Test data acquisition method and system for helicopter full-task simulator

Abstract

The invention provides a test data acquisition method and system for a helicopter full-task simulator, belongs to the field of helicopter full-task simulators, and is used for solving the problem that the acquisition frequency of a sensor cannot be intelligently and dynamically determined according to complex conditions and requirements in an actual simulation flight task in related technologies. According to the method and the system, the acquisition frequency of each sensor can be comprehensively and intelligently analyzed according to real-time flight scene information, flight task information and flight operation information in a simulated flight task in combination with specific conditions of the sensors and historical flight task records; according to the method and the system, the acquisition frequency data of each sensor not only meets the requirement range of a flight scene and a flight task, but also meets the operation requirement of a pilot, and the acquisition frequency is independently and dynamically determined for each sensor, so that the pertinence, the accuracy and the efficiency of data acquisition are favorably improved, and more intelligent and efficient data acquisition is realized.

Description

Technical Field

[0001] The present application relates to the field of helicopter full-mission simulators, and in particular 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 development and testing. They can simulate real flight environments and conditions, allowing pilots to train under safe and controllable conditions, while providing support for the performance and reliability evaluation of helicopter flight systems. Data acquisition, as a key link in the operation of simulators, can obtain various simulated flight data such as flight attitude, control system status, engine parameters, etc., providing a basis for evaluating pilot training effects and optimizing simulator performance.

[0003] At present, the data collection technology of helicopter simulators has made some progress. Most simulators use a fixed collection frequency to collect sensor data, that is, the collection frequency of each sensor is pre-set and remains unchanged during the entire simulated flight process. This method is simple to implement and has low requirements for software and hardware. Some advanced simulators have begun to adjust the collection frequency according to the flight phase, such as setting different values ​​for different phases such as take-off, cruising and landing, which has improved the pertinence of the collection to a certain extent, but the adjustment strategy is single and only considers the flight phase.

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

[0005] The present application provides a test data collection method and system for a helicopter full-mission simulator, which dynamically adjusts the sensor collection frequency based on factors such as flight scenarios, tasks, and pilot operations, which is conducive to improving the pertinence, accuracy, and efficiency of data collection and achieving more intelligent and efficient data collection.

[0006] In a first aspect, the present application provides a test data collection method for a helicopter full mission simulator. The method comprises: 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 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, 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, a basic acquisition frequency range is determined based on associated task records, and acquisition frequency data is determined within the basic acquisition frequency range in combination with similar operation records.

[0007] By adopting the above technical scheme, the acquisition frequency of each sensor can be comprehensively and intelligently analyzed according to the real-time flight scene information, flight mission information and flight operation information in the simulated flight mission, combined with the specific conditions of the sensor and the historical flight mission records. The acquisition frequency data of each sensor meets both the required range of the flight scene and the flight mission and the operational requirements of the pilot, and the acquisition frequency is determined independently and dynamically for each sensor, which is conducive to improving the pertinence, accuracy and efficiency of data collection and realizing more intelligent and efficient data collection.

[0008] Further, 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.

[0009] Further, 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; The basic acquisition frequency range is determined according to the associated average value and the associated standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus the associated standard deviation of a preset multiple.

[0010] Further, the combining similar operation records to determine the acquisition frequency data in the basic acquisition frequency range includes: 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 .

[0011] Furthermore, 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.

[0012] 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; The data acquisition module is used to 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; The data analysis module is used to analyze and determine 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 and the historical acquisition frequency of each sensor, 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 similarity 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 the 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 is used to determine the basic acquisition frequency range for each sensor in the simulator based on the associated task records, and determine the acquisition frequency data within the basic acquisition frequency range in combination with similar operation records.

[0013] Further, the data analysis module is further configured to analyze and determine the associated mission records and similar operation records in the pre-acquired historical flight mission records based on the flight scene 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.

[0014] Furthermore, the data processing module 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; The basic acquisition frequency range is determined according to the associated average value and the associated standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus the associated standard deviation of a preset multiple.

[0015] Furthermore, the data processing module 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 .

[0016] Furthermore, the data processing module is further configured as follows: 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.

[0017] In summary, this application at least has the following beneficial effects: 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, which is conducive to improving the pertinence, accuracy and efficiency of data acquisition.

