A method and device for generating data for identifying satellite jet control behavior

Abstract

The present disclosure provides a method for generating data for identifying satellite jet control behaviors, which relates to the field of data processing and can solve the problem of inaccurate control caused by the inability of the satellite operation plan to timely reflect the actual working conditions of the engine. The specific technical solution is as follows: obtain first data, where the first data includes data of jet behaviors that have occurred; determine second data according to the first data, and the second data is the first data after purification; judge the start and end times of different types of control behaviors according to the second data; generate third data according to the second data and the data of the start and end times of different types of control behaviors, and the third data is summary data. The present invention is used to directly identify the satellite engine jet control behaviors through satellite parameter data without referring to the satellite operation plan, accurately obtain the start and end moments and the duration of each time the satellite engines in each direction use jets to achieve attitude control behaviors, orbit control behaviors or attitude-orbit control behaviors, and improve the control accuracy of the satellite.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and in particular, to a method and device for generating data for identifying satellite jet control behavior. Background Art

[0002] Currently, in some fields, such as the field of aerospace measurement and control, the satellite attitude and orbit control system is an important part of the satellite to perform various tasks and maintain stable operation, and is also the main support force for the satellite to cope with sudden failures and carry out emergency disposal.

[0003] However, once the satellite is in orbit, the ability of manual intervention will inevitably become very limited. Currently, identifying the engine jet control behavior is mainly completed by referring to the satellite control plan and the satellite working mode. Since the engine does not work all the time when the satellite control system is in the orbit control mode, and the satellite control plan cannot reflect the real working conditions of the engine in time, the above methods are not accurate enough. Summary of the Invention

[0004] Embodiments of the present disclosure provide a method and device for generating data for identifying satellite jet control behavior, which can solve the problem that the control is not accurate enough due to the fact that the satellite control plan cannot reflect the real working conditions of the engine in time. The technical solutions are as follows:

[0005] According to the first aspect of the embodiments of the present disclosure, a method for generating data for identifying satellite jet control behavior is provided. The method includes: obtaining first data, where the first data includes data of jet behaviors that have occurred; determining second data according to the first data, where the second data is the first data after purification; judging the start and end times of different types of control behaviors according to the second data; and generating third data according to the second data and the data of the start and end times of the different types of control behaviors, where the third data is summary data.

[0006] Herein, purification means that after processing the first data, the processed data (i.e., the second data) is more concise than the first data. The control behaviors include any one of orbit control behavior, attitude control behavior, and attitude and orbit control behavior. The attitude and orbit control behavior includes attitude control behavior and orbit control behavior.

[0007] In a possible implementation manner, obtaining the first data may be to read the sub-data of the working mode of a certain satellite in a certain year and the data of the cumulative jet time of the engines in several directions of the satellite in that year (i.e., the first data), and convert the time corresponding to all the sampled data from "year, month, day, hour, minute, second" to the cumulative number of seconds since 0:00:00 on January 1 of that year (hereinafter simply referred to as cumulative seconds).

[0008] In one possible implementation, it is possible to read the purification result (i.e., the second data) of the cumulative amount of engine jet time in each year and each direction during the entire life cycle of the satellite, and (through subroutine calls) extract the data of each characteristic node in each engine jet control behavior in each year and each direction of the satellite (i.e., the data of the start and end times of different types of control behaviors); then, generate the third data based on the second data and the data of the start and end times of different types of control behaviors, and the third data is summary data.

[0009] Among them, the information corresponding to each characteristic node in each engine jet control behavior in each direction mainly includes: the start and end times and the cumulative working duration of the jet control behavior, the start and end times (if there is an attitude control behavior) and the cumulative working duration of the attitude control behavior in the jet control behavior, the start and end times (if there is an orbit control behavior) and the cumulative working duration of the orbit control behavior, and the start and end times (if there is a continuous occurrence of attitude control behavior and orbit control behavior) and the cumulative working duration of the attitude-orbit control behavior.

[0010] Based on the above solution, the beneficial effects are as follows:

[0011] (1) It can not only identify that the satellite is performing a control behavior, provide support for observing the effect of satellite orbit control, improve the control accuracy of the satellite, understand the change of the control law caused by the change of the satellite's center of mass, and help to master the working state of the satellite and find satellite faults. It can quickly obtain the long-term change trend of the peak charge and discharge current of the battery pack;

[0012] (2) It can not only provide a basis for analyzing the change law of various parameter data in the satellite attitude-orbit control process, but also serve as the basis for establishing a detection model for various abnormal phenomena in the satellite attitude-orbit control state;

[0013] (3) It can assist in analyzing the change law of other telemetry parameters of the satellite, then excavate the hidden information in different explicit data, explore the inherent correlation relationship presented by the data due to physical association, and help to better obtain the change trend of engine performance;

[0014] (4) It can timely understand the working state of the satellite attitude-orbit control system, monitor the satellite attitude-orbit control behavior, and is of great significance for improving the in-orbit fault tolerance and self-repair ability of the satellite and enhancing the robustness of the satellite system.

[0015] In one embodiment, the determining the start and end times of different types of control behaviors according to the second data includes: determining the start and end times of different types of control behaviors according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between the data included in the second data.

[0016] In one possible implementation, the second data can be read to construct a data change feature verification window, calculate the amplitude difference, time difference, and absolute value of the connection slope of the data at each sampling point within the verification window, set the initial value and a preset constant threshold value, assign an initial value to the identifier of the time interval of the control behavior, identify the time interval in which the control behavior occurs, identify different control behaviors and their time intervals, and then determine the start and end times of different types of control behaviors. Herein, the identifier of the time interval refers to the time identifier when the jet control behavior occurs and when this jet control behavior ends. The initial value is usually set to 0, that is, when the satellite is operating normally, it is considered that there is no jet control behavior of the engine.

[0017] Based on the above solution, by comparing the coordinate differences and connection slopes of adjacent sampling data, without referring to the satellite's control plan, the start and end times of different types of jet control behaviors of the satellite engine can be directly identified through the satellite parameter data, accurately obtaining the start and end moments and the duration of each attitude control behavior, orbit control behavior, or attitude and orbit control behavior achieved by jetting of the engines in each direction of the satellite, thereby improving the control accuracy of the satellite.

[0018] In one embodiment, the determining the second data according to the first data includes: performing at least one calculation on the first data to obtain a fourth data, where the fourth data is data that has completed the characterization process; determining the second data according to at least one parameter among the amplitude difference, time difference, or slope value of the connection between the data included in the fourth data.

