CN114298367A - Posture and orbit control subsystem health early warning method - Google Patents
Posture and orbit control subsystem health early warning method Download PDFInfo
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- CN114298367A CN114298367A CN202111348783.9A CN202111348783A CN114298367A CN 114298367 A CN114298367 A CN 114298367A CN 202111348783 A CN202111348783 A CN 202111348783A CN 114298367 A CN114298367 A CN 114298367A
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Abstract
The invention discloses a posture and orbit control subsystem health early warning method, which comprises the following steps: s1, dividing the attitude and orbit control subsystem into a plurality of characteristic blocks, and setting health weight coefficients of the characteristic blocks; s2, carrying out real-time health state evaluation on each feature block to obtain a real-time health state score and a health influence coefficient of each feature block; s3, calculating the real-time health state of the attitude and orbit control subsystem by combining the health weight coefficients, the health state scores and the health influence coefficients of the feature blocks; and S4, estimating the future health state of the system according to the real-time health state value of the attitude and orbit control subsystem, and carrying out health early warning when the estimated value exceeds a warning value. The invention can carry out early warning on the health state of the attitude and orbit control subsystem, and realizes the on-orbit autonomous health management of the attitude and orbit control subsystem.
Description
Technical Field
The invention relates to an on-orbit management technology of a satellite attitude and orbit control subsystem, in particular to a health assessment and health early warning method of the attitude and orbit control subsystem based on a prior algorithm.
Background
The development tasks of the current satellites are continuously increased, the emission density is continuously increased, so that the number of the satellites which are operated and maintained in orbit and the maintenance cost are increased sharply under the condition of a macroscopic environment, and the requirement for developing an efficient and reliable in-orbit autonomous health management system of the satellites is more and more urgent and imperative.
Disclosure of Invention
The invention provides a posture and orbit control subsystem health early warning method which can quantitatively evaluate the health state of a posture and orbit control subsystem, so that the future health state of the system can be estimated, and when the estimated value exceeds a health warning value, health early warning is given out, and the health management of the posture and orbit control subsystem is realized.
In order to achieve the aim, the invention discloses a health early warning method of an attitude and orbit control subsystem, which comprises the following steps:
s1, dividing the attitude and orbit control subsystem into a plurality of characteristic blocks, and setting health weight coefficients of the characteristic blocks;
s2, carrying out real-time health state evaluation on each feature block to obtain a real-time health state score and a health influence coefficient of each feature block;
s3, calculating the real-time health state of the attitude and orbit control subsystem by combining the health weight coefficients, the health state scores and the health influence coefficients of the feature blocks;
and S4, estimating the future health state of the system according to the real-time health state value of the attitude and orbit control subsystem, and carrying out health early warning when the estimated value exceeds a warning value.
Furthermore, the feature blocks are divided into a hardware operation resource feature block, a software operation resource feature block, a measuring sensor feature block and an execution component feature block.
Further, the hardware operation resource feature block includes, but is not limited to, a management standalone feature block and an extension unit feature block, the software operation feature block includes, but is not limited to, an operation environment feature block and an application processing feature block, the measurement sensor feature block includes, but is not limited to, a star sensor feature block and a gyro feature block, and the execution component feature block includes, but is not limited to, a thruster feature block and a flywheel feature block.
And further, determining the health weight coefficient of each feature block according to the influence of each feature block on the functions and the performances of the whole attitude and orbit control subsystem.
Further, in step S2, the health status of the feature block is evaluated in real time, and in the evaluation time period, the health status score of the feature block is evaluated according to the number of times that the feature block is abnormal or the ratio of abnormal status time, and the health impact coefficient of the feature block is determined according to the health impact value of the feature block on the system.
Further, in step S3, the real-time health status of the system is calculated according to an attitude and orbit control health assessment algorithm, where the attitude and orbit control health assessment algorithm is:
H＝(a1×V1-a2×V2-...-ai×Vi-...-an×Vn)×b1×b2×...bi...×bn
in the formula, aiIs the health weight coefficient of the feature block, i ═ 1, 2, ·, n, where a1+...+ai+...+an＝1；ViIs a real-time health status score of the feature block, V is greater than or equal to 0i≤100，biB is a health influence coefficient of the feature block, 0 ≦ bi≤1。
Further, a trend prediction algorithm is used to estimate the future health of the system in step S4.