[0018] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended 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

[0019] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein: Figure 1 A flow chart of a test data collection method for a helicopter full mission simulator in an embodiment of the present application is shown; Figure 2 A block diagram of a test data acquisition system for a helicopter full-mission simulator in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0022] In helicopter simulation flight missions, the test data collection strategy is affected by the flight scenario, mission, and pilot operation. Different flight scenarios (such as low altitude, high altitude, and complex weather conditions) and missions (such as rescue, patrol, and transportation missions) have different data collection requirements, and pilot operations will also affect the collection requirements. For example, rescue missions need to pay attention to hovering stability and precise control data, while patrol missions pay more attention to flight trajectories and environmental monitoring data; during intense control, a higher collection frequency is required to capture system responses. However, existing technologies cannot perceive and adjust in real time, resulting in the possibility that the collected data may not meet actual needs.

[0023] At the same time, existing technologies also lead to the coexistence of data redundancy and loss. Fixed or simple staged collection frequencies result in high-frequency collection during periods when high-frequency collection is not required, generating a large amount of redundant data and increasing the storage and processing burden; and at critical moments when high-frequency collection is required, such as emergency operations or emergencies, key data may not be captured in time, resulting in data loss, affecting the accurate analysis and evaluation of the flight process.

[0024] In addition, existing technologies are difficult to accurately match sensor requirements. Different sensors have different importance and data change characteristics in different flight scenarios, tasks and operations. For example, when the flight attitude is adjusted, the attitude sensor data changes frequently and critically; when the fuel system is running stably, the fuel sensor data changes relatively slowly. However, existing acquisition technology cannot accurately adjust the acquisition frequency according to the specific situation of each sensor, which reduces the efficiency and quality of data acquisition.

[0025] In summary, the existing helicopter simulator data acquisition technology can no longer meet the increasingly complex flight simulation needs. Therefore, there is an urgent need for a method and model to dynamically adjust the sensor acquisition frequency based on flight scenarios, tasks, pilot operations and other factors to improve the pertinence, accuracy and efficiency of data acquisition and provide stronger 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.

[0026] The present application provides a test data collection method and system for a helicopter full-mission simulator, which dynamically adjusts the sensor collection frequency based on factors such as flight scenarios, tasks, and pilot operations, which is conducive to improving the pertinence, accuracy, and efficiency of data collection and achieving more intelligent and efficient data collection.

[0027] In a first aspect, an embodiment of the present application discloses a test data collection method for a helicopter full mission simulator. The method can be executed by a controller of the helicopter simulator.

[0028] Figure 1 A flow chart of a test data collection method for a helicopter full mission simulator in an embodiment of the present application is shown.

[0029] Reference Figure 1 , the method specifically comprises the following steps: S110: Acquire the flight scene information, flight mission information and pilot operation information of the simulated flight mission in real time, and acquire the sensor characteristic information of each sensor in the simulator.

[0030] The flight scene information includes multiple flight scene tags, which characterize the specific situation of the specific flight scene, such as flight altitude, flight position, flight environment, etc.; the flight mission information includes multiple flight mission tags, which characterize the specific flight mission to be achieved; the pilot operation information includes specific operation actions; the flight scene information, flight mission information and pilot operation information are all characterized as high-dimensional feature vectors, and the flight scene information, flight mission information and pilot operation information are described by high-dimensional feature vectors. In addition, the flight scene information, flight mission information and pilot operation information all carry timestamps to reflect the real-time flight scene, flight mission and pilot operation.

[0031] S120: 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.

[0032] In the method of this step, the historical flight mission record includes real-time historical flight scenes, historical flight missions and historical operation information as well as the historical collection frequency of each sensor, the scene similarity between the historical flight scenes of the associated mission record 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 similarity operation record 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 the second similarity threshold, and the operation similarity between the historical operation record and the pilot operation information is higher than a third similarity threshold.

[0033] Specifically, the historical flight mission records are records of simulated flight missions performed in the past by this helicopter simulator or even this type of helicopter simulator. They include past flight scenes, flight missions, pilot operations, and the specific test data collection strategies at that time, that is, the historical collection frequency of each sensor at each moment.

