On-orbit data analysis method and on-orbit data analysis system

Abstract

The invention provides an on-orbit data analysis method and an on-orbit data analysis system, and belongs to the technical field of aerospace, and the method comprises the steps: obtaining an extreme environment model of an on-orbit aircraft in a targeted manner according to the difference between an orbit of the on-orbit aircraft and a ground environment and first segmentation data, and carrying out the analysis to obtain a single machine normal working reference value model; cutting the current serial telemetry data in real time based on the model of the on-orbit aircraft and the on-orbit task to obtain second segmentation data; the extreme environment model is adopted to interpret the second segmentation data sent back to the ground by the on-orbit aircraft, and the corresponding current on-orbit working condition is output; and interpreting the second segmented data by adopting a single-machine normal working reference value model, and outputting a key single-machine creep value corresponding to the current serial telemetry data. Through the processing scheme disclosed by the invention, data classification extraction requirements in a multi-source data scene provided by different task types and different satellite loads can be quickly adapted.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and in particular to an on-orbit data analysis method and an on-orbit data analysis device. Background Art

[0002] For a long time, satellite and its supporting equipment development units have not made effective and full use of various data assets. Since the satellite equipment was established, most of its "life cycle" occurs in the on-orbit operation stage. However, the characteristics of on-orbit data are that it occurs under comprehensive working conditions, and various physical fields are naturally coupled, which is different from the exclusive typical working condition data on the ground.

[0003] During the on-orbit operation of the satellite, the onboard environment is complex and changeable, and there are many slight differences in data under the same working conditions caused by the environment. In order to process such data in a way that is in line with reality and convenient for relevant personnel to read, it is necessary to establish a stable and accurate data extraction and classification system.

[0004] The gaps in existing on-orbit data extraction systems are mainly reflected in the following aspects:

[0005] 1) The existing data acquisition system is unable to achieve rapid classification of on-orbit satellite data. Data extraction based on working conditions is often done manually, which is time-consuming and difficult to ensure the accuracy and stability of data extraction, resulting in low work efficiency.

[0006] 2) The human-computer interaction interface of the existing data acquisition system is single and fixed, and is seriously coupled with the model. It is not universal. The system requires a lot of development work for different satellite models, which is not conducive to the rapid construction of data extraction systems and multi-dimensional data analysis. The platform acquisition process has a low degree of abstraction, and the extracted data has weak support for multi-source data comparison and low value.

[0007] 3) The existing data acquisition system is unable to judge the current environment of the satellite based on its orbit and mark the data when the satellite faces the complex environment of outer space, making it difficult for ground support personnel to effectively analyze the satellite status.

[0008] 4) The existing data acquisition system lacks the analysis and collection of key single-machine creep data, and in the objective situation where there is a gap between the on-orbit operation data of the single machine on the satellite and the ground test data, it is unable to support the collection and comparison of the data of the two, and thus it is impossible to infer accurate and reliable creep data.

[0009] Therefore, there is currently a lack of platforms for the precise collection, extraction and processing of in-orbit satellite operation data. Summary of the invention

[0010] Therefore, in order to overcome the shortcomings of the above-mentioned prior art, the present invention provides an on-orbit data analysis method and an on-orbit data analysis system that can quickly adapt to data classification and extraction requirements in multi-source data scenarios provided by different mission types and different satellite payloads.

[0011] In order to achieve the above-mentioned purpose, the present invention provides an on-orbit data analysis method, comprising: receiving sent historical serial telemetry data and historical on-orbit conditions corresponding to an on-orbit aircraft; segmenting the historical serial telemetry data based on the historical on-orbit conditions to obtain first segmented data; modeling different types of on-orbit aircraft in a targeted manner according to the difference between the on-orbit aircraft orbit and the ground environment and the first segmented data to obtain an extreme environment model of the on-orbit aircraft; and analyzing historical satellite single-machine ground test data with the historical serial telemetry data and the historical on-orbit conditions to obtain a single-machine normal operating reference value model; receiving current serial telemetry data transmitted back to the ground by the on-orbit aircraft; segmenting the current serial telemetry data in real time based on the model and on-orbit mission of the on-orbit aircraft to obtain second segmented data; using the extreme environment model to interpret the second segmented data transmitted back to the ground by the on-orbit aircraft, and outputting and storing the current on-orbit conditions corresponding to the second segmented data; using the single-machine normal operating reference value model to interpret the second segmented data, and outputting the key single-machine creep amount corresponding to the current serial telemetry data.

