机译:基于数据特征的自动气门静摩擦检测系统
Aalto University School of Chemical Technology, Department of Biotechnology and Chemical Technology, P.O. Box 16100, 00076 Aalto, Finland;
Department of Electrical, Electronic and Information Engineering 'G. Marconi, Alma Mater Studiorum, University of Bologna, 40136 Bologna, Italy;
Department of Control Science & Technology, Zhejiang University, Hangzhou, Zhejiang Province, 310027, PR China;
Aalto University School of Chemical Technology, Department of Biotechnology and Chemical Technology, P.O. Box 16100, 00076 Aalto, Finland;
Aalto University School of Chemical Technology, Department of Biotechnology and Chemical Technology, P.O. Box 16100, 00076 Aalto, Finland;
Valves; Stiction; Oscillations; Control loops; Fault detection and diagnosis; Industrial applications;
机译:自动检测控制回路中阀门静摩擦的数据和可靠性表征策略
机译:使用扩展的Hammerstein系统识别方法从振荡数据中检测非对称控制阀静摩擦*
机译:一种简单的无模型蝴蝶形状检测(BSD)方法,集成了深度学习CNN,用于阀门静态检测和量化
机译:数据特征化,用于自动选择气门静摩擦检测算法
机译:检测和诊断控制回路非线性,阀静摩擦和数据压缩。
机译:基于网络安全数据集的预处理表征的IOT聚焦的入侵检测系统方法
机译:基于数据特征的自动气门静摩擦检测系统