Experimental and Numerical Based Defect Detection in a Model Combustion Chamber through Machine Learning

被引：0
|
作者：
von der Haar, Henrik [1 ]
Ignatidis, Panagiotis [1 ]
Dinkelacker, Friedrich [1 ]
机构：
[1] Institute of Technical Combustion, Leibniz Universität Hannover, An der Universität 1, Garbsen, 30823, Germany
来源：
International Journal of Gas Turbine, Propulsion and Power Systems | 2021年 / 12卷 / 04期
关键词：
Automatic defect detections - Combustion pro-cess - Combustion state - Defect detection - Down time - Internal flows - Machine-learning - Resource management - Species distributions - Support vector machines algorithms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：1 / 9
相关论文
共 50 条
  • [31] Machine Vision-based Defect Detection Using Deep Learning Algorithm
    Kim, Dae-Hyun
    Boo, Seung Bin
    Hong, Hyeon Cheol
    Yeo, Won Gu
    Lee, Nam Yong
    JOURNAL OF THE KOREAN SOCIETY FOR NONDESTRUCTIVE TESTING, 2020, 40 (01) : 47 - 52
  • [32] Visual-based defect detection for product classification: a machine learning approach
    Saragaglia, A.
    Calafat, N.
    INFRARED TECHNOLOGY AND APPLICATIONS XLVII, 2021, 11741
  • [33] Machine Learning based DDos Detection Through NetFlow Analysis
    Hou, Jiangpan
    Fu, Peipei
    Cao, Zigang
    Xu, Anlin
    2018 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM 2018), 2018, : 565 - 570
  • [34] Automatic defect detection for virtual network perceptual data based on machine learning
    Fang W.
    Huang Y.
    Ma X.-Q.
    Huang, Yi (fanjigong8975@163.com), 1844, Editorial Board of Jilin University (50): : 1844 - 1849
  • [35] Resilient machine learning for steel surface defect detection based on lightweight convolution
    Liu, Li-Juan
    Zhang, Yu
    Karimi, Hamid Reza
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 134 (9-10): : 4639 - 4650
  • [36] Machine learning based approach for automatic defect detection and classification in adhesive joints
    Smagulova, Damira
    Samaitis, Vykintas
    Jasiuniene, Elena
    NDT & E INTERNATIONAL, 2024, 148
  • [37] Review on Machine Learning-based Defect Detection of Shield Tunnel Lining
    Kuang, Guixing
    Li, Bixiong
    Mo, Site
    Hu, Xiangxin
    Li, Lianghui
    PERIODICA POLYTECHNICA-CIVIL ENGINEERING, 2022, 66 (03): : 943 - 957
  • [38] Enhancing Machine Learning Based Malware Detection Model by Reinforcement Learning
    Wu, Cangshuai
    Shi, Jiangyong
    Yang, Yuexiang
    Li, Wenhua
    ICCNS 2018: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMMUNICATION AND NETWORK SECURITY, 2018, : 74 - 78
  • [39] The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning
    Porcu, Emilio
    Bevilacqua, Moreno
    Schaback, Robert
    Oates, Chris J.
    STATISTICAL SCIENCE, 2024, 39 (03) : 469 - 492
  • [40] Rapid detection of defect structures in graphene by the machine learning
    Wu, Youtao
    Li, Lianxin
    Wang, Bei
    Zhu, Zhongzhong
    Gao, Tinghong
    Xie, Quan
    Chen, Qian
    Xiao, Qingquan
    MODERN PHYSICS LETTERS B, 2022, 36 (15):
12345