Wang Rui, Li Yanxiao, Sun Hui, Chen Zengqiang
College of Information Engineering and Automation, Haihang Building, South campus, Civil Aviation University of China, Tianjin 300300, China.
Innovation Center, China Electronics Technology Avionics Co., Ltd., Chengdu, China.
ISA Trans. 2017 Nov;71(Pt 1):112-120. doi: 10.1016/j.isatra.2017.06.027. Epub 2017 Jul 11.
The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results. The paper develops the sufficient proof of the Kalman consensus filter stability when considering the system and the observation noises and compares the mean estimation and the mean consensus errors between Kalman consensus filter and local Kalman filter. The numerical example analyses show the effectiveness of the algorithm.
现代民用飞机使用受限于空间的通风加压舱。为了监测多种污染物并克服单一传感器的超敏性，本文在与其他两种不同配置进行比较后，构建了一种使用具有不同测量理论的传感器的输出校正集成传感器配置。这种提议的配置作为污染物分布式无线传感器监测网络中的一个节点。还通过使用卡尔曼共识滤波器估计状态并进行数据融合来提出集成传感器的相应测量误差模型，以便调节单一传感器的测量结果。本文在考虑系统和观测噪声时给出了卡尔曼共识滤波器稳定性的充分证明，并比较了卡尔曼共识滤波器与局部卡尔曼滤波器之间的均值估计和均值共识误差。数值示例分析表明了该算法的有效性。
