A Spacecraft On-orbit Abnormal Alarm and Fault Diagnosis System

Abstract

The invention discloses a spacecraft on-orbit anomaly alarming and fault diagnosing system. A knowledge editor inputs well-compiled alarming diagnosis knowledge; a data buffer area buffers inputted original telemetering data; a data area extracts telemetering data or a telemetering instruction from the data buffer area when a reasoning controller carries out logic matching operation and stores the data or the instruction; a rule area loads the well-compiled alarming diagnosis knowledge from the knowledge editor, and in the rule area, each piece of the alarming diagnosis knowledge is called a rule; the reasoning controller carries out logic matching operation on the original telemetering data in the data area and the alarming diagnosis knowledge in the rule area to acquire diagnosis results; a diagnosis result which needs to be outputted is selected to be outputted to a blackboard; the blackboard stores the diagnosis result acquired through the logic matching operation by the reasoning controller; and a result buffer area buffers the diagnosis result which is selected to be outputted by the reasoning controller and the result is sent to a client, and after a user checks the diagnosis result via the client, a confirmation message is answered.

Description

technical field [0001] The invention belongs to the technical field of aerospace fault diagnosis, in particular to an on-orbit abnormal alarm and fault diagnosis system for spacecraft. Background technique [0002] The core of the reasoning machine subsystem is to perform logical reasoning operations based on expert knowledge and input measurement and control data, and finally deduce the abnormal state of the spacecraft. Its essence is to realize a virtual machine with logical reasoning ability. Early expert systems mainly used deterministic reasoning algorithms, and the evidence represented by this method was deterministic. For example, taking the state of the earth shadow as an example, it is either the light area or the earth shadow area, and there is no ambiguity. Its reasoning process is based on mathematical logic, the reasoning process is rigorous, and the conclusion is also accurate, either true or false. However, the evidence used in the actual diagnosis process i...

AI Technical Summary

Problems solved by technology

However, the evidence used in the actual diagnosis process is not completely accurate, some information is not perfect, and some are uncertain

For example, in the state of the earth's shadow, it is more difficult to describe the penumbra area. Since when the penumbra is regarded as the earth's shadow, it is difficult to describe it with precise reasoning

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