[0012] In one embodiment, the current serial telemetry data is cut in real time based on the model and on-orbit mission of the on-orbit aircraft to obtain second segmented data, including: obtaining the corresponding attitude control working mode or payload working mode based on the model and on-orbit mission of the on-orbit aircraft; according to the attitude control working mode or the payload working mode, the current serial telemetry data is cut in real time based on the model and on-orbit mission of the on-orbit aircraft to obtain the second segmented data.

[0013] In one embodiment, the historical satellite stand-alone ground test data is analyzed with the historical serial telemetry data and the historical on-orbit operating conditions to obtain a stand-alone normal operating benchmark value model, including: obtaining a historical stand-alone creep amount corresponding to the historical on-orbit operating conditions based on a comparison between the historical satellite stand-alone ground test data and the historical serial telemetry data; and analyzing the historical stand-alone creep amount and the on-orbit operating parameters in the historical serial telemetry data to obtain a stand-alone normal operating benchmark value model.

[0014] In one embodiment, the analyzing the historical single-machine creep amount and the on-orbit operating parameters in the historical serial telemetry data to obtain a single-machine normal operating benchmark value model includes: setting dynamic simulation parameters of the on-orbit aircraft according to the evaluation object; analyzing the historical single-machine creep amount and the on-orbit operating parameters in the historical serial telemetry data according to the dynamic simulation parameters and exclusive typical operating condition data on the ground to obtain a single-machine normal operating benchmark value model related to the on-orbit creep amount of the on-orbit aircraft and each parameter of the historical serial telemetry data.

[0015] In one embodiment, the method further includes: adjusting the extreme environment model of the on-orbit vehicle according to the segmented current serial telemetry data.

[0016] An on-orbit data analysis device comprises: a telemetry data acquisition module, receiving sent historical serial telemetry data and historical on-orbit working conditions corresponding to an on-orbit aircraft; receiving current serial telemetry data transmitted back to the ground by the on-orbit aircraft; a task working condition cutting module, dividing the historical serial telemetry data according to the on-orbit working conditions to obtain first segmented data; dividing the current serial telemetry data in real time based on the model of the on-orbit aircraft and the on-orbit mission to obtain second segmented data; and a model building module, according to the difference between the on-orbit aircraft orbit and the ground environment and the first segmented data, building a model for different models of on-orbit aircraft. The on-orbit vehicle is modeled specifically to obtain an extreme environment model of the on-orbit vehicle; and historical satellite single-machine ground test data, the historical serial telemetry data and the historical on-orbit operating conditions are analyzed to obtain a single-machine normal operating benchmark value model; an extreme environment model system uses the extreme environment model to interpret the second segmented data, and outputs and stores the current on-orbit operating conditions corresponding to the second segmented data; a single-machine creep amount acquisition module uses the single-machine normal operating benchmark value model to interpret the second segmented data, and outputs the key single-machine creep amount corresponding to the current serial telemetry data.

[0017] Compared with the prior art, the advantages of the present invention are: it is convenient to build various models for fine collection, extraction and processing of on-orbit satellite operation data, solve the problems of single data category, vague data classification standard and huge data volume in the current on-orbit satellite data collection system; and it can realize the rapid classification of various working condition data of on-orbit satellites, simplify the data cutting and classification time, improve the work efficiency of ground monitoring and analysis personnel, and minimize unnecessary losses; and realize the configurability of rapid adaptation to multiple satellites with different missions, build a highly abstract configurable platform, improve the value of data after extraction, facilitate the comparison and analysis of the extracted multi-dimensional and multivariate data, and facilitate analysts to quickly build data extraction systems for satellites with different missions, reducing the development workload; it can automatically identify the configurable extreme environmental conditions based on the orbit, judge the environment of the satellite according to the orbit, so as to mark the data, and effectively help ground support personnel to analyze the satellite status; in addition, the added creep model can obtain the benchmark data value, so as to facilitate ground analysts to infer accurate and reliable creep data, and effectively realize the analysis of the satellite status. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 is a flow chart of an on-orbit data analysis method in an embodiment of the present invention;