[0019] In one possible implementation, starting from the first point of the list of the cumulative jet time data of each satellite engine read (i.e., the first data), k consecutive sampling points are continuously selected to construct a data compression window, and the amplitudes of every two adjacent data within the taken window are compared. When and only when the amplitudes are the same at m consecutive points, the sampling data of the middle point among the m points is removed, where k is greater than or equal to m.

[0020] After that, the data compression window is slid point by point to compress the redundant information in each data list respectively (for example, the sampling data of the middle point among the m points removed as described above), until the lossless compression of all the data in the data list is completed, and one calculation is completed. Through the satellite technical documents and the test results of the satellite parameter data, the variation rules of the cumulative jet time data of the engines in each direction of the satellite are summarized.

[0021] Further, starting from the first sampling point of the first data, a test window that can slide point by point is constructed using a continuous number of sampling points (e.g., 5), and the amplitude difference, time difference, and connection slope value of each sampling data within the test window are calculated. Moreover, based on the technical documents of the satellite and the variation law of the cumulative jet time data of the satellite engine (i.e., the first data), the isolated outliers and abnormal jump data in the cumulative jet time data of the satellite engine (i.e., the first data) are cleaned, and the second calculation is completed to obtain the purified result data (i.e., the fourth data).

[0022] Among them, the essence of data characterization is to transform the original sampled time series data into time series data with certain characteristics, that is, no more than two consecutive data with the same amplitude. Such data is helpful for subsequent data purification processing and identification of data curve inflection points.

[0023] Furthermore, the test window is slid point by point towards the back end of the fourth data to complete the purification of the fourth data, and redundant data verification is performed by calculating the amplitude difference, time difference, and slope value of the connection between adjacent data included in the fourth data (i.e., consecutive sampling data in the fourth data), and the newly emerged redundant data after purification is compressed again to obtain the second data.

[0024] Based on the above solution, by analyzing the variation law of the cumulative jet time data of the engine, the compression and purification of the cumulative jet time data of the engine in each direction during the entire life cycle of each satellite can be accurately and quickly completed.

[0025] In one embodiment, the second data includes characteristic nodes, and the characteristic nodes are used to indicate the start and end times of switching the control behavior.

[0026] Among them, the characteristic nodes are helpful for distinguishing control behaviors. For example, the characteristic nodes can divide the second data into intervals with slower changes and intervals with faster changes. At this time, the interval with slower changes is identified as the attitude control behavior, the interval with faster changes is identified as the orbit control behavior, and the interval that jointly includes both slower and faster changes is identified as the attitude-orbit control behavior.

[0027] It should be understood that the characteristic nodes do not necessarily exist. If there is no turning point in the change interval, that is, there is only the attitude control behavior or the orbit control behavior, then there are no characteristic nodes.

[0028] Based on the above solution, the turning points (i.e., characteristic nodes) of the data curve change trend can be accurately obtained. Furthermore, without referring to the satellite operation plan, the jet control behavior of the satellite engine can be directly identified through satellite parameter data, and the start and end times and durations of each time the satellite uses jet to achieve attitude control behavior, orbit control behavior, or attitude-orbit control behavior in each direction of the satellite can be accurately obtained, thereby improving the control accuracy of the satellite.

[0029] In one embodiment, the third data is used to indicate the start and end times of the different types of control actions by natural time.

[0030] For example, all the times representing the left and right boundaries of the intervals (i.e., the start and end moments of the control actions) in the third data can be converted from accumulated seconds to natural time, that is, the absolute time corresponding to the annual data. At this time, the third data can indicate the start and end times of the different types of control actions by natural time.

[0031] Based on the above solution, indicating control actions by natural time can improve the user experience.

[0032] According to a second aspect of the embodiments of the present disclosure, there is provided a data generation device for identifying satellite jet control actions, including a memory and a processor. The memory stores a program. When the program is executed by the processor, the processor is configured to: obtain first data, where the first data includes data of jet actions that have occurred; determine second data according to the first data, and the second data is the first data after purification; determine the start and end times of different types of control actions according to the second data; generate third data according to the second data and the data of the start and end times of the different types of control actions, and the third data is summary data.

[0033] Herein, purification means that after processing the first data, the processed data (i.e., the second data) is more concise than the first data. The control actions include any one of orbit control actions, attitude control actions, and attitude-orbit control actions. The attitude-orbit control action includes an attitude control action and an orbit control action.

[0034] In a possible implementation manner, obtaining the first data may be to read the sub-data of the working mode of a certain satellite in a certain year and the accumulated jet time data of the engines in several directions of the satellite in that year (i.e., the first data), and convert the time corresponding to all the sampling data from "year, month, day, hour, minute, second" to the accumulated seconds from 0:00:00 on January 1 of that year (hereinafter simply referred to as accumulated seconds).

[0035] In a possible implementation manner, the purification results of the accumulated jet time of the engines in each year and each direction during the entire life cycle of the satellite (i.e., the second data) can be read, and (through subroutine calls) the data of each characteristic node in each jet control action of the engines in each year and each direction of the satellite can be extracted (i.e., the data of the start and end times of different types of control actions); then, the third data is generated according to the second data and the data of the start and end times of different types of control actions, and the third data is summary data.

[0036] Among them, the information corresponding to each characteristic node in each jet control behavior of the engines in all directions mainly includes: the start and end times and the cumulative working duration of this jet control behavior, the start and end times (if there is an attitude control behavior) and the cumulative working duration of the attitude control behavior in this jet control behavior, the start and end times (if there is an orbit control behavior) and the cumulative working duration of the orbit control behavior, and the start and end times (if there is a continuous occurrence of an attitude control behavior and an orbit control behavior) and the cumulative working duration of the attitude and orbit control behavior.

[0037] Based on the above solution, the beneficial effects are as follows:

[0038] (1) It can not only identify that the satellite is performing control behaviors, provide support for observing the effect of satellite orbit control, improve the control accuracy of the satellite, understand the change of control laws caused by the change of the satellite's center of mass, and help to master the working state of the satellite and find satellite faults. It can quickly obtain the long-term change trend of the charge and discharge current peak value of the battery pack;

[0039] (2) It can not only provide a basis for analyzing the change laws of various parameter data in the satellite attitude and orbit control process, but also serve as the basis for establishing detection models for various abnormal phenomena in the satellite attitude and orbit control state;

[0040] (3) It can assist in analyzing the change laws of other telemetry parameters of the satellite, then excavate the hidden information in different explicit data, explore the inherent correlation relationships presented by the data due to physical associations, and help to better obtain the change trend of engine performance;

[0041] (4) It can timely understand the working state of the satellite attitude and orbit control system, monitor the satellite attitude and orbit control behaviors, and is of great significance for improving the in-orbit fault tolerance and self-repair ability of the satellite and enhancing the robustness of the satellite system.

