Integrated portal design data management system and method based on intelligent middle platform

Abstract

The invention discloses an integrated portal design data management system and method based on an intelligent platform, and relates to the technical field of integrated portal design data management, and the system comprises a flight training data integration module, a flight training data calling module, a data analysis module and a training management module. The flight training data integration module is used for carrying out safety risk integration processing on the collected flight training data; the flight training data calling module is used for selectively calling the flight training data after the safety risk integration processing; the data analysis module is used for performing security analysis on various flight training data called by the flight training data calling module; and the training management module is used for managing the execution condition of each flight training sub-process. According to the method, the safety analysis is carried out on the called flight training data by adopting a method of combining transverse analysis and longitudinal analysis, so that the analysis precision and the analysis efficiency of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated portal design data management, and in particular to an integrated portal design data management system and method based on an intelligent middle platform. Background Art

[0002] An integrated portal refers to the front-end management platform of a system and is a type of portal. A portal refers to the direct display window facing users, such as an APP, a website, etc. The integrated intelligent middle platform includes a technology middle platform and a management middle platform, and realizes the management and analysis of flight training data by providing service support for upper-layer applications. The technology middle platform forms unified standardized management for all business systems by integrating a series of development engines based on a low-code development platform, mainly including permission management, application management, dictionary management, system management, process engine, report engine, form management, data visualization, etc.; permission management provides permission management capabilities for each business data to realize data control of each business application; application management includes microservice menu management and application authorization management to provide basic maintenance for the applications of the system; dictionary management includes business dictionaries and system dictionaries according to classification, and supports completely extracting all solidifiable fields involved in all businesses; system management provides management for basic information, theme configuration, login page configuration, parameter configuration of each section area, log buried point maintenance, etc. of the system, and presents the data in a visual list to facilitate user management and maintenance; the process flow engine is developed based on the BPM standard and provides a convenient Web-side visual editing interface for users in the form of intelligent applications; form management provides sub-level management such as form entity, model object management, form object, etc., provides basic support for task services such as process management and workflow binding, and supports users to manage each item of data in the form separately; the report engine supports visual operations, and various page controls, elements, etc. support typesetting design in a drag-and-drop manner; data visualization provides management for intelligent graphic visualization presentation of each business data in the business information system.

[0003] When the prior art manages the flight training process, it usually manually supervises the entire flight training process of the unmanned aerial vehicle, and analyzes the supervision data in the supervision process by using the empirical analysis method to realize the safety management of the flight training process. This method has low work efficiency and low safety analysis accuracy. At the same time, it is impossible to quickly capture abnormal data in the supervision data, which in turn causes the unmanned aerial vehicle to be in a dangerous state for a long time, increasing the flight risk of the unmanned aerial vehicle. Summary of the Invention

[0004] The purpose of the present invention is to provide an integrated portal design data management system and method based on an intelligent middle platform to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions: An integrated portal design data management system based on an intelligent middle platform, the system includes a flight training data integration module, a flight training data call module, a data analysis module, and a training management module; The flight training data integration module is used to collect the flight training data of the training personnel when the training personnel execute the training tasks of each flight training sub-process, and perform security risk integration processing on the collected flight training data; The flight training data call module is used to selectively call the flight training data after security risk integration processing according to the adaptability between the flight training data stored in the security risk data set and the abnormal data set and each job type; The data analysis module is used to perform security analysis on various types of flight training data called by the flight training data call module; The training management module is used to manage the execution of each flight training sub-process.

[0006] Further, the flight training data integration module includes a flight training data collection unit and a flight training data integration unit; The flight training data collection unit obtains the entire flight training process, and collects the flight training data of the training personnel when the training personnel execute the training tasks of each flight training sub-process; The flight training data integration unit receives the flight training data collected by the flight training data collection unit, and in the flight training three-dimensional simulation scene, compares the received flight training data with the matching standard flight training data, and the restricted flight training data corresponding to the matching standard flight training data, to obtain the security risk data set and the abnormal data set of each flight training full process.

