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Unsupervised Anomaly Detection for Power Batteries: A Temporal Convolution Autoencoder Framework
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: To prevent potential abnormalities from escalating into critical faults, a rapid and precise algorithm should be employed for detecting power battery anomalies. An unsupervised model based on a temporal convolutional ...
Quantitative Evaluation on the Evolution of Water Cone Behavior in a Heavy Oil Reservoir With Bottom Water
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In order to solve the problem of the unclear understanding of the water cone behavior and its influencing factors of horizontal well in a heavy oil reservoir with bottom water, in this paper, a series of physical models ...