Can I read Digital Twin-driven Fault Diagnosis Service of Rotating Machinery on EtoBox?

Digital Twin-driven Fault Diagnosis Service of Rotating Machinery by Jinjiang Wang; Yilin Li; Zuguang Huang; Qianzhe Qiao is a book available to read on EtoBox.

What is Digital Twin-driven Fault Diagnosis Service of Rotating Machinery about?

With the advent of Industry 4.0, smart manufacturing becomes more digital and productive, requiring equipment to be more flexible to adapt to emergencies. For long-term and reliable operation of equipment in a full life cycle process, not only intrinsically safe designs but also continuous condition monitoring is mandatory. The machinery in smart manufacturing is equipped with a large number of sensing and communication devices. Intelligent sensing and information fusion are the basis of machine condition monitoring. A lot of research works have been conducted on the continuous signal analysis of equipment under multiple working conditions. Emerging computer technologies, such as big data, industrial Internet of things (IIOT), cloud computing, etc., have provided the foundation for applying data-driven methods to machine fault diagnosis with improved efficiency. However, data-driven methods rely heavily on statistical models to determine the existence of faults and predict future operating conditions of machinery. Due to the various failure modes and the complex relationship between faults and system response, data-driven methods may not be able to accurately detect faulty status,

Author

Jinjiang Wang; Yilin Li; Zuguang Huang; Qianzhe Qiao

Published

2022

Language

EN