Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis
- Southeast Univ., Nanjing (China). School of Instrument Science and Engineering
- Xi'an Jiaotong Univ. (China). School of Mechanical Engineering
- South China Univ. of Technology (SCUT), Guangzhou (China). School of Mechanical and Automotive Engineering
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issue is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 1168761
- Report Number(s):
- NREL/JA-5000-63143; MainId:18493; UUID:861a5016-1a5e-e411-b769-d89d67132a6d; MainAdminID:6971
- Journal Information:
- Mathematical Problems in Engineering, Vol. 2014, Issue 2014; ISSN 1024-123X
- Publisher:
- HindawiCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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