[0007] Further, the specific method for the flight training data integration unit to obtain the security risk data set and the abnormal data set of each flight training sub-process is: Perform three-dimensional simulation on the flight training scene of the training personnel, render the three-dimensional simulated flight training scene according to the meteorological parameters at the location of the flight training scene, obtain the flight training three-dimensional simulation scene, the meteorological parameters include visibility, rainfall, snowfall, and wind speed, based on the flight training three-dimensional simulation scene, determine the standard flight training data matching the received flight training data, and the restricted flight training data corresponding to the standard flight training data matching the received flight training data, the restricted flight training data corresponding to the training task of the flight training sub-process numbered i = min{U i -K 1i ,U i -K 2i ,Ui -K 3i ,U i -K 4i}; Among them, i = 1, 2, …, m, representing the numbers corresponding to the respective training sub-processes of the entire flight training process, and m representing the total number of training sub-processes in the entire flight training process, K 1i = h 1 *Q i , K 2i = h 2 *Y i , K 3i = h 3 *A i , K 4i = h 4 *B i , h 1 , h 2 , h 3 , h 4 all represent weight coefficients, Q i , Y i , A i , B i respectively represent the visibility, rainfall, snowfall, and wind speed corresponding to the location where the training task is located when the trainer performs the training task of the flight training sub-process numbered i, and min represents the minimum value symbol; If W i ≤ R i ≤ U i , then put R i into the set M to obtain the safety risk data set of the entire flight training process; If R i > U i , then put R i into the set N to obtain the abnormal data set of the entire flight training process; Among them, R i represents the flight training data collected in real time when the trainer performs the training task of the flight training sub-process numbered i, and U i represents the standard flight training data corresponding to the training task of the flight training sub-process numbered i, and W i represents the restricted flight training data corresponding to the training task of the flight training sub-process numbered i.

[0008] Further, the flight training data calling module obtains the job types of the personnel who have undergone identity authentication in the intelligent middle platform. The job types include commanders, controllers, meteorological mechanics, and training personnel. According to the fitness between each flight training data stored in the safety risk data set and the abnormal data set and each job type, the flight training data stored in the safety risk data set and the abnormal data set is selectively called.

[0009] Further, the specific method for the flight training data calling module to selectively call the flight training data stored in the safety risk data set and the abnormal data set is as follows: For the safety risk data set: S ij =exp[-(U i -R i ) / (U i -W i )]*(H j / F); Among them, j = 1, 2, 3, 4, representing the numbers corresponding to each job type, exp represents the exponential function with the natural constant e as the base, F represents the total number of historical flight training data stored in the safety risk data set. When j = 1, H j represents the total number of historical flight training data stored in the safety risk data set called by the commander. When j = 2, H j represents the total number of historical flight training data stored in the safety risk data set called by the controller. When j = 3, H j represents the total number of historical flight training data stored in the safety risk data set called by the meteorological mechanic. When j = 4, H j represents the total number of historical flight training data stored in the safety risk data set called by the training personnel. S ij represents the fitness between the flight training data R i stored in the safety risk data set and the job type with the number j; For the abnormal data set: D ij =exp[-(R i -U i ) / (U i -W i )]*(K j / P); Among them, P represents the total number of historical flight training data stored in the abnormal data set, K j represents the total number of historical flight training data stored in the abnormal data set called by the staff of the job type with the number j, D ij represents the flight training data R i, the fitness degree with the job type numbered j; When 0.8 ≤ S ij ≤ 1, it means that the staff of the job type numbered j calls the flight training data R stored in the safety risk dataset. i Conversely, the flight training data R stored in the safety risk dataset is not called. i Call; When 0.8 ≤ D ij ≤ 1, it means that the staff of the job type numbered j calls the flight training data R stored in the abnormal dataset. i Conversely, the flight training data R stored in the safety risk dataset is not called. i Call.

