Skip to main content
placeholder image

Identification of diesel engine cylinder pressure based on RBF network with time statistic average

Journal Article


Abstract


  • As the identification of diesel engine cylinder pressure is influenced by the low signal noise ratio and nonstationary of the cylinder cover vibration signal, it is proposed to preprocess the training sample with the denoising method of time statistic average before the training of radial basis function network and then to identify the testing sample. It is proved by practice that the signal noise ratios of the training samples are enhanced effectively by the method, and the identification of diesel engine cylinder pressure is characterized with quick computer rate and high precision.

Publication Date


  • 2003

Citation


  • Shen, X. Z., Shi, X. Z., Du, H. P., & Zhang, L. (2003). Identification of diesel engine cylinder pressure based on RBF network with time statistic average. Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 37(1), 97-99.

Scopus Eid


  • 2-s2.0-0038137518

Web Of Science Accession Number


Start Page


  • 97

End Page


  • 99

Volume


  • 37

Issue


  • 1

Abstract


  • As the identification of diesel engine cylinder pressure is influenced by the low signal noise ratio and nonstationary of the cylinder cover vibration signal, it is proposed to preprocess the training sample with the denoising method of time statistic average before the training of radial basis function network and then to identify the testing sample. It is proved by practice that the signal noise ratios of the training samples are enhanced effectively by the method, and the identification of diesel engine cylinder pressure is characterized with quick computer rate and high precision.

Publication Date


  • 2003

Citation


  • Shen, X. Z., Shi, X. Z., Du, H. P., & Zhang, L. (2003). Identification of diesel engine cylinder pressure based on RBF network with time statistic average. Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 37(1), 97-99.

Scopus Eid


  • 2-s2.0-0038137518

Web Of Science Accession Number


Start Page


  • 97

End Page


  • 99

Volume


  • 37

Issue


  • 1