[0020] Figure 2 Schematic diagram of an on-orbit data analysis system in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0022] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0023] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0024] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0025] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0026] like Figure 1 As shown, the embodiment of the present disclosure provides an on-orbit data analysis method, which can be set in the measurement and control center, and the measurement and control center can receive various parameter data of the on-orbit spacecraft and its robotic arm during the on-orbit operation stage. The satellite on-orbit data analysis system in the measurement and control center can receive the telemetry data transmitted by the on-orbit satellite, segment and extract the original serial telemetry data according to the on-orbit working conditions, and import it into the database for subsequent analysis and traceability; collect the relevant data of the key single machine, and extract the single machine creep amount according to the model; establish the satellite on-orbit extreme environment model, and mark the relevant data transmitted by the satellite according to the model.

[0027] Specifically, Figure 2 As shown, an embodiment of the present disclosure provides an on-orbit data analysis system, including a telemetry data acquisition module 201, a model building module, a mission condition cutting module 202, an extreme environment model system 203 and a single-machine creep amount acquisition module 204.

[0028] The telemetry data acquisition module 201 receives the historical serial telemetry data and on-orbit working conditions sent by the on-orbit aircraft; the telemetry data acquisition module 201 also receives the current serial telemetry data transmitted back to the ground by the on-orbit aircraft. Telemetry data acquisition is the basic data acquisition process of the satellite. The ground sends a telemetry request, and the satellite collects the relevant variables and packages them according to the protocol and transmits them back to the ground. The current serial telemetry data is the telemetry data transmitted in real time by the on-orbit aircraft according to the telemetry request. The telemetry data contains the relevant data of the key single machine.

[0029] The model building module specifically models different types of on-orbit vehicles based on the difference between the on-orbit vehicle orbit and the ground environment and the first segmentation data to obtain the extreme environment model of the on-orbit vehicle; and analyzes the historical satellite single-machine ground test data, historical serial telemetry data, and historical on-orbit working conditions to obtain the normal working benchmark value model of the single machine. The model building module stores a database formed by various data blocks.

[0030] The mission condition cutting module 202 divides the historical serial telemetry data according to the on-orbit conditions to obtain the first divided data; the mission condition cutting module 202 can also divide the current serial telemetry data in real time based on the model of the on-orbit aircraft and the on-orbit mission to obtain the second divided data. The mission condition cutting module 202 divides and extracts the original serial telemetry data according to the on-orbit conditions and imports them into the database for subsequent analysis and traceability.

[0031] The extreme environment model system 203 uses the extreme environment model to interpret the second segmented data, and outputs and stores the current on-orbit working condition corresponding to the current serial telemetry data. The extreme environment model system 203 adaptively models different types of satellites according to the satellite orbit and the ground environment, and then interprets and annotates the data transmitted back to the ground by the satellite, so as to improve the efficiency of information extraction.

[0032] The single-machine creep amount acquisition module 204 uses the single-machine normal working reference value model to interpret the second segmented data, and outputs the key single-machine creep amount corresponding to the current serial telemetry data. The single-machine creep amount acquisition module 204 essentially uses the single-machine normal working reference value model obtained by statistically comparing the satellite single-machine ground test data with the actual parameters of the on-orbit operation, and judges and extracts the creep amount of the key single machine according to the model.

[0033] The above-mentioned on-orbit data analysis system combines the characteristics of on-orbit satellite data collection, enables the information of the entire life cycle of the satellite to be connected, breaks the information silos of traditional satellite manufacturing, and completes on-orbit satellite data collection and analysis through independent division of labor of telemetry data collection module, mission condition cutting module, extreme environment model system and single-machine creep variable collection module.