[0042] In some embodiments, the processor is specifically configured to determine the start and end times of the different types of control behaviors according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between the data included in the second data.

[0043] In a possible implementation manner, it is possible to read the second data, construct a data change feature test window, calculate the amplitude difference, time difference, and absolute value of the connection line slope of the data at each sampling point within the test window, set an initial value and a preset constant threshold value, assign an initial value to the identifier of the time interval of the control behavior, identify the time interval in which the control behavior occurs, identify different control behaviors and their time intervals, and then determine the start and end times of the different types of control behaviors. Among them, the identifier of the time interval refers to the time identifier when the jet control behavior occurs and when this jet control behavior ends. The initial value is usually set to 0, that is, it is considered that when the satellite is working normally, the engine has no jet control behavior.

[0044] Based on the above solution, by comparing the coordinate differences and connection slopes of adjacent sampled data, it is possible to directly identify the start and end times of different types of jet control behaviors of the satellite engine without referring to the satellite's control plan. The start and end times and durations of each attitude control behavior, orbit control behavior, or attitude-orbit control behavior achieved by jetting of the satellite's engines in each direction can be accurately obtained, thereby improving the control accuracy of the satellite.

[0045] In some embodiments, the processor is specifically configured to perform at least one calculation on the first data to obtain fourth data, where the fourth data is data that has undergone feature extraction processing; determine the second data based on at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the fourth data.

[0046] In a possible implementation manner, starting from the first point of the cumulative jet time data list of each satellite engine read (i.e., the first data), k consecutive sampling points are continuously selected to construct a data compression window. The amplitude values of every two adjacent data within the taken window are compared. When and only when the amplitudes are the same at m consecutive points, the sampling data of the middle point among the m points is removed, where k is greater than or equal to m.

[0047] After that, the data compression window is slid point by point to compress the redundant information in each data list (for example, the sampling data of the middle point among the m points removed as described above) until the lossless compression of all data lists is completed, and one calculation is completed. Based on the satellite technical documents and the test results of the satellite parameter data, the variation rules of the cumulative jet time data of the satellite's engines in each direction are summarized.

[0048] Furthermore, starting from the first sampling point of the first data, a slidable inspection window is constructed with a continuous number of sampling points (for example, 5). The amplitude differences, time differences, and connection line slope values of the sampling data within the inspection window are calculated. And, based on the satellite's technical documents and the variation rules of the cumulative jet time data of the satellite engine (i.e., the first data), the isolated outliers and abnormal jump data in the cumulative jet time data of the satellite engine (i.e., the first data) are cleaned, and the second calculation is completed to obtain the cleaned result data (i.e., the fourth data).

[0049] Among them, the essence of data feature extraction processing is to transform the original sampled time series data into time series data with certain features, that is, no more than two consecutive data with the same amplitude. Such data is helpful for subsequent data cleaning processing and data curve inflection point identification.

[0050] Further, slide the inspection window point by point towards the backend of the fourth data to complete the purification of the fourth data, and perform redundant data inspection by calculating the amplitude difference, time difference, and slope value of the connection line between adjacent data contained in the fourth data (i.e., continuous sampling data in the fourth data), and further compress the new redundant data that appears after purification to obtain the second data.

[0051] Based on the above solution, by analyzing the variation law of the cumulative engine jet time data, the compression and purification of the cumulative engine jet time data in each direction during the full life cycle of each satellite can be accurately and quickly completed.

[0052] In some embodiments, the second data includes feature nodes, and the feature nodes are used to indicate the start and end times of switching the control behavior.

[0053] Among them, the feature nodes help to distinguish control behaviors. For example, the feature nodes can divide the second data into intervals with slower changes and intervals with faster changes. At this time, the intervals with slower changes are identified as attitude control behaviors, the intervals with faster changes are identified as orbit control behaviors, and the intervals that jointly include slower and faster changes are identified as attitude-orbit control behaviors.

[0054] It should be understood that the feature nodes do not necessarily exist. If there is no turning point in the change interval, that is, there is only an attitude control behavior or an orbit control behavior, then there are no feature nodes.

[0055] Based on the above solution, the turning points (i.e., feature nodes) of the data curve change trend can be accurately obtained. Furthermore, without referring to the satellite's control plan, the satellite engine jet control behavior can be directly identified through the satellite parameter data, and the start and end times and the duration of each time the satellite's engine uses jet to achieve attitude control behavior, orbit control behavior, or attitude-orbit control behavior in each direction can be accurately obtained, thereby improving the satellite's control accuracy.

[0056] In some embodiments, the third data is used to indicate the start and end times of different types of control behaviors through natural time.

[0057] For example, the time representing the left and right boundaries of the interval (i.e., the start and end times of the control behavior) in the third data can be converted from integrated seconds to natural time, that is, the absolute time corresponding to the annual data. At this time, the third data can indicate the start and end times of different types of control behaviors through natural time.

[0058] Based on the above solution, indicating control behaviors through natural time can improve the user experience.

[0059] According to a third aspect of the embodiments of the present disclosure, there is provided a device for generating data for identifying satellite jet control behavior. The data generation processing device includes a processor and a memory. At least one computer instruction is stored in the memory, and the instruction is loaded and executed by the processor to implement the steps performed in the data generation method described in the first aspect and any embodiment of the first aspect.

[0060] According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer program storage medium, characterized in that the computer program storage medium has program instructions, and when the program instructions are executed by a processor, the processor is caused to execute the method described in the first aspect.

[0061] According to a fifth aspect of the embodiments of the present disclosure, there is provided a chip system, characterized in that the chip system includes at least one processor, and when program instructions are executed in the at least one processor, the at least one processor is caused to execute the method described in the first aspect.

