发明名称 |
GAS TURBINE FAILURE PREDICTION UTILIZING SUPERVISED LEARNING METHODOLOGIES |
摘要 |
A system and method for predicting failures of machinery such as a gas turbine. The system and method utilizes computer-based system to annotate historical data locate a prior failure event. Data associated with sensor readings prior to the failure event is annotated to note that it is likely associated with a failure and is compared to normal operating condition data. A fast boxes algorithm is used to learn the location of the pre-event data (positive class, minority group) with respect to the normal operation data (negative class, majority group). An evaluation is performed to analyze the discriminatory strength of the pre-event data with respect to the normal data, and if a relatively strong difference is found, the associated pre-event data is stored and used as a symptom to monitor the on-going performance of a machine and predict the possibility of an unexpected failure days before it would otherwise occur. |
申请公布号 |
WO2016040085(A1) |
申请公布日期 |
2016.03.17 |
申请号 |
WO2015US48285 |
申请日期 |
2015.09.03 |
申请人 |
SIEMENS AKTIENGESELLSCHAFT;SIEMENS CORPORATION |
发明人 |
CAI, XINMIN;CHARKRABORTY, AMIT;EVANS, MATTHEW;GOH, SIONG THYE;YUAN, CHAO |
分类号 |
G05B23/02 |
主分类号 |
G05B23/02 |
代理机构 |
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