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公开(公告)号:US11436395B2
公开(公告)日:2022-09-06
申请号:US16629752
申请日:2018-06-27
Applicant: Dalian University of Technology
Inventor: Shuo Zhang , Xiaoyu Sun , Jibang Li , Ximing Sun
Abstract: A method for prediction of key performance parameters of an aero-engine transition state acceleration process based on space reconstruction. Aero-engine transition state acceleration process test data provided by a research institute is used for establishing a training dataset and a testing dataset; dimension increase is conducted on the datasets based on the data space reconstruction of an auto-encoder; model parameters optimization is conducted by population optimization algorithms which is represented by particle swarm algorithm; and random forest regression algorithm performing well on high-dimensional data is used for carrying out regression on transition state performance parameters, which realizes effective real-time prediction from the perspective of engineering application.
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公开(公告)号:US11333575B2
公开(公告)日:2022-05-17
申请号:US16629423
申请日:2018-03-01
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor: Shuo Zhang , Jibang Li , Ximing Sun , Tao Sun
IPC: G01M13/045 , G06K9/62 , G06N20/20 , G06F17/14 , G06K9/00
Abstract: The present invention belongs to the technical field of fault diagnosis of aero-engines, and provides a method for fault diagnosis of an aero-engine rolling bearing based on random forest of power spectrum entropy. Aiming at the above-mentioned defects existing in the prior art, a method for fault diagnosis of an aero-engine rolling bearing based on random forest is provided, wherein test measured data for an aero-engine rolling bearing provided by a research institute are used for establishing a training dataset and a test dataset first; and based on an idea of fault feature extraction, time domain statistical analysis and frequency domain analysis are conducted on original collection data by adopting wavelet analysis; thereby realizing effective fault diagnosis from the perspective of engineering application.
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公开(公告)号:US11124317B2
公开(公告)日:2021-09-21
申请号:US16629513
申请日:2018-01-26
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor: Shuo Zhang , Jibang Li , Ximing Sun , Min Liu
Abstract: A method for prediction of key performance parameters of an aero-engine in transition condition. Bench test data for an aero-engine in transition condition provided by a research institute is used for establishing a training dataset and a testing dataset first; parameter combination is used for predicting and analyzing engine exhaust temperature based on the idea of information fusion; and the method of rolling windows is used for rolling learning in order to predict the parameters such as low pressure rotor speed and exhaust temperature of an engine from the perspective of practical engineering application.
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