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传感器优化配置是航空航天设备PHM系统功能得以有效实现的基础和保证。针对目前传感器配置研究中未考虑传感器实际属性的问题,建立了考虑传感器故障检测能力的PHM系统传感器优化配置模型。首先分析了系统故障-传感器相关性矩阵的含义,将传感器的故障检测能力和相关性矩阵相结合,以概率形式描述了传感器对故障的检测性能。在此基础上根据系统的测试性指标要求建立传感器优化配置模型,并采用混沌二进制粒子群优化算法求解。仿真实例结果表明,本文建立的优化模型更加符合实际情况,配置结果更加准确和可靠。 相似文献
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分形和混沌作为两种常见的非线性现象,它们之间是否存在什么联系?本文通过Lorenz方程的研究,得出利用随参数变化的时间序列分维图,可以很好地识别非线性模型从确定性状态到混沌状态的临界参数点或区域。 相似文献
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一类复杂力场中磁性刚体航天器的混沌姿态运动 总被引:3,自引:0,他引:3
研究在地球万有引力场和磁场中具有结构内阻尼的磁性刚体航天器的近赤道圆轨道上平面天平动的混沌行为。应用Melnikow方法建立了系统存在横截异宿环的条件,分别采用功率谱和Lyapunov指数等数值方法对系统力学行为进行识别。数值结果表明,在不同参数条件下系统出现周期运动和混沌运动。 相似文献
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Ershen Wang Chaoying Jia Gang Tong Pingping Qu Xiaoyu Lan Tao Pang 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2018,61(5):1260-1272
The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm. 相似文献
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为排查超高速转子系统碰摩故障的原因,利用混沌、分岔理论,研究了碰摩转子动力学特性。以实际转子结构为对象,建立物理模型,由拉格朗日(Lagrange)法建立系统动力学方程并数值求解,结合分岔图、轴心轨迹、相图、Poincare映射等手段,考察了碰摩转子的动力学行为及系统参数变化对其动力学特性的影响。研究结果表明:质量盘之间的动力耦合效应较弱,有利于系统稳定性;既定转子结构不致引起高速混沌状态进而导致碰摩。研究内容为探求故障原因提供了依据,所涉及的故障分析方法和过程可作为系列化微型涡喷发动机设计的参考。 相似文献