[0010] Furthermore, the data analysis module respectively performs discrete analysis on the flight training data called by the commander, controller, meteorological technician, and training personnel, and combines the fluctuation situation of the called flight training data to analyze the safety of each flight training sub-process in real time.

[0011] Furthermore, the specific formula for the data analysis module to analyze the safety of each flight training sub-process in real time is: ; Among them, q = 1, 2, …, g, which means that when the training personnel execute the training tasks of each flight training sub-process, the acquisition times of the called flight training data are numbered in chronological order, g represents the total number of numbers, and E j represents the standard deviation calculated based on the flight training data called by the staff of the job type numbered j, and L j represents the mean value calculated based on the flight training data called by the staff of the job type numbered j, and R iq represents the flight training data collected at the moment corresponding to the number q when the training personnel execute the training tasks of the flight training sub-process numbered i, and C i represents the maximum allowable deviation value between the flight training data collected at adjacent acquisition times when the training personnel execute the training tasks of the flight training sub-process numbered i. When |R i(q+1) -R iq |-C i > 0, , when |R i(q+1) -R iq |-C i ≤ 0, , V ij(q+1)Denote the safety factor corresponding to the flight training sub-process numbered i executed by the training personnel obtained from the flight training data called by the staff of the job type numbered j at the moment corresponding to the number q + 1; According to maxV ij(q+1) Determine the safety factor corresponding to the flight training sub-process numbered i executed by the staff at the moment corresponding to the number q + 1, where max represents the maximum symbol.

[0012] Furthermore, the training management module includes a process management time calculation unit and a training management unit; The process management time calculation unit calculates the management time of each flight training sub-process according to the safety analysis result of the data analysis module; The training management unit receives the management time calculated by the process management time calculation unit, matches the corresponding management time of the staff, and manages the execution situation of the training personnel for each flight training sub-process.

[0013] Furthermore, the specific method for the process time management calculation unit to calculate the management time of each flight training sub-process is as follows: When maxV ij(q+1) > 0.5, the management time T of the flight training sub-process numbered i i = T q+1 , T q+1 represents the moment corresponding to the number q + 1; Let the number of the job type corresponding to maxV ij(q+1) be μ, μ = 1, 2, 3, 4. At the moment T q+1 , the staff of the job type numbered μ manages the execution situation of the training personnel for the flight training sub-process numbered i.

[0014] An integrated portal design data management method based on an intelligent middle platform, the method includes: S10: When the training personnel execute the training tasks of each flight training sub-process, collect the flight training data of the training personnel, and perform safety risk integration processing on the collected flight training data; S20: According to the adaptability between the flight training data stored in the safety risk data set and the abnormal data set and each job type, selectively call the flight training data after safety risk integration processing; S30: Perform safety analysis on various types of flight training data called by the flight training data calling module; S40: Based on the safety analysis result in S30, calculate the management time of each flight training sub-process, and based on the calculation result, manage the execution situation of each flight training sub-process.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In the three-dimensional simulation scene of the flight training of the unmanned aerial vehicle (UAV), the present invention determines the restricted flight training data of the UAV flight training. Based on the determination result, the abnormal data and safety risk data in the collected flight training data are quickly captured and called, avoiding the UAV being in a dangerous state for a long time, which reflects the high security of the system.

[0016] 2. The present invention analyzes the compatibility between the screened abnormal data, safety risk data and various types of staff, and based on the analysis result, selectively calls the flight training data of the UAV, shortening the analysis efficiency of the abnormal data and safety risk data.

