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PCA9632TK2 其他数据使用手册 - NXP（恩智浦）
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PCA9632TK2数据手册
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Abstract: For traditional principle component analysis
(
PCA
)
, there was no generative model during monitoring
process, so that the monitoring indiceswere different and fault identification only can be carried off2line. While proba2
bilistic principle component analysis
(
PPCA
)
can overcome the above limitations. After probability functions of princi2
ple component and error were determined, the generated model can be constructed using the expectation and maximi2
zation
(
EM
)
algorithm. At last PCA and PPCA were compared in monitoring process of chemical separation and the
convenience and validity of PPCA were proved.
Key words:probabilistic principle component analysis; process monitoring; fault detection; fault identification
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上接第 6页
)
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Research on Co2design of Scheduling and Control for Network Control System s
ZHAO Wei2quan
1,2
,L IDi
1
(
1. School of Mechanical Engineering, South China University of Technology, Guangzhou 510640, China;
2. School of Software, Dongguan University of Technology, Dongguan 523808, China
)
Abstract:The relationship between scheduling and control in network control system was analyzed and the present
situation of the research on co2design of scheduling control was reviewed. Also the research advancement on the field
was summarized in dynamic and static aspects. At last a basic feedback control and scheduling frame was proposed.
Key words:network control system; scheduling; co2design
·11·
第 6期 杨沛武等. PCA和 PPCA在化工分离过程监控中的应用比较
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