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A method for generating process topology-based causal models

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dc.contributor Aalto University en
dc.contributor Aalto-yliopisto fi
dc.contributor.advisor Kortela, Jukka
dc.contributor.advisor Tikkala, Vesa-Matti
dc.contributor.author Sun, Qiang
dc.date.accessioned 2013-10-16T08:05:28Z
dc.date.available 2013-10-16T08:05:28Z
dc.date.issued 2013-09-10
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/11136
dc.description.abstract Process disturbances always spread along the connected equipment in a plant and are detected in many places. In order to identify the root disturbance, many data-based fault detection and diagnosis (FDD) methods have been developed in recent years. However, most of these methods can generate spurious solutions. Several authors have observed that FDD methods are enhanced if topology information about the causal relationships of a process is considered as well. Generally, this topology information is manually created by using the process knowledge. However, such a way is always time-consuming and the result is imprecise. Hence, there is a requirement for an automated generation of effective topology-based causal models. This thesis developed a thorough approach to implement two types of causal models, i.e., a connectivity matrix and a causal digraph, based on piping and instrumentation diagrams (P&IDs). As the core development tools, AutoCAD P&ID and object-oriented programming (OOP) of MATLAB were used. The development included three procedures: generate topology data, define the class for generating causal models, and obtain the causal models by instantiating the class with the topology data. In conclusion, it appears that both the connectivity matrix and causal digraph manifest the internal relationship between different process components caused by material flows and signal flows in a clear way. Therefore, these models can play an important role in the research associated with the FDD methods. en
dc.format.extent 81+7
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title A method for generating process topology-based causal models en
dc.type G2 Pro gradu, diplomityö en
dc.contributor.school Kemian tekniikan korkeakoulu fi
dc.subject.keyword topology-based causal models en
dc.subject.keyword digraph en
dc.subject.keyword connectivity matrix en
dc.subject.keyword fault detection and diagnosis (FDD) en
dc.subject.keyword XML en
dc.identifier.urn URN:NBN:fi:aalto-201310167710
dc.programme.major Process Systems Engineering fi
dc.programme.mcode KE3004 fi
dc.type.ontasot Diplomityö fi
dc.type.ontasot Master's thesis en
dc.contributor.supervisor Jämsä-Jounela, Sirkka-Liisa
dc.programme Master's Programme in Process Systems Engineering fi
dc.location PK fi
local.aalto.openaccess yes
local.aalto.digifolder Aalto_69066
dc.rights.accesslevel openAccess
local.aalto.idinssi 48094
dc.type.publication masterThesis
dc.type.okm G2 Pro gradu, diplomityö

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