Explosive decompression control method based on self-attention mechanism

Abstract

The invention discloses an explosive pressure reduction control method based on a self-attention mechanism, and relates to the technical field of explosive pressure reduction, the explosive pressure reduction control method comprises an explosive pressure reduction control system based on the self-attention mechanism, the control system comprises sensor devices arranged on the inner side and the outer side of a collection cabin, and a pipeline throat is arranged on one side of the collection cabin; a first-stage valve and a second-stage valve are arranged on the outer side of the pipeline throat, and a monitoring device used for monitoring the opening time of the first-stage valve and the opening degree of the second-stage valve is further arranged on one side of the pipeline throat. According to the explosive pressure reduction control method based on the self-attention mechanism, key parameters in the pressure reduction process can be accurately predicted and controlled by the self-attention mechanism model through comprehensive analysis of various influence factors, and various factors such as pressure inside and outside a cabin, environment temperature and valve states are comprehensively considered; accurate control over the explosive pressure reduction process is achieved, and a control strategy can be dynamically adjusted conveniently.

Description

Technical Field

[0001] The present invention relates to the technical field of explosive decompression, and in particular to an explosive decompression control method based on a self-attention mechanism. Background Art

[0002] Explosive decompression is an extreme pressure change phenomenon, which usually occurs in the fields of aerospace, deep-sea diving, etc. Its characteristic is that the pressure inside and outside the cabin is quickly balanced in a very short time, which can easily cause serious damage to the personnel and equipment in the cabin. China is one of the countries with the largest number of civil airliners in the world, and there are many cases in which the safety of pilots and passengers is endangered due to extreme weather or aircraft failure during flight. The explosive decompression training cabin is designed to simulate the rapid loss of airtightness and pressure in the cabin of civil aircraft during high-altitude flight. The simulation process requires high accuracy of explosive decompression time. The explosive decompression time in the explosive decompression training cabin is mainly completed by presetting the valve opening. There are two levels of valves on the throat of the pipeline: the first level is a fast-opening valve, which is closed in the preparation stage; the second level is a pneumatic eccentric butterfly valve and other valves. According to the time requirements of explosive decompression, the opening is preset by the control program in the preparation stage and then fixed. At the beginning of explosive decompression, the first-level valve is opened quickly to complete the explosive decompression. At present, the control of explosive decompression time is completed by recording the preset value of the valve opening during the debugging phase. However, the above method relies on preset programs and simple feedback mechanisms, and lacks the ability to dynamically analyze and adjust real-time data. In the actual operation process, due to factors such as changes in the system environment and the deviation of the valve opening, the explosive decompression time may be inaccurate, affecting the operation process of the system.

[0003] Based on this, a method for explosive decompression control based on a self-attention mechanism is now provided, which can eliminate the drawbacks of the existing technical solutions. Summary of the invention

[0004] The purpose of the present invention is to provide an explosive decompression control method based on a self-attention mechanism to solve the problem that traditional control methods in the background technology lack the ability to dynamically analyze and adjust real-time data, and cannot adjust the explosive decompression, resulting in inaccurate explosive decompression time.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for controlling explosive decompression based on a self-attention mechanism, including an explosive decompression control system based on a self-attention mechanism, wherein the control system includes sensor devices arranged on both sides of a collection cabin, a pipeline throat is arranged on one side of the collection cabin, a primary valve and a secondary valve are arranged on the outside of the pipeline throat, a monitoring device for monitoring the opening time of the primary valve and the opening degree of the secondary valve is also arranged on one side of the pipeline throat, and a central controller is also included, wherein the central controller communicates with the sensor device and the monitoring device through a network.

[0007] Preferably, the sensor device comprises a temperature module and a pressure module which are electrically connected, the temperature module is used to automatically identify and collect the ambient temperature inside and outside the collection cabin, and the pressure module is used to automatically identify and collect the pressure inside and outside the collection cabin.

