1,279 research outputs found
Integration of a failure monitoring within a hybrid dynamic simulation environment
The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering
Model based fault diagnosis for hybrid systems : application on chemical processes
The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering
A review of applications of fuzzy sets to safety and reliability engineering
Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering
Petri Nets for Smart Grids: The Story So Far
Since the energy domain is in a transformative shift towards sustainability,
the integration of new technologies and smart systems into traditional power
grids has emerged. As an effective approach, Petri Nets (PN) have been applied
to model and analyze the complex dynamics in Smart Grid (SG) environments.
However, we are currently missing an overview of types of PNs applied to
different areas and problems related to SGs. Therefore, this paper proposes
four fundamental research questions related to the application areas of PNs in
SGs, PNs types, aspects modelled by PNs in the identified areas, and the
validation methods in the evaluation. The answers to the research questions are
derived from a comprehensive and interdisciplinary literature analysis. The
results capture a valuable overview of PNs applications in the global energy
landscape and can offer indications for future research directions
Power system fault analysis based on intelligent techniques and intelligent electronic device data
This dissertation has focused on automated power system fault analysis. New
contributions to fault section estimation, protection system performance evaluation
and power system/protection system interactive simulation have been achieved. Intelligent techniques including expert systems, fuzzy logic and Petri-nets, as well as
data from remote terminal units (RTUs) of supervisory control and data acquisition
(SCADA) systems, and digital protective relays have been explored and utilized to
fufill the objectives.
The task of fault section estimation is difficult when multiple faults, failures
of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets
approach has been proposed to tackle the complexities. In this approach, the fuzzy
reasoning starting from protection system status data and ending with estimation of
faulted power system section is formulated by Petri-nets. The reasoning process is
implemented by matrix operations. Data from RTUs of SCADA systems and digital
protective relays are used as inputs. Experiential tests have shown that the proposed
approach is able to perform accurate fault section estimation under complex scenarios.
The evaluation of protection system performance involves issues of data acquisition, prediction of expected operations, identification of unexpected operations and
diagnosis of the reasons for unexpected operations. An automated protection system performance evaluation application has been developed to accomplish all the tasks. The application automatically retrieves relay files, processes relay file data,
and performs rule-based analysis. Forward chaining reasoning is used for prediction
of expected protection operation while backward chaining reasoning is used for diagnosis of unexpected protection operations. Lab tests have shown that the developed
application has successfully performed relay performance analysis.
The challenge of power system/protection system interactive simulation lies in
modeling of sophisticated protection systems and interfacing the protection system
model and power system network model seamlessly. An approach which utilizes the
"compiled foreign model" mechanism of ATP MODELS language is proposed to model
multifunctional digital protective relays in C++ language and seamlessly interface
them to the power system network model. The developed simulation environment
has been successfully used for the studies of fault section estimation and protection
system performance evaluation
Supervisory Control Systems: Theory and Industrial Applications
Hybrid control system is an exciting field of research where it contains two distinct types of systems: one with continuous dynamics continuous variable dynamic system and the other with discrete dynamics discrete event dynamic system, that interact with each other. The research in the area of hybrid control can be categorized into two areas: one deals with the conventional control systems, and the other deals with the decision making systems. The former addresses the control functions at the low level (field level). The latter addresses the modeling, analysis, and design at the higher level found in the supervision, coordination and management levels. The study of hybrid systems is central in designing intelligent hybrid control systems with high degree of autonomy and it is essential in designing discrete event supervisory controllers for continuous systems
Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review
YesSystem safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches
are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include,
but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event
Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically
make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive
and accurate analysis of complex systems, different characteristics such as functional dependencies among
components, temporal behaviour of systems, multiple failure modes/states for components/systems, and
uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical
approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity
in risk assessment applications due to their flexible structure and capability of incorporating most of the
above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis.
Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic
behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This
paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability
and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over
other classical approaches, and relative strengths and weaknesses in different practical application scenarios.This work was funded by the DEIS H2020 project (Grant Agreement 732242)
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