个人信息Personal Information
教授
博士生导师
硕士生导师
任职 : 工业装备数字孪生省重点实验室主任,大工碳中和研究院院长
性别:男
毕业院校:The Ohio State University
学位:博士
所在单位:能源与动力学院
学科:计算力学. 机械制造及其自动化
办公地点:能动学院508
联系方式:0411-84706279
电子邮箱:xiaomojiang2019@dlut.edu.cn
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能源物联网(电厂、LNG,综合能源)、物联技术、远程可靠性和性能监测、预测维护
Energy IoT (Gas Turbine, Steam Turbine, Combined Cycle, Coal, Nuclear etc.), AIoT, Monitoring & Diagnostics, Performance Modeling, Predictive Maintenance
大型旋转机械设备智慧运维(燃机、汽机、离心压缩机、风机等),燃机的压缩机、透平、燃烧炉等主要故障监测诊断,预测维护
Smart operation & maintenance for large turbo-machine, i.e.,gas turbine, steam turbine, centrifugal compressor, wind turbine; remote monitoring & diagnostics of key GT components, e.g., turbine, combustion, compressor; predictive maintenance
大数据分析,人工智能算法:小波信号处理、机器学习、神经元网络、贝叶斯推理、深度学习
Big data analytics, AI algorithms, e.g., wavelet signal processing, machine learning, neural networks, Bayesian inference, deep learning
不确定性下可靠性建模,模型定量验证,贝叶斯模型参数估计和验证,非线性结构等式建模
Stochastic modeling under uncertainties, quantitative model validation, Bayesian estimation, nonlinear structural equation modeling
- 鲁业明, 郭振洋, 张美娜, 姜孝谟, 王晓放.Flow-heat coupling analysis of the 1/4 symmetrical CAP1400 nuclear island loop based on the source term approach[J],Annals of Nuclear Energy,2024,211
- 刘昶军, 曹士铎, 漆超, 王晓放, 姜孝谟, Sui, Yongfeng, 刘海涛.A parallel and multi-scale probabilistic temporal convolutional neural networks for forecasting the key monitoring parameters of gas turbine[J],ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2024,138
- 韦曼曼, 刘祎阳, 葛新, 姜孝谟.A PHYSICS-INFORMED DEEP LEARNING APPROACH FOR HDGT COMPRESSOR PERFORMANCE SIMULATION[A],PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 12D,2024
- 刘祎阳, 韦曼曼, 葛新, 姜孝谟.RESEARCH ON PERFORMANCE DEGRADATION PREDICTION METHOD OF HEAVY-DUTY GAS TURBINE BASED ON DATA-PHYSICS FUSION UNDER UNCERTAINTY[A],PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 4,2024
- 惠怀宇, 陈荟泽, 张可欣, 姜孝谟.A WIND TURBINE POWER FORECASTING METHOD BASED ON MTGP TRANSFER LEARNING[A],PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 13,2024
- 陈荟泽, 张可欣, 姜孝谟, Hull, Huaiyu.A WIND SPEED FORECASTING METHOD USING A GAUSSIAN PROCESS REGRESSION MODEL CONSIDERING DATA UNCERTAINTY[A],PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 13,2024
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