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机译:基于堆叠的AutomEncoder提取齿轮故障特征的方法
Beijing Informat Sci & Technol Univ Key Lab Electromech Measurement & Control Beijing Peoples R China;
Beijing Informat Sci & Technol Univ Key Lab Electromech Measurement & Control Beijing Peoples R China;
Beijing Informat Sci & Technol Univ Key Lab Electromech Measurement & Control Beijing Peoples R China;
Beijing Informat Sci & Technol Univ Key Lab Electromech Measurement & Control Beijing Peoples R China;
mechanical engineering computing; fault diagnosis; gears; feature extraction; neural nets; learning (artificial intelligence); practical fault feature extraction; fault features; network training; modified activation function; training network performance; deep learning model; complex working environments; pattern recognition; deep learning techniques; changeable condition; complicated condition; different transmission systems; stacked autoencoder; gear fault feature;
机译:基于一维卷积神经网络和堆叠去噪自身叠层特征学习的多变量的故障检测与识别
机译:基于歧管正则化的堆叠自动化器的故障检测在工业过程中的特征学习
机译:基于随机森林和堆叠式自动编码器的混合特征变换方法在高压断路器故障诊断中的应用
机译:基于堆叠的AuteNiCoder提取齿轮故障特征的方法
机译:使用相关和基于特征的方法从立体视觉系统中提取深度信息。
机译:基于堆叠去噪自动化器的自适应EEG特征提取方法用于精神疲劳连通性
机译:基于融合AES的行星齿轮故障诊断的新型深度特征学习方法