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A novel sensors fault detection and self-correction method for HVAC systems using decentralized swarm intelligence algorithm

机译:使用分散的群智能算法的HVAC系统的新型传感器故障检测与自我校正方法

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摘要

Under a self-organizing and flat sensors network structure, a novel decentralized sensors fault detection and self-correction method is proposed. In the self-organizing sensors network, each sensor is updated as smart agent and is connected based on basic physical relations and can communicate with adjacent nodes. This network possess the advantages of plug-and-play and can reduce the high labor and maintenance cost, without having to build central monitor. For the proposed decentralized method, each smart sensor is treated as an individual which has its own utility with local coupling between adjacent nodes. And a decentralized swarm intelligence optimization algorithm is designed and executed in all the smart nodes in parallel to achieve the sensors fault detection and self-correction. Moreover, convergence property of the presented method is analyzed theoretically. Simulation results and hardware platform test on an actual HVAC system illustrate the effectiveness of the proposed method. (C) 2019 Elsevier Ltd and IIR. All rights reserved.
机译:在自组织和平坦的传感器网络结构下,提出了一种新颖的分散传感器故障检测和自校正方法。在自组织传感器网络中,每个传感器都被更新为智能代理,并根据基本物理关系连接,可以与相邻节点通信。该网络具有即插即用的优点,可以降低高劳动力和维护成本,而无需建立中央显示器。对于提出的分散方法,每个智能传感器被视为具有自己的实用程序的个体,在相邻节点之间具有本地耦合。和分散的群智能优化算法在所有智能节点中都设计和执行,以实现传感器故障检测和自我校正。此外,理论上分析了所提出的方法的收敛性。实际HVAC系统的仿真结果和硬件平台测试说明了所提出的方法的有效性。 (c)2019年Elsevier Ltd和IIR。版权所有。

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