Mechanical engineering Model-based and data-driven fault diagnosis for wind turbine hydraulic pitching system THE UNIVERSITY OF WISCONSIN - MILWAUKEE Yaoyu Li WuXinThe objective of this dissertation research is to investigate both model-based and data-driven fault diagnosis and prognosis approaches for ...
Example implementations described herein are directed to a system and software for integrating model-based and data-driven diagnosis solutions, automatically generating residuals in dynamic systems and using these residuals for fault detection and isolation (FDI), and automatic fault identification. Through...
model-basedBP neural networkAiming at the current popular fault methods' disadvantages on diagnosing faults existing in electromechanical actuator, this paper presents a novel hybrid fault diagnosis approach combining Model-Based and Data-Driven. Firstly, the extended Kaiman filter is used...
Therefore, it seems that more than one approach is usually required for developing a complete robust fault detection and diagnosis tool. In this paper, the features of different model-based and data-driven approaches are investigated separately as well as the existing works that attempted to ...
This paper discusses a hybrid model-based, data-driven and knowledge-based integrated diagnosis and prognosis framework, and applies it to automotive (suspension and battery systems) and on-board electronic systems. 展开 关键词: automotive electronics condition monitoring fault diagnosis automotive systems...
Automatic data-driven real-time segmentation and recognition of surgical workflow AdaBoostHidden semi-Markov ModelPurpose With the intention of extending the perception and action of surgical staff inside the operating room, the medical ... O Dergachyova,D Bouget,A Huaulmé,... - 《International...
Although traditional data-driven methods achieve automatic diagnosis in fault identification process based on machine learning algorithms such as supporting vector machine (SVM), artificial neural network (ANN) and k-nearest neighbor (KNN) [7], feature extraction is still manual. Depending on advanced...
On the other hand, purely data-driven approaches that are model-agnostic are becoming increasingly popular as datasets become abundant and the power of modern deep learning pipelines increases. Deep neural networks (DNNs) use generic architectures which learn to operate from data, and demonstrate ...
Intelligent fault diagnosis of rolling bearing under unbalanced samples based on simulation data fusion With the rapid development of intelligent manufacturing, data-driven deep-learning techniques have been widely used in bearing fault diagnosis. However, th... S Mei,T Xu,Q Zhang,... - IOP Publi...
Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the tra... L Fang,C Shen,Q He,... - 《Se...