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Machine learning based predictive maintenance of a dryer

机译:基于机器学习的烘干机的预测性维护

摘要

A machine learning method and system for predictive maintenance of a dryer. The method includes obtaining over a communication network, an information associated with the dryer and receiving measurements of a vibration level of one of a process blower, a cassette motor and a regeneration blower associated with the dryer. Further, an anomaly is determined based on at least one of a back pressure and a fault and balance of at least one of the process blower and the regeneration blower is tracked. An alarm for maintenance is raised when one of an anomaly and an off-balance is detected.
机译:用于烘干机的预测性维护的机器学习方法和系统。该方法包括通过通信网络获得与干燥机相关联的信息,并接收与该干燥机相关联的过程鼓风机,盒式电动机和再生鼓风机之一的振动水平的测量值。此外,基于背压和故障中的至少一个来确定异常,并且跟踪过程鼓风机和再生鼓风机中的至少一个的平衡。当检测到异常和不平衡之一时,会发出维护警报。

著录项

  • 公开/公告号US10648735B2

    专利类型

  • 公开/公告日2020-05-12

    原文格式PDF

  • 申请/专利权人 MACHINESENSE LLC;

    申请/专利号US201514833111

  • 发明设计人 BIPLAB PAL;STEVE GILLMEISTER;

    申请日2015-08-23

  • 分类号F25B25;F26B25;

  • 国家 US

  • 入库时间 2022-08-21 11:31:20

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