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    Stochastic configuration network based turbofan engine health parameter estimation method
    11.
    发明授权
    Stochastic configuration network based turbofan engine health parameter estimation method 有权

    公开(公告)号：US11022524B2

    公开(公告)日：2021-06-01

    申请号：US16967313

    申请日：2019-11-28

    Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

    Inventor： Yanhua Ma ,  Xian Du ,  Ximing Sun ,  Yuhu Wu ,  Yanlei Gao

    IPC: G01M15/05 ,  G06N3/04 ,  B64F5/60 ,  G05B23/02

    Abstract: A stochastic configuration network based turbofan engine health parameter estimation method is disclosed. The stochastic configuration network based turbofan engine health parameter estimation method designed by the present invention combines the model based Kalman filter algorithm and the data-driven based stochastic configuration network, i.e. using the output of the stochastic configuration network as the compensation of the Kalman filter algorithm, so as to take into account the estimated result of the Kalman filter and the estimated result of the stochastic configuration network and improve the estimation accuracy of the original Kalman filter algorithm when the measurable parameters of the turbofan engine are less than the health parameters to be estimated. In addition, the present invention effectively reduces the accuracy loss caused by the poor structure of the neural network through the stochastic configuration network, and improves the generalization ability of the network.

    Method of aero-engine on-line optimization and multivariable control based on model prediction
    12.
    发明授权
    Method of aero-engine on-line optimization and multivariable control based on model prediction 有权

    公开(公告)号：US11454177B2

    公开(公告)日：2022-09-27

    申请号：US16462519

    申请日：2018-06-15

    Applicant: Dalian University of Technology

    Inventor： Xian Du ,  Yanhua Ma ,  Ximing Sun ,  Zhimin Wang

    IPC: F02C9/00 ,  F02C9/28 ,  G05B17/02 ,  G06F17/16 ,  B64D31/06 ,  G06F30/15 ,  G06F111/10

    Abstract: A design method of aero-engine on-line optimization and multivariable control based on model prediction control realizes aero-engine multivariable control and on-line optimization according to thrust, rotational speed and other needs under the condition of meeting constraints. The first part is a prediction model acquisition layer that continuously establishes a small deviation linear model of an aero-engine near different steady state points based on the actual operating state of the aero-engine in each control cycle and external environment parameters and that supplies model parameters to a controller; and the second part is a control law decision-making layer which is a closed loop structure that consists of a model prediction controller and an external output feedback. The model prediction controller determines the output of the controller at next moment by solving a linear optimization problem according to an engine model in the current state, a control instruction and relevant constraints.

    Vehicle running status field model-based information transmission frequency optimization method in internet of vehicles
    13.
    发明授权
    Vehicle running status field model-based information transmission frequency optimization method in internet of vehicles 有权

    公开(公告)号：US11380144B2

    公开(公告)日：2022-07-05

    申请号：US17048362

    申请日：2020-07-02

    Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

    Inventor： Nan Ding ,  Ximing Sun ,  Di Wu ,  Weiguo Xia

    IPC: G01S13/58 ,  G07C5/00 ,  H04W4/40 ,  G01S13/50 ,  H04L101/622

    Abstract: A vehicle running status field model-based information transmission frequency optimization method in the Internet of Vehicles belongs to the technical field of network communications. The method establishes a running status field model according to the real-time running status of a road vehicle to describe the degree of risk of the vehicle, the degree of risk can be used to dynamically adjust the transmission frequency of safety-critical information, and the transmission frequency of non-safety-critical information is adjusted through the real-time transmission frequency of safety-critical information to achieve the purpose of improving the utilization ratio of link. The method establishes the running status field model of a moving vehicle, uses the risk intensity of the vehicle in the running status field to describe the current running risk of the vehicle, and takes account of different application scenarios, thereby having generality. In addition, the improved network resource optimization method can effectively improve the communication efficiency of heterogeneous networks, and dynamically adjust the transmission frequency of safety-critical information through the magnitude of the risk intensity to improve the utilization ratio of link.