[0008] Preferably, the monitoring device includes a high-precision camera, which is used to monitor the image information of the first-level valve and the second-level valve. One side of the high-precision camera is provided with a data acquisition module for identifying image features and updating the image data of the opening state of the first-level valve and the opening degree of the second-level valve based on the above-mentioned identification features. One side of the data acquisition module is provided with a timing module, which is used to identify the opening state of the first-level valve and automatically update and record the opening time data of the first-level valve.

[0009] Preferably, the central controller includes a data information library, a data transmission module, and a self-attention mechanism model module, and the data information library, the data transmission module, and the self-attention mechanism model module are electrically connected. The data information library is used to divide the corresponding data into several groups according to time and parameter type, and record historical decompression and experimental data. The data transmission module is used to wirelessly transmit data processed by different modules. The self-attention mechanism model module uses a self-attention mechanism model to identify the parameter information and actual operation data in the above-mentioned data information library, and analyzes and calculates the decompression control strategies under different conditions based on the above-mentioned parameter information and actual data.

[0010] Preferably, the self-attention mechanism model module includes a data preprocessing module, a data calculation module and a data analysis module. The data preprocessing module is used to receive and identify the collected data and perform feature extraction operations on it to extract the features most relevant to time and pressure parameters, and filter out redundant or irrelevant information. The data calculation module is used to calculate the optimal decompression control strategy based on the existing pressure inside and outside the collection cabin, valve state parameters, and combined with the actual operation results in the data information library. The decompression control strategy includes valve switching timing, opening and duration. The data analysis module is used to receive and identify the calculation results of the data calculation module, and analyze various factors affecting the explosive decompression process, and convert the above data information into a report data form with text content.

[0011] Preferably, an information access port module is provided on one side of the central controller, and the information access port module includes a wireless transmission port and a charging interface.

[0012] Preferably, a display panel is also provided on one side of the central controller for identifying features of the report data and displaying the report data based on the above-mentioned identification features, and the display panel is electrically connected to the central controller.

[0013] Preferably, the specific steps of using the explosive decompression control method based on the self-attention mechanism are as follows:

[0014] S1. Collect the pressure and temperature data before explosive decompression inside and outside the cabin through the sensor device, take the image information of the first-level valve and the second-level valve through the monitoring device, and transmit the above data information to the central controller through the data transmission module;

[0015] S2. Input the collected data into the self-attention mechanism model through the self-attention mechanism model module. The above model calculates the optimal decompression control strategy based on the current pressure and temperature parameters and the actual operation data;

[0016] S3. The data transmission module transmits the calculation results and analysis data to the data information database.

[0017] Preferably, the step S1 comprises:

[0018] S11. The sensor device identifies the actual temperature and pressure conditions around the collection cabin, the temperature module automatically senses and identifies the temperature and obtains the corresponding temperature information, and the pressure module automatically senses and identifies the pressure before explosive decompression and obtains the corresponding pressure data;

[0019] S12, the high-precision camera captures the image information of the pipeline throat, and transmits the image information to the data acquisition module to perform the recognition operation of the first-level valve opening state and the second-level valve opening information. When the high-precision camera recognizes that the first-level valve is open, the timing module starts and automatically updates the time;

[0020] S13, the data transmission module transmits the above data information to the data information library and the self-attention mechanism model module, and divides the corresponding data into different groups through the data information library.

[0021] Preferably, the step S2 comprises:

[0022] S21, the data preprocessing module reads the collected raw data, performs data processing and extracts important parameter features, and then filters out useless data information. The data transmission module transmits the preprocessed data to the data calculation module;

[0023] S22, build a self-attention mechanism model through the data calculation module, input the data into the model, use the model to identify data parameters, and calculate the optimal pressure reduction control strategy according to environmental changes and valve opening factors;

[0024] S23. The calculation result data is converted into a report format through the data analysis module to cope with different environments and situations after the valve status changes.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention provides an explosive decompression control method based on a self-attention mechanism. Through comprehensive analysis of multiple influencing factors, the self-attention mechanism model can accurately predict and control key parameters in the decompression process, and realize accurate control of the explosive decompression process. By using real-time data and the self-attention model, the valve control strategy can be dynamically adjusted to achieve rapid response and accurate control of explosive decompression. The self-attention mechanism model can comprehensively consider multiple factors such as cabin indoor and outdoor pressure, ambient temperature, valve status, etc., and comprehensively analyze and control the decompression process to ensure the stability and safety of the decompression process. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the structure of the collection cabin of the present invention.

