机译:基于Dempster-Shafer证据理论的基于传感器融合和分类器组合的火花塞故障识别
Department of Mechanical Engineering of Agricultural Machinery, Tarbiat Modares University (TMU), Jalale-E-Aleahmad Highway, Tehran, Iran ,P.O. Box 14115-111, Iran;
Department of Mechanical Engineering of Agricultural Machinery, Tarbiat Modares University (TMU), Jalale-E-Aleahmad Highway, Tehran, Iran;
Department of Mechanical Engineering of Agricultural Machinery, Tarbiat Modares University (TMU), Jalale-E-Aleahmad Highway, Tehran, Iran;
Department of Mechanical Engineering, Karlsruhe University of Applied Sciences, 76131 Karlsruhe, Germany;
Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia;
Engine spark plug; Fault diagnosis; Acoustic signals; Vibration signals; Sensor fusion; Classifier combination; D-S evidence theory;
机译:故障问题:传感器数据融合,用于检测基于IOT的应用程序的Dempster-Shafer证据的故障
机译:基于Dempster-Shafer证据理论的振动和声学信号分类器融合,用于行星齿轮的故障诊断和分类
机译:基于Dempster-Shafer证据理论的基于多传感器信息融合的发动机故障诊断
机译:基于Dempster-Shafer证据理论的多分类器组合方法及其在故障诊断中的应用
机译:使用证据的Dempster-Shafer理论组合分类器。
机译:基于证据理论和模糊偏好方法的多传感器数据融合故障诊断技术
机译:基于Dempster-Shafer证据理论的基于传感器融合和分类器组合的火花塞故障识别
机译:用于人员检测的Dempster-shafer融合:使用超声微多普勒和pIR传感器的Dempster-shafer理论的应用。