Establishment Method of Quantitative Analysis Model for Reliability of Flight and Landing Guidance System

Abstract

The invention relates to a method for establishing a quantitative analysis model for the reliability of a flight and landing guidance system. First, a number of variation models are generated for the same candidate model, and then the Boosting algorithm is used to train these variation models on the failure data set and dynamically assign weights. Finally, a linear combination software reliability growth model composed of multiple mutation models is obtained. This model can be trained and learned for the failure data set of the flight and landing guidance system software, and fully exploit the failure data of the flight and landing guidance system software contained in the failure data set. mechanism, thereby effectively improving the fitting performance and predicted performance of a single candidate reliability quantitative analysis model for reliability parameters, without adding any other factors and assumptions. The invention proposes that the efficiency and quality of the software reliability quantitative analysis work of the flight and landing guidance system can be significantly improved.

Description

technical field [0001] The invention relates to the technical field of software reliability analysis, in particular to a method for establishing a reliability quantitative analysis model of a flight and landing guidance system. Background technique [0002] With the rapid development of computer technology, software has become the core component of the flight and landing guidance system, completing important functions such as data calculation, target tracking, command and control. The ensuing problem is that software failure becomes the main cause of system danger. Therefore, how to ensure the high reliability and high security of the flight and landing guidance system software is very important. Software reliability refers to the ability of the software to run without causing system failure under specified conditions and within a specified period of time. It has become one of the core elements of the quality of the flight and landing guidance system. [0003] The flight a...

AI Technical Summary

Problems solved by technology

However, the research results show that there is no such universal quantitative analysis model, and there is no method to choose the most appropriate model according to the specific situation

In other words, many quantitative analysis models can obtain good analysis results on this set of failure data sets, but may obtain poor analysis results on another set of data sets

The possible underlying reason is because the quantitative performance of these models is heavily dependent on their assumptions about failure behavior and the type of failure data set to which they are applied

The flight and landing guidance system software has the characteristics of high real-time and control precision requirements, many cross-linked equipment participating in the control, high requirements for equipment fault tolerance, complex and changeable operating environment, etc., and the failure mechanism is relatively complicated.

The traditional software reliability quantitative analysis model assumes that it is difficult to accurately describe the failure mechanism of the flight and landing guidance system software, so it is difficult to directly apply this type of software reliability quantitative analysis process

[0006] In summary, the traditional software reliability quantitative analysis model has limitations in assumptions, and it is difficult to accurately evaluate and predict the reliability growth trend of flight and landing guidance system software, leaving a large number of safety hazards

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