[0028] Figure 2 It is a structural schematic diagram of the present invention.

[0029] Figure 3 It is a schematic diagram of the structure of the sensor device and the monitoring device of the present invention.

[0030] Figure 4 It is a structural schematic diagram of the central controller of the present invention.

[0031] Figure 5 It is a schematic diagram of the process of the present invention.

[0032] Figure 6 It is a schematic flow chart of step S1 of the present invention.

[0033] Figure 7 It is a schematic diagram of the process of step S2 of the present invention.

[0034] Notes on the accompanying drawings: collection cabin 100, pipeline throat 110, primary valve 120, secondary valve 130, sensor device 200, temperature module 210, pressure module 220, monitoring device 300, high-precision camera 310, data collection module 320, timing module 330, central controller 400, data information library 410, data transmission module 420, self-attention mechanism model module 430, data preprocessing module 431, data calculation module 432, data analysis module 433, information access port module 440, display panel 500. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0036] In this embodiment, if Figure 1-Figure 4 As shown, a method for controlling explosive decompression based on a self-attention mechanism includes an explosive decompression control system based on a self-attention mechanism. The control system includes sensor devices 200 arranged on both sides of a collection cabin 100. The sensor device 200 is responsible for real-time and accurate collection of physical quantities affecting the decompression process, such as pressure changes and ambient temperature, and has good sensitivity and anti-interference capabilities to ensure the accuracy and reliability of data collection. A pipeline throat 110 is arranged on one side of the collection cabin 100, and a primary valve 120 and a secondary valve 130 are arranged on the outside of the pipeline throat 110. A monitoring device 300 for monitoring the opening time of the primary valve 120 and the opening degree of the secondary valve 130 is also arranged on one side of the pipeline throat 110. The monitoring device 300 can record the valve action state and parameter changes with high precision for subsequent data. The analysis and control strategy adjustment provide a key basis. The explosive decompression time is affected by factors such as the opening of the secondary valve 130 in the pipeline throat 110, the pressure conditions before the explosive decompression inside and outside the collection cabin 100, the ambient temperature, and the opening time of the primary valve 120. The data of the above factors can be collected through the sensor device 200 and the monitoring device 300. The central controller 400 also includes a central controller 400. The central controller 400 communicates with the sensor device 200 and the monitoring device 300 through the network. The central controller 400 realizes real-time interconnection with various components such as the sensor device 200 and the monitoring device 300 through a stable network communication mechanism, receives data information from the sensor device 200 and the monitoring device 300, and is convenient for using advanced algorithms to process and analyze data to formulate an optimal decompression control strategy.

[0037] Among them Figure 2-Figure 4As shown, the sensor device 200 includes an electrically connected temperature module 210 and a pressure module 220. The temperature module 210 is used to automatically identify and collect the ambient temperature inside and outside the collection cabin 100. The temperature module 210 adopts advanced temperature sensing technology and can accurately reflect temperature changes in various complex environments. It is electrically connected to the data transmission module 420 and uploads the collected temperature data to the central controller 400 in real time. The pressure module 220 is used to automatically identify and collect the internal and external pressures of the collection cabin 100. It adopts advanced pressure sensing technology and can achieve rapid response and accurate measurement of changes in indoor and outdoor pressures of the collection cabin 100, thereby increasing the overall practicality of the device.