[0034] The on-orbit data analysis method comprises the following steps:

[0035] Step 101, receiving historical serial telemetry data and on-orbit operating conditions corresponding to an on-orbit vehicle.

[0036] The historical serial telemetry data are all original serial telemetry data collected by the satellite. The data corresponds to the on-orbit conditions, satellite models, etc., and can be stored in a database. The database can be set up in the measurement and operation control center, or it can be a cache database on the satellite. The measurement and operation control center can send a telemetry request, and the satellite (on-orbit vehicle) collects telemetry data and packages the collected historical serial telemetry data according to the protocol and transmits it back to the ground. The on-orbit conditions can be those collected and stored when the satellite collects the historical serial telemetry data, or they can be monitored and determined by the measurement and operation control center. The telemetry data acquisition module 201 receives the sent historical serial telemetry data corresponding to the on-orbit vehicle and the on-orbit conditions.

[0037] Step 102 : segment the historical serial telemetry data based on the on-orbit operating conditions to obtain first segmented data.

[0038] The mission condition cutting module 202 segments the historical serial telemetry data based on the on-orbit condition to obtain first segmented data.

[0039] Step 103, based on the difference between the orbit of the on-orbit vehicle and the ground environment and the first segmented data, targeted modeling is performed on the on-orbit vehicle of different types to obtain an extreme environment model of the on-orbit vehicle; and historical satellite single-machine ground test data, historical serial telemetry data, and historical on-orbit operating conditions are analyzed to obtain a normal operating benchmark value model of the single machine.

[0040] The model building module can adaptively model different types of satellites according to the differences between satellite orbits and ground environments, and obtain extreme environment models for different models; the extreme environment model can be used to interpret and annotate the data transmitted back to the ground by the satellite, so as to improve the efficiency of subsequent information extraction.

[0041] The historical satellite stand-alone ground test data is the satellite stand-alone ground test data corresponding to the historical serial telemetry data and the historical on-orbit working conditions. The satellite stand-alone ground test data is the satellite test data obtained by fitting the test system on the ground according to the historical on-orbit working conditions.

[0042] The model building module can analyze the historical satellite single-machine ground test data, historical serial telemetry data and historical on-orbit working conditions to obtain a single-machine normal working benchmark value model. The model building module can build a correlation test model related to the single-machine creep variable of the on-orbit aircraft and the various parameters of the historical serial telemetry data; then statistically compare the on-orbit aircraft theoretical test data obtained by the correlation test model with the on-orbit working parameters in the historical serial telemetry data to obtain a single-machine normal working benchmark value model.

[0043] Step 104, receiving the current serial telemetry data transmitted back to the ground by the on-orbit vehicle.

[0044] The telemetry data acquisition module 201 receives the current serial telemetry data transmitted back to the ground by the on-orbit vehicle.

[0045] Step 105 , based on the model and on-orbit mission of the on-orbit spacecraft, the current serial telemetry data is segmented in real time to obtain second segmented data.

[0046] The mission condition cutting module 202 cuts the current serial telemetry data in real time based on the model of the on-orbit aircraft and the on-orbit mission to obtain the second segmented data. The mission condition cutting module 202 can be configured based on the satellite model and the on-orbit mission of the satellite, and cuts the data transmitted by the satellite in real time according to the configured parameters.

[0047] Step 106, using the extreme environment model to interpret the current serial telemetry data transmitted back to the ground by the on-orbit vehicle, and output and store the current on-orbit operating conditions corresponding to the second segmented data.

[0048] When the measurement and control center receives the current serial telemetry data transmitted back to the ground by the on-orbit vehicle, the current serial telemetry data is only segmented but not analyzed. The extreme environment model system 203 uses the extreme environment model to interpret the current serial telemetry data (second segmented data) transmitted back to the ground by the on-orbit vehicle, and outputs and stores the current on-orbit working condition corresponding to the current serial telemetry data (second segmented data).

[0049] Step 107, using the normal operation reference value model of a single machine to interpret the second segmented data, and outputting the key single machine creep value corresponding to the current serial telemetry data.

