purpose and other related purposes, the present invention also includes an intelligent nuclear power fire monitoring system, including a data acquisition module 10, a data acquisition module 20, an analysis module 30 and a visualization module 40. The data acquisition module 10 obtains the equipment data of the fire detection equipment and the fire linkage equipment; the data acquisition module 20 cleans the equipment data to obtain the equipment processing data; the analysis module 30 calculates the normal reference value of the equipment processing data based on the historical statistics; compares and analyzes the current equipment processing data with its normal reference value to obtain the equipment health prediction; the visualization module 40 displays the location information of the equipment and its equipment health prediction information.

[0095] It should be noted that the intelligent nuclear power fire monitoring system of the present invention can be connected to the nuclear power monitoring system already installed in the nuclear power plant, and the nuclear power monitoring system can be installed with a fire image recognition unit. The obtained video image can be processed by fire image recognition technology to identify the fire situation, and the fire alarm of the fire detection equipment can be further confirmed to avoid false alarms.

[0096] In summary, see Figure 3 The intelligent nuclear power fire monitoring method and system of the present invention can achieve the following objectives:

[0097] (1) The demand for fire detection equipment (including smoke and temperature detectors, combustible gas detectors and flame detectors, etc.), including the prediction of the health of the above equipment, improving the accuracy of the alarm of the above equipment and displaying the probe position of the above detector equipment in three dimensions by region.

[0098] (2) The need for fire linkage equipment (sprinkler heads, fire doors, fire dampers and smoke exhaust systems, etc.), including monitoring the health of fire linkage equipment to ensure its effectiveness in the event of a fire.

[0099] At the same time, due to the special nature of nuclear power, the activation of fire linkage equipment must take into account nuclear power safety requirements. The fire linkage equipment cannot be directly controlled by the fire alarm of the fire detection equipment. For example, if a smoke detector in an area alarms, the fire sprinkler head in that area will not be opened directly, but requires manual confirmation to start normally. Therefore, the confirmation speed can be accelerated through the 3D visualization model.

[0100] (3) Provide historical equipment processing data for fire detection equipment and fire linkage equipment at the inspection location. It can obtain previous fault data and fault locations, thereby improving inspection efficiency and reliability.

[0101] (4) The nuclear power fire protection system evaluates the rationality of the distribution of fire detection equipment and fire linkage equipment and provides reference layout opinions. It provides suggestions on the number of personnel in each position for fire-related personnel in the nuclear power plant, and provides firefighters with reasonable route planning and required firefighting equipment planning in the event of a fire.

[0102] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

[0103] In the description herein, many specific details, such as examples of components and / or methods, are provided to provide a complete understanding of embodiments of the present invention. However, those skilled in the art will recognize that embodiments of the present invention may be practiced without one or more of the specific details or with other devices, systems, components, methods, components, materials, parts, etc. In other cases, well-known structures, materials, or operations are not specifically shown or described in detail to avoid obscuring aspects of embodiments of the present invention.

[0104] References throughout this specification to "one embodiment," "an embodiment," or "a specific embodiment" mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention, and not necessarily in all embodiments. Thus, various appearances of the phrases "in one embodiment," "in an embodiment," or "in a specific embodiment" in different places throughout this specification do not necessarily refer to the same embodiment. In addition, the particular features, structures, or characteristics of any specific embodiment of the invention may be combined with one or more other embodiments in any suitable manner. It should be understood that other variations and modifications of the embodiments of the invention described and illustrated herein may be possible in light of the teachings herein and are to be considered part of the spirit and scope of the invention.

[0105] It should also be understood that one or more of the elements shown in the figures may also be implemented in a more separate or more integrated manner, or even removed because they are inoperable in certain circumstances or provided because they may be useful depending on the application.

[0106] In addition, unless otherwise explicitly indicated, any marking arrows in the drawings should be regarded as exemplary only and not limiting. In addition, unless otherwise indicated, the term "or" used herein is generally intended to mean "and / or". In the case where the term is not clear because it is anticipated that the ability to separate or combine is provided, the combination of components or steps will also be regarded as indicated.

[0107] As used in the description herein and throughout the claims that follow, "a," "an," and "the" include plural references unless otherwise indicated. Likewise, as used in the description herein and throughout the claims that follow, the meaning of "in" includes "in" and "on," unless otherwise indicated.

[0108] The above description of the illustrated embodiments of the present invention (including the contents described in the Abstract) is not intended to be an exhaustive list or to limit the present invention to the precise form disclosed herein. Although specific embodiments of the present invention and examples of the present invention are described herein for illustrative purposes only, various equivalent modifications are possible within the spirit and scope of the present invention as will be recognized and appreciated by those skilled in the art. As noted, these modifications may be made to the present invention in accordance with the above description of the embodiments described in the present invention, and these modifications will be within the spirit and scope of the present invention.

