A Test Data Acquisition Method and System for a Helicopter Full Mission Simulator

Abstract

The present application provides a test data acquisition method and system for a helicopter full mission simulator, belonging to the field of helicopter full mission simulators, and is used to solve the problem in the related art that the acquisition frequency of sensors cannot be intelligently and dynamically determined according to the complex situations and requirements in the actual simulated flight mission. In this method and system, the acquisition frequency of each sensor can be comprehensively and intelligently analyzed based on the real-time flight scene information, flight mission information, and flight operation information in the simulated flight mission, combined with the specific situation of the sensor and the historical flight mission records, so that the acquisition frequency data of each type of sensor not only meets the required range of the flight scene and flight mission, but also meets the operation requirements of the pilot, and the acquisition frequency is independently and dynamically determined for each sensor, which is beneficial to improving the pertinence, accuracy, and efficiency of data acquisition, and realizing more intelligent and efficient data acquisition.

Description

Technical Field

[0001] This application relates to the field of helicopter full-mission simulators, and particularly to a test data acquisition method and system for helicopter full-mission simulators. Background Art

[0002] Helicopter simulators are of great significance in the fields of pilot training, flight system R & D and testing. It can simulate real flight environments and conditions, enabling pilots to train under safe and controllable conditions, and at the same time providing support for the performance and reliability evaluation of helicopter flight systems. Data acquisition, as a key link in the operation of the simulator, can obtain various simulated flight data such as flight attitudes, control system states, and engine parameters, providing a basis for the evaluation of pilot training effects and the optimization of simulator performance.

[0003] Currently, certain progress has been made in the data acquisition technology of helicopter simulators. Most simulators collect sensor data at a fixed acquisition frequency, that is, during the entire simulated flight process, the acquisition frequency of each sensor is preset and remains unchanged. This method is simple to implement and has low requirements for software and hardware. Some advanced simulators have begun to adjust the acquisition frequency according to flight phases, such as setting different values in different phases such as takeoff, cruise, and landing, which improves the pertinence of acquisition to a certain extent, but the adjustment strategy is single, only considering the factor of flight phase.

[0004] However, the existing data acquisition technology has obvious defects. It lacks dynamic adaptability and cannot intelligently and dynamically determine the acquisition frequency of sensors according to the complex situations and requirements in the actual simulated flight tasks. Summary of the Invention

[0005] This application provides a test data acquisition method and system for helicopter full-mission simulators, which dynamically adjusts the sensor acquisition frequency based on factors such as flight scenarios, tasks, and pilot operations, facilitating the improvement of the pertinence, accuracy, and efficiency of data acquisition, and achieving more intelligent and efficient data acquisition.

[0006] In a first aspect, this application provides a test data acquisition method for helicopter full-mission simulators. The method includes:

[0007] Real-time obtain the flight scenario information, flight task information, and pilot operation information of the current simulated flight task, and obtain the sensor characteristic information of each sensor in the simulator. The flight scenario information, flight task information, and pilot operation information are all represented as high-dimensional feature vectors;

[0008] Analyze and determine associated task records and similar operation records in the pre-acquired historical flight task records based on flight scenario information, flight mission information, and pilot operation information. The historical flight task records include real-time historical flight scenarios, historical flight missions, historical operation information, and the historical acquisition frequency of each sensor. The historical flight scenario of the associated task record has a scenario similarity with the flight scenario information higher than the first similarity threshold, and the historical flight mission has a task similarity with the flight mission information higher than the second similarity threshold. The historical flight scenario of the similar operation record has a scenario similarity with the flight scenario information higher than the first similarity threshold, the historical flight mission has a task similarity with the flight mission information higher than the second similarity threshold, and the historical operation record has an operation similarity with the pilot operation information higher than the third similarity threshold;

[0009] For each sensor in the simulator, determine the basic acquisition frequency range based on the associated task records, and determine the acquisition frequency data within the basic acquisition frequency range in combination with the similar operation records.