[0050] The single-machine creep amount acquisition module 204 can use the single-machine normal operation reference value model to interpret the current serial telemetry data (second segmented data) transmitted back to the ground by the on-orbit vehicle, and output the key single-machine creep amount corresponding to the current serial telemetry data.

[0051] The above method and device can conveniently build various models for the fine collection, extraction and processing of on-orbit satellite operation data, solve the problems of single data category, vague data classification standards and huge data volume in the current on-orbit satellite data collection system; and can realize the rapid classification of various working condition data of on-orbit satellites, simplify the data cutting and classification time, improve the work efficiency of ground monitoring and analysis personnel, and minimize unnecessary losses; and realize the configurability of rapid adaptation to multiple satellites with different missions, build a highly abstract configurable platform, improve the value of data after extraction, facilitate the comparison and analysis of the extracted multi-dimensional and multivariate data, and facilitate analysts to quickly build data extraction systems for satellites with different missions, reducing the development workload; it can automatically identify the configurable extreme environmental conditions based on the orbit, judge the environment of the satellite according to the orbit, and thus mark the data, effectively helping ground support personnel to analyze the satellite status; in addition, the added creep model can obtain the baseline data value, so that it is convenient for ground analysts to infer accurate and reliable creep data, and effectively realize the analysis of the satellite status.

[0052] In one embodiment, the current serial telemetry data is cut in real time based on the model and on-orbit mission of the on-orbit aircraft to obtain second segmented data, including: obtaining the corresponding attitude control working mode or payload working mode based on the model and on-orbit mission of the on-orbit aircraft; according to the attitude control working mode or the payload working mode, the current serial telemetry data is cut in real time based on the model and on-orbit mission of the on-orbit aircraft to obtain the second segmented data.

[0053] In the above method, the segmentation mode can be configured according to the on-orbit mission conditions to achieve multi-mode data analysis.

[0054] In one embodiment, historical satellite stand-alone ground test data, historical serial telemetry data, and historical on-orbit operating conditions are analyzed to obtain a stand-alone normal operating benchmark value model, including: obtaining historical stand-alone creep quantities corresponding to historical on-orbit operating conditions based on comparison of historical satellite stand-alone ground test data and historical serial telemetry data; analyzing historical stand-alone creep quantities and on-orbit operating parameters in historical serial telemetry data to obtain a stand-alone normal operating benchmark value model.

[0055] In one embodiment, historical single-machine creep amounts and on-orbit operating parameters in historical serial telemetry data are analyzed to obtain a normal operating benchmark value model for the single-machine, including: setting dynamic simulation parameters of the on-orbit aircraft according to the evaluation object; analyzing the historical single-machine creep amounts and on-orbit operating parameters in historical serial telemetry data according to the dynamic simulation parameters and exclusive typical operating condition data on the ground to obtain a normal operating benchmark value model for the single-machine related to the on-orbit creep amount of the aircraft and various parameters of the historical serial telemetry data.

[0056] The model building module can perform simulation based on the original telemetry data collected by the measurement, operation and control center, simulate and deduce the execution process of the on-orbit vehicle and its robotic arm according to time, tasks and resources, and present it in multiple dimensions. It can also analyze the historical single-machine creep variables and the on-orbit working parameters in the historical serial telemetry data based on the dynamic simulation parameters and the exclusive typical working condition data on the ground, and obtain the normal working benchmark value model of the single-machine related to the single-machine creep variables of the on-orbit vehicle and the various parameters of the historical serial telemetry data.

[0057] In one embodiment, the method further includes: adjusting the extreme environment model of the on-orbit vehicle according to the segmented current serial telemetry data. The model building module can continuously obtain data information from the actual information system for learning and evolution, and is used to adjust the parameters, structure or attributes of various simulation models to form a simulation model that continuously evolves and supports the on-orbit vehicle deduction.

[0058] The simulation model and the actual information system are evolvable parallel simulations based on closed-loop feedback. The simulation system and the actual information system interact with each other. The evolutionary modeling of the simulation system is driven by intelligence data, and a virtual-real symbiotic relationship is formed between the simulation system and the actual information system.