The invention has the following advantages:
the attitude and orbit control subsystem is divided into a plurality of characteristic blocks, and the health state value of the whole system can be obtained in real time by calculating the real-time health state value of each characteristic block and the health influence coefficient of the characteristic block on the whole system, so that the health evaluation of the attitude and orbit control subsystem is realized. Meanwhile, the future health state of the system is estimated according to the real-time health state value of the attitude and orbit control subsystem, so that health early warning is facilitated, and the on-orbit autonomous health management of the system is realized.
Drawings
Fig. 1 is a flowchart of a posture and orbit control subsystem health early warning method provided by the invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are all used in a non-precise ratio for the purpose of facilitating and distinctly aiding in the description of the embodiments of the invention.
As shown in FIG. 1, the invention discloses a health early warning method of a posture and orbit control subsystem, which comprises the following steps:
s1, dividing the attitude and orbit control subsystem into a plurality of feature blocks, and setting the health weight coefficient of each feature block.
Specifically, the attitude and orbit control subsystem is divided according to the types of the feature blocks, and can be divided into a hardware operation resource feature block, a software operation resource feature block, a measurement sensor feature block and an execution component feature block. The hardware operation resource feature block comprises a management single machine feature block, an expansion unit feature block and the like, the software operation feature block comprises an operation environment feature block, an application processing feature block and the like, the measurement sensor feature block comprises a star sensor feature block, a gyro feature block and the like, and the execution component feature block comprises a thruster feature block, a flywheel feature block and the like.
In this embodiment, the attitude and orbit control subsystem is divided into n blocks. For each feature block, determining the health weight coefficient a of each feature block according to the influence of each feature block on the functions and performances of the whole attitude and orbit control subsystemiWherein i ═ 1, 2, ·, n, a1+...+ai+...+an＝1。
And S2, carrying out real-time health state evaluation on each feature block to obtain the real-time health state score and the health influence coefficient of each feature block.
Specifically, an independent health scoring algorithm is designed for each feature block, and health status of each feature block is sequentially evaluated in real time. The general design principle of the health scoring algorithm of each feature block is as follows: in the evaluation time period, the evaluation time is set to 24 hours in the embodiment, and the real-time health state score V of the feature block is evaluated according to the abnormal times or abnormal state time ratio of the feature blocki，0≤ViAnd (5) being less than or equal to 100, wherein the higher the real-time health state score of the feature block is, the healthier the feature block is. Determining a health influence coefficient b of the feature block according to the real-time health state score of the feature block and the system health influencei，0≤biAnd (4) less than or equal to 1, wherein the higher the health influence coefficient of the feature block is, the smaller the influence of the current health state of the feature block on the attitude and orbit control subsystem is.
S3, calculating the real-time health state of the attitude and orbit control subsystem by combining the health weight coefficients, the health state scores and the health influence coefficients of the feature blocks;
specifically, health state quantitative evaluation is carried out on the attitude and orbit control subsystem in real time according to the attitude and orbit control health evaluation algorithm to obtain a real-time health state numerical value of the system.
The attitude and orbit control health assessment algorithm comprises the following steps:
H＝(a1×V1-a2×V2-...-ai×Vi-...-an×Vn)×b1×b2×...bi...×bn
and S4, estimating the future health state of the system according to the real-time health state value of the attitude and orbit control subsystem, and carrying out health early warning when the estimated value exceeds a warning value.