[0062] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0064] Figure 1 is a flowchart of a data generation method 100 for identifying satellite jet control behavior provided by an embodiment of the present disclosure;

[0065] Figure 2 is a purification effect diagram of the cumulative jet time data of the satellite - A direction engine provided by an embodiment of the present disclosure;

[0066] Figure 3 is a purification effect diagram of the cumulative jet time data of the satellite + A direction engine provided by an embodiment of the present disclosure;

[0067] Figure 4 is a comparison diagram of the purification results of the cumulative jet time data of the satellite engines in each direction provided by an embodiment of the present disclosure;

[0068] Figure 5 is a variation law diagram of the cumulative jet time of a certain jet control behavior of the satellite - A direction engine provided by an embodiment of the present disclosure;

[0069] Figure 6 is a variation law diagram of the cumulative jet time of a certain jet control behavior of the satellite - B direction engine;

[0070] Figure 7It is a graph showing the variation law of the cumulative jet time of a certain jet control behavior of the satellite +C direction engine provided by an embodiment of the present disclosure;

[0071] Figure 8 It is a graph showing the variation of the cumulative jet time data of a certain jet attitude and orbit control behavior of the satellite -A direction engine provided by an embodiment of the present disclosure;

[0072] Figure 9 It is a graph showing the variation of the cumulative jet time data of a certain jet attitude and orbit control behavior of the satellite -B direction engine provided by an embodiment of the present disclosure;

[0073] Figure 10 It is a graph showing the variation of the cumulative jet time data of a certain jet attitude and orbit control behavior of the satellite +C direction engine provided by an embodiment of the present disclosure;

[0074] Figure 11 It is a graph showing the variation of the cumulative jet time data of a certain jet orbit control behavior of the satellite +B direction engine provided by an embodiment of the present disclosure;

[0075] Figure 12 It is a graph showing the variation of the cumulative jet time data of a certain jet attitude control behavior of the satellite -C direction engine provided by an embodiment of the present disclosure;

[0076] Figure 13 It is a flowchart of a method 200 for determining the start and end times of different types of control behaviors provided by an embodiment of the present disclosure;

[0077] Figure 14 It is a structural diagram of a data generation device 300 for identifying satellite jet control behaviors provided by an embodiment of the present disclosure;

[0078] Figure 15 It is a structural diagram of a data generation device 400 for identifying satellite jet control behaviors provided by an embodiment of the present disclosure. Detailed implementation manners

[0079] Here, exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0080] In some fields, such as the field of aerospace measurement and control, the satellite attitude and orbit control system is an important part for the satellite to perform various tasks and maintain stable operation, and is also the main support force for the satellite to cope with sudden failures and carry out emergency disposal.

[0081] However, once a satellite is in orbit, the ability of manual intervention will inevitably become very limited. In the face of complex space environment impacts and various possible space confrontations, the satellite may malfunction at any time. If these malfunctions occur in the attitude and orbit control system, the satellite may experience serious failures such as attitude loss of control and orbit deviation. Therefore, it is of great significance to timely understand the working state of the satellite attitude and orbit control system and monitor the satellite attitude and orbit control behavior to improve the in-orbit fault tolerance and self-repair ability of the satellite and enhance the robustness of the satellite system.

[0082] Under normal circumstances, the components related to the working state of the satellite attitude and orbit control system include gyroscopes, magnetometers, sun sensors, star sensors, momentum wheels, magnetic torque devices, thrusters, controllers, etc. Among these components, the thruster is undoubtedly the most core component that actively affects the working state of the satellite attitude and orbit control system. For a satellite using a bipropellant engine as a thruster, the engine jet control behavior is the most direct parameter for changing the working state of the engine. Accurately identifying the characteristic nodes of each direction of the engine and each jet control behavior is not only the basis for analyzing the variation laws of various parameter data in the satellite attitude control and orbit control processes, but also the foundation for establishing detection models for various abnormal phenomena in the satellite attitude control and orbit control states.

[0083] Currently, the identification of engine jet control behavior mainly refers to the satellite operation plan and the satellite working mode. When the satellite control system working mode is the orbit control mode, the engine does not work all the time, and the satellite operation plan cannot reflect the real working conditions of the engine in a timely manner. Therefore, the above methods are not accurate enough.

[0084] In view of this, the present disclosure provides a data generation method, which can alleviate the above problems.

[0085] The embodiment of the present disclosure provides a data generation method 100 for identifying satellite jet control behavior, as Figure 1 shown. The data generation method 100 for identifying satellite jet control behavior includes the following steps:

[0086] 101. Obtain first data.

[0087] Among them, the first data contains data on the jet behavior that has occurred, that is, the original data.

[0088] Exemplarily, read the working mode sub-data of a certain satellite in a certain year and the data of the cumulative jet time of the engines in several directions (for example, 6 directions) of the satellite in that year (that is, the first data), and convert the time corresponding to all sampling data from "year, month, day, hour, minute, second" to the accumulated seconds from 0:00:00 on January 1 of that year (hereinafter simply referred to as accumulated seconds).

[0089] 102. Determine second data according to the first data.

[0090] Among them, the second data is the first data after purification. Purification means that after processing the first data, the processed data (i.e., the second data) is more concise than the first data.

[0091] In a possible implementation, the first data can be calculated at least once to obtain the fourth data; then, the second data is determined according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the fourth data. Among them, the fourth data is the data after the feature extraction process. The essence of the data feature extraction process is to transform the original sampled time series data into time series data with certain features, that is, no more than two consecutive data with the same amplitude. Such data is helpful for subsequent data purification processing and the identification of data curve inflection points.

[0092] Exemplarily, starting from the first point of the list of the cumulative jet time data of each engine of the satellite read (i.e., the first data), k sampling points are continuously selected to construct a data compression window. The amplitudes of every two adjacent data within the taken window are compared. When and only when the amplitudes of m consecutive points are the same, the sampling data of the middle point of the m points is removed, where k is greater than or equal to m.

[0093] For example, 5 sampling points are continuously selected to construct a data compression window. The amplitudes of every two adjacent data within the taken window are compared. When and only when the amplitudes of 3 consecutive points are the same, the sampling data of the middle point of the 3 points is removed.

[0094] After that, the data compression window is slid point by point to compress the redundant information in each data list (for example, the sampling data of the middle point of the m points removed above) until the lossless compression of all data lists is completed, and one calculation is completed. Through the test results of the satellite technical documents and the satellite parameter data, the variation law of the cumulative jet time data of each engine of the satellite in each direction is summarized.

