公开(公告)号：US20150160096A1

公开(公告)日：2015-06-11

申请号：US14097540

申请日：2013-12-05

Applicant: General Electric Company

Inventor： Romano Patrick ,  Matthew Francis Lemmon ,  Subrat Nanda ,  Jonathan David White ,  Achalesh Kumar Pandey

IPC: G01M15/14 ,  F23R3/00 ,  F23M11/00

CPC classification number: G01M15/14 ,  F05D2260/80 ,  F23M11/00 ,  F23N5/16 ,  F23N5/242 ,  F23N2023/48 ,  F23N2023/54 ,  F23N2041/20 ,  F23R3/00 ,  F23R2900/00005 ,  Y02T50/677

Abstract: A system for detecting an at-fault combustor includes a sensor that is configured to sense combustion dynamics pressure data from the combustor and a computing device that is in electronic communication with the sensor and configured to receive the combustion dynamics pressure data from the sensor. The computing device is programmed to convert the combustion dynamics pressure data into a frequency spectrum, segment the frequency spectrum into a plurality of frequency intervals, extract a feature from the frequency spectrum, generate feature values for the feature within a corresponding frequency interval over a period of time, and to store the feature values to generate a historical database. The computing device is further programmed to execute a machine learning algorithm using the historical database of the feature values to train the computing device to recognize feature behavior that is indicative of an at-fault combustor.

Abstract translation: 用于检测故障期间燃烧器的系统包括传感器，其被配置为感测来自燃烧器的燃烧动力学压力数据和与传感器电子通信并被配置为从传感器接收燃烧动力学压力数据的计算设备。 计算装置被编程为将燃烧动态压力数据转换成频谱，将频谱分段成多个频率间隔，从频谱中提取特征，在一段时间内在对应的频率间隔内生成特征的特征值 的时间，并存储特征值以生成历史数据库。 计算设备还被编程为使用特征值的历史数据库来执行机器学习算法，以训练计算设备以识别指示故障燃烧器的特征行为。