[0017] 3. When analyzing the security of the called flight training data, the present invention adopts a method combining horizontal analysis (discrete analysis) and vertical analysis (fluctuation analysis), improving the analysis accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the working principle structure of an integrated portal design data management system and method based on an intelligent middle platform of the present invention; Figure 2 It is a schematic diagram of the working process of an integrated portal design data management system and method based on an intelligent middle platform of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] Embodiment: As Figure 1 and Figure 2 shown, the present invention provides a technical solution for an integrated portal design data management system and method based on an intelligent middle platform. An integrated portal design data management system based on an intelligent middle platform includes a flight training data integration module, a flight training data call module, a data analysis module and a training management module; The flight training data integration module is used to collect the flight training data of the training personnel when the training personnel execute the training tasks of each flight training sub-process, and perform safety risk integration processing on the collected flight training data; The flight training data integration module includes a flight training data collection unit and a flight training data integration unit; The flight training data acquisition unit obtains the entire process of flight training and collects the flight training data of the training personnel when they perform the training tasks of each sub-process of flight training; The flight training data integration unit receives the flight training data collected by the flight training data acquisition unit. In the three-dimensional simulation scenario of flight training, it compares the received flight training data with the matching standard flight training data and the restricted flight training data corresponding to the matching standard flight training data to obtain the safety risk data set and abnormal data set of each entire process of flight training. The specific method is as follows: Perform three-dimensional simulation on the flight training scenario of the training personnel, and render the three-dimensional simulated flight training scenario according to the meteorological parameters at the location of the flight training scenario. The obtained flight training three-dimensional simulation scenario, the meteorological parameters include visibility, rainfall, snowfall and wind speed. Based on the flight training three-dimensional simulation scenario, determine the standard flight training data that matches the received flight training data and the restricted flight training data corresponding to the standard flight training data that matches the received flight training data. The standard flight training data refers to the training requirement data corresponding to each training task when the training personnel perform the training tasks of each sub-process. The restricted flight training data corresponding to the training task of the i-th flight training sub-process = min{U i -K 1i ,U i -K 2i ,U i -K 3i ,U i -K 4i}; Among them, i = 1, 2,..., m, representing the numbers corresponding to each sub-process of the entire flight training process, m represents the total number of sub-processes existing in the entire flight training process, K 1i =h 1 *Q i , K 2i =h 2 *Y i , K 3i =h 3 *A i , K 4i =h 4 *B i , The above linear equations are all trained from historical training experience data. The experience data refers to the training requirement data corresponding to the training parts completed by the training personnel under various meteorological parameters during the training process. h 1 , h 2 , h 3 , h 4 all represent weight coefficients, Q i , Y i , Ai , B i respectively represent the visibility, rainfall, snowfall, and wind speed corresponding to the location where the training task is located when the trainer is performing the training task of the flight training sub-process numbered i. min represents the minimum value symbol, h 1 *Q i represents that when the visibility at the location where the training task of the flight training sub-process numbered i is Q i , the reduction value of the training requirement data corresponding to the training task, h 2 *Y i represents that when the rainfall at the location where the training task of the flight training sub-process numbered i is Y i , the reduction value of the training requirement data corresponding to the training task, h 3 *A i represents that when the snowfall at the location where the training task of the flight training sub-process numbered i is A i , the reduction value of the training requirement data corresponding to the training task, h 4 *B i represents that when the wind speed at the location where the training task of the flight training sub-process numbered i is B i , the reduction value of the training requirement data corresponding to the training task; If W i ≤R i ≤U i , then put R i into the set M to obtain the safety risk data set of the entire flight training process; If R i >U i , then put R i into the set N to obtain the abnormal data set of the entire flight training process; Among them, R i represents the flight training data collected in real time when the trainer is performing the training task of the flight training sub-process numbered i, and U i represents the standard flight training data corresponding to the training task of the flight training sub-process numbered i, and W i represents the restricted flight training data corresponding to the training task of the flight training sub-process numbered i; The flight training data calling module is used to selectively call the flight training data after safety risk integration processing according to the adaptability between the flight training data stored in the safety risk data set and the abnormal data set