共查询到16条相似文献,搜索用时 203 毫秒
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从传感器行为的空间相关性和时间相关性入手,提出一种基于相似度的以局部检测为主的分布式传感器行为信任认证机制.该机制通过检验传感器本地采样值构成的时空相似度与传感器行为随机过程统计特征的符合程度实现行为信任认证.模拟仿真试验表明,该机制可以减少传感器之间的数据交换,当网络中10%的传感器存在不安全行为时,该模型可以检测到93%的不可信传感器. 相似文献
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事件检测与事件边界检测是无线传感器网络的重要应用之一,节点故障的准确检测是提高事件与事件边界检测效率的前提.然而,目前的故障检测机制对节点故障类型分析不够明晰,导致系统可能将事件边界节点误判为故障节点,且常需要传感器节点间进行频繁通信,导致网络系统容错性能和节点利用率低下,并带来额外的能耗开销.为了达到较高的检测精度与能源利用率,提出了一种新的高效容错的无线传感网事件及其边界检测算法:利用时间相关性实现无线传感器网络事件检测,利用空间相关性实现故障检测与事件边界检测;提出了节点的信息可靠度恢复机制,使得节点能够根据网络环境的变化,自动调整节点的信息可靠度.实验结果表明,即使在故障概率较高的情况下,该策略仍然具有良好的性能表现. 相似文献
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基于多阶段注意力机制的多种导航传感器故障识别研究 总被引:1,自引:0,他引:1
导航传感器在使用过程中容易发生故障, 针对传统方法对其间歇性和渐变性故障识别率低的问题提出了一种基于多阶段注意力机制的多传感器故障识别算法. 该算法采用基于长短期记忆神经网络和注意力机制的编码器?解码器结构, 根据多类导航传感器数据之间的空间相关性和时间相关性来进行多传感器的故障互判. 经验证, 该算法对多种类传感器的故障识别率高达97.5%, 可以高效地实现故障的检测和分类. 该方法可以准确识别出故障传感器和故障类型, 具有很强的工程应用价值. 相似文献
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当网络异常事件发生时,传感器节点间的时空相关性往往非常明显.而现有方法通常将时间和空间数据性质分开考虑,提出一种分散的基于概率图模型的时空异常事件检测算法.该算法首先利用连通支配集算法(CDS)选择部分传感器节点监测,避免监测所有的传感器节点;然后通过马尔可夫链(MC)预测时间异常事件;最后用贝叶斯网络(BN)推测空间异常事件是否出现,结合时空事件来预测异常事件是否会发生.与简单阈值算法和基于贝叶斯网络算法对比,实验结果表明该算法有高检测精度、低延迟率, 能大幅降低通信开销,提高响应速度. 相似文献
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事件监测是无线传感器网络的一种重要应用。针对该应用中软故障节点提供的错误数据会降低监测的准确性的问题,提出了一种分布式的容错事件边界检测算法。节点只需与邻节点交换一次传感数据,通过简单地计算识别故障;正常的事件节点利用统计比较的方法判断其是否处于事件边界,边界宽度可根据网络用户的要求调节。该算法执行时所需的通信量小,计算复杂度低,时延小,对大规模网络具有很好的可扩展性。仿真结果表明即使节点故障率很高,应用该算法仍可以获得很好的检测效果。 相似文献
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Distributed micro flow-sensor arrays and networks (DMFSA/N), built from collections of spatially scattered, cooperating intelligent and redundant micro flow-sensor nodes, can improve the accuracy and reliability of system. However, it is unrealistic to expect all the sensor nodes and communication links in the system to function properly all the time. This paper is based on an earlier research, in which a DMFSA/N with a cluster architecture and fault-tolerant time-out Protocol (FTTP) was developed. In this paper, a fault-tolerant sensor integration algorithm (FTSIA) is proposed and evaluated in simulations. Experimental results showed that the FTSIA could always give reliable results even when certain portion of the sensors yielded faulty information. Furthermore, the results from FTSIA were significantly more accurate than the mean of sensor readings (popularly applied in industry) if some of the sensors produced faulty readings. Finally, the application of the proposed FTSIA is illustrated by measuring flow pressure using a pressure sensor array of eight sensors. 相似文献
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In this paper, we present a fault-tolerant control scheme for linear parameter-varying systems that utilises multiple sensor switching to compensate for sensor faults. The closed-loop scheme consists of an estimator-based feedback tracking controller and sensor-estimate switching strategy which allows for the reintegration of previously faulty sensors. The switching mechanism tracks the transitions from faulty to healthy behaviour by means of set separation and pre-computed transition times. The sensor-estimate pairings are then reconfigured based on available healthy sensors. Under the proposed scheme, preservation of closed-loop system boundedness is guaranteed for a wide range of sensor fault situations. An example is presented to illustrate the performance of the fault-tolerant control strategy. 相似文献
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Xuejing Cai 《International journal of control》2013,86(7):1475-1484
In this article, we study a robust fault-tolerant control (FTC) problem for linear systems subject to time-varying actuator and sensor faults. The faults under consideration are loss of effectiveness in actuators and sensors. Based on the estimated faults from a fault detection and isolation scheme, robust parameter-dependent FTC will be designed to stabilise the faulty system under all possible fault scenarios. The synthesis condition of such an FTC control law will be formulated in terms of linear matrix inequalities (LMIs) and can be solved efficiently by semi-definite programming. The proposed FTC approach will be demonstrated on a simple faulty system with different fault levels and fault estimation error bounds. 相似文献
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感应器失效节点通常发送错误数据,干扰全局信息判断,若转为睡眠状态则容易造成网络连通度下降,增加其他节点的路由转发负载.因此,对这些感应器失效节点的剩余能量进行利用,并进行自身估值,对于获取更准确的全局信息,保持网络负载平衡,具有重要的意义.提出一种基于点割集的感应失效节点容错算法,该算法基于数据相关图,筛选出与失效节点具有强数据相关性的点割集,然后利用所监听到的点割子集的观测量,进行正交估算,获取失效节点的最小均方误差估值.理论分析和实验结果表明,所提出的容错算法能较准确地估计失效点观测盲区,获取较完整的全局信息,同时由于算法使网络内的失效节点可以继续工作,保证了已有的网络负载平衡,维持原有的网络连通度. 相似文献
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《Advanced Robotics》2013,27(8):887-904
This article presents a robust sensor fault-tolerant control (FTC) scheme and its implementation on a flexible arm robot. Sensor faults affect the system's performance in the closed loop when the faulty sensor readings are used to generate the control input. In this article, the non-faulty sensors are used to reconstruct the faults on the potentially faulty sensors. The reconstruction is subtracted from the faulty sensors to generate a 'virtual sensor' which (instead of the normally used faulty sensor output) is then used to generate the control input. A design method is also presented in which the virtual sensor is made insensitive to any system uncertainties (which could corrupt the fault reconstruction) that cannot fit into the framework of the model used. Two fault conditions are tested: total failure and incipient faults. Then the scheme robustness is tested and evaluated through its implementation on two flexible arm systems, one with a flexible joint and the other with a flexible link. Excellent results have been obtained for both cases (joint and link); the FTC scheme produced system performance almost identical to the fault-free scenario, whilst providing an indication that a fault is present, even for simultaneous faults. 相似文献