[0038] Among them Figure 2-Figure 4 As shown, the monitoring device 300 includes a high-precision camera 310, which is used to monitor the image information of the first-level valve 120 and the second-level valve 130. The high-precision camera 310 has good resolution and clarity, and can accurately capture the real-time status of the valve under various lighting conditions. A data acquisition module 320 is provided on one side of the high-precision camera 310 for identifying image features and updating the image data of the opening state of the first-level valve 120 and the opening degree of the second-level valve 130 based on the above-mentioned identification features. The data acquisition module 320 has an advanced image processing algorithm built in, which can automatically identify and extract key features in the image captured by the high-precision camera 310, such as the opening state and opening degree of the valve, so as to improve the accuracy and reliability of data processing. A timing module 330 is provided on one side of the data acquisition module 320, which is used to identify the opening state of the first-level valve 120 and automatically update and record the opening time data of the first-level valve 120. Once the high-precision camera 310 detects that the valve is open, the timing module 330 immediately starts the timing function and continuously records the opening time of the valve until it is closed, which provides an important time reference for the subsequent analysis and optimization of the decompression process.

[0039] Among them Figure 2-Figure 4As shown, the central controller 400 includes a data information library 410, a data transmission module 420, and a self-attention mechanism model module 430. The data information library 410, the data transmission module 420, and the self-attention mechanism model module 430 are electrically connected. The data information library 410 is used to divide the corresponding data into several groups according to time and parameter type to ensure clear organization and rapid retrieval of the data, and record historical decompression and experimental data. The data information library 410 has powerful data classification and indexing capabilities. It not only records a large amount of historical decompression data and experimental data, but also continuously receives real-time data from the sensor device 200 and the monitoring device 300. The data transmission module 420 is used to wirelessly transmit the data processed by different modules. The module supports multiple wireless communication protocols, and can efficiently and stably transmit the historical data and real-time data in the data information library 410, as well as the prediction results and control instructions of the self-attention mechanism model module 430 to various related modules. At the same time, the data transmission module 420 is also responsible for receiving sensor data, monitoring videos and other original information from the front-end device, and forwarding it to the corresponding processing unit for processing. The self-attention mechanism model module 430 uses the self-attention mechanism model to identify the parameter information and actual operation data in the above-mentioned data information library 410, and analyzes and calculates the pressure reduction control strategy under different conditions based on the above-mentioned parameter information and actual data. According to the importance of the extracted features, useless information is ignored, thereby improving the prediction accuracy of the model.

[0040] Among them Figure 4 As shown, the self-attention mechanism model module 430 includes a data preprocessing module 431, a data calculation module 432 and a data analysis module 433. The data preprocessing module 431 is used to receive and identify the collected data and perform feature extraction operations on it, extract the features most related to the time and pressure parameters, use statistical methods and learning algorithms to extract features highly related to the time and pressure parameters from the original data, and filter out redundant or irrelevant information to reduce data dimensions and improve subsequent processing efficiency. The data calculation module 432 is used to collect the internal and external pressures of the cabin 100, the valve state parameters, and the actual data in the data information library 410. The result of the operation is used to calculate the optimal decompression control strategy, which includes the valve opening and closing timing, opening degree and duration. The data analysis module 433 is used to receive and identify the calculation results of the data calculation module 432, accurately identify the calculated decompression control strategy, and explain it in detail, including the specific content, expected effects and potential risks of the strategy, and analyze various factors that affect the explosive decompression process, such as pressure changes, valve opening time, etc., evaluate their impact on the explosive decompression time, and convert the above data information into a report data format with text content, which can clearly, accurately and comprehensively help users understand and make corresponding adjustments.

[0041] Among them Figure 3 and Figure 4 As shown, an information access port module 440 is provided on one side of the central controller 400. The information access port module 440 includes a wireless transmission port and a charging interface, and is connected to other power storage devices through the charging interface to supply power to the central controller 400 and other components.

[0042] Among them Figure 2 As shown, a display panel 500 is also provided on one side of the central controller 400 for identifying report data features and displaying the report data based on the above identification features. The display panel 500 is electrically connected to the central controller 400, so that the user can quickly understand the data conditions under different parameter changes, thereby making more accurate control decisions.

