ARTÍCULO
TITULO

Fault Recognition Method Based on Independent Component Analysis and Hidden Markov Model

Zhinong Li    
Jie Han    
Junjie Sun    
Yongyong He    
and Fulei Chu    

Resumen

No disponible

 Artículos similares

       
 
Pablo Sarabia, Alvaro Araujo, Luis Antonio Sarabia and María de la Cruz Ortiz    
Surface electromyography (sEMG) plays a crucial role in several applications, such as for prosthetic controls, human?machine interfaces (HMI), rehabilitation, and disease diagnosis. These applications are usually occurring in real-time, so the classifier... ver más
Revista: Algorithms

 
Umberto Albertin, Giuseppe Pedone, Matilde Brossa, Giovanni Squillero and Marcello Chiaberge    
New technologies are developed inside today?s companies with the ascent of Industry 4.0 paradigm; Artificial Intelligence applied to Predictive Maintenance is one of these, helping factories automate their systems in detecting anomalies. The deviation of... ver más
Revista: Algorithms

 
Yong Zhu, Qingyi Wu, Shengnan Tang, Boo Cheong Khoo and Zhengxi Chang    
As the modern industry rapidly advances toward digitalization, networking, and intelligence, intelligent fault diagnosis technology has become a necessary measure to ensure the safe and stable operation of mechanical equipment and effectively avoid major... ver más

 
Zitong Yan, Hongmei Liu, Laifa Tao, Jian Ma and Yujie Cheng    
To address the limited data problem in real-world fault diagnosis, previous studies have primarily focused on semi-supervised learning and transfer learning methods. However, these approaches often struggle to obtain the necessary data, failing to fully ... ver más
Revista: Aerospace

 
Hong Je-Gal, Seung-Jin Lee, Jeong-Hyun Yoon, Hyun-Suk Lee, Jung-Hee Yang and Sewon Kim    
Ensuring operational reliability in machinery requires accurate fault detection. While time-domain vibration pulsation signals are intuitive for pattern recognition and feature extraction, downsampling can reduce analytical complexity, but may result in ... ver más