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Satellite gyrounit fault diagnosis method based on principal component analysis algorithm

A technology of gyroscope components and principal component analysis, which is applied in calculation, special data processing applications, measuring devices, etc., to achieve good fault diagnosis, improve accuracy, and avoid false alarms.

Active Publication Date: 2014-06-25
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The present invention aims to solve the shortcomings of the existing principal component analysis algorithm for fault diagnosis, such as the problem of false alarms, and provides a fault detection and diagnosis based on Butterworth low-pass filter and principal component analysis (PCA) method

Method used

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  • Satellite gyrounit fault diagnosis method based on principal component analysis algorithm
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  • Satellite gyrounit fault diagnosis method based on principal component analysis algorithm

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specific Embodiment approach 1

[0026] Specific implementation mode 1: The satellite gyroscope component fault diagnosis method based on principal component analysis algorithm of this embodiment is implemented in the following steps:

[0027] Step 1: Filter and preprocess the output angular velocity data Xp of the satellite gyro component based on the Butterworth low-pass filter;

[0028] Step 2: Use the preprocessed satellite gyro component output angular velocity data X to construct a PCA mathematical model;

[0029] Step 3: Use the PCA mathematical model parameters obtained in step 2, and use the square prediction error SPE statistic to detect the process data in the residual subspace;

[0030] Step 4: After detecting the fault, diagnose the fault location according to the process variable contribution graph.

specific Embodiment approach 2

[0031] The second embodiment is different from the first embodiment: the first step is based on the output angular velocity data X of the satellite gyro component based on the Butterworth low-pass filter. p The filtering preprocessing is specifically:

[0032] 1. Model definition

[0033] The model of rate gyroscope is expressed as:

[0034] w out =w in +D+N

[0035] Where w out Is the measurement output of the rate gyroscope, w in Is the actual angular velocity of the satellite, D is the random drift, and N is the measurement noise;

[0036] Butterworth low-pass filter amplitude square function|H a (jΩ)| 2 defined as

[0037] | H a ( jΩ ) | 2 = 1 1 + ( Ω Ω c ) 2 N

[0038] Where N is a positive integer representing the order of the filter, Ω represents the analog corner frequency, Ω c It is called the cut-off frequency, j represents the imaginary unit, a represents the analog filter, and H(·) represents the analog filter...

specific Embodiment approach 3

[0053] Specific embodiment three: This embodiment is different from specific embodiment one or two in:

[0054] In the second step, using the preprocessed output angular velocity data X of the satellite gyro component to construct the PCA mathematical model is specifically as follows:

[0055] 1. First, use the following method to standardize the angular velocity data X after filtering and preprocessing:

[0056] X 1 ij = X ij - X ‾ ( j ) s ( j ) , 1,2 , . . . n , j = 1,2 . . . m

[0057] Where X∈R n×m , R represents a real number, n is the number of sampling points of the gyroscope output data, that is, the observation data sample, m is the number of process variables at each sampling point, X(j) represents the jth column of X, Represents the mean value of X(j), s(j) represents the standard deviation of X(j);

[0058] Record the standardized sample data array as X1;

[0059] 2. Find the covariance ma...

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Abstract

The invention discloses a satellite gyrounit fault diagnosis method based on a principal component analysis algorithm, relates to a fault diagnosis for a satellite gyrounit, and particularly relates to a fault diagnosis method based on a Butterworth lowpass filter and the principal component analysis algorithm in order to overcome the shortcoming in fault diagnosis of the conventional principal component analysis algorithm and solve the problem of misreport. The method comprises the steps of 1, performing filtering preprocessing on output angular speed data Xp of the satellite gyrounit through the Butterworth lowpass filter; 2, constructing a PCA (principal component analysis) math model according to the preprocessed output angular speed data X of the satellite gyrounit; 3, detecting process data in a residual subspace by adopting a squared prediction error (SPE) statistical magnitude according to parameters of the PCA math model obtained in the second step; 4, diagnosing a fault position according to a process variable contribution figure after a fault is detected. The satellite gyrounit fault diagnosis method is applied to the field of fault diagnosis in a satellite gyrounit running process with observable process data.

Description

Technical field [0001] The invention relates to a fault diagnosis method for satellite gyroscope components, in particular to a fault diagnosis method based on a Butterworth low-pass filter and a principal component analysis algorithm. Background technique [0002] The gyroscope was first used for navigation and navigation, but with the development of science and technology, it has also been widely used in the aerospace industry. The gyroscope can be used not only as an indicating instrument, but also as a sensitive component in an automatic control system, that is, as a signal sensor. According to needs, the gyroscope can provide accurate azimuth, level, position, speed and acceleration signals, so that the pilot or autopilot can control aircraft, naval guns, or space shuttles to fly on certain routes. In the guidance of navigational objects such as satellite carriers or space exploration rockets, these signals are directly used to complete the attitude control and orbit contro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C25/00G06F19/00
CPCG01C25/005G16Z99/00
Inventor 王敏金晶崔捷曹洪霞
Owner HARBIN INST OF TECH
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