公开(公告)号：US20240345572A1

公开(公告)日：2024-10-17

申请号：US18580364

申请日：2022-07-11

Applicant: ROLLS-ROYCE PLC

Inventor： Kee Khoon LEE ,  Henry KASIM ,  Terence HUNG ,  Jair Weigui ZHOU ,  Rajendra Prasad SIRIGINA

IPC: G05B23/02

CPC classification number: G05B23/0281 ,  G05B23/0272

Abstract: A computer-implemented method including: receiving a first data set including a plurality of values for a plurality of features; identifying at least a first feature of the first data set that is non-redundant and at least a second feature of the first data set that is redundant; identifying one or more clusters of features in the plurality of features of the first data set, a first cluster of the one or more clusters including at least the first feature and the second feature; and controlling a display to display the first feature and one or more redundant features from the first cluster, the displayed one or more redundant features from the first cluster including the second feature.

公开(公告)号：US20240362193A1

公开(公告)日：2024-10-31

申请号：US18291117

申请日：2022-07-11

Applicant: ROLLS-ROYCE plc

Inventor： Kee Khoon LEE ,  Henry KASIM ,  Terence HUNG ,  Airil Seet BIN AZRY SEET ,  Yirui FENG ,  Jonathan TAY ,  Albert PHANG ,  Piyush TAGADE

IPC: G06F16/215 ,  G06F16/28

CPC classification number: G06F16/215 ,  G06F16/285

Abstract: A computer-implemented method including: receiving a first data set including a plurality of values for a plurality of features; removing one or more features and associated values from the first data set to generate a second data set; determining feature importance of at least a subset of the features of the second data set using multiple-evaluation criteria; and performing an action using at least one feature of the second data set and the determined feature importance.

公开(公告)号：US20180268257A1

公开(公告)日：2018-09-20

申请号：US15925010

申请日：2018-03-19

Applicant: ROLLS-ROYCE plc

Inventor： Rux Xu REN ,  Terence HUNG ,  Kay Chen TAN

IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06T7/00

CPC classification number: G06K9/6256 ,  G06N3/04 ,  G06N3/084 ,  G06T7/0004 ,  G06T7/001 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30164

Abstract: A method is provided of forming a neural network for detecting surface defects in aircraft engine components. The method includes: providing (i) a pre-trained deep learning network and (ii) a learning machine network; providing a set of pixelated training images of aircraft engine components exhibiting examples of different classes of surface defect; training the trainable weights of the learning machine network on the set of training images.