[0010] By adopting the above technical solution, it is possible to comprehensively and intelligently analyze the acquisition frequency of each sensor according to the real-time flight scenario information, flight mission information, and flight operation information in the simulated flight mission, combined with the specific situation of the sensor and the historical flight task records, so that the acquisition frequency data of each sensor not only meets the required range of the flight scenario and flight mission, but also meets the operation requirements of the pilot, and independently and dynamically determines the acquisition frequency for each sensor, which is beneficial to improving the pertinence, accuracy, and efficiency of data acquisition, and realizing more intelligent and efficient data acquisition.

[0011] Furthermore, the analysis and determination of associated task records and similar operation records in the pre-acquired historical flight task records based on flight scenario information, flight mission information, and pilot operation information include:

[0012] For the historical flight task records, determine the scenario similarity between the historical flight scenario of each unit time length and the flight scenario information, and determine the task similarity between the historical flight mission of each unit time length and the flight mission information;

[0013] Determine the historical flight task records of the unit time length with a scenario similarity higher than the first similarity threshold and a task similarity higher than the second similarity threshold as the associated task records;

[0014] Analyze each associated task record to determine the operation similarity between the historical operation record and the pilot operation information;

[0015] Determine the associated task records with an operation similarity higher than the third similarity threshold as the similar operation records.

[0016] Further, the determination of the basic acquisition frequency range based on the associated task records includes: for each sensor in the simulator,

[0017] determine the historical acquisition frequencies of the sensors in the associated task records whose similarity to the target sensor is higher than the fourth similarity threshold;

[0018] calculate the average value and the standard deviation of the historical acquisition frequencies of all the associated task records as the associated average value and the associated standard deviation respectively;

[0019] determine the basic acquisition frequency range according to the associated average value and the associated standard deviation, where the lower limit of the basic acquisition frequency range is equal to the associated average value minus a preset multiple of the associated standard deviation, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus a preset multiple of the associated standard deviation.

[0020] Further, the determination of the acquisition frequency data within the basic acquisition frequency range by combining the similar operation records includes: for each sensor in the simulator,

[0021] calculate the average value and the standard deviation of the historical acquisition frequencies of all the similar operation records as the similar average value and the similar standard deviation respectively;

[0022] Let the associated average value of the i-th sensor be , the associated standard deviation be , the similar average value be , the similar standard deviation be , the acquisition frequency data be , then

[0023] ;

[0024] ;

[0025] In the formula, is a preset multiple, is the first preset positive integer, are the first preset weight, the second preset weight and the third preset weight respectively, , is the first preset constant, is the comprehensive influence coefficient pre-acquired for the i-th sensor, and the value range of the comprehensive influence coefficient is .

[0026] Further, the method for obtaining the comprehensive influence coefficient includes: for each sensor in the simulator,

[0027] Let there be n sensors in the simulator, the acquisition frequency data of the i-th sensor be , and the acquisition frequency data of the j-th sensor be And , the similarity between the i-th sensor and the j-th sensor is , then , where is the fifth similarity threshold.

[0028] In a second aspect, the present application provides a test data acquisition system for a helicopter full mission simulator. The system includes a data acquisition module, a data analysis module, and a data processing module;

[0029] The data acquisition module is configured to acquire in real time the flight scene information, flight mission information, and pilot operation information of the current simulated flight mission, and acquire the sensor feature information of each sensor in the simulator, where the flight scene information, flight mission information, and pilot operation information are all represented as high-dimensional feature vectors;

[0030] The data analysis module is configured to analyze and determine associated mission records and similar operation records in the pre-acquired historical flight mission records based on the flight scene information, flight mission information, and pilot operation information. The historical flight mission records include real-time historical flight scenes, historical flight missions, and historical operation information, as well as the historical acquisition frequency of each sensor. The scene similarity between the historical flight scene of the associated mission record and the flight scene information is higher than the first similarity threshold, and the mission similarity between the historical flight mission and the flight mission information is higher than the second similarity threshold. The scene similarity between the historical flight scene of the similar operation record and the flight scene information is higher than the first similarity threshold, the mission similarity between the historical flight mission and the flight mission information is higher than the second similarity threshold, and the operation similarity between the historical operation record and the pilot operation information is higher than the third similarity threshold;

[0031] The data processing module is configured to, for each sensor in the simulator, determine a basic acquisition frequency range based on the associated mission records, and determine acquisition frequency data within the basic acquisition frequency range in combination with the similar operation records.

