公开(公告)号：US20230410012A1

公开(公告)日：2023-12-21

申请号：US18091663

申请日：2022-12-30

Applicant: Qingdao University of Technology

Inventor： Liming Zhang ,  Zhongyuan Liu ,  Yu Cong ,  Xiaoshan Wang ,  Zaiquan Wang ,  Fanxiu Chen ,  Jinfeng Cao

IPC: G06Q10/0635 ,  G06Q50/26 ,  G06F18/25 ,  G06N3/0442 ,  G06N3/08

CPC classification number: G06Q10/0635 ,  G06Q50/265 ,  G06F18/251 ,  G06N3/0442 ,  G06N3/08

Abstract: A project disaster warning method and system based on collaborative fusion of multi-physical field monitoring data is provided. The method includes: acquiring and preprocessing multi-sensor real-time monitoring data of potentially dangerous parts of a project structure; normalizing multi-physical field monitoring time sequence data to construct a normalized sample matrix; analyzing sensitivities of various physical field monitoring indicators to a safety state of a project by using a multivariate statistical method; guiding initialization training of a LSTM network according to the sensitivities, and obtaining output results of the LSTM network; obtaining basic probability assignments of various warning levels after fusion according to an improved D-S evidence theory based on Chebyshev distance, with the output results of the LSTM network as evidence inputs; determining disaster danger levels of the potentially dangerous parts of the project structure using a basic probability assignment-based decision method.

公开(公告)号：US12123292B1

公开(公告)日：2024-10-22

申请号：US18606428

申请日：2024-03-15

Applicant: QINGDAO UNIVERSITY OF TECHNOLOGY ,  CHINA UNIVERSITY OF PETROLEUM (EAST CHINA)

Inventor： Kai Zhang ,  Guojing Xin ,  Zhongzheng Wang ,  Piyang Liu ,  Liming Zhang ,  Xia Yan ,  Huaqing Zhang ,  Zifeng Sun ,  Feng Jia

IPC: E21B43/16 ,  G06F30/28 ,  G06N3/092

CPC classification number: E21B43/16 ,  G06F30/28 ,  G06N3/092 ,  E21B2200/20

Abstract: A differentiated real-time injection-production optimization adjustment method of an intelligent injection-production linkage device belongs to the field of oil reservoir injection-production technologies. The method includes: initializing networks; building an injection-production environment model; by an agent, reading an initial state of an injection-production environment; writing a file by an injection-production policy network; obtaining state data of the moment t+1; reading a next state and an economic net present value within the time step; assigning the next state to the current state until a to-be-optimized production period is completed; by batch training on the model, updating a parameter of the environment agent model; updating a parameter of the action evaluation network and a parameter of the injection-production policy network; repeating the above steps until an optimal model is obtained; based on the stored optimal model, linking the intelligent injection-production device to obtain state information of the oil reservoir.

公开(公告)号：US20240410870A1

公开(公告)日：2024-12-12

申请号：US18595510

申请日：2024-03-05

Applicant: Qingdao University of Technology

Inventor： Liming Zhang ,  Tao Lan ,  Faxing Zhang ,  Zhongyuan Liu ,  Juan Lan

IPC: G01N33/2045 ,  G06N5/01 ,  G06N5/048

Abstract: The present disclosure relates to a multi-factor coupling cooperative early warning method and system for fatigue crack propagation of a steel structure. The multi-factor coupling cooperative early warning method includes: obtaining multi-physical field monitoring data of a dangerous source distribution point of a steel structure project, and obtaining a monitoring time series data set; establishing an intuitionistic fuzzy matrix of the monitoring time series data set; obtaining uncertainties of indexes by using a grey relation coefficient between the monitoring indexes of physical fields; taking obtained uncertainties as basic probability assignments of evidences; preprocessing the evidences through weighed averaging, and obtaining corrected basic probability assignments; obtaining basic probability assignments of fatigue crack propagation of the steel structure at different development stages; and determining a fatigue crack propagation grade of the dangerous source distribution point of the steel structure project through the basis probability assignment.