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

Process Mining of Programmable Logic Controllers: Input/Output Event Logs

This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data flow log to an event log suitable for Process Mining. In a third step, we propose a hybrid Petri net (PN) and neural network approach to approximate the logic of the actual underlying PLC program. We demonstrate the applicability of our proposed approach on a case study with three simulated scenarios

Modeling of Water Treatment Plant using Hybrid Petri Nets

Hybrid Petri nets are modeling framework for a system that contains discrete and continuous states. In this paper, we construct a model of water treatment plant using Hybrid Petri nets. We choose hybrid petri nets because the water treatment plant contains discrete and continuous parts. The discrete part consists of the state of pumps and the continuous part consists of water volume in each processing unit. The Petri Nets obtained were further simplified to facilitate simulation. Through simulation we can determine the amount of water production with certain specifications

Modelling dynamic reliability via Fluid Petri Nets

Combinatorial models for reliability analysis (like fault-trees or block diagram) are static models that cannot include any type of component dependence. In the CTMC (Continuous Time Markov Chain) framework, the transition rates can depend on the state of the system thus allowing the analyst to include some dependencies among components. However, in more general terms, the system reliability may depend on parameters or quantities that vary continuously in time (like temperature, pressure, distance, etc.). Systems whose behavior in time can be described by discrete as well as continuous variables, are called hybrid systems. In the dependability literature, the case in which the reliability characteristics vary continuously versus a process parameter, is sometimes referred to as dynamic reliability [1]. The modelling and analysis of hybrid dynamic systems is an open research area. The present paper discusses the evaluation of a benchmark on dynamic reliability proposed in [1] via a modelling framework called Fluid Stochastic Petri Net (FSPN)

Dynamic state reconciliation and model-based fault detection for chemical processes

In this paper, we present a method for the fault detection based on the residual generation. The main idea is to reconstruct the outputs of the system from the measurements using the extended Kalman filter. The estimations are compared to the values of the reference model and so, deviations are interpreted as possible faults. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. The use of this method is illustrated through an application in the field of chemical processe

Methodologies synthesis

This deliverable deals with the modelling and analysis of interdependencies between critical infrastructures, focussing attention on two interdependent infrastructures studied in the context of CRUTIAL: the electric power infrastructure and the information infrastructures supporting management, control and maintenance functionality. The main objectives are: 1) investigate the main challenges to be addressed for the analysis and modelling of interdependencies, 2) review the modelling methodologies and tools that can be used to address these challenges and support the evaluation of the impact of interdependencies on the dependability and resilience of the service delivered to the users, and 3) present the preliminary directions investigated so far by the CRUTIAL consortium for describing and modelling interdependencies

Petri Nets Modelling and Analysis of the Veneer Layup System of Plywood Manufacturing Plant

In this paper performance behaviour is analysed in respect of the availability of the Veneer layup system of a plywood manufacturing plant. Generalized Stochastic Petri Nets (GSPN) technique is applied for modelling interactions among various components as well as the subsystems. The effects of the failure and repair rates, as well as availability of repair facilities on the behaviour of the system is investigated using a licensed software package. The outcomes will provide guidelines for the effective maintenance priorities to the practitioners and help in selecting appropriate maintenance strategies

Evaluation of a benchmark on dynamic reliability via Fluid Stochastic Petri Nets

The paper presents the evaluation of a benchmark on dynamic reliability. Such system consists of a tank containing some liquid, two pumps and one valve to renew the liquid in the tank, a heat source warming the liquid, and a controller acting on the state of the components. Three failure conditions are possible: the dry out, the over\ufb02ow or the high temperature of the liquid. Due to the presence of continuous variables, such as the liquid level and temperature, the system is modelled as a Fluid Stochastic Petri Net which is the object of simulation obtaining the unreliability evaluation of the system