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Predictive classification of future operations

机译:预测未来运营的分类

摘要

A system evaluates a plurality of faults in an operation of a machine at a set of future instances of time. The system uses a neural network including a first subnetwork sequentially connected with a sequence of second subnetworks for each of the future instance of time such that an output of one subnetwork is an input to a subsequent subnetwork. The first subnetwork accepts the current time-series data and the current setpoints of operation of the machine. Each of the second subnetworks accepts the output of a preceding subnetwork, an internal state of the preceding subnetwork, and a future setpoint for a corresponding future instance of time. Each of the second subnetworks outputs an individual prediction of each fault of a plurality of faults at the corresponding future instance of time.
机译:系统在一组未来的时间实例中评估机器的操作中的多个故障。该系统使用神经网络,该神经网络包括针对每个未来的时间实例的第二子网序列顺序地连接的第一子网络,使得一个子网的输出是对后续子网的输入。第一个子网络接​​受当前的时间序列数据和机器操作的当前设定点。每个第二个子网络接​​受前面的子网,前一个子网的内部状态的输出以及相应的未来时间实例的未来设定值。每个第二子网,在相应的未来时间实例中输出多个故障的每个故障的单独预测。

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