The Experts below are selected from a list of 36 Experts worldwide ranked by ideXlab platform

H. Kanemoto - One of the best experts on this subject based on the ideXlab platform.

  • An adaptive State estimator for pulverizer control using moments of particle size distribution
    IEEE Transactions on Control Systems Technology, 2004
    Co-Authors: Y. Fukayama, K. Hirasawa, K. Shimohira, H. Kanemoto
    Abstract:

    An adaptive state estimator for pulverizers consisting of blending, grinding, and classifying processes has been developed in order to improve control of pulverized-Coal-fired power stations. Though Coal flow and non-Gaussian particle size distributions in the processes are mutually related, the estimator is able to efficiently simulate flow and normalized moments of the distributions with a state vector. The estimator also identifies Coal grindability for adapting to variation in Coal Characteristic in parallel with the process simulation. The accuracy of the adaptive estimation and the effectiveness in improving the load-swinging performance have been validated at a 1000-MWe class power station.

Y. Fukayama - One of the best experts on this subject based on the ideXlab platform.

  • An adaptive State estimator for pulverizer control using moments of particle size distribution
    IEEE Transactions on Control Systems Technology, 2004
    Co-Authors: Y. Fukayama, K. Hirasawa, K. Shimohira, H. Kanemoto
    Abstract:

    An adaptive state estimator for pulverizers consisting of blending, grinding, and classifying processes has been developed in order to improve control of pulverized-Coal-fired power stations. Though Coal flow and non-Gaussian particle size distributions in the processes are mutually related, the estimator is able to efficiently simulate flow and normalized moments of the distributions with a state vector. The estimator also identifies Coal grindability for adapting to variation in Coal Characteristic in parallel with the process simulation. The accuracy of the adaptive estimation and the effectiveness in improving the load-swinging performance have been validated at a 1000-MWe class power station.

K. Shimohira - One of the best experts on this subject based on the ideXlab platform.

  • An adaptive State estimator for pulverizer control using moments of particle size distribution
    IEEE Transactions on Control Systems Technology, 2004
    Co-Authors: Y. Fukayama, K. Hirasawa, K. Shimohira, H. Kanemoto
    Abstract:

    An adaptive state estimator for pulverizers consisting of blending, grinding, and classifying processes has been developed in order to improve control of pulverized-Coal-fired power stations. Though Coal flow and non-Gaussian particle size distributions in the processes are mutually related, the estimator is able to efficiently simulate flow and normalized moments of the distributions with a state vector. The estimator also identifies Coal grindability for adapting to variation in Coal Characteristic in parallel with the process simulation. The accuracy of the adaptive estimation and the effectiveness in improving the load-swinging performance have been validated at a 1000-MWe class power station.

K. Hirasawa - One of the best experts on this subject based on the ideXlab platform.

  • An adaptive State estimator for pulverizer control using moments of particle size distribution
    IEEE Transactions on Control Systems Technology, 2004
    Co-Authors: Y. Fukayama, K. Hirasawa, K. Shimohira, H. Kanemoto
    Abstract:

    An adaptive state estimator for pulverizers consisting of blending, grinding, and classifying processes has been developed in order to improve control of pulverized-Coal-fired power stations. Though Coal flow and non-Gaussian particle size distributions in the processes are mutually related, the estimator is able to efficiently simulate flow and normalized moments of the distributions with a state vector. The estimator also identifies Coal grindability for adapting to variation in Coal Characteristic in parallel with the process simulation. The accuracy of the adaptive estimation and the effectiveness in improving the load-swinging performance have been validated at a 1000-MWe class power station.

Cao Daiyong - One of the best experts on this subject based on the ideXlab platform.

  • metadata description method of Coal geology base on resource description framework
    Coal science and technology, 2008
    Co-Authors: Cao Daiyong
    Abstract:

    Resource Description Framework(RDF) is to promote the innovation and exchange of the Web metadata.In order to meet the share needs of the Coal geology information,with the comprehensive analysis of the Coal geology data and Coal geology metadate,and in combined with itself features of the RDF/XML,the paper provided the ideal and method to describe the Coal geology metadata based on RDF,which could make the Coal geology metadata exchange with other metadatas standard and could make easy to be extended.The Metadata description case application of the China Coal Characteristic database showed that the description method was feasible and effective.