[0095] Figure 2 This is the purification effect diagram of the cumulative jet time data of the satellite in the -A direction provided by the embodiment of the present disclosure. Figure 3 This is the purification effect diagram of the cumulative jet time data of the satellite in the +A direction provided by the embodiment of the present disclosure. For example, Figure 2 And Figure 3 The dotted line part in is the sampling data after the lossless compression of all data lists is completed.

[0096] Among them, the variation law of the cumulative amount of satellite engine jet time data is mainly manifested in two points: one is that it can remain constant within a very long time period (for example, greater than or equal to 10,000 s); the other is that it can show multi-step or multi-fold jump within a certain time period (for example, greater than or equal to 7 s and less than or equal to 4,000 s), that is, it shows a discrete time series with limited continuous amplitude change (the change of the cumulative amount of time is less than or equal to 5 s) or limited continuous time interval (the time difference between adjacent sampling data is less than or equal to 500 s), and the amplitude jump is not strictly monotonically increasing.

[0097] Figure 4 This is a comparison chart of the purification results of the cumulative amount of satellite engine jet time data in each direction provided by the embodiments of the present disclosure. Figure 5 This is a graph showing the variation law of the cumulative amount of jet time of a certain satellite - A direction engine during a certain jet control behavior provided by the embodiments of the present disclosure. Figure 6 This is a graph showing the variation law of the cumulative amount of jet time of a certain satellite - B direction engine during a certain jet control behavior. Figure 7 This is a graph showing the variation law of the cumulative amount of jet time of a satellite + C direction engine during a certain jet control behavior provided by the embodiments of the present disclosure. Figure 8 This is a graph showing the change of the cumulative amount of jet time data of a satellite - A direction engine during a certain jet attitude and orbit control behavior provided by the embodiments of the present disclosure. Figure 9 This is a graph showing the change of the cumulative amount of jet time data of a satellite - B direction engine during a certain jet attitude and orbit control behavior provided by the embodiments of the present disclosure. Figure 10 This is a graph showing the change of the cumulative amount of jet time data of a satellite + C direction engine during a certain jet attitude and orbit control behavior provided by the embodiments of the present disclosure. Figure 11 This is a graph showing the change of the cumulative amount of jet time data of a satellite + B direction engine during a certain jet orbit control behavior provided by the embodiments of the present disclosure. Figure 12 This is a graph showing the change of the cumulative amount of jet time data of a satellite - C direction engine during a certain jet attitude control behavior provided by the embodiments of the present disclosure. For example, the variation law of the cumulative amount of satellite engine jet time data can be as shown in Figures 2 to 12 any one of the figures.

[0098] Further, starting from the first sampling point of the first data, a test window that can slide point by point is constructed with a continuous number of sampling points (for example, 5), and the amplitude difference, time difference, and connection slope value of each sampling data within the test window are calculated. And, according to the technical documents of the satellite and the variation law of the cumulative amount of satellite engine jet time data (i.e., the first data), the isolated outliers and abnormal jump data in the cumulative amount of satellite engine jet time data (i.e., the first data) are cleaned, and the second calculation is completed to obtain the purified result data (i.e., the fourth data). For example, the purified result data (i.e., the fourth data) can be as shown in Figure 2 、 Figure 3as shown by the solid line part in

[0099] Further, slide the inspection window point by point towards the back end of the fourth data to complete the purification of the fourth data, and perform redundant data inspection by calculating the amplitude difference, time difference, and connection line slope value between the data included in the fourth data (i.e., the continuous sampling data in the fourth data), and compress the new redundant data that appears after purification again to obtain the second data.

[0100] Optionally, output the obtained second data of the satellite (for example, the purification result of the cumulative amount of engine jet time in each direction of the satellite in one year) as independent text files with file names containing information such as "satellite + engine direction + year + purification identifier".

[0101] Based on the above solution, by analyzing the variation law of the cumulative amount of engine jet time data, the compression and purification of the cumulative amount of engine jet time data in each direction of each satellite during its entire life cycle can be accurately and quickly completed.

[0102] 103. Determine the start and end times of different types of control behaviors according to the second data.

[0103] Among them, the control behavior includes any one of attitude control behavior, orbit control behavior, and attitude-orbit control behavior, and the attitude-orbit control behavior includes attitude control behavior and orbit control behavior.

[0104] In one implementation, the start and end times of different types of control behaviors can be determined according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the second data. As an example, Figure 13 is a flowchart of a method 200 for determining the start and end times of different types of control behaviors provided by an embodiment of the present disclosure. As Figure 13 shown, the specific steps can be as follows:

[0105] 201. Read the second data.

[0106] Exemplarily, assume that the i-th point sampling data in the second data is (t i , x(t i )), then there is a time series parameter {x(t i )|t i = t i-1 + h i , i = 1, 2, 3..., n}, where t0 = 0, h i is the time interval between the i-th point sampling data and the previous point sampling data in the second data, t1 = h1 is the time parameter corresponding to the first sampling point of the time series, and x(t i ) is briefly recorded as x i ;

[0107] 202. Construct a data change feature test window.

[0108] Exemplarily, starting from the first point of the data included in the second data, continuously select 5 sampling points to construct a data change feature test window, such as {(t i-4 , x i-4 ), (t i-3 , x i-3 ), (t i-2 , x i-2 ), (t i-1 , x i-1 ), (t i , x i ) | i = 5, 6, 7…, n};

[0109] 203. Calculate the amplitude difference, time difference, and absolute value of the connection slope of the data at each sampling point within the test window.

