0引言我院新生儿重症监护病房（neonatal intensive care unit,NICU）使用的是德国斯蒂芬Stephanie呼吸机,它适用于婴幼儿和体质量小于20 kg的小儿,具有高频振荡通气功能。高频通气是利用高频率的振动促进对流及气体扩散、弥散过程[1],...0引言我院新生儿重症监护病房（neonatal intensive care unit,NICU）使用的是德国斯蒂芬Stephanie呼吸机,它适用于婴幼儿和体质量小于20 kg的小儿,具有高频振荡通气功能。高频通气是利用高频率的振动促进对流及气体扩散、弥散过程[1],配备有多种适用于新生儿患者的呼吸模式。它使用的是吸气和呼气端同步控制的比例阀系统,展开更多
The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data ...The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.展开更多
文摘0引言我院新生儿重症监护病房（neonatal intensive care unit,NICU）使用的是德国斯蒂芬Stephanie呼吸机,它适用于婴幼儿和体质量小于20 kg的小儿,具有高频振荡通气功能。高频通气是利用高频率的振动促进对流及气体扩散、弥散过程[1],配备有多种适用于新生儿患者的呼吸模式。它使用的是吸气和呼气端同步控制的比例阀系统,
基金supported by National Key Natural Science Foundation of China (Grant No. 50635010)
文摘The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.
