公开(公告)号：US10410116B2

公开(公告)日：2019-09-10

申请号：US14644346

申请日：2015-03-11

Applicant: SparkCognition, Inc.

Inventor： Syed Mohammad Amir Husain ,  Martin Andreas Abel ,  Qasim Iqbal

IPC: G06N3/08

Abstract: An aspect of the present invention is to provide a system and method for predicting the remaining useful time of mechanical components such as bearings. Another aspect of the present invention is to provide a system and method for predicting the remaining useful time of bearings based on available condition monitoring data. Another aspect of the present invention is to provide a system and method for automatically deciding which columns of input information are the most significant for predicting the remaining useful life of bearings. Another aspect of the present invention is to provide a system and method for performing an analysis of both test bearings and training bearings and determining which training bearings are most similar to a given test bearing. Another aspect of the present invention is to provide a system and method for training an artificial neural network.

公开(公告)号：US20150262060A1

公开(公告)日：2015-09-17

申请号：US14644346

申请日：2015-03-11

Applicant: SparkCognition, Inc.

Inventor： Syed Mohammad Amir Husain ,  Martin Andreas Abel ,  Qasim Iqbal

IPC: G06N3/08 ,  G06N7/00

CPC classification number: G06N3/08

Abstract: An aspect of the present invention is to provide a system and method for predicting the remaining useful time of mechanical components such as bearings. Another aspect of the present invention is to provide a system and method for predicting the remaining useful time of bearings based on available condition monitoring data. Another aspect of the present invention is to provide a system and method for automatically deciding which columns of input information are the most significant for predicting the remaining useful life of bearings. Another aspect of the present invention is to provide a system and method for performing an analysis of both test bearings and training bearings and determining which training bearings are most similar to a given test bearing. Another aspect of the present invention is to provide a system and method for training an artificial neural network.

Abstract translation: 本发明的一个方面是提供一种用于预测诸如轴承的机械部件的剩余有用时间的系统和方法。 本发明的另一方面是提供一种用于基于可用状态监视数据预测轴承的剩余有用时间的系统和方法。 本发明的另一方面是提供一种用于自动地确定输入信息列对于预测轴承剩余使用寿命最重要的系统和方法。 本发明的另一方面是提供一种用于对测试轴承和训练轴承进行分析并确定哪些训练轴承与给定的测试轴承最相似的系统和方法。 本发明的另一方面是提供一种用于训练人造神经网络的系统和方法。