Machine performance monitoring and fault classification using an exponentially weighted moving average scheme
US5602761A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Dec 30, 1993 |
| Grant date | Feb 11, 1997 |
| Priority date | — |
| Expiry date | Dec 30, 2013 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01M13/045
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
The present invention provides an accurate machine monitoring technique based on vibration analysis. An AR parametric model is generated to characterize a normal machine condition. Subsequently, data is collected from a machine during operation. This data is fit to the AR parametric model, and an Exponentially Weighted Moving Average (EWMA) statistic is derived therefrom. The EWMA statistic is able to identify whether the machine is in a normal state ("in control") or in an abnormal state ("out of control"). Additionally, an EWMA control chart is generated that distinguishes between normal and abnormal conditions, and between different abnormal conditions. As a result, once the EWMA statistic is generated, it is compared to the EWMA chart for determination of the specific fault that is ailing the machine.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.