[0043] Among them Figure 5 As shown, the specific steps of using the explosive decompression control method based on the self-attention mechanism are as follows:

[0044] S1. The pressure and temperature data before the explosive decompression inside and outside the collection cabin 100 are collected by the sensor device 200, the image information of the primary valve 120 and the secondary valve 130 are photographed by the monitoring device 300, and the above data information is transmitted to the central controller 400 by the data transmission module 420;

[0045] S2, inputting the collected data into the self-attention mechanism model through the self-attention mechanism model module 430, and the above model calculates the optimal pressure reduction control strategy according to the current pressure and temperature parameters combined with the actual operation data;

[0046] S3. The data transmission module 420 transmits the calculation result and analysis data to the data information library 410.

[0047] Among them Figure 6 As shown, step S1 includes:

[0048] S11, the sensor device 200 identifies the actual temperature and pressure conditions around the collection cabin 100, the temperature module 210 automatically senses and identifies the temperature and obtains corresponding temperature information, and the pressure module 220 automatically senses and identifies the pressure before explosive decompression and obtains corresponding pressure data;

[0049] S12, the high-precision camera 310 captures the image information of the pipeline throat 110, and transmits the image information to the data acquisition module 320, and performs the recognition operation of the opening state of the first-level valve 120 and the opening information of the second-level valve 130. When the high-precision camera 310 recognizes that the first-level valve 120 is open, the timing module 330 is started and automatically performs the time update operation;

[0050] S13, the data transmission module 420 transmits the above data information to the data information library 410 and the self-attention mechanism model module 430, and divides the corresponding data into different groups through the data information library 410.

[0051] Among them Figure 7 As shown, step S2 includes:

[0052] S21, the data preprocessing module 431 reads the collected raw data, performs data processing and extracts important parameter features, and then filters out useless data information. The data transmission module 420 transmits the preprocessed data to the data calculation module 432;

[0053] S22, building a self-attention mechanism model through the data calculation module 432, and inputting data into the model, using the model to identify data parameters, and calculating the optimal pressure reduction control strategy according to environmental changes and valve opening factors;

[0054] S23. The calculation result data is converted into a report format through the data analysis module 433 to cope with different environments and situations after the valve status changes.

[0055] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for controlling explosive decompression based on a self-attention mechanism, characterized in that: The invention comprises an explosive decompression control system based on a self-attention mechanism, the control system comprising sensor devices (200) arranged on both sides of a collection cabin (100), a pipeline throat (110) being arranged on one side of the collection cabin (100), a primary valve (120) and a secondary valve (130) being arranged on the outside of the pipeline throat (110), and a monitoring device (300) for monitoring the opening time of the primary valve (120) and the opening degree of the secondary valve (130) being arranged on one side of the pipeline throat (110); The invention also comprises a central controller (400), wherein the central controller (400) communicates with the sensor device (200) and the monitoring device (300) via a network.

2. The explosive decompression control method based on the self-attention mechanism according to claim 1 is characterized in that: The sensor device (200) comprises a temperature module (210) and a pressure module (220) which are electrically connected, wherein the temperature module (210) is used to automatically identify and collect the ambient temperature inside and outside the collection chamber (100), and the pressure module (220) is used to automatically identify and collect the pressure inside and outside the collection chamber (100).

3. The explosive decompression control method based on the self-attention mechanism according to claim 1 is characterized in that: The monitoring device (300) comprises a high-precision camera (310), wherein the high-precision camera (310) is used to monitor image information of a primary valve (120) and a secondary valve (130); a data acquisition module (320) is provided on one side of the high-precision camera (310) for identifying image features and updating image data of an opening state of the primary valve (120) and an opening degree of the secondary valve (130) based on the above-identified features; a timing module (330) is provided on one side of the data acquisition module (320) for identifying an opening state of the primary valve (120) and automatically updating and recording opening time data of the primary valve (120).