[0110] Specifically, the calculation method is as follows:

[0111] td1 = |t i - t i-1 |, td2 = |t i - t i-2 |, td3 = |t i - t i-3 |, td4 = |t i - t i-4 |; t 12 = |t i-1 - t i-2 |, t 13 = |t i-1 - t i-3 |, t 14 = |t i-1 - t i-4 |, t 23 = |t i-2 - t i-3 |, t 24 = |t i-2 - t i-4 |, t 34 = |t i-3 - t i-4 |; xd1 = |x i - x i-1 |, xd2 = |x i - x i-2 |, xd3 = |x i - x i-3 |, xd4 = |x i - x i-4 |; x 12 = |x i-1 - x i-2|, x 13 = |x i-1 -x i-3 |, x 14 = |x i-1 -x i-4 |, x 23 = |x i-2 -x i-3 |, x 24 = |x i-2 -x i-4 |, x 34 = |x i-3 -x i-4 |; sd1 = |(x i -x i-1 ) / (t i -t i-1 )|, sd2 = |(x i -x i-2 ) / (t i -t i-2 )|, sd3 = |(x i -x i-3 ) / (t i -t i-3 )|, sd4 = |(x i -x i-4 ) / (t i -t i-4 )|; s 12 = |(x i-1 -x i-2 ) / (t i-1 -t i-2 )|, s 13 = |(x i-1 -x i-3 ) / (t i-1 -t i-3 )|, s 14 = |(x i-1 -x i-4 ) / (t i-1 -t i-4 )|, s 23 = |(x i-2 -x i-3 ) / (t i-2 -t i-3 )|, s 24 = |(x i-2 -x i-4 ) / (t i-2 -t i-4 )|, s 34 = |(x i-3 -x i-4 ) / (t i-3 -t i-4)|。

[0112] Among them, td1, td2, td3, and td4 are all time difference parameters; t 12 , t 13 , t 14 , t 23 , t 24 , t 34 are all time difference parameters between two sampling point data; xd1, xd2, xd3, and xd4 are all amplitude difference parameters; x 12 , x 13 , x 14 , x 23 , x 24 , x 34 are all amplitude difference parameters between two sampling point data; sd1, sd2, sd3, sd4, s 12 , s 13 , s 14 , s 23 , s 24 , s 34 all represent the slope parameters of the line connecting two sampling point data.

[0113] 204. Set the initial value and a preset constant threshold value.

[0114] Exemplarily, according to the design index or test data of the engine jet control behavior, a set of threshold values that can reflect the monotonic increase or step jump law of the engine jet time is preset in advance, that is, the coordinate differences and the reference values of the connection slopes between any 5 consecutive sampling point data in the purification result of the jet time cumulative amount data during normal jetting of the engine are given, which are also the initial values and the preset constant threshold values of each parameter in the above step 3.

[0115] 205. Assign an initial value to the identifier of the time interval of the control behavior.

[0116] Exemplarily, set the identifier of the time interval of the satellite engine (jet) control behavior as EBZ. Use EBZ = 1 to represent the start of a control behavior and EBZ = 0 to represent the end of a control behavior. Assign an initial value of 0. For example, the initial value assignment situation of EBZ can be as shown in the annotation of any one of the figures in Figure 5 , Figures 7 to 12 ; Set the identifier of the time interval of the satellite engine (jet) attitude control behavior as ABZ. Use ABZ = 1 to represent the start of an attitude control behavior and ABZ = 0 to represent the end of an attitude control behavior. Assign an initial value of 0. For example, the initial value assignment situation of ABZ can be as shown in Figure 5 , Figures 6 to 10 , Figure 12as shown in the annotation of any one of the figures; set the identifier of the satellite engine (jet) orbital control behavior time interval as OBZ, use OBZ = 1 to represent the start of an orbital control behavior, use OBZ = 0 to represent the end of an orbital control behavior, and assign an initial value of 0. For example, the initial value assignment situation of OBZ can be as Figures 5 to 11 as shown in the annotation of any one of the figures; set the identifier of the satellite engine (jet) attitude and orbital control behavior time interval as FBZ, use FBZ = 1 to represent the start of an attitude and orbital control behavior, use FBZ = 0 to represent the end of an attitude and orbital control behavior, and assign an initial value of 0. For example, the initial value assignment situation of FBZ can be as Figures 5 to 10 as shown in the annotation of any one of the figures. Among them, the identifier of the time interval refers to the time identifier when the jet control behavior occurs and the end of this jet control behavior. The initial value is usually set to 0, that is, it is considered that when the satellite is working normally, the engine has no jet control behavior.

[0117] It should be understood that the start and end time intervals of the jet control behavior EBZ are determined by the abnormal working state interval of the satellite; the start and end times of the jet attitude and orbital control behavior FBZ are determined by the change interval of the jet time accumulation; the start and end times of the jet attitude control behavior ABZ and the jet orbital control behavior OBZ are determined by the change rate of the "jet time accumulation".

[0118] 206. Identify the time interval when the control behavior occurs.

[0119] Exemplarily, compare the calculation results of each parameter in the third step with the initial values corresponding to each parameter in the third step preset and the preset constant threshold value, and determine the start and end moments of each (jet) control behavior of the engines in each direction according to the comparison results, that is, the jth (jet) control behavior interval of the engine {[c j , d j |j = 1, 2, 3,..., m}, and use EBZ = 1 or EBZ = 0 to mark the start and end of the (jet) control behavior respectively, and use the value of the counter JE to record the jet number j. Use m to represent the total number of (jet) control behaviors implemented by the engines in each direction within one year, and different engines take different m values;

[0120] For example, compare the various calculation result values of the sampled data in the comparison and inspection window with the preset reference value, identify the time interval when the engine jet control behavior occurs, and change the values of EBZ, ABZ, OBZ, FBZ according to whether the interval ends;

[0121] 207. Identify different control behaviors and their time intervals.

[0122] Exemplarily, in the interval {[c j , d jWithin {j = 1, 2, 3, ..., m}, select 5 sampling points continuously again to reconstruct the data change feature test window {(t i-4 , x i-4 ), (t i-3 , x i-3 ), (t i-2 , x i-2 ), (t i-1 , x i-1 ), (t i , x i )|i = 5, 6, 7…, n}. Again, compare the calculation results of each parameter in step 3 with the initial values of each parameter corresponding to step 3 preset and the preset constant threshold value. According to the comparison results, identify the characteristic nodes representing the obvious turning points in the changing trend during the monotonic increase of the engine (jet) time cumulative amount (in other words, the characteristic nodes can be used to indicate the start and end times of the switching control behavior), and divide the second data (i.e., the cleaning result of the jet time cumulative amount data) into a slower-changing interval and a faster-changing interval through these characteristic nodes. At this time, the slower-changing interval is identified as the attitude control behavior, the faster-changing interval is identified as the orbit control behavior, and the interval jointly containing the slower-changing and faster-changing intervals is identified as the attitude-orbit control behavior.

[0123] For example, identify the time intervals of different jet control behaviors of the engine according to the time corresponding to the characteristic nodes, and change the corresponding values of ABZ, OBZ, and FBZ. For example, the time intervals of different jet control behaviors of the engine can be as shown in the annotation of any one of the figures in Figures 5 to 7 .