[0032] Further, the data analysis module is further configured such that the analyzing and determining the associated mission records and the similar operation records in the pre-acquired historical flight mission records based on the flight scene information, flight mission information, and pilot operation information includes:

[0033] For the historical flight mission records, determine the scene similarity between the historical flight scene of each unit time length and the flight scene information, and determine the mission similarity between the historical flight mission of each unit time length and the flight mission information;

[0034] Determine the historical flight mission records of the unit time length with a scene similarity higher than the first similarity threshold and a mission similarity higher than the second similarity threshold as the associated mission records;

[0035] Analyze each associated task record to determine the operational similarity between the historical operation records and the pilot operation information;

[0036] Determine the associated task records with an operational similarity higher than the third similarity threshold as similar operation records.

[0037] Furthermore, the data processing module is further configured such that the determination of the basic acquisition frequency range based on the associated task records includes: for each sensor in the simulator,

[0038] Determine the historical acquisition frequency of the sensors in the associated task records whose similarity to the target sensor is higher than the fourth similarity threshold;

[0039] Calculate the average value and standard deviation of the historical acquisition frequencies of all associated task records as the associated average value and associated standard deviation respectively;

[0040] Determine the basic acquisition frequency range according to the associated average value and associated standard deviation. The lower limit of the basic acquisition frequency range is equal to the associated average value minus a preset multiple of the associated standard deviation, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus a preset multiple of the associated standard deviation.

[0041] Furthermore, the data processing module is further configured such that the determination of the acquisition frequency data within the basic acquisition frequency range by combining the similar operation records includes: for each sensor in the simulator,

[0042] Calculate the average value and standard deviation of the historical acquisition frequencies of all similar operation records as the similar average value and similar standard deviation respectively;

[0043] Let the associated average value of the i-th sensor be , the associated standard deviation be , the similar average value be , the similar standard deviation be , the acquisition frequency data be , then

[0044] ;

[0045] ;

[0046] In the formula, is the preset multiple, is the first preset positive integer, are the first preset weight, the second preset weight and the third preset weight respectively, , is the first preset constant, The comprehensive influence coefficient pre-acquired for the i-th sensor, and the value range of the comprehensive influence coefficient is .

[0047] Further, the data processing module is further configured that the method for obtaining the comprehensive influence coefficient includes: for each sensor in the simulator,

[0048] Suppose there are n sensors in the simulator, the acquisition frequency data of the i-th sensor is , and the acquisition frequency data of the j-th sensor is and , the similarity between the i-th sensor and the j-th sensor is , then , where, is the fifth similarity threshold.

[0049] In summary, the present application at least includes the following beneficial effects:

[0050] A test data acquisition method and system for a helicopter full mission simulator are provided, which can dynamically adjust the acquisition frequency of each sensor based on the specific simulated flight mission situation, and is beneficial to improving the pertinence, accuracy and efficiency of data acquisition.

[0051] It should be understood that the content described in the invention content part is not intended to limit the key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Combined with the drawings and referring to the following detailed description, the above and other features, advantages and aspects of the embodiments of the present application will become more obvious. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0053] Figure 1 Shows a flowchart of a test data acquisition method for a helicopter full mission simulator in an embodiment of the present application;

[0054] Figure 2 Shows a block diagram of a test data acquisition system for a helicopter full mission simulator in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0056] In addition, the term "and / or" in this document is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after.

[0057] In a helicopter simulation flight mission, the acquisition strategy of test data is affected by the flight scenario, mission, and pilot operation. Different flight scenarios (such as low-altitude, high-altitude, and complex meteorological condition flights) and missions (such as rescue, patrol, and transportation missions) have significant differences in data acquisition requirements, and pilot operation also affects the acquisition requirements. For example, in a rescue mission, attention should be paid to hover stability and precise control data, while in a patrol mission, more emphasis is placed on flight trajectory and environmental monitoring data; a higher acquisition frequency is required to capture the system response during intense control. However, the existing technology cannot perceive and adjust in real time, resulting in the possibility that the acquired data may not meet the actual requirements.