and each job type; The flight training data calling module obtains the job types of the personnel who have undergone identity authentication in the intelligent middle platform. The job types include commanders, controllers, meteorological maintenance personnel, and training personnel. According to the fitness between each flight training data stored in the safety risk dataset and the abnormal dataset and each job type, the flight training data stored in the safety risk dataset and the abnormal dataset is selectively called. The specific method is as follows: For the safety risk dataset: S ij =exp[-(U i -R i ) / (U i -W i )]*(H j / F); Among them, j = 1, 2, 3, 4, representing the numbers corresponding to each job type. exp represents the exponential function with the natural constant e (e = 2.72) as the base. F represents the total number of historical flight training data stored in the safety risk dataset. When j = 1, H j represents the total number of historical flight training data stored in the safety risk dataset called by the commander (the commander is the person responsible for commanding the operation). When j = 2, H j represents the total number of historical flight training data stored in the safety risk dataset called by the controller (the controller is the abbreviation of air traffic controller). When j = 3, H j represents the total number of historical flight training data stored in the safety risk dataset called by the meteorological maintenance personnel (the meteorological maintenance personnel refer to the personnel responsible for civil aviation meteorological observation, detection, information exchange, and maintenance of meteorological equipment and facilities). When j = 4, H j represents the total number of historical flight training data stored in the safety risk dataset called by the training personnel (the training personnel refer to the personnel who control the operation of the drone). S ij represents the flight training data stored in the safety risk dataset R i , and the fitness between the job type numbered j; For the abnormal dataset: D ij =exp[-(R i -U i ) / (U i -W i )]*(K j / P); Among them, P represents the total number of historical flight training data stored in the abnormal dataset. K j represents the total number of historical flight training data stored in the abnormal dataset called by the staff of the job type numbered j. D ij represents the flight training data stored in the abnormal dataset R i, the fitness degree with the job type numbered j; When 0.8 ≤ S ij ≤ 1, it means that the staff of the job type numbered j calls the flight training data R stored in the safety risk dataset. i Otherwise, the flight training data R stored in the safety risk dataset is not called. i ; When 0.8 ≤ D ij ≤ 1, it means that the staff of the job type numbered j calls the flight training data R stored in the abnormal dataset. i Otherwise, the flight training data R stored in the safety risk dataset is not called. i ; The data analysis module is used to perform safety analysis on various flight training data called by the flight training data calling module. The data analysis module performs discrete analysis on the flight training data called by the commander, controller, meteorological technician, and training personnel respectively. Combining with the fluctuation of the called flight training data, it analyzes the safety of each flight training subprocess in real time. The specific analysis formula is: ; Among them, q = 1, 2, …, g, which means that when the training personnel execute the training tasks of each flight training subprocess, the acquisition times of the called flight training data are numbered in chronological order. g represents the total number of numbers. E j represents the standard deviation calculated according to the flight training data called by the staff of the job type numbered j, and L j represents the mean value calculated according to the flight training data called by the staff of the job type numbered j, and R iq represents the flight training data collected at the corresponding moment of the qth number when the training personnel execute the training task of the flight training subprocess numbered i, and C i represents the maximum allowable deviation value between the flight training data collected at adjacent acquisition times when the training personnel execute the training task of the flight training subprocess numbered i. When |R i(q+1) -R iq |-C i > 0, , when |R i(q+1) -R iq |-C i ≤ 0, , V ij(q+1) represents the safety factor corresponding to the training personnel executing the flight training subprocess numbered i obtained according to the flight training data called by the staff of the job type numbered j at the corresponding moment of the q + 1th number. According to maxV ij(q+1) Determine the safety factor corresponding to the flight training sub-process numbered i when the staff executes it at the moment corresponding to q + 1. max represents the maximum value symbol; The training management module is used to manage the execution status of each flight training sub-process; The training management module includes a process management time calculation unit and a training management unit; The process management time calculation unit calculates the management time of each flight training sub-process according to the safety analysis result of the data analysis module. The specific method is: When maxV ij(q+1) > 0.5, the management time T of the flight training sub-process numbered i i = T q+1 , T q+1 represents the moment corresponding to q + 1; Let the job type number corresponding to maxV ij(q+1) be μ, μ = 1, 2, 3, 4. At the moment of T q+1 the staff of the job type numbered μ manages the execution status of the training personnel for the flight training sub-process numbered i; The training management unit receives the management time calculated by the process management time calculation unit, matches the staff at the corresponding management time, and manages the execution status of the training personnel for each flight training sub-process.

