摘要
A soft sensing strategy based on neural network is proposed for product quality of FCCU main fractionator.From the analysis of the process mechanism and the use of operating data,a neural network soft sensing model （static） was developed for the end point of naphtha.A dynamic error correction ele ment is supplemented.Long-time running shows that it can substitute conventional process analyzer and no measurement delay times is expected.
A soft sensing strategy based on neural network is proposed for product quality of FCCU main fractionator.From the analysis of the process mechanism and the use of operating data,a neural network soft sensing model （static） was developed for the end point of naphtha.A dynamic error correction ele ment is supplemented.Long-time running shows that it can substitute conventional process analyzer and no measurement delay times is expected.
出处
《化工学报》
EI
CAS
CSCD
北大核心
1998年第2期251-255,共5页
CIESC Journal
