Servizio Comunitario di Informazione in materia di Ricerca e Sviluppo - CORDIS

Fault diagnosis and abnormal situation management using neuro-fuzzy reasoning

The aim of the CHEM project was to develop and implement advanced Decision Support Systems (DSS) for process monitoring, data and event analysis, and operation support in industrial processes. The systems are synergistic integration of innovative software tools, which improve the safety, product quality and operation reliability as well as reduce the economic losses due to faulty states, mainly in refining, chemical and petrochemical processes.

The CHEM applications consist of integrated sets of software toolboxes that provide robust detection and diagnosis of process problems in real-time. The systems assist operators in assessing process status and responding to abnormal events. The project provides a flexible architecture and a methodology in order to facilitate the development of such applications on many processes.

This software ("Fault diagnosis and abnormal situation management using neuro-fuzzy reasoning") is a tool for alarm generation and decision-making support. It acquires expert knowledge from the operator in a visual and intuitive manner and by writing if-then rules. It has also the capability to automatically adapt to process changes in order to avoid false alarms allowing in addition fast and reliable fault detection and diagnosis.

Information coming from a Hazard and Operability analysis (HAZOP) is used to provide operators support in case of alarms.

In addition, the use of artificial neural networks allows the utilisation of available data (i.e. process variables data or data pre-processed by other CHEM software) to realise a classification or a clustering of the plant states and to realize process models. This capability can be used to perform fault diagnosis, as well as to generate symptoms for a further diagnosis stage.

The main objective is to avoid plant shutdowns. Furthermore, early diagnosis can reduce the loss of productivity during an abnormal event if it is performed when the plant is still operating in a controllable region.

The on-line connection of this toolbox with the real process, as well as the integration with other toolbox/es of the CHEM project allows the implementation of real-time on-line fault diagnosis.

The FDS includes the identification of the root causes of process upsets (fault diagnosis) and can provide recommended corrective actions to restore the process to normal operating condition (fault correction). In this regard, real-time appropriate actions must be taken in present chemical and petrochemical manufacturing.

The complexity of process control in present batch chemical plants affects the execution of the supervision tasks making it very difficult. This support is also necessary at the upper levels in the decision-making system as is the planning and scheduling level. Due to its inherent flexibility, batch plants can operate efficiently under different scenarios if the consequences of abnormal situations can be anticipated. This robust Fault Diagnosis System (FDS), that timely provides the fault information to the scheduling level, allows improving the efficiency of the reactive scheduling, to update the schedules in the most effective way.

Reported by

Univ. Politecnica de Catalunya, Chem. Eng. Dep.
Av. Diagnoal 647, G2
08028 Barcelona
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