[0021] An integrated portal design data management method based on an intelligent middle platform. The method includes: S10: When the training personnel execute the training tasks of each flight training sub-process, collect the flight training data of the training personnel, and perform security risk integration processing on the collected flight training data; S20: According to the adaptability between the flight training data stored in the security risk data set and the abnormal data set and each job type, selectively call the flight training data after security risk integration processing; S30: Perform security analysis on various types of flight training data called by the flight training data calling module; S40: Based on the security analysis result in S30, calculate the management time of each flight training sub-process, and based on the calculation result, manage the execution status of each flight training sub-process.

[0022] Example 1: Suppose the training requirement data corresponding to the training task of the flight training sub-process numbered 1 is to hover for 3 minutes (in the case of no rainfall), h 2= 0.2. When the rainfall at the location of the training task of the flight training subprocess numbered 1 is 5.1 mm, the reduction value of the training requirement data corresponding to the training task of the flight training subprocess numbered 1 = 0.2 * 5.1 = 1.02 minutes.

[0023] Embodiment 2: The integrated portal supports docking with the existing unified identity authentication system in the flight training area to achieve the ability of single sign-on and free jumping. The main functions include a personal workbench and a management middle platform; After the user logs in to the system through unified identity authentication and enters the personal workbench in the intelligent middle platform, the workbench supports the following functions: (1) Support unified pending task management, can display multiple types of pending tasks, support users to execute with one key, and support viewing the details of pending events and process information; (2) Support unified message management, can receive system messages and internal starred messages, and support unread message reminders; (3) Support unified schedule management, can default to highlight and display the schedule information of the current day; support users to flexibly create schedule information; support personalized display of multiple types of schedule information; (4) Support full-screen display of the personal workbench and support multiple theme settings; provide an interface lock screen password; (5) Integrate a personal center, support the display of basic information, unit information, and job information, support users to modify passwords; support the display of user footprints; can provide system usage help documents; The general management capabilities of the management middle platform form a unified organizational structure and user role permission system for the platform, and uniformly manage the access control rules and permissions of objects such as resources, data, applications, and services. The main functions include: system functions such as account management, permission management, message management, organization structure, online users, and operation logs.

[0024] Embodiment 3: When performing three-dimensional simulation of the flight training scenario of training personnel, support modeling of target buildings through aerial photography, oblique photography, etc., establish a two / three-dimensional model library, customize visualization management components, and combine with BI engines, two / three-dimensional engines, digital twins, GIS resource libraries, etc. to achieve three-dimensional simulation of the flight training scenario.

[0025] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An integrated portal design data management system based on intelligent middle platform, characterized by: The system includes a flight training data integration module, a flight training data calling module, a data analysis module and a training management module; The flight training data integration module is used to collect the flight training data of the trainees when the trainees perform the training tasks of each flight training sub-process, and perform safety risk integration processing on the collected flight training data; The flight training data calling module is used to selectively call the flight training data after the safety risk integration processing according to the adaptability between the flight training data stored in the safety risk data set and the abnormal data set and each job type; The data analysis module is used to perform safety analysis on various types of flight training data called by the flight training data calling module; The training management module is used to manage the execution status of each flight training sub-process.

