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An Approach for Intelligent Evaluation of the State of Complex Autonomous Objects Based on the Wavelet Analysis

机译:基于小波分析的复杂自主对象状态智能评估方法

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Increasing requirements for the quality of functioning of complex autonomous technical objects (bodynets, robotic complexes, unmanned cars and aerial vehicles, etc.), as well as their security and reliability, made the problem of assessing their state particularly relevant given the impact of various types of attacks and destabilizing factors, aging and technological dispersion of parameters. The paper proposes a new approach to intelligent evaluation of the state of such objects. The approach is based on interval assessment of parameters, use of a knowledge base about critical and state conditions, and application of wavelet analysis. The architecture and realization of an intelligent system for evaluation of the state of complex autonomous technical objects is considered. The carried-out experimental assessment of the offered approach showed that use of wavelet analysis when forming areas of objects' operability allows one to make accurate differentiation of classes of their technical states that increases the accuracy and reliability of state identification and also to expand possibilities of technical means of control and diagnostics.
机译:增加了复杂自主技术对象(Bodynet,机器人复合物,无人驾驶汽车和航空车辆等)的运作质量要求,以及它们的安全性和可靠性,使其在鉴于各种影响的影响特别相关的国家参数攻击和稳定性因素,老化和技术分散的类型。本文提出了一种智能评估这些物体的智能评估的新方法。该方法基于对参数的间隔评估,使用关于关键和状态条件的知识库,以及对小波分析的应用。考虑了评估复杂自主技术对象状态的智能系统的结构和实现。所提供方法的开展实验评估表明,在形成物体的可操作性面积时,使用小波分析允许人们对其技术国家的类别进行准确分化,这增加了国家识别的准确性和可靠性以及扩大的可能性控制和诊断技术手段。

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