    Method for fault diagnosis of aero-engine sensor and actuator based on LFT
    15.
    发明授权
    Method for fault diagnosis of aero-engine sensor and actuator based on LFT 有权

    公开(公告)号：US11203446B2

    公开(公告)日：2021-12-21

    申请号：US16604042

    申请日：2018-12-11

    Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

    Inventor： Yanhua Ma ,  Xian Du ,  Rui Wang ,  Min Liu ,  Ximing Sun

    IPC: B64F5/60

    Abstract: The present invention discloses a method for fault diagnosis of the sensors and actuators of an aero-engine based on LFT, and belongs to the field of fault diagnosis of aero-engines. The method comprises: establishing an aero-engine state space model using a combination of a small perturbation method and a linear fitting method; establishing an affine parameter-dependent linear-parameter-varying (LPV) model of the aero-engine based on the model; converting the LPV model of the aero-engine having perturbation signals and sensor and actuator fault signals into a linear fractional transformation (LFT) structure to obtain an synthesis framework of an LPV fault estimator; solving a set of linear matrix inequalities (LMIs) to obtain the solution conditions of the fault estimator; and designing the fault estimator in combination with the LFT structure to realize fault diagnosis of the sensors and actuators of an aero-engine.

    Simulink modeling method for mechanical hydraulic device of aeroengine fuel regulator
    16.
    发明授权
    Simulink modeling method for mechanical hydraulic device of aeroengine fuel regulator 有权

    公开(公告)号：US11002212B1

    公开(公告)日：2021-05-11

    申请号：US16764304

    申请日：2019-03-15

    Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

    Inventor： Ximing Sun ,  Xian Du ,  Rui Wang ,  Yanhua Ma ,  Xinyue Wang

    IPC: F02D41/20 ,  F02D41/22 ,  F02D41/28 ,  F02D41/18

    Abstract: A Simulink modeling method for a mechanical hydraulic device of an aeroengine fuel regulator is proposed. The Simulink modeling method can implement high precision simulation of a mechanical hydraulic device of an engine fuel conditioning system, and greatly increase the simulation speed as compared with the existing modeling simulation in AMESim; solve the problem of a double-layered nested algebraic loop occurring when the mechanical hydraulic device is modeled in Simulink, and improve the simulation precision of the system. In addition, because of having certain universality, the resolving method for a double-layered nested algebraic loop can be generalized to resolve other types of algebraic loops. Meanwhile, the parameters of the simulation model provided by the present invention can be conveniently modified, and can provide a reference for modeling simulation of mechanical and hydraulic devices of engine fuel conditioning systems of other types.

    Prediction method for stall and surge of axial compressor based on deep learning
    17.
    发明授权
    Prediction method for stall and surge of axial compressor based on deep learning 有权

    公开(公告)号：US12288164B2

    公开(公告)日：2025-04-29

    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: G06N3/084 ,  G06N3/045

    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.

    Speed control method for permanent magnet synchronous motor considering current saturation and disturbance suppression
    19.
    发明授权
    Speed control method for permanent magnet synchronous motor considering current saturation and disturbance suppression 有权

    公开(公告)号：US11695358B2

    公开(公告)日：2023-07-04

    申请号：US17431326

    申请日：2020-10-27

    Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

    Inventor： Ximing Sun ,  Jianyi Zhang

    IPC: H02P21/00 ,  H02P21/13 ,  H02P21/18 ,  H02P21/22

    CPC classification number: H02P21/13 ,  H02P21/18 ,  H02P21/22

    Abstract: A speed control method for a permanent magnet synchronous motor considering current saturation and disturbance suppression aims to effectively ensure that a current of the motor is always within a given range to avoid the problem of control performance reduction caused by the fact that the current gets into a saturation state, ensure the safety of a system, do not need to use unavailable state variables such as motor acceleration and the like, effectively estimate and compensate disturbances including parameters uncertainty and unknown load torque disturbance existing in a permanent magnet synchronous motor system, and rapidly and accurately control a speed of the motor finally. There is no need to configure a plurality of sensors in practical industrial application, so system building costs can be reduced on the one hand, and the stability of the system can be improved on the other hand.

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