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公开(公告)号：US10047757B2
公开(公告)日：2018-08-14
申请号：US15189776
申请日：2016-06-22
Applicant: General Electric Company
Abstract: Systems and methods for predicting a surge event in a compressor of a turbomachine are provided. According to one embodiment of the disclosure, a system may include one or more computer processors associated with the turbomachine. The one or more computer processors may be operable to receive a plurality of performance parameters of the compressor and analyze the plurality of performance parameters to determine corrected performance values of the performance parameters. Based at least partially on the corrected performance values, a compressor efficiency may be determined. The processor may be further operable to standardize the compressor efficiency for a standard mode of operation, ascertain historical performance data associated with the standard mode of operation, and analyze the compressor efficiency based at least partially on the historical performance data. Based on the analysis of the compressor efficiency, a surge event may be selectively predicted.
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公开(公告)号：US20170370368A1
公开(公告)日：2017-12-28
申请号：US15189776
申请日：2016-06-22
Applicant: General Electric Company
IPC: F04D27/00
CPC classification number: F04D27/001 , F05D2220/32 , F05D2260/81 , F05D2260/821 , F05D2260/83 , F05D2270/101 , F05D2270/44
Abstract: Systems and methods for predicting a surge event in a compressor of a turbomachine are provided. According to one embodiment of the disclosure, a system may include one or more computer processors associated with the turbomachine. The one or more computer processors may be operable to receive a plurality of performance parameters of the compressor and analyze the plurality of performance parameters to determine corrected performance values of the performance parameters. Based at least partially on the corrected performance values, a compressor efficiency may be determined. The processor may be further operable to standardize the compressor efficiency for a standard mode of operation, ascertain historical performance data associated with the standard mode of operation, and analyze the compressor efficiency based at least partially on the historical performance data. Based on the analysis of the compressor efficiency, a surge event may be selectively predicted.
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公开(公告)号：US09719366B2
公开(公告)日：2017-08-01
申请号：US13916179
申请日：2013-06-12
Applicant: General Electric Company
Inventor： Lijie Yu , Venkatesh Rajagopalan , Sachin Srivastava , Mayank Lalan
CPC classification number: F01D11/14 , F01D11/20 , F01D17/02 , F01D21/003 , F01D21/04 , F01D21/045 , F01D21/10 , F01D21/14
Abstract: Systems and methods for blade health monitoring are provided. According to one embodiment of the disclosure, a system may include a feature extraction module and an anomaly detection module in communication with the extraction module. The feature extraction module may be configured to continuously receive blade passing signal data associated with clearance of a blade and pre-process the blade passing signal data. Blade clearance feature data may be extracted from the blade passing signal data prior to transmission to the anomaly detection module. The anomaly detection module may be configured to normalize the blade clearance feature data received from the extraction module, analyze the blade clearance feature data to detect a shift in the clearance of the blade, and determine an abnormality of the blade based on the shift exceeding a predetermined shift threshold.
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公开(公告)号：US20140369833A1
公开(公告)日：2014-12-18
申请号：US13916179
申请日：2013-06-12
Applicant: General Electric Company
Inventor： Lijie Yu , Venkatesh Rajagopalan , Sachin Srivastava , Mayank Lalan
IPC: F01D5/12
CPC classification number: F01D11/14 , F01D11/20 , F01D17/02 , F01D21/003 , F01D21/04 , F01D21/045 , F01D21/10 , F01D21/14
Abstract: Systems and methods for blade health monitoring are provided. According to one embodiment of the disclosure, a system may include a feature extraction module and an anomaly detection module in communication with the extraction module. The feature extraction module may be configured to continuously receive blade passing signal data associated with clearance of a blade and pre-process the blade passing signal data. Blade clearance feature data may be extracted from the blade passing signal data prior to transmission to the anomaly detection module. The anomaly detection module may be configured to normalize the blade clearance feature data received from the extraction module, analyze the blade clearance feature data to detect a shift in the clearance of the blade, and determine an abnormality of the blade based on the shift exceeding a predetermined shift threshold.
Abstract translation: 提供了叶片健康监测的系统和方法。 根据本公开的一个实施例，系统可以包括与提取模块通信的特征提取模块和异常检测模块。 特征提取模块可以被配置为连续接收与叶片的间隙相关联的叶片通过信号数据，并且预处理叶片通过信号数据。 刀片间隙特征数据可以在传输到异常检测模块之前从刀片通过信号数据中提取。 异常检测模块可以被配置为对从提取模块接收到的叶片间隙特征数据进行归一化，分析叶片间隙特征数据以检测叶片的间隙中的移动，并且基于超过a的移位来确定叶片的异常 预定移位阈值。
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