公开(公告)号：US20220092428A1

公开(公告)日：2022-03-24

申请号：US17312278

申请日：2020-09-28

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Ximing SUN ,  Fuxiang QUAN ,  Hongyang ZHAO ,  Yanhua MA ,  Pan QIN

IPC: G06N3/08 ,  G06N3/04

Abstract: The present invention relates to a prediction method for stall and surge of an axial compressor based on deep learning. The method comprises the following steps: firstly, preprocessing data with stall and surge of an aeroengine, and partitioning a test data set and a training data set from experimental data. Secondly, constructing an LR branch network module, a WaveNet branch network module and a LR-WaveNet prediction model in sequence. Finally, conducting real-time prediction on the test data: preprocessing test set data in the same manner, and adjusting data dimension according to input requirements of the LR-WaveNet prediction model; giving surge prediction probabilities of all samples by means of the LR-WaveNet prediction model according to time sequence; and giving the probability of surge that data with noise points changes over time by means of the LR-WaveNet prediction model, to test the anti-interference performance of the model.

公开(公告)号：US20220372891A1

公开(公告)日：2022-11-24

申请号：US17606180

申请日：2021-01-14

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Ximing SUN ,  Qi TANG ,  Hongyang ZHAO ,  Fuxiang QUAN ,  Ziyao DING ,  Di GUO

IPC: F01D21/00 ,  G06F30/28

Abstract: A method for stability analysis of a combustion chamber of a gas turbine engine based on image sequence analysis belongs to the field of fault prediction and health management of aeroengine. Firstly, flow field data inside a combustion chamber of a gas turbine engine is acquired. Secondly, flow field images of the combustion chamber are preprocessed to respectively obtain a discrimination model data set and a prediction model data set. Then, a 3DWaveNet model is constructed as a generation network of a prediction model. A discrimination network of the module is constructed. The generation network and the discrimination network are combined to form the prediction model. Finally, a discrimination model is constructed according to the discrimination model data set; the training set in the discrimination model data set is used for training, and the test set is used for assessment.

公开(公告)号：US20210129981A1

公开(公告)日：2021-05-06

申请号：US16769482

申请日：2019-04-26

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Ximing SUN ,  Hongyang ZHAO ,  Zhuocheng JIANG

IPC: B64C29/00 ,  B64C27/26

Abstract: A vehicle capable of taking off and landing vertically and operating in water, land, air and submarine environments includes a fuselage, two main wings, ailerons, a vertical tail, a rudder, a horizontal tail, elevators, a propeller, rotor wings, rotor wing supports, etc. The vehicle has the advantages of adaptability to various environments, good concealment and strong survivability. Compared with a traditional unmanned rotorcraft, the vehicle has longer endurance time and larger load. Compared with a fixed wing UAV, the vertical take-off and landing function makes the work more convenient. Compared with unmanned diving equipment, the vehicle is applicable to richer environments, and can complete designated missions in air, land, water and submarine environments. Compared with a tilt rotor UAV in water, land, air and submarine environments, the vehicle is rapider in switching of various modes and is higher in stability.