[0058] At the same time, the existing technology also leads to the coexistence of data redundancy and missing data. The fixed or simple staged acquisition frequency causes high-frequency acquisition during periods when high-frequency acquisition is not required, generating a large amount of redundant data and increasing the storage and processing burden; while at critical moments when high-frequency acquisition is required, such as during emergency operations or emergencies, it may not be possible to capture key data in time, resulting in missing data and affecting the accurate analysis and evaluation of the flight process.

[0059] In addition, it is difficult for the existing technology to accurately match sensor requirements. The importance and data change characteristics of different sensors are different under different flight scenarios, missions, and operations. For example, when adjusting the flight attitude, the data of the attitude sensor changes frequently and is crucial; when the fuel system operates stably, the data of the fuel sensor changes relatively slowly. However, the existing acquisition technology cannot accurately adjust the acquisition frequency according to the specific situation of each sensor, reducing the efficiency and quality of data acquisition.

[0060] In summary, the existing data acquisition technology for helicopter simulators can no longer meet the increasingly complex flight simulation requirements. Therefore, there is an urgent need for a method and model that can dynamically adjust the sensor acquisition frequency based on factors such as flight scenarios, tasks, and pilot operations, so as to improve the pertinence, accuracy, and efficiency of data acquisition, and provide more powerful support for the development and application of helicopter simulators. The present invention is proposed to solve the above problems, aiming to make up for the deficiencies of the existing technology and achieve more intelligent and efficient data acquisition.

[0061] The present application provides a test data acquisition method and system for a helicopter full-mission simulator, which dynamically adjusts the sensor acquisition frequency based on factors such as flight scenarios, tasks, and pilot operations, facilitating the improvement of the pertinence, accuracy, and efficiency of data acquisition and achieving more intelligent and efficient data acquisition.

[0062] In the first aspect, an embodiment of the present application discloses a test data acquisition method for a helicopter full-mission simulator. This method can be executed by the controller of the helicopter simulator.

[0063] Figure 1 The flowchart of a test data acquisition method for a helicopter full-mission simulator in an embodiment of the present application is shown.

[0064] Referring to Figure 1 , the method specifically includes the following steps:

[0065] S110: Real-time obtain the flight scenario information, flight task information, and pilot operation information of the current simulated flight mission, and obtain the sensor feature information of each sensor in the simulator.

[0066] The flight scenario information includes multiple flight scenario tags, which characterize the specific situation of the specific flight scenario, such as flight altitude, flight position, flight environment, etc.; the flight task information includes multiple flight task tags, which characterize the specific flight tasks to be achieved; the pilot operation information includes specific operation actions; the flight scenario information, flight task information, and pilot operation information are all represented as high-dimensional feature vectors to describe the flight scenario information, flight task information, and pilot operation information with high-dimensional feature vectors. And the flight scenario information, flight task information, and pilot operation information all carry time stamps to facilitate reflecting the real-time flight scenario, flight task, and pilot operation.

[0067] S120: Analyze and determine the associated task records and similar operation records in the pre-obtained historical flight task records based on the flight scenario information, flight task information, and pilot operation information.

[0068] In the method of this step, the historical flight mission record includes real-time historical flight scenarios, historical flight missions, historical operation information, and the historical acquisition frequency of each sensor. The scenario similarity between the historical flight scenario of the associated mission record and the flight scenario information is higher than the first similarity threshold, and the mission similarity between the historical flight mission and the flight mission information is higher than the second similarity threshold. The scenario similarity between the historical flight scenario of the similar operation record and the flight scenario information is higher than the first similarity threshold, the mission similarity between the historical flight mission and the flight mission information is higher than the second similarity threshold, and the operation similarity between the historical operation record and the pilot operation information is higher than the third similarity threshold.