2. According to claim 1, an integrated portal design data management system based on intelligent middle platform is characterized in that: The flight training data integration module includes a flight training data acquisition unit and a flight training data integration unit; The flight training data acquisition unit acquires the entire flight training process, and collects the flight training data of the trainees when the trainees perform the training tasks of each flight training sub-process; The flight training data integration unit receives the flight training data collected by the flight training data collection unit, and compares the received flight training data with the matching standard flight training data and the restricted flight training data corresponding to the matching standard flight training data in a three-dimensional flight training simulation scene to obtain a safety risk data set and an abnormal data set for the entire flight training process.

3. According to claim 2, an integrated portal design data management system based on intelligent middle platform is characterized in that: The specific method for the flight training data integration unit to obtain the safety risk data set and the abnormal data set of each flight training sub-process is: A three-dimensional simulation is performed on a flight training scene for training personnel, and the three-dimensional simulated flight training scene is rendered according to meteorological parameters at a location of the flight training scene to obtain a three-dimensional simulated flight training scene, wherein the meteorological parameters include visibility, rainfall, snowfall, and wind speed. Based on the three-dimensional simulated flight training scene, standard flight training data matching the received flight training data and restricted flight training data corresponding to the standard flight training data matching the received flight training data are determined, and the restricted flight training data corresponding to the training task of the flight training sub-process numbered i=min{U i -K 1i ,U i -K 2i ,U i -K 3i ,U i -K 4i }; Among them, i=1,2,…,m, represents the number corresponding to each training sub-process of the whole flight training process, m represents the total number of training sub-processes in the whole flight training process, K 1i =h1*Q i , K 2i =h2*Y i , K 3i =h3*A i , K 4i =h4*B i , h1, h2, h3, h4 all represent weight coefficients, Q i , Y i , A i , B i They respectively represent the visibility, rainfall, snowfall, and wind speed corresponding to the location of the training task when the training personnel perform the training task of the flight training sub-process numbered i, and min represents the minimum value symbol; If W i ≤R i ≤U i , then R i Put it into the set M to obtain the safety risk data set of the whole flight training process; If R i >U i , then R i Put it into set N to obtain the abnormal data set of the whole process of flight training; Among them, R i represents the flight training data collected in real time by the trainer when performing the training task of the flight training sub-process numbered i, U i represents the standard flight training data corresponding to the training task of the flight training sub-process numbered i, W i Indicates the restricted flight training data corresponding to the training task of the flight training sub-process numbered i.

4. According to claim 3, an integrated portal design data management system based on intelligent middle platform is characterized in that: The flight training data calling module obtains the job type of the personnel who undergo identity authentication in the intelligent middle station, and the job types include command, control, meteorological maintenance and training personnel. According to the compatibility between each flight training data stored in the safety risk data set and the abnormal data set and each job type, the flight training data stored in the safety risk data set and the abnormal data set are selectively called.

5. According to claim 4, an integrated portal design data management system based on intelligent middle platform is characterized in that: The specific method for the flight training data calling module to selectively call the flight training data stored in the safety risk data set and the abnormal data set is: For the security risk dataset: S ij =exp[-(U i -R i ) / (U i -W i )]*(H j / F); Where, j = 1, 2, 3, 4, representing the number corresponding to each job type, exp represents the exponential function with the natural constant e as the base, F represents the total number of historical flight training data stored in the safety risk data set, and when j = 1, H j represents the total number of historical flight training data stored in the safety risk dataset called by the commander. When j=2, H j represents the total number of historical flight training data stored in the safety risk dataset called by the controller. When j=3, H j represents the total number of historical flight training data stored in the safety risk data set called by the meteorological maintenance personnel. When j=4, H j represents the total number of historical flight training data stored in the safety risk dataset called by the training personnel, S ij Represents the flight training data R stored in the safety risk dataset i , and the degree of fit between it and the job type numbered j; For the abnormal dataset: D ij =exp[-(R i -U i ) / (U i -W i )]*(K j / P); Among them, P represents the total number of historical flight training data stored in the abnormal data set, K j The total number of historical flight training data stored in the abnormal data set called by the staff with the job type number j, D ij Represents the flight training data R stored in the anomaly dataset i , and the degree of fit between it and the job type numbered j; When 0.8≤S ij ≤1, it means that the staff with the job type number j has a certain understanding of the flight training data R stored in the safety risk dataset. i Otherwise, the flight training data R stored in the safety risk dataset will not be called. i Make a call; When 0.8≤D ij ≤1, it means that the staff with the job type number j has a good understanding of the flight training data R stored in the abnormal data set. i Otherwise, the flight training data R stored in the safety risk dataset will not be called. i Make a call.