Specifically, a trend prediction algorithm is adopted to perform trend prediction on the real-time health state value of the attitude and orbit control subsystem, so that the future health state of the system is predicted, and when the predicted value reaches the set health warning value, health early warning is given out, and the on-orbit autonomous health management of the attitude and orbit control subsystem is realized. Generally, the trend prediction algorithm adopts an algorithm such as numerical analysis-quadratic polynomial curve fitting.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (7)
1. The attitude and orbit control subsystem health early warning method is characterized by comprising the following steps of:
s1, dividing the attitude and orbit control subsystem into a plurality of characteristic blocks, and setting health weight coefficients of the characteristic blocks;
s2, carrying out real-time health state evaluation on each feature block to obtain a real-time health state score and a health influence coefficient of each feature block;
s3, calculating the real-time health state of the attitude and orbit control subsystem by combining the health weight coefficients, the health state scores and the health influence coefficients of the feature blocks;
and S4, estimating the future health state of the system according to the real-time health state value of the attitude and orbit control subsystem, and carrying out health early warning when the estimated value exceeds a warning value.
2. The attitude and orbit control subsystem health warning method of claim 1, wherein the feature blocks are divided into hardware operating resource type feature blocks, software operating resource type feature blocks, measuring sensor type feature blocks and executive component type feature blocks.
3. The attitude and orbit control subsystem health warning method according to claim 2, wherein the hardware operation resource feature blocks include but are not limited to a management standalone feature block and an extension unit feature block, the software operation feature blocks include but are not limited to an operation environment feature block and an application processing feature block, the measurement sensor feature blocks include but are not limited to a star sensor feature block and a gyro feature block, and the execution component feature blocks include but are not limited to a thruster feature block and a flywheel feature block.
4. The attitude and orbit control subsystem health warning method of claim 1, wherein in step S1, the health weight coefficients of the feature blocks are determined according to the influence of the feature blocks on the functions and performances of the entire attitude and orbit control subsystem.
5. The attitude and orbit control subsystem health warning method of claim 1, wherein in step S2, the method for real-time health status assessment of the feature block comprises: and in the evaluation time period, evaluating the health state score of the feature block according to the abnormal times or abnormal state time ratio of the feature block, and determining the health influence coefficient of the feature block according to the health state score of the feature block on the system health influence.
6. The attitude and orbit control subsystem health warning method of claim 1, wherein in step S3, the attitude and orbit control health assessment algorithm is used to calculate the real-time health status of the attitude and orbit control subsystem, and the attitude and orbit control health assessment algorithm is:
H＝(a1×V1-a2×V2-...-ai×Vi-...-an×Vn)×b1×b2×...bi...×bn
in the formula, aiIs the health weight coefficient of the feature block, i ═ 1, 2, ·, n, where a1+...+ai+...+an＝1；ViIs a real-time health status score of the feature block, V is greater than or equal to 0i≤100，biB is a health influence coefficient of the feature block, 0 ≦ bi≤1。
7. The attitude and orbit control subsystem health warning method of claim 1, wherein in step S4, a trend prediction algorithm is used to estimate the future health status of the system.
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| CN109885907A (en) * | 2019-01-29 | 2019-06-14 | 南京航空航天大学 | A kind of Satellite Attitude Control System health state evaluation and prediction technique based on cloud model |
| CN110032790A (en) * | 2019-04-08 | 2019-07-19 | 上海微小卫星工程中心 | A kind of in-orbit autonomous health status monitoring method of non-intrusion type microsatellite |
| KR20210048844A (en) * | 2019-10-24 | 2021-05-04 | 한국전력공사 | Apparatus and method establishing maintenance plan based on health index of equipment asset |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103019885A (en) * | 2012-11-26 | 2013-04-03 | 大唐移动通信设备有限公司 | Method and system for monitoring embedded Linux-based hard disc bad track |
| CN106066252A (en) * | 2016-05-24 | 2016-11-02 | 中国人民解放军防化学院 | The health state evaluation method of equipment subsystem level destroyed by a kind of dangerous materials |
| CN109885907A (en) * | 2019-01-29 | 2019-06-14 | 南京航空航天大学 | A kind of Satellite Attitude Control System health state evaluation and prediction technique based on cloud model |
| CN110032790A (en) * | 2019-04-08 | 2019-07-19 | 上海微小卫星工程中心 | A kind of in-orbit autonomous health status monitoring method of non-intrusion type microsatellite |
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