[0069] Specifically, the historical flight mission record is a record of the simulated flight missions previously executed by this helicopter simulator or even simulators of this type of helicopter, which includes past flight scenarios, flight missions, pilot operations, and the specific test data acquisition strategy at that time, that is, the historical acquisition frequency of each sensor at each moment.

[0070] The method of this step specifically includes: for the historical flight mission record, determining the scenario similarity between the historical flight scenario of each unit time length and the flight scenario information, and determining the mission similarity between the historical flight mission of each unit time length and the flight mission information; determining the historical flight mission record of the unit time length with a scenario similarity higher than the first similarity threshold and a mission similarity higher than the second similarity threshold as the associated mission record; analyzing each associated mission record to determine the operation similarity between the historical operation record and the pilot operation information; determining the associated mission record with an operation similarity higher than the third similarity threshold as the similar operation record.

[0071] In the method of this step, the unit time length is the smallest time length unit, and it can be considered that the flight scenario, flight mission, pilot operation, and the acquisition frequency of each sensor therein remain unchanged. The foregoing scenario similarity, mission similarity, and operation similarity can all be determined by the vector similarity of the corresponding feature vectors. The first similarity threshold, the second similarity threshold, and the third similarity threshold are all pre-acquired. The purpose of the method of this step is to screen the sensor acquisition strategies under similar flight scenarios, similar flight missions, and similar pilot operations.

[0072] S130: For each sensor in the simulator, determine the basic acquisition frequency range based on the associated mission record, and determine the acquisition frequency data within the basic acquisition frequency range in combination with the similar operation record.

[0073] In the method of this step, determining the basic acquisition frequency range based on the associated task records includes: for each sensor in the simulator, determining the historical acquisition frequencies of the sensors in the associated task records whose similarity to the target sensor is higher than the fourth similarity threshold; calculating the average value and the standard deviation of the historical acquisition frequencies of all the associated task records as the associated average value and the associated standard deviation respectively; determining the basic acquisition frequency range according to the associated average value and the associated standard deviation, where the lower limit of the basic acquisition frequency range is equal to the associated average value minus a preset multiple of the associated standard deviation, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus a preset multiple of the associated standard deviation.

[0074] In the method of this step, the sensor carries multiple sensor tags, and a high-dimensional feature vector characterizing the sensor situation can be determined based on all the sensor tags.

[0075] In the method of this step, determining the acquisition frequency data within the basic acquisition frequency range by combining the similarity operation records includes: for each sensor in the simulator, calculating the average value and the standard deviation of the historical acquisition frequencies of all the similarity operation records as the similarity average value and the similarity standard deviation respectively;

[0076] Let the associated average value of the i-th sensor be , the associated standard deviation be , the similarity average value be , the similarity standard deviation be , and the acquisition frequency data be , then

[0077] ;

[0078] ;

[0079] In the formula, is a preset multiple, is a first preset positive integer, are the first preset weight, the second preset weight and the third preset weight respectively, , is a first preset constant, , is the comprehensive influence coefficient pre-acquired for the i-th sensor, and the value range of the comprehensive influence coefficient is . In the method of this step, .

[0080] Among them, the method for obtaining the comprehensive influence coefficient includes: for each sensor in the simulator, assuming that there are n sensors in the simulator, the acquisition frequency data of the i-th sensor is , the acquisition frequency data of the j-th sensor is and The similarity between the i-th sensor and the j-th sensor is , then , where is the fifth similarity threshold. Among them, is the hyperbolic tangent function, whose independent variable ranges from negative infinity to positive infinity, and the dependent variable ranges from .

[0081] In summary, the method can comprehensively and intelligently analyze the acquisition frequency of each sensor according to the real-time flight scene information, flight mission information, and flight operation information in the simulated flight mission, combined with the specific situation of the sensor and the historical flight mission records, so that the acquisition frequency data of each sensor not only meets the required range of the flight scene and flight mission, but also meets the operation requirements of the pilot, and independently and dynamically determines the acquisition frequency for each sensor, which is beneficial to improving the pertinence, accuracy, and efficiency of data acquisition, and realizing more intelligent and efficient data acquisition.