[0124] Based on the above scheme, the following points are explained:

[0125] (1) According to the design index or test data of the selected engine jet control behavior, quantitatively preset in advance a set of thresholds that can reflect the monotonic increase or step jump law of the engine jet time. In other words, give the reference values of the coordinate differences and connection slopes between any 5 consecutive sampling points in the cleaning result of the jet time cumulative amount data when the engine is jetting normally. Since the purposes and working states of jet control behaviors implemented by engines in different directions are different, different sets of thresholds need to be set for different satellites and engines in different directions.

[0126] (2) The slower-changing interval and the faster-changing interval of the cleaning result of the engine jet time cumulative amount data are divided by the characteristic nodes. The two intervals may be adjacent or may appear independently. In other words, the interval where the cleaning result of the engine jet time cumulative amount data remains unchanged for a long time can be adjacent to either the slower-changing interval of the cumulative amount data or the faster-changing interval of the cumulative amount data, which is related to the jet direction of the engine.

[0127] (3) The change of the purification result of the cumulative engine jet time data is relatively slow or fast, which is defined for the same engine and cannot be used for comparison between multiple engines. For example, in the same time-domain coordinate system, the similar change of the purification result of the cumulative jet time data may be relatively fast for an engine in one direction and relatively slow for an engine in another direction.

[0128] (4) The characteristic nodes do not necessarily exist. If there is no turning point in the change interval, that is, there is only attitude control behavior or orbit control behavior, then there are no characteristic nodes.

[0129] Further, for each interval with a relatively slow change {[ac p , ad p |p = 1, 2, 3…, v}, ABZ = 1 or ABZ = 0 is used to represent the start or end of a jet attitude control behavior respectively, and the value of the counter JA is used to record the number of jet times p of the attitude control behavior; for each interval with a relatively fast change {[oc q , od q |q = 1, 2, 3..., w}, OBZ = 1 or OBZ = 0 is used to represent the start or end of an orbit control behavior respectively, and the value of the counter JO is used to record the number of jet times q of the orbit control behavior; for each interval that is continuous between the interval with a relatively slow change and the interval with a relatively fast change {[fc k , fd k |k = 1, 2, 3..., l}, FBZ = 1 or FBZ = 0 is used to represent the start or end of a jet attitude-orbit control behavior respectively, and the value of the counter JF is used to record the number of jet times of the attitude-orbit control behavior. For example, the situation of the number of jet times of different control behaviors can be as shown in the annotation of any one of the figures in Figures 5 to 10 .

[0130] Furthermore, after completing the above steps, the characteristic information of the jet control behavior of each engine of the satellite in each direction and each year can be respectively output as an independent text file named "satellite + engine direction + year".

[0131] Based on the above solution, the embodiments provided by the present disclosure can achieve the following beneficial effects:

[0132] 1. By comparing the coordinate differences and connection slopes of adjacent sampling data, the embodiments of the present disclosure can accurately obtain the turning points (i.e., characteristic nodes) of the change trend of the data curve, and then directly identify different types of jet control behaviors of the satellite engine and their start and end times through the satellite parameter data without referring to the satellite operation plan, accurately obtain the start and end moments and durations of each time the satellite's engines in each direction achieve attitude control behavior, orbit control behavior or attitude-orbit control behavior by jet, thereby improving the control accuracy of the satellite;

[0133] 2. The disclosed embodiment can not only identify the satellite's ongoing control behavior, provide support for observing the effect of satellite orbit control, recognize the change in control law caused by the change in the satellite's center of mass, and provide help for mastering the satellite's working status and finding satellite faults. It can quickly obtain the long-term change trend of the peak value of the battery pack's charge and discharge current;

[0134] 3. The disclosed embodiments can not only provide a basis for analyzing the changing rules of various parameter data in the process of satellite attitude and orbit control, but also serve as a basis for establishing a detection model for various abnormal phenomena in the satellite attitude and orbit control state;

[0135] 4. The disclosed embodiments can assist in analyzing the changing patterns of other satellite telemetry parameters, and then dig out the implicit information in different explicit data, explore the inherent correlation between data due to physical association, and provide help for better obtaining the trend of engine performance changes;

[0136] 5. The embodiments of the present disclosure can timely understand the working status of the satellite attitude and orbit control system and monitor the satellite attitude and orbit control behavior, which is of great significance to improving the satellite's on-orbit fault tolerance and self-repair capabilities and enhancing the robustness of the satellite system.

[0137] 104. Generate third data according to the second data and data on start and end times of different types of control behaviors.

[0138] Among them, the third data is summary data.

[0139] For example, the cleansing result (i.e., the second data) of the cumulative engine jet time in each year and in each direction during the entire life cycle of the satellite can be read, and the data of each characteristic node in each jet control behavior of the satellite engine in each year and in each direction (i.e., the start and end time of different types of control behaviors) can be extracted (through a subroutine call); then, the third data is generated based on the second data and the data of the start and end times of different types of control behaviors.

[0140] Among them, the information corresponding to each characteristic node in each jet control behavior of the engine in each direction mainly includes: the start and end time and the cumulative working time of the jet control behavior, the start and end time of the attitude control behavior in the jet control behavior (if there is an attitude control behavior) and the cumulative working time, the start and end time of the orbit control behavior (if there is an orbit control behavior) and the cumulative working time, the start and end time of the attitude and orbit control behavior (if the attitude control behavior and the orbit control behavior occur continuously) and the cumulative working time.

[0141] Further, all the times in the third data representing the left and right boundaries of the intervals (i.e., the start and end times of the control actions) can be converted from accumulated seconds to natural time, that is, the absolute time corresponding to the data of each year. At this time, the third data can indicate the start and end times of different types of control actions through natural time.

[0142] Among them, the cumulative working durations of different jet control actions of the engine respectively reflect the time increments within the start and end times of these actions, and are uniformly expressed in seconds; for the start and end times of different jet control actions of the engine, it is necessary to combine the year information in each file name to restore the accumulated seconds to the absolute time of "a certain year, a certain month, a certain day, a certain hour, a certain minute, and a certain second".

[0143] Furthermore, text files recording the characteristics of the engines in various directions of the satellite and various jet control actions can be respectively output, that is, text files containing the third data.

[0144] Based on the above Figures 1 to 13 data generation method for identifying the jet control behavior of a satellite described in the corresponding embodiment, the following is an embodiment of the apparatus of the present disclosure, which can be used to execute the method embodiment of the present disclosure.