[0034] The method of this step specifically includes: for historical flight mission records, determining the scene similarity between each unit length of historical flight scene and the flight scene information, and determining the task similarity between each unit length of historical flight mission and the flight mission information; determining the historical flight mission records of each unit length whose scene similarity is higher than a first similarity threshold and whose task similarity is higher than a second similarity threshold as the associated task records; analyzing each associated task record to determine the operation similarity between the historical operation record and the pilot operation information; determining the associated task records whose operation similarity is higher than a third similarity threshold as similar operation records.

[0035] In the method of this step, the unit duration is the minimum duration unit, and it can be considered that the flight scenes, flight tasks, pilot operations, and the acquisition frequency of each sensor remain unchanged. The aforementioned scene similarity, task 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 method of this step is intended to screen the sensor acquisition strategy under similar flight scenes and similar pilot operations under similar flight tasks.

[0036] S130: For each sensor in the simulator, determine a basic acquisition frequency range based on associated task records, and determine acquisition frequency data within the basic acquisition frequency range in combination with similar operation records.

[0037] 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 frequency of the sensor in the associated task records whose similarity with the target sensor is higher than a fourth similarity threshold; calculating the average value and standard deviation of the historical acquisition frequencies of all associated task records as the associated average value and the associated standard deviation, respectively; determining the basic acquisition frequency range based on the associated average value and the associated standard deviation, the lower limit of the basic acquisition frequency range being equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range being equal to the associated average value plus the associated standard deviation of a preset multiple.

[0038] In the method of this step, the sensor carries multiple sensor tags, and a high-dimensional feature vector representing the sensor situation can be determined based on all the sensor tags.

[0039] In the method of this step, the determining of the acquisition frequency data in the basic acquisition frequency range in combination with similar operation records includes: for each sensor in the simulator, calculating the average value and standard deviation of the historical acquisition frequencies of all similar operation records as the similarity average value and the 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 In the method of this step, .

[0040] 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 jth sensor is and , the similarity between the i-th sensor and the j-th sensor is ,but , where is the fifth similarity threshold. is a hyperbolic tangent function, whose independent variable ranges from negative infinity to positive infinity, and the dependent variable ranges from .

[0041] In summary, this 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 conditions of the sensor and the historical flight mission records, so that the acquisition frequency data of each sensor not only meets the requirements of the flight scene and flight mission, but also meets the operational requirements of the pilot, and the acquisition frequency is determined independently and dynamically for each sensor, which is conducive to improving the pertinence, accuracy and efficiency of data collection, and realizing more intelligent and efficient data collection.

[0042] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0043] In a second aspect, the present application discloses a test data acquisition system for a helicopter full mission simulator. The system may be included in a controller of the helicopter simulator, or implemented as a controller of the helicopter simulator.

[0044] Figure 2 A block diagram of a test data acquisition system for a helicopter full-mission simulator in an embodiment of the present application is shown.

[0045] Reference Figure 2, the system specifically 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 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; The data analysis module 220 is used to analyze and determine 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 and the historical acquisition frequency of each sensor, 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 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, 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.

[0046] Furthermore, the data analysis module 220 is further configured to analyze and determine 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, 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.

[0047] Furthermore, the data processing module 230 is further configured to: determine 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; The basic acquisition frequency range is determined according to the associated average value and the associated standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus the associated standard deviation of a preset multiple.

[0048] Furthermore, 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 .

[0049] Furthermore, the data processing module 230 is further configured as follows: 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.

[0050] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0051] In summary, this application at least has the following beneficial effects: 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, which is conducive to improving the pertinence, accuracy and efficiency of data acquisition.

[0052] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

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 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, 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, a basic acquisition frequency range is determined based on associated task records, and acquisition frequency data is determined within the basic acquisition frequency range in combination with similar operation records.

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 2, characterized in that 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; The basic acquisition frequency range is determined according to the associated average value and the associated standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus the associated standard deviation of a preset multiple.

4. The method according to claim 3, characterized in that 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 .

5. The method according to claim 4, 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.

6. 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 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, 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.

7. The system according to claim 6, 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, flight mission information and 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.

8. The system according to claim 7, characterized in that 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; The basic acquisition frequency range is determined according to the associated average value and the associated standard deviation, wherein the lower limit of the basic acquisition frequency range is equal to the associated average value minus the associated standard deviation of a preset multiple, and the upper limit of the basic acquisition frequency range is equal to the associated average value plus the associated standard deviation of a preset multiple.

9. The system according to claim 8, characterized in that 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 .

10. The system according to claim 9, 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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