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

Integration of an object formalism within a hybrid dynamic simulation environment

PrODHyS is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of systems engineering. Its major characteristic is its ability to simulate processes described by a hybrid model. In this framework, this paper focuses on the "Object Differential Petri Net" (ODPN) formalism integrated within PrODHyS. The use of this formalism is illustrated through a didactic example relating to the field of Chemical Process System Engineering (PSE)

Effective retrieval and new indexing method for case based reasoning: Application in chemical process design

In this paper we try to improve the retrieval step for case based reasoning for preliminary design. This improvement deals with three major parts of our CBR system. First, in the preliminary design step, some uncertainties like imprecise or unknown values remain in the description of the problem, because they need a deeper analysis to be withdrawn. To deal with this issue, the faced problem description is soften with the fuzzy sets theory. Features are described with a central value, a percentage of imprecision and a relation with respect to the central value. These additional data allow us to build a domain of possible values for each attributes. With this representation, the calculation of the similarity function is impacted, thus the characteristic function is used to calculate the local similarity between two features. Second, we focus our attention on the main goal of the retrieve step in CBR to find relevant cases for adaptation. In this second part, we discuss the assumption of similarity to find the more appropriated case. We put in highlight that in some situations this classical similarity must be improved with further knowledge to facilitate case adaptation. To avoid failure during the adaptation step, we implement a method that couples similarity measurement with adaptability one, in order to approximate the cases utility more accurately. The latter gives deeper information for the reusing of cases. In a last part, we present a generic indexing technique for the base, and a new algorithm for the research of relevant cases in the memory. The sphere indexing algorithm is a domain independent index that has performances equivalent to the decision tree ones. But its main strength is that it puts the current problem in the center of the research area avoiding boundaries issues. All these points are discussed and exemplified through the preliminary design of a chemical engineering unit operation

Predictive functional control for the temperature control of a chemical batch reactor

A predictive functional control (PFC) technique is applied to the temperature control of a pilot-plant batch reactor equipped with a mono-fluid heating/cooling system. A cascade control structure has been implemented according to the process sub-units reactor and heating/cooling system. Hereby differences in the sub-units dynamics are taken into consideration. PFC technique is described and its main differences with a standard model predictive control (MPC) technique are discussed. To evaluate its robustness, PFC has been applied to the temperature control of an exothermic chemical reaction. Experimental results show that PFC enables a precise tracking of the set-point temperature and that the PFC performances are mainly determined by its internal dynamic process model. Finally, results show the performance of the cascade control structure to handle different dynamics of the heating/cooling system

Acceleration of the retrieval of past experiences in Case Based Reasoning : application for preliminary design in Chemical Engineering

The way to manage knowledge accumulated is one of the firm’s trends, in order to capitalize and to transmit this knowledge. Some Artificial Intelligence methods are devoted to preserve and to reuse past experiences. Case Based Reasoning (CBR) is one of these methods dedicated to problem solving, new knowledge acquisition and knowledge management. CBR is a cyclic method where the central notion is a case which represents an earlier experience. Several cases are collected and stored in a memory: the case base. The goal of this paper is to soften the way to describe problem and to increase the effectiveness of the system during the retrieval of relevant case

Innovation and Knowledge Management : using the combined approach TRIZ-CBR in Process System Engineering

In this article, a TRIZ based model is proposed to support the innovation and knowledge capitalization process. This model offers a knowledge base structure, which contains several heuristics to solve problems, synthesized from a large range of domains and industries and, also, the capacity to capture, store and make available the experiences produced while solving problems

Towards a pivotal-based approach for business process alignment.

This article focuses on business process engineering, especially on alignment between business analysis and implementation. Through a business process management approach, different transformations interfere with process models in order to make them executable. To keep the consistency of process model from business model to IT model, we propose a pivotal metamodel-centric methodology. It aims at keeping or giving all requisite structural and semantic data needed to perform such transformations without loss of information. Through this we can ensure the alignment between business and IT. This article describes the concept of pivotal metamodel and proposes a methodology using such an approach. In addition, we present an example and the resulting benefits

Management of innovation and process systems engineering

In this paper, Innovation on technological point of view will be explored. Some tracks for helping for innovative aspects as well as the role of PSE and CAPE methodologies will be analyzed. Some new directions will be proposed as well as some examples of success will be enlighted

The TRIZ-CBR synergy: A knowledge based innovation process

Today innovation is recognised as the main driving force in the market. This complex process involves several intangible dimensions, such as creativity, knowledge and social interactions among others. Creativity is the starting point of the process, and knowledge is the force that transforms and materialises creativity in new products, services and processes. In this paper a synergy that aims to assists the innovation process is presented. The synergy combines several concepts and tools of the theory of inventive problem solving (TRIZ) and the case-based reasoning (CBR) process. The main objective of this synergy is to support creative engineering design and problem solving. This synergy is based on the strong link between knowledge and action. In this link, TRIZ offers several concepts and tools to facilitate concept creation and to solve problems, and the CBR process offers a framework capable of storing and reusing knowledge with the aim of accelerating the innovation process

Dynamic models for start-up operations of batch distillation columns with experimental validation

The simulation of batch distillation columns during start-up operations is a very challenging modelling problem because of the complex dynamic behaviour. Only few rigorous models for distillation columns start-up are available in literature and generally required a lot of parameters related to tray or pack geometry. On an industrial viewpoint, such a complexity penalizes the achievement of a fast and reliable estimate of start-up periods. In this paper, two “simple” mathematical models are proposed for the simulation of the dynamic behaviour during start-up operations from an empty cold state. These mathematical models are based on a rigorous tray-by-tray description of the column described by conservation laws, liquid–vapour equilibrium relationships and equations representative of hydrodynamics. The models calibration and validation are studied through experiments carried out on a batch distillation pilot plant, with perforated trays, supplied by a water methanol mixture. The proposed models are shown by comparison between simulation and experimental studies to provide accurate and reliable representations of the dynamic behaviour of batch distillation column start-ups, in spite of the few parameters entailed