[0082] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to the embodiments of this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0083] In a second aspect, an embodiment of this application discloses a test data acquisition system for a helicopter full-mission simulator. This system can be included in the controller of the helicopter simulator or be implemented as the controller of the helicopter simulator.

[0084] Figure 2 FIG. shows a block diagram of a test data acquisition system for a helicopter full-mission simulator in an embodiment of this application.

[0085] Referring to Figure 2 , this system specifically includes a data acquisition module 210, a data analysis module 220, and a data processing module 230;

[0086] The data acquisition module 210 is used to obtain the flight scene information, flight mission information, and pilot operation information of the current simulated flight mission in real time, and obtain the sensor feature information of each sensor in the simulator. The flight scene information, flight mission information, and pilot operation information are all characterized as high-dimensional feature vectors;

[0087] The data analysis module 220 is configured to analyze and determine associated task records and similar operation records in the pre-acquired historical flight task records based on flight scenario information, flight mission information, and pilot operation information. The historical flight task records include real-time historical flight scenarios, historical flight missions, historical operation information, and the historical acquisition frequency of each sensor. The historical flight scenario of the associated task record has a scenario similarity with the flight scenario information higher than a first similarity threshold, and the historical flight mission has a task similarity with the flight mission information higher than a second similarity threshold. The historical flight scenario of the similar operation record has a scenario similarity with the flight scenario information higher than a first similarity threshold, the historical flight mission has a task similarity with the flight mission information higher than a second similarity threshold, and the historical operation record has an operation similarity with the pilot operation information higher than a third similarity threshold;

[0088] The data processing module 230 is configured to, for each sensor in the simulator, determine a basic acquisition frequency range based on the associated task records, and determine acquisition frequency data within the basic acquisition frequency range in combination with the similar operation records.

[0089] Further, the data analysis module 220 is further configured that the analyzing and determining the associated task records and similar operation records in the pre-acquired historical flight task records based on the flight scenario information, flight mission information, and pilot operation information includes:

[0090] For the historical flight task records, determine the scenario similarity between the historical flight scenario of each unit time length and the flight scenario information, and determine the task similarity between the historical flight mission of each unit time length and the flight mission information;

[0091] Determine the historical flight task records of the unit time length with a scenario similarity higher than the first similarity threshold and a task similarity higher than the second similarity threshold as the associated task records;

[0092] Analyze each associated task record to determine the operation similarity between the historical operation record and the pilot operation information;

[0093] Determine the associated task records with an operation similarity higher than the third similarity threshold as the similar operation records.

[0094] Further, the data processing module 230 is further configured that the determining the basic acquisition frequency range based on the associated task records includes: for each sensor in the simulator,

[0095] Determine the historical acquisition frequency of the sensors in the associated task records with a similarity higher than a fourth similarity threshold to the target sensor;

[0096] Calculate the average value and standard deviation of the historical acquisition frequencies of all associated task records, which are the associated average value and the associated standard deviation respectively;

[0097] Determine the basic acquisition frequency range according to the associated average value and the associated standard deviation. The lower limit of the basic acquisition frequency range is equal to the associated average value minus a preset multiple of the associated standard deviation, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus a preset multiple of the associated standard deviation.

[0098] Furthermore, the data processing module 230 is further configured such that determining the acquisition frequency data within the basic acquisition frequency range for the combined similar operation records includes: for each sensor in the simulator,

[0099] Calculate the average value and standard deviation of the historical acquisition frequencies of all similar operation records, which are the similar average value and the similar standard deviation respectively;

[0100] Let the associated average value of the i-th sensor be , the associated standard deviation be , the similar average value be , the similar standard deviation be , the acquisition frequency data be , then

[0101] ;

[0102] ;

[0103] In the formula, is a preset multiple, is a first preset positive integer, are the first preset weight, the second preset weight and the third preset weight respectively, , is a first preset constant, is the comprehensive influence coefficient pre-acquired for the i-th sensor, and the value range of the comprehensive influence coefficient is .

