@article{
 title = {Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste},
 type = {article},
 year = {2012},
 keywords = {Bayesian Networks,Destruc*tion equipment,Health assessment,Health status,High-risk hazardous chemical wastes},
 pages = {192-201},
 volume = {16},
 websites = {http://www.sciencedirect.com/science/article/pii/S1878029612005658},
 id = {42ee5947-da27-3dba-9e58-0291cce06870},
 created = {2015-04-11T19:52:14.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.},
 bibtype = {article},
 author = {Zhang, Hongyuan and Zhang, Jing and Liu, Xuecheng and Yan, Guohui and Liu, Yanzhao},
 doi = {10.1016/j.proenv.2012.10.027},
 journal = {Procedia Environmental Sciences}
}

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