[0109] Systems and methods have been generally described herein as details that aid in understanding the present invention. In addition, various specific details have been given to provide an overall understanding of embodiments of the present invention. However, those skilled in the relevant art will recognize that embodiments of the present invention may be practiced without one or more of the specific details, or may be practiced using other devices, systems, accessories, methods, components, materials, parts, etc. In other cases, well-known structures, materials, and / or operations are not specifically shown or described in detail to avoid confusion with various aspects of embodiments of the present invention.

[0110] Thus, although the invention has been described herein with reference to specific embodiments thereof, freedom of modification, various changes and substitutions are also within the foregoing disclosure, and it should be understood that in some cases, some features of the invention will be employed without the corresponding use of other features without departing from the scope and spirit of the proposed invention. Thus, many modifications may be made to adapt a particular environment or material to the essential scope and spirit of the invention. The invention is not intended to be limited to the specific terms used in the claims below and / or the specific embodiments disclosed as the best mode contemplated for carrying out the invention, but the invention will include any and all embodiments and equivalents falling within the scope of the appended claims. Thus, the scope of the invention will be determined solely by the appended claims.

Claims

1. An intelligent nuclear power fire monitoring method, characterized in that: include: Obtain equipment data of fire detection equipment and fire linkage equipment; Clean the equipment data to obtain equipment processing data; Compare and analyze the current device processing data with its normal reference value to obtain a device health prediction, wherein the normal reference value is calculated based on historical statistical device processing data; The location information of the corresponding fire detection equipment and fire linkage equipment and their equipment health prediction information are sent to the display screen for display.

2. The intelligent nuclear power fire monitoring method according to claim 1 is characterized in that: The calculation formula of the normal reference value is: Among them, x1 is the initial value of the device, that is, the set value, x2 is the average value of the historical statistical device processing data, and w1 and w2 are the weights of x1 and x2 respectively.

3. The intelligent nuclear power fire monitoring method according to claim 1 is characterized in that: The calculation of the weight w2 includes: Among them, e -kx is an exponential decay term, where k is a positive constant.

4. The intelligent nuclear power fire monitoring method according to claim 3 is characterized in that: The calculation of the average value of the device processing data includes the following steps: Step 1: Create a first data set and a second data set, wherein the first data set is used to accumulate the sum of all added data points, and the second data set is used to record the number of added data points; wherein the data of the data points are device processing data; Step 2: adding new data points to the current first data set and the second data set; Step three: Check whether the second data set is 0. When the second data set is 0, terminate the current operation; otherwise, divide the first data set by the second data set to obtain the current average value, that is, the average value of the data processed by the device.

5. The intelligent nuclear power fire monitoring method according to claim 4 is characterized in that: The step of sending the location information of the corresponding fire detection equipment and fire linkage equipment and the equipment health prediction information thereof to the display screen for display comprises: Obtain building structure data; Fusing the equipment data of the fire detection equipment and the fire linkage equipment with the building structure data, and establishing a 3D visualization model; The location information of the corresponding fire detection equipment and fire linkage equipment and their equipment health prediction information are displayed in the 3D visualization model.

6. The intelligent nuclear power fire monitoring method according to claim 5 is characterized in that: The method for fusing the equipment data of the fire detection equipment and the fire linkage equipment with the building structure data is a coordinate system mapping method, including: converting the regional location information of the fire detection equipment and the fire linkage equipment into a coordinate system in the building structure so that the equipment and its corresponding regional location information match.

7. The intelligent nuclear power fire monitoring method according to claim 6 is characterized in that: The method further comprises: Obtain equipment data of temperature and humidity sensors in key areas; Compare the environmental monitoring data of the temperature and humidity sensor with its environmental normal reference value to obtain regional fire warning information of the key area monitored by the temperature and humidity sensor; The normal environment reference value is calculated based on historical statistical environmental monitoring data.

8. The intelligent nuclear power fire monitoring method according to claim 7 is characterized in that: The key areas include dangerous goods storage areas, and their location information can be obtained by manual entry or by obtaining material storage information in the nuclear power warehouse management system and displayed in the 3D visualization model.

9. The intelligent nuclear power fire monitoring method according to claim 8, characterized in that: The method further includes: according to the input inspection signal, calling the historical device processing data of the corresponding device to inspect the device.

10. An intelligent nuclear power fire monitoring system, characterized in that: include: Data acquisition module, which obtains the equipment data of fire detection equipment and fire linkage equipment; The data processing module cleans the device data to obtain device processing data; The analysis module calculates the normal reference value of the equipment processing data according to the historical statistics; compares and analyzes the current equipment processing data with the normal reference value to obtain the equipment health prediction; The visualization module displays the location information of the device and its device health prediction information.

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