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1.发明授权公开(公告)号：US11892003B2
公开(公告)日：2024-02-06
申请号：US16294358
申请日：2019-03-06
发明人： James Ryan Reepmeyer , Johan Michael Reimann , Gagan Adibhatla , Evin Nathaniel Barber , Stefan Joseph Cafaro , Rahim Panjwani , Frederick John Menditto, III , Aaron James Schmitz , Suchot Kongsomboonvech , Richard Anthony Zelinski
CPC分类号： F04D27/001 , F04D27/02 , F04D27/0207 , F04D27/0246 , F04D27/0253 , G01M15/14 , G05B13/027 , G06N3/04 , G06N3/044 , G06N3/045 , F05D2270/101 , F05D2270/709
摘要： A control system for active stability management of a compressor element of a turbine engine is provided. In one example aspect, the control system includes one or more computing devices configured to receive data indicative of an operating characteristic associated with the compressor element. For instance, the data can be received from a high frequency sensor operable to sense pressure at the compressor element. The computing devices are also configured to determine, by a machine-learned model, a stall margin remaining of the compressor element based at least in part on the received data. The machine-learned model is trained to recognize certain characteristics of the received data and associate the characteristics with a stall margin remaining of the compressor element. The computing devices are also configured to cause adjustment of one or more engine systems based at least in part on the determined stall margin remaining.
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2.发明申请公开(公告)号：US20200284265A1
公开(公告)日：2020-09-10
申请号：US16294358
申请日：2019-03-06
发明人： James Ryan Reepmeyer , Johan Michael Reimann , Gagan Adibhatla , Evin Nathaniel Barber , Stefan Joseph Cafaro , Rahim Panjwani , Frederick John Menditto, III , Aaron James Schmitz , Suchot Kongsomboonvech , Richard Anthony Zelinski
摘要： A control system for active stability management of a compressor element of a turbine engine is provided. In one example aspect, the control system includes one or more computing devices configured to receive data indicative of an operating characteristic associated with the compressor element. For instance, the data can be received from a high frequency sensor operable to sense pressure at the compressor element. The computing devices are also configured to determine, by a machine-learned model, a stall margin remaining of the compressor element based at least in part on the received data. The machine-learned model is trained to recognize certain characteristics of the received data and associate the characteristics with a stall margin remaining of the compressor element. The computing devices are also configured to cause adjustment of one or more engine systems based at least in part on the determined stall margin remaining.
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