4. The explosive decompression control method based on the self-attention mechanism according to claim 1 is characterized in that: The central controller (400) includes a data information library (410), a data transmission module (420), and a self-attention mechanism model module (430). The data information library (410), the data transmission module (420), and the self-attention mechanism model module (430) are electrically connected to each other. The data information library (410) is used to divide the corresponding data into a plurality of groups according to time and parameter type, and record historical decompression and experimental data. The data transmission module (420) is used to wirelessly transmit the data processed by different modules. The self-attention mechanism model module (430) uses the self-attention mechanism model to identify the parameter information and actual operation data in the above-mentioned data information library (410), and analyzes and calculates the decompression control strategy under different conditions based on the above-mentioned parameter information and actual data.

5. The explosive decompression control method based on the self-attention mechanism according to claim 4 is characterized in that: The self-attention mechanism model module (430) includes a data preprocessing module (431), a data calculation module (432) and a data analysis module (433). The data preprocessing module (431) is used to receive and identify the collected data and perform feature extraction operations on the data to extract the features most relevant to the time and pressure parameters, and filter out redundant or irrelevant information. The data calculation module (432) is used to calculate the optimal decompression control strategy based on the existing internal and external pressures of the collection cabin (100), valve state parameters, and combined with the actual operation results in the data information library (410). The decompression control strategy includes the valve opening and closing timing, opening degree and duration. The data analysis module (433) is used to receive and identify the calculation results of the data calculation module (432), analyze various factors that affect the explosive decompression process, and convert the above data information into a report data form with text content.

6. The explosive decompression control method based on the self-attention mechanism according to claim 4 is characterized in that: An information access port module (440) is provided on one side of the central controller (400), and the information access port module (440) comprises a wireless transmission port and a charging interface.

7. The explosive decompression control method based on the self-attention mechanism according to claim 4 is characterized in that: A display panel (500) is also provided on one side of the central controller (400) for identifying report data characteristics and displaying the report data based on the above identification characteristics. The display panel (500) is electrically connected to the central controller (400).

8. The explosive decompression control method based on the self-attention mechanism according to claim 1 is characterized in that: The specific steps of using the explosive decompression control method based on the self-attention mechanism are as follows: S1, collecting pressure and temperature data before explosive decompression inside and outside the collection cabin (100) through the sensor device (200), photographing image information of the first-stage valve (120) and the second-stage valve (130) through the monitoring device (300), and transmitting the above data information to the central controller (400) through the data transmission module (420); S2, inputting the collected data into the self-attention mechanism model through the self-attention mechanism model module (430), and the above model calculates the optimal pressure reduction control strategy based on the current pressure and temperature parameters combined with the actual operation data; S3. The data transmission module (420) transmits the calculation result and analysis data to the data information library (410).

9. The explosive decompression control method based on the self-attention mechanism according to claim 8, characterized in that: The step S1 comprises: S11, the sensor device (200) identifies the actual temperature and pressure conditions around the collection chamber (100), the temperature module (210) automatically senses and identifies the temperature and obtains corresponding temperature information, and the pressure module (220) automatically senses and identifies the pressure before explosive decompression and obtains corresponding pressure data; S12, the high-precision camera (310) captures image information of the pipeline throat (110), and transmits the image information to the data acquisition module (320), and performs an identification operation of the opening state of the first-level valve (120) and the opening information of the second-level valve (130); when the high-precision camera (310) identifies that the first-level valve (120) is open, the timing module (330) is started, and the time is automatically updated; S13, the data transmission module (420) transmits the above data information to the data information library (410) and the self-attention mechanism model module (430), and divides the corresponding data into different groups through the data information library (410).

10. The explosive decompression control method based on the self-attention mechanism according to claim 8, characterized in that: The step S2 comprises: S21, the data preprocessing module (431) reads the collected raw data, performs data processing and extracts important parameter features, and then filters out useless data information. The data transmission module (420) transmits the preprocessed data to the data calculation module (432); S22, building a self-attention mechanism model through the data calculation module (432), inputting data into the model, using the model to identify data parameters, and calculating the optimal pressure reduction control strategy according to environmental changes and valve opening factors; S23. The calculation result data is converted into a report format through the data analysis module (433) to cope with different environments and situations after the valve status changes.

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