6. The integrated portal design data management system based on intelligent middle platform according to claim 5 is characterized by: The data analysis module performs discrete analysis on the flight training data called by the commander, the air traffic controller, the meteorological maintenance personnel and the training personnel, and analyzes the safety of each flight training sub-process in real time in combination with the fluctuation of the called flight training data.

7. The integrated portal design data management system based on intelligent middle platform according to claim 6 is characterized by: The specific formula for the data analysis module to analyze the safety of each flight training sub-process in real time is: ； Among them, q = 1, 2, ..., g, which means that when the training personnel perform the training tasks of each flight training sub-process, they number the collection time of each flight training data called in chronological order, g represents the total number, E j represents the standard deviation calculated based on the flight training data called by the staff with the job type number j, L j represents the mean value of the flight training data called by the staff with the job type numbered j, R iq represents the flight training data collected at the time corresponding to number q when the training personnel performs the training task of the flight training sub-process numbered i, C i It indicates the maximum deviation allowed between the flight training data collected at adjacent collection times when the training personnel performs the training task of the flight training sub-process numbered i. i(q+1) -R iq |-C i >0 o'clock, , when |R i(q+1) -R iq |-C i When ≤0, , V ij(q+1) It represents the safety factor corresponding to the flight training sub-process numbered i executed by the training personnel obtained according to the flight training data called by the staff of the job type numbered j at the time corresponding to numbered q+1; According to maxV ij(q+1) The safety factor corresponding to the flight training sub-process numbered i executed by the staff at the time corresponding to the numbered q+1 is determined, and max represents the maximum value symbol.

8. The integrated portal design data management system based on intelligent middle platform according to claim 7 is characterized by: The training management module includes a process management time calculation unit and a training management unit; The process management time calculation unit calculates the management time of each flight training sub-process according to the safety analysis result of the data analysis module; The training management unit receives the management time calculated by the process management time calculation unit, matches the staff at the corresponding management time, and manages the execution of each flight training sub-process by the training personnel.

9. The integrated portal design data management system based on intelligent middle platform according to claim 8 is characterized by: The specific method for the process time management calculation unit to calculate the management time of each flight training sub-process is: When maxV ij(q+1) > 0.5, the management time T of the flight training sub-process numbered i i =T q+1 , T q+1 Indicates the time corresponding to number q+1; Let maxV ij(q+1) The corresponding job type is numbered μ, μ=1,2,3,4. q+1 At this moment, the staff member of the job type numbered μ manages the execution of the flight training sub-process numbered i by the training personnel.

10. An integrated portal design data management method based on an intelligent middle platform applied to the integrated portal design data management system based on an intelligent middle platform according to any one of claims 1 to 9, characterized in that: The method comprises: S10: When the trainer performs the training tasks of each flight training sub-process, the flight training data of the trainer is collected, and the collected flight training data is integrated for safety risks; S20: selectively calling the flight training data after safety risk integration processing according to the adaptability between the flight training data stored in the safety risk data set and the abnormal data set and each job type; S30: Performing safety analysis on various types of flight training data called by the flight training data calling module; S40: Based on the safety analysis result in S30, the management time of each flight training sub-process is calculated, and based on the calculation result, the execution status of each flight training sub-process is managed.

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