中文摘要：

特殊环境中的事件区域检测是无线传感器网络的一种重要应用．由于传感器的错误会导致事件区域检测的不准确，所以相关的容错算法成为近年来的研究热点．已有研究工作都仅考虑了事件的空间相关性，通过相邻传感器之间的数据交换实现容错．文中从事件的空间相关性和时间相关性入手，提出了一种以局部检测为主的分布式事件区域检测算法．该算法通过检验传感器本地采样值构成的时间序列与事件随机过程统计特征的符合程度实现容错．算法分析的结果表明，该算法可以减少传感器之间的数据交换，从而有效地利用传感器的能量．模拟实验表明，当有10％的传感器发生错误时，该算法可以检测到93％的事件区域和88％的错误传感器．

英文摘要：

Detecting the region of emergent events is an important application of wireless sensor networks. In recent years, research on fault-tolerant event region detection algorithms becomes a hot topic. By assuming that the occurrence of an event is spatially correlated, previous work distinguish fault and event by exchanging readings among neighboring sensors. Considering that in many cases, an event is both spatially and temporally correlated, this paper proposes a distributed and localized algorithm for fault-tolerant event region detection. Aiming at reducing the network traffic, this algorithm determines a faulty sensor by using statistical hypothesis test for matching the reading sequence of sensors and statistical characters of the event. The analysis shows that the proposed algorithm is more energy-efficient than existing ones. The simulation results show that the algorithm can detect as much as 93% of the event region and 88% of faults, when 10% of sensors are faulty.