[0145] The embodiment of the present disclosure provides a data generation device for identifying the jet control behavior of a satellite. As Figure 14 shown, the data generation device 300 for identifying the jet control behavior of a satellite includes: a storage module 301 and a processing module 302.

[0146] The storage module 301 is used to store programs.

[0147] When the program is executed in the processing module 302, the processing module 302 is used to execute the data generation method for identifying the jet control behavior of a satellite described above.

[0148] The processing module 302 is used for:

[0149] Obtain first data, where the first data includes data of jet actions that have occurred;

[0150] Determine second data according to the first data, where the second data is the first data after purification;

[0151] Judge the start and end times of different types of control actions according to the second data;

[0152] Generate third data according to the second data and the data of the start and end times of different types of control actions, where the third data is summary data.

[0153] Optionally, the processing module 302 is specifically configured to determine the start and end times of the different types of control behaviors according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the second data.

[0154] Optionally, the processing module 302 is specifically configured to,

[0155] perform at least one calculation on the first data to obtain fourth data, where the fourth data is data that has completed the characterization process;

[0156] determine the second data according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the fourth data.

[0157] Optionally, the second data includes feature nodes, and the feature nodes are used to indicate the start and end times of switching the control behavior.

[0158] Optionally, the third data is used to indicate the start and end times of the different types of control behaviors through natural time.

[0159] Based on the above Figures 1 to 13 data generation method for identifying satellite jet control behaviors described in the corresponding embodiments, the embodiments of the present disclosure further provide a data generation device for identifying satellite jet control behaviors, as Figure 4 shown.

[0160] The data generation device 400 for identifying satellite jet control behaviors includes a memory 401 and a processor 402. The data generation device 400 may be a server.

[0161] The memory 401 is used to store program instructions.

[0162] When the program is executed in the processor 402, the processor 402 is used to execute the data generation method for identifying satellite jet control behaviors described above.

[0163] The processor 402 is used for:

[0164] obtain first data, where the first data includes data of the occurred jetting behaviors;

[0165] determine second data according to the first data, where the second data is the first data after cleaning;

[0166] judge the start and end times of different types of control behaviors according to the second data;

[0167] generate third data according to the second data and the start and end time data of the different types of control behaviors, where the third data is summary data.

[0168] Optionally, the processor 402 is specifically configured to determine the start and end times of different types of control behaviors according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the second data.

[0169] Optionally, the processor 402 is specifically configured to perform at least one calculation on the first data to obtain fourth data, where the fourth data is data that has completed the characterization process;

[0170] Determine the second data according to at least one parameter among the amplitude difference, time difference, or slope value of the connection line between the data included in the fourth data.

[0171] Optionally, the second data includes feature nodes, and the feature nodes are used to indicate the start and end times of switching the control behavior.

[0172] Optionally, the third data is used to indicate the start and end times of different types of control behaviors through natural time.

[0173] Based on the above Figures 1 to 13 For the data generation method for identifying satellite jet control behaviors described in the corresponding embodiments above, the embodiments of the present disclosure further provide a computer-readable storage medium. For example, a non-temporary computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc. Computer instructions are stored on this storage medium for executing the above Figures 1 to 13 The data generation method for identifying satellite jet control behaviors applied to a terminal device or a server described in the corresponding embodiments above will not be elaborated here.

[0174] Based on the above Figures 1 to 13 For the data generation method for identifying satellite jet control behaviors described in the corresponding embodiments above, the embodiments of the present disclosure further provide a chip system. The chip system includes at least one processor. When program instructions are executed in at least one processor, at least one processor is caused to execute the above Figures 1 to 13 The data generation method for identifying satellite jet control behaviors applied to a terminal device or a server described in the corresponding embodiments above will not be elaborated here.

[0175] Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed herein. The specification and examples are only to be considered as exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0176] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A method for generating data for identifying satellite jet control behavior, characterized in that, The method includes: Obtaining first data, where the first data includes data of jetting behaviors that have occurred; Determining second data according to the first data, where the second data is the first data after purification; Judging the start and end times of different types of control behaviors according to the second data; Generating third data according to the second data and the data of the start and end times of different types of control behaviors, where the third data is summary data, and the third data is used to indicate the start and end times of different types of control behaviors through natural time; The judging the start and end times of different types of control behaviors according to the second data includes: judging the start and end times of different types of control behaviors according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between the data included in the second data; The judging the start and end times of different types of control behaviors includes: reading the second data; constructing a data change feature inspection window; calculating the absolute values of the amplitude difference, time difference, and connection line slope of each sampling point data within the inspection window; setting an initial value and a preset constant threshold value; assigning an initial value to the identifier of the time interval of the control behavior; identifying the occurrence time interval of the control behavior; identifying different control behaviors and their time intervals.

2. The method according to claim 1, characterized in that, The determining the second data according to the first data includes: Performing at least one calculation on the first data to obtain fourth data, where the fourth data is data after feature extraction; Determining the second data according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between the data included in the fourth data.

3. The method according to claim 1, wherein The second data includes feature nodes, and the feature nodes are used to indicate the start and end times of switching the control behavior.

4. A data generation device for identifying satellite jet control behavior, characterized in that, Including a memory and a processor; The memory stores a program; When the program is executed in the processor, the processor is used to: Obtain first data, where the first data includes data of jetting behaviors that have occurred; Determine second data according to the first data, where the second data is the first data after purification; Judge the start and end times of different types of control behaviors according to the second data; Generate third data according to the second data and the data of the start and end times of different types of control behaviors, where the third data is summary data, and the third data is used to indicate the start and end times of different types of control behaviors through natural time; Specifically, the processor is used to judge the start and end times of different types of control behaviors according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between the data included in the second data; specifically, read the second data; construct a data change feature inspection window; Calculate the absolute values of the amplitude difference, time difference, and connection line slope of each sampling point data within the inspection window; set an initial value and a preset constant threshold value; assign an initial value to the identifier of the time interval of the control behavior; identify the occurrence time interval of the control behavior; identify different control behaviors and their time intervals.

5. The device according to claim 4, characterized in that, Specifically, the processor is used to Perform at least one calculation on the first data to obtain fourth data; Determine the second data according to at least one parameter among the amplitude difference, time difference or slope value of the connection line between adjacent data included in the fourth data.

6. The device according to claim 4, characterized in that The second data includes feature nodes, and the feature nodes are used to indicate the start and end times of switching the control behavior.

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