Sun Heng
Research Subjects
Research Interests
Sun Heng has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
- Huajie Qu
Electro Mechanic Engineering College, Beijing Polytechnic University
1 shared publication - Mengdi Shi
Beijing Polytechnic, China
1 shared publication
Latest Publications
- Open Access
- 24 May 2024
- Published by Association for Computing Machinery (ACM)
- p. 74-80
Application of Equipment Monitoring and Fault Diagnosis System Based on Industrial Internet
This paper introduces the application of equipment monitoring and fault diagnosis system of industrial Internet. This system is mainly based on signals from rotating mechanical equipment (such as bearings and gears) to complete the design work of the MoniVIEW equipment operation status fault diagnosis system. This system not only includes algorithms such as statistical index analysis, time-domain analysis, frequency-domain analysis, and short-time Fourier transform in time-frequency analysis, but also includes relatively new adaptive time-frequency analysis methods such as EMD, ITD, and LCD. In mechanical rotating equipment, non-stationary and complex vibration signals are often encountered. Conventional fault diagnosis and analysis algorithms sometimes cannot determine the cause of faults. Introducing adaptive time-frequency analysis methods not only facilitates user fault identification and analysis, but also directly achieves data analysis and processing of vibration signals.
- 24 May 2024
- Published by Association for Computing Machinery (ACM)
- p. 74-80
Open AccessApplication of Equipment Monitoring and Fault Diagnosis System Based on Industrial Internet
This paper introduces the application of equipment monitoring and fault diagnosis system of industrial Internet. This system is mainly based on signals from rotating mechanical equipment (such as bearings and gears) to complete the design work of the MoniVIEW equipment operation status fault diagnosis system. This system not only includes algorithms such as statistical index analysis, time-domain analysis, frequency-domain analysis, and short-time Fourier transform in time-frequency analysis, but also includes relatively new adaptive time-frequency analysis methods such as EMD, ITD, and LCD. In mechanical rotating equipment, non-stationary and complex vibration signals are often encountered. Conventional fault diagnosis and analysis algorithms sometimes cannot determine the cause of faults. Introducing adaptive time-frequency analysis methods not only facilitates user fault identification and analysis, but also directly achieves data analysis and processing of vibration signals.