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Generating Estimates of Failure Risk for a Vehicular Component in Situations of High-Dimensional and Low Sample Size Data

机译:在高维和低样本量数据情况下生成车辆部件的失效风险估计

摘要

Methods, systems, and computer program products for generating estimates of failure risk for a vehicular component in situations of high-dimensional and low sample size data are provided herein. A method includes splitting a first input time series comprising multiple data points derived from a vehicular component across a fleet of multiple vehicles into multiple sub-time series; generating a first failure status predicting function of a first selected sub-time series; deleting, from the first input time series, the portion of the data points that corresponds to the first selected sub-time series; repeating the preceding two steps for a second selected sub-time series; generating a second failure status predicting function of each selected sub-time series; applying each second failure status predicting function to a second input time series to calculate prediction of failure values; and identifying the largest prediction of failure value as an estimate of failure risk for the vehicular component.
机译:本文提供了用于在高维和低样本量数据的情况下生成车辆部件的故障风险的估计的方法,系统和计算机程序产品。一种方法,包括将包括多个数据点的第一输入时间序列划分为多个子时间序列,所述第一输入时间序列包括从多个车辆的车队中的车辆组件导出的多个数据点;生成第一选择子时间序列的第一故障状态预测函数;从第一输入时间序列中删除与第一选择的子时间序列相对应的数据点部分;对第二个选定的子时间序列重复上述两个步骤;生成每个选择的子时间序列的第二故障状态预测功能;将每个第二故障状态预测函数应用于第二输入时间序列以计算故障值的预测;确定最大的故障预测值作为车辆部件故障风险的估计值。

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