摘要
以燃料电池发动机控制系统为背景,以该系统的多种传感器为研究对象,利用神经网络信息融合的方法,构建了传感器的在线故障识别模型,给出了其算法。用MATLAB仿真验证了所给方案的有效性。能有效地识别传感器的故障,为系统获取有效的测量数据奠定了基础。
With the increasing demands on the stability of the fuel cell engines the fault detection of the online sensors that ensure the proper working condition of the engine became vital. This article utilized the information-fusion method in neural networks to construct an on-line sensor fault diagnosis model. An algorithm for the model was presented. A MATLAB simulation was used to validate the proposed plan. This model can identify the sensor-faults effectively. This model also provided a foundation for effectively obtaining the system survey data.
出处
《武汉理工大学学报》
EI
CAS
CSCD
北大核心
2006年第6期113-116,共4页
Journal of Wuhan University of Technology
基金
湖北省科技攻关(2005lg0004b)