[0059] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. An on-orbit data analysis method, characterized in that: include: Receive historical serial telemetry data and historical on-orbit operating conditions corresponding to the on-orbit vehicle; Segmenting the historical serial telemetry data based on the historical on-orbit operating conditions to obtain first segmented data; Based on the difference between the orbit of the on-orbit spacecraft and the ground environment and the first segmented data, on-orbit spacecraft of different models are modeled specifically to obtain the extreme environment model of the on-orbit spacecraft; and the historical satellite single-machine ground test data, the historical serial telemetry data and the historical on-orbit working conditions are analyzed to obtain the normal working reference value model of the single-machine; Receiving current serial telemetry data transmitted back to the ground by the on-orbit vehicle; Based on the model and on-orbit mission of the on-orbit aircraft, the current serial telemetry data is segmented in real time to obtain second segmented data; Using the extreme environment model to interpret the second segmented data transmitted back to the ground by the on-orbit vehicle, and outputting and storing the current on-orbit operating conditions corresponding to the second segmented data; The second segmented data is interpreted using the normal operating reference value model of the single machine, and the key single machine creep amount corresponding to the current serial telemetry data is output.

2. The method according to claim 1, characterized in that The current serial telemetry data is segmented in real time based on the model and the on-orbit mission of the on-orbit aircraft to obtain the second segmented data, including: Acquire a corresponding attitude control working mode or payload working mode based on the model of the on-orbit aircraft and the on-orbit mission; According to the attitude control working mode or the payload working mode, the current serial telemetry data is segmented in real time based on the model of the on-orbit vehicle and the on-orbit mission to obtain second segmented data.

3. The method according to claim 1, characterized in that The analyzing of the historical satellite single-machine ground test data, the historical serial telemetry data and the historical on-orbit working conditions to obtain the normal working reference value model of the single-machine includes: Based on the comparison of the historical satellite single-machine ground test data with the historical serial telemetry data, a historical single-machine creep amount corresponding to the historical on-orbit operating condition is obtained; The historical single-machine creep amount and the on-orbit operating parameters in the historical serial telemetry data are analyzed to obtain a normal operating reference value model for the single-machine.

4. The method according to claim 3, characterized in that: The analyzing the historical single-machine creep amount and the on-orbit operating parameters in the historical serial telemetry data to obtain a normal operating reference value model for the single-machine includes: Setting dynamic simulation parameters of the on-orbit aircraft according to the evaluation object; According to the dynamic simulation parameters and the exclusive typical operating condition data on the ground, the historical single-machine creep amount and the on-orbit operating parameters in the historical serial telemetry data are analyzed to obtain a single-machine normal operating benchmark value model related to the single-machine creep amount of the on-orbit spacecraft and the various parameters of the historical serial telemetry data.

5. The method according to claim 1, characterized in that Also includes: The extreme environment model of the on-orbit vehicle is adjusted according to the segmented current serial telemetry data.

6. An on-orbit data analysis system, characterized in that: include: A telemetry data acquisition module receives historical serial telemetry data and historical on-orbit operating conditions corresponding to the on-orbit vehicle; Receiving current serial telemetry data transmitted back to the ground by the on-orbit vehicle; The mission condition cutting module is configured to cut the historical serial telemetry data according to the on-orbit conditions to obtain first cut data; and to cut the current serial telemetry data in real time based on the model of the on-orbit aircraft and the on-orbit mission to obtain second cut data; A model building module is used to specifically build models for different types of on-orbit vehicles according to the difference between the on-orbit vehicle orbit and the ground environment and the first segmented data to obtain an extreme environment model of the on-orbit vehicle; and to analyze the historical satellite single-machine ground test data, the historical serial telemetry data, and the historical on-orbit working conditions to obtain a normal working benchmark value model of the single-machine; an extreme environment model system, which uses the extreme environment model to interpret the second segmented data, and outputs and stores a current on-orbit operating condition corresponding to the second segmented data; The single-machine creep amount acquisition module uses the single-machine normal operation reference value model to interpret the second segmented data, and outputs the key single-machine creep amount corresponding to the current serial telemetry data.

Images