共查询到18条相似文献,搜索用时 125 毫秒
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基于ZigBee和ARM技术的火灾信息数据无线采集系统 总被引:2,自引:1,他引:1
为解决目前火灾自动报警及其联动系统信号采集时布线困难,尤其是联动系统信号采集点分散的问题,设计了一套采用ARM处理器、传感器、ZigBee网络、无线通信等技术组成的火灾信息数据无线采集系统。该系统主要由数据采集与控制模块、ZigBee数传模块及传输设备组成。其中数据采集与控制模块负责采集火灾自动报警系统的信息,ZigBee数传模块负责将采集到的数据传送给传输设备,传输设备将接收到的数据通过电话、Internet网或无线网络远传到集中监控中心。经过连接火灾报警联动系统实验,此套系统数据采集准确及时,工作可靠稳定。 相似文献
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风电机组一旦因组件故障而停机,将耗费较长时间排故,给风电场带来较大的经济损失,因此需加强机组运行状态的实时监测,科学评估机组状态,以指导日常检修、维护等工作,有效降低机组发生故障的概率。在明确机组运行状态监测评估需求的基础上,引入大数据技术实现机组运行调度、故障处理等操作,需做好数据收集、分析和推理。把握大数据应用的技术思路,利用存储模块、收集模块、分析系统等加强技术实践应用,有效实现风电机组运行状态的监测评估,为解决风电机组运行管理问题提供有效的技术方案。 相似文献
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Nowadays wireless sensor networks (WSNs) has been used in enormous applications for data collection in an unfriendly environment. Forest fire makes vast hazard to the consuming plant of the world. To preserve the forest from fire, sensor nodes monitor the environment temperature. If the temperature is increased and it exceeds the threshold, the sensor sends the notification message to the fire monitoring system. The forest fire is measured by Fire Weather Index. Most of the existing fire monitoring systems only highlight in detection, but not the verification of the sensor. Suppose, if the attacker inserts any malicious sensor, the malicious sensor sends false information or create an additional delay in fire monitoring system. As a result, the more chances for the forest to be destroyed by fire. To solve this problem, Shift Reduce Parser based Malicious Sensor Detection (SRP_MSD) in WSN is proposed. The Bivariate Pascal Triangle method hides the original identity of nodes, data route from the malicious observer and sends confidential information to the Base Station. This method is analyzed and evaluated using network simulator-2. The results show that it is possible to detect malicious sensor nodes and send the reliable information to the forest fire monitoring system. 相似文献
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针对传统火灾报警检测系统的许多缺点,研制了火灾报警检测系统的无线传感器网络,并对WSN在智能化火灾报警系统中的应用进行了分析,使得火灾报警检测系统的节点位置、监测范围、节点敏感度、节点间距离都得以改善和提高。 相似文献
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Cooperative ad hoc wireless networks are more vulnerable to malicious attacks than traditional wired networks. Many of these attacks are silent in nature and cannot be detected by conventional intrusion detection methods such as traffic monitoring, port scanning, or protocol violations. These sophisticated attacks operate under the threshold boundaries during an intrusion attempt and can only be identified by profiling the complete system activity in relation to normal behavior. In this article we discuss a control- theoretic hidden Markov modelstrategy for intrusion detection using distributed observation across multiple nodes. This model comprises a distributed HMM engine that executes in a randomly selected monitor node and functions as a part of the feedback control engine. This drives the defensive response based on hysteresis to reduce the frequency of false positives, thereby avoiding inappropriate ad hoc responses. 相似文献