[0104] Furthermore, the data processing module 230 is further configured such that the method for obtaining the comprehensive influence coefficient includes: for each sensor in the simulator,

[0105] Let there be n sensors in the simulator, the acquisition frequency data of the i-th sensor be , the acquisition frequency data of the j-th sensor be and , the similarity between the i-th sensor and the j-th sensor be , then , in the formula, is the fifth similarity threshold.

[0106] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the described system can refer to the corresponding process in the foregoing method embodiments, and will not be elaborated herein.

[0107] In summary, the present application at least includes the following beneficial effects:

[0108] A test data acquisition method and system for a helicopter full mission simulator are provided, which can dynamically adjust the acquisition frequency of each sensor based on the specific situation of the simulated flight mission, facilitating the improvement of the pertinence, accuracy, and efficiency of data acquisition.

[0109] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present application.

Claims

1. A test data acquisition method for a helicopter full mission simulator, characterized in that: include: Acquire the flight scene information, flight mission information and pilot operation information of the simulated flight mission in real time, and acquire the sensor feature information of each sensor in the simulator, wherein the flight scene information, flight mission information and pilot operation information are all represented as high-dimensional feature vectors; Analyzing and determining associated mission records and similar operation records in pre-acquired historical flight mission records based on flight scene information, flight mission information, and pilot operation information, wherein the historical flight mission records include real-time historical flight scenes, historical flight missions, and historical operation information, as well as historical acquisition frequencies of each sensor, wherein the scene similarity between the historical flight scenes of the associated mission records and the flight scene information is higher than a first similarity threshold, and the task similarity between the historical flight missions and the flight mission information is higher than a second similarity threshold, the scene similarity between the historical flight scenes of the similar operation records and the flight scene information is higher than the first similarity threshold, and the task similarity between the historical flight missions and the flight mission information is higher than a second similarity threshold, and the operation similarity between the historical operation records and the pilot operation information is higher than a third similarity threshold; For each sensor in the simulator, determine the basic acquisition frequency range based on the associated task records, and determine the acquisition frequency data within the basic acquisition frequency range in combination with similar operation records; The determining of the basic acquisition frequency range based on the associated task record includes: for each sensor in the simulator, determining a historical acquisition frequency of a sensor in the associated task record whose similarity to the target sensor is greater than a fourth similarity threshold; Calculate the average and standard deviation of the historical acquisition frequency of all associated task records as the associated mean and associated standard deviation respectively; Determine the basic acquisition frequency range according to the correlation mean value and the correlation standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the correlation mean value minus the correlation standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the correlation mean value plus the correlation standard deviation of a preset multiple; The step of determining the acquisition frequency data in the basic acquisition frequency range by combining similar operation records comprises: for each sensor in the simulator, Calculate the average and standard deviation of the historical collection frequency of all similar operation records as the similarity average and similarity standard deviation respectively; Assume that the correlation average value of the i-th sensor is , the associated standard deviation is , similar to the average value , similar standard deviation is , the acquisition frequency data is ,but ； ； In the formula, is the preset multiple, is the first preset positive integer, are respectively a first preset weight, a second preset weight and a third preset weight, , is the first preset constant, is the comprehensive influence coefficient pre-acquired relative to the i-th sensor, and the value range of the comprehensive influence coefficient is .

2. The method according to claim 1, characterized in that The analyzing and determining the associated mission records and similar operation records in the pre-acquired historical flight mission records based on the flight scenario information, the flight mission information and the pilot operation information includes: For the historical flight mission records, determine the scene similarity between the historical flight scene of each unit time and the flight scene information, and determine the task similarity between the historical flight mission of each unit time and the flight mission information; Determine the historical flight mission records of unit duration whose scene similarity is higher than a first similarity threshold and whose mission similarity is higher than a second similarity threshold as the associated mission records; Analyze each associated mission record to determine the operational similarity between the historical operation record and the pilot's operation information; Determine the associated task records whose operation similarity is higher than a third similarity threshold as similar operation records.

