Ma Jin, Jiang Zhinong, "A New Feature Reduction Method and Its Application in the Reciprocating Engine Fault Diagnosis," WSEAS Transactions on Signal Processing, vol. 8, pp. -, 2012, DOI:
Ma Jin, Jiang Zhinong. A New Feature Reduction Method and Its Application in the Reciprocating Engine Fault Diagnosis.
WSEAS Transactions on Signal Processing. 2012;8:-.
WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 8, 2012
A New Feature Reduction Method and Its Application in the Reciprocating Engine Fault Diagnosis
Authors: ,
Abstract: On the basis of complicated fault feature of the reciprocating engine, a new feature reduction method based on the principle of the knowledge granularity to estimate the significance of symptomatic parameters is presented in this paper. The current problem that in the process of reducing and compressing the symptomatic parameters of fault diagnosis, the smallest symptom sets obtained is not always the smallest and optimal one, has been solved by the new method. By calculating on two instance of reciprocating engine knowledge set, the feature reduction method is effective.
Keywords:
symptomatic parameter, reciprocating engine, granularity entropy, fault diagnosis, fault feature, knowledge granularity
Pages: - WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 8, 2012DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
, Art. #
×
Citation Tools