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Inertial navigation system fault characteristic judging and testability predicting method

A technology of inertial navigation system and judgment method, which is applied in the field of testability, can solve the problems that the analysis conclusion of testability prediction cannot be accurately given, and achieve the effect of reducing maintenance workload

Active Publication Date: 2018-04-24
BEIJING AUTOMATION CONTROL EQUIP INST
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Problems solved by technology

[0002] The traditional testability technology can only simply analyze the fault characteristics of the inertial navigation system, and cannot accurately give the analysis conclusion of the testability prediction

Method used

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  • Inertial navigation system fault characteristic judging and testability predicting method

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Embodiment Construction

[0062] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0063] The multi-signal model is adopted. Based on the system structure and function analysis, the multi-signal model uses a hierarchical diagram to represent the signal flow direction and the composition and interconnection of each component unit (fault mode), and defines the signal (function) and composition. A model representation method to characterize the correlation between system composition, function, fault and test by using the correlation between unit (failure mode), test and signal.

[0064] The signal (function) in the multi-signal model refers to the characteristics, states, attributes and parameters that characterize the characteristics of the system or its constituent units, which can be regarded as quantitative parameter values ​​or qualitative feature descriptions, and can be divided into normal and abnormal Two state...

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Abstract

The invention belongs to the technical field of testability, and particularly discloses an inertial navigation system fault characteristic judging and testability predicting method. The judging methodincludes the steps: firstly, determining a multi-signal information model of testability; secondly, searching accessible test points of faults; thirdly, analyzing fault correlation, and determining fault-test correlation matrixes; finally, judging fault characteristics. The predicting method includes the steps: determining FDR (fault detection rate) and FIR (fault isolation rate) after determining of the fault-test correlation matrixes, and performing comprehensive and accurate testability predicting on system fault characteristics; analyzing the fault characteristics by the aid of the fault-test correlation matrixes, and analyzing single-fault characteristics and multi-fault characteristics. Accurate judging and testability predicting of the fault characteristics of the inertial navigation system are facilitated, fault analysis of the inertial navigation system is facilitated, and the maintenance workload of the inertial navigation system is reduced.

Description

technical field [0001] The invention belongs to the technical field of testability, and in particular relates to a method for judging fault characteristics of an inertial navigation system and predicting testability. Background technique [0002] The traditional testability technology can only simply analyze the fault characteristics of the inertial navigation system, and cannot accurately give the analysis conclusion of the testability prediction. In order to accurately analyze the testability of the inertial navigation system, the method of multi-signal model is used to model the testability of the inertial navigation system, which can accurately judge the fault characteristics of the inertial navigation system and predict the testability. Therefore, it is necessary to provide a fault characteristic judgment and testability prediction method for the inertial navigation system to reduce the maintenance workload of the inertial navigation system. Contents of the invention ...

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Application Information

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IPC IPC(8): G01C25/00
CPCG01C25/005
Inventor 孙伟李海军徐海刚李群刘冲裴玉锋郭元江原润钟润伍
Owner BEIJING AUTOMATION CONTROL EQUIP INST
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