3. The method according to claim 1, characterized in that: The method for obtaining the comprehensive influence coefficient includes: for each sensor in the simulator, Assume that there are n sensors in the simulator, and the acquisition frequency data of the i-th sensor is , the acquisition frequency data of the jth sensor is and , the similarity between the i-th sensor and the j-th sensor is ,but , where is the fifth similarity threshold.

4. A test data acquisition system for a helicopter full mission simulator, characterized in that: It includes a data acquisition module (210), a data analysis module (220) and a data processing module (230); The data acquisition module (210) is used to acquire in real time the flight scene information, flight mission information and pilot operation information of the simulated flight mission, and acquire sensor feature information of each sensor in the simulator, wherein the flight scene information, flight mission information and pilot operation information are all represented as high-dimensional feature vectors; The data analysis module (220) is used to analyze and determine associated task records and similar operation records in pre-acquired historical flight task records based on flight scene information, flight mission information and pilot operation information, the historical flight mission records including real-time historical flight scenes, historical flight missions and historical operation information and historical acquisition frequency of each sensor, the scene similarity between the historical flight scenes of the associated task records and the flight scene information is higher than a first similarity threshold, and the task similarity between the historical flight missions and the flight mission information is higher than a second similarity threshold, the scene similarity between the historical flight scenes of the similar operation records and the flight scene information is higher than the first similarity threshold, and the task similarity between the historical flight missions and the flight mission information is higher than a second similarity threshold, and the operation similarity between the historical operation records and the pilot operation information is higher than a third similarity threshold; The data processing module (230) is used to determine a basic acquisition frequency range for each sensor in the simulator based on associated task records, and determine acquisition frequency data within the basic acquisition frequency range in combination with similar operation records; The data processing module (230) is further configured such that the determining of the basic acquisition frequency range based on the associated task record comprises: for each sensor in the simulator, determining a historical acquisition frequency of a sensor in the associated task record whose similarity to the target sensor is greater than a fourth similarity threshold; Calculate the average and standard deviation of the historical acquisition frequency of all associated task records as the associated mean and associated standard deviation respectively; Determine the basic acquisition frequency range according to the correlation mean value and the correlation standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the correlation mean value minus the correlation standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the correlation mean value plus the correlation standard deviation of a preset multiple; The data processing module (230) is further configured to determine the acquisition frequency data in the basic acquisition frequency range by combining similar operation records, including: for each sensor in the simulator, Calculate the average and standard deviation of the historical collection frequency of all similar operation records as the similarity average and similarity standard deviation respectively; Assume that the correlation average value of the i-th sensor is , the associated standard deviation is , similar to the average value , similar standard deviation is , the acquisition frequency data is ,but ； ； In the formula, is the preset multiple, is the first preset positive integer, are respectively a first preset weight, a second preset weight and a third preset weight, , is the first preset constant, is the comprehensive influence coefficient pre-acquired relative to the i-th sensor, and the value range of the comprehensive influence coefficient is .

5. The system according to claim 4, characterized in that The data analysis module (220) is further configured to analyze and determine associated mission records and similar operation records in pre-acquired historical flight mission records based on the flight scenario information, the flight mission information and the pilot operation information, including: For the historical flight mission records, determine the scene similarity between the historical flight scene of each unit time and the flight scene information, and determine the task similarity between the historical flight mission of each unit time and the flight mission information; Determine the historical flight mission records of unit duration whose scene similarity is higher than a first similarity threshold and whose mission similarity is higher than a second similarity threshold as the associated mission records; Analyze each associated mission record to determine the operational similarity between the historical operation record and the pilot's operation information; Determine the associated task records whose operation similarity is higher than a third similarity threshold as similar operation records.

6. The system according to claim 4, characterized in that The data processing module (230) is further configured such that the method for obtaining the comprehensive influence coefficient comprises: for each sensor in the simulator, Assume that there are n sensors in the simulator, and the acquisition frequency data of the i-th sensor is , the acquisition frequency data of the jth sensor is and , the similarity between the i-th sensor and the j-th sensor is ,but , where is the fifth similarity threshold.

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