Key subsystem based on historical telemetry data and single-machine relevance health baseline construction method

A technology of telemetry data and construction methods, applied in complex mathematical operations and other directions, can solve problems such as poor robustness of anomaly detection, insensitivity to early anomalies, and complex model size, achieving low computing resource requirements, lightweight stability, and expert knowledge. less dependent effect

Active Publication Date: 2021-03-09
BEIHANG UNIV
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Problems solved by technology

[0005] In view of the problems existing in the current satellite health state characterization methods, such as high dependence on expert knowledge, insensitivity to early anomalies, poor robustness of anomaly detection, and too complex model volume, this application aims to propose a key subsystem based on historical telemetry data and A method for building a health baseline based on a single computer

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  • Key subsystem based on historical telemetry data and single-machine relevance health baseline construction method
  • Key subsystem based on historical telemetry data and single-machine relevance health baseline construction method
  • Key subsystem based on historical telemetry data and single-machine relevance health baseline construction method

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Experimental program
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Effect test

Embodiment 1

[0143] Embodiment 1. Description of the linear correlation health baseline construction process

[0144] Step 1. Time Calibration Preprocessing

[0145] Select a group of binary remote reference sequence combinations that are linearly related, record the "battery 1-9 voltage" remote reference sequence as X, and record the "battery voltage" remote reference sequence as Y. Select the working condition sensitive remote reference sequence combination, record the "battery charging current" remote reference sequence as Z 1 , record the "battery discharge current" remote reference sequence as Z 2 .

[0146] Its original remote reference local sequence without time calibration is as follows: figure 2 shown.

[0147] Depend on figure 2 It can be seen that the four original remote reference sequences without time calibration have different sampling frequencies and sampling moments.

[0148] Through the difference processing method described in step 101, m(D 1 )=1, m(D 2 )=1, m...

Embodiment 2

[0166] Embodiment 2. Description of the non-linear correlation health baseline construction process

[0167] Step 1, time calibration processing. Select a group of binary remote reference sequence combinations with nonlinear correlation, record the "battery charging current" remote reference sequence as X, and record the "battery capacity" remote reference sequence as Y. Select the working condition sensitive remote reference sequence combination, record the "battery charging current" remote reference sequence as Z 1 , record the "battery discharge current" remote reference sequence as Z 2 .

[0168] Its original remote reference local sequence without time calibration is as follows: Figure 8 shown.

[0169] Depend on Figure 8 It can be seen that the three original remote reference sequences without time calibration have different sampling frequencies and sampling times.

[0170] Through the difference processing method described in step 101, m(D 1 )=5, m(D 2 )=1, m(...

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Abstract

The invention discloses a key subsystem based on historical telemetry data and a single-machine relevance health baseline construction method. The method comprises the steps: selecting a set of binaryremote parameter sequence combinations in linear relevance or nonlinear relevance; to be specific, step 1, carrying out time calibration on a selected binary remote parameter sequence combination; 2,performing target working condition identification and cutting on the binary remote parameter sequence subjected to time calibration to obtain a binary remote parameter sequence in a target working condition time period; and 3, carrying out fitting by utilizing binary remote parameter sequence data of a normal state target working condition to obtain a binary linear correlation health baseline, or carrying out conversion from a nonlinear relation to a linear relation by adopting a method based on discrete integration, and carrying out fitting to obtain a binary nonlinear correlation health baseline, the binary linear relevance health baseline and the binary nonlinear relevance health baseline forming a relevance health baseline library together. Quantitative and stable representation of the health states of the satellite key subsystem and the single machine is realized through the constructed relevance health baseline library.

Description

technical field [0001] This application relates to a satellite health monitoring technology, in particular to a method for constructing key subsystems and stand-alone correlation health baselines based on historical telemetry data. Background technique [0002] A satellite is a system with very complex functions and components. It contains a large number of key subsystems and stand-alone systems, and a large number of operating status data. By analyzing the operation status data of satellites and monitoring whether they are in abnormal operation status, it is helpful to discover and deal with satellite operation failures in time, which is of great significance to ensure the operation reliability of satellites. [0003] To carry out satellite anomaly monitoring, it is first necessary to accurately, effectively, and quantitatively characterize the health status of the satellite. The traditional health state characterization methods are mainly divided into three types, and the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/11G06F17/18
CPCG06F17/11G06F17/18
Inventor 吕琛宋登巍陶来发王自力
Owner BEIHANG UNIV
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