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Machine learning systems for automated event analysis and categorization, equipment status and maintenance action recommendation

机译:用于自动化事件分析和分类,设备状态和维护行动建议的机器学习系统

摘要

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to analyze and categorize events associated with an equipment asset, such as industrial machinery, to determine a status (e.g., insight) associated with the equipment asset, and to determine maintenance actions to be performed with respect to the equipment asset to prevent, or reduce the likelihood or severity of, occurrence of a fault at the equipment asset. Machine learning (ML) models may be trained to categorize events that are detected based on operating characteristics data associated with the equipment asset, to determine a status of the equipment asset, and to recommend one or more maintenance actions (or other actions). Output that indicates the maintenance actions may be displayed to a user or used to automatically initiate performance of one or more of the maintenance actions.
机译:本公开的各方面提供了利用人工智能和机器学习的系统,方法和计算机可读存储介质,以分析和分类与设备资产(例如工业机械)相关联的事件,以确定与之相关的状态(例如,洞察力)设备资产,并确定对设备资产进行的维护行动,以防止或降低设备资产发生故障的可能性或严重程度。机器学习(ML)模型可以接受培训,以对基于与设备资产相关的操作特性数据进行分类的事件,以确定设备资产的状态,并推荐一个或多个维护操作(或其他操作)。表示维护操作的输出可以显示给用户或用于自动启动一个或多个维护操作的性能。

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