基于隐马尔可夫模型的航空电子系统下一状态预测算法

M. Lokesh, Y. S. Kumaraswamy
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引用次数: 0

摘要

本文介绍了航电系统下一状态预测在航电系统领域日益增长的需求,以预测和克服由航电系统引起的故障。“下一个状态预测”用于预测系统可能存在的状态。本文解释了如何使用马尔可夫模型和隐马尔可夫模型来预测系统存在的状态,并在此基础上说明系统是否处于安全状态。在当前的场景中,不可能对所有的测试用例都有100%的测试覆盖率。在某些情况下,某些部分将不会被测试覆盖,并且可能导致灾难性的错误。在软件运行之前,进行了非常好的验证和确认过程。然而,所有这些都是在软件在目标上进行规定使用之前进行的。此外,V&V是在模拟环境中进行的。模拟环境是非常困难的。可能会有一些环境条件没有被模拟,这可能会触发软件状态到一个不安全的状态。因此,我们使用这种方法来预测飞机可能存在的当前状态或任何未来状态是否更安全,如果不安全,可以采取必要的措施使其更安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next State Prediction algorithm for the avionic systems using the hidden Markov models
This paper covers increasing need for next state prediction in the field of the avionics system that will predict and overcome the faults caused by the avionics systems. “Next State Prediction” is used for the predication of the possible states that the system can exist. This paper explains about how Markov models and hidden Markov models can be used for the prediction of the state in which the system exist based on which it could be stated if it is in a safe state. In the current scenario, it is not possible to have 100% test coverage for all the test cases. There will be instances where some of the portions that will not be covered by the test coverage and may lead to catastrophic faults. A very good process of verification and validation is carried out before the software is operational. However, all these are carried out before the software is commissioned on the target for its stipulated use. Further, the V&V is carried out in a simulated environment. It is very difficult to simulate the environment into. There could be some environmental conditions which have not been simulated and which could trigger the software state to an unsafe condition. Hence we use this methodology so as to predict if the current state or any further states in which an aircraft could exist would be safer one, if not, necessary steps could be carried out so as to make it safer.
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