On-line industrial supervision and diagnosis, knowledge level description and experimental results

摘要

This paper presents a detailed description of a knowledge-based system for on-line supervision and diagnosis of industrial continuous processes: TURBOLID. The system has been developed for a Spanish beet sugar factory, and it is in use in two plants. The system supports three main tasks; monitoring, operation mode and diagnosis. A detailed knowledge level account of the systems is presented in this paper, using CommonKADS methodology. The knowledge level description presented here will allow the reuse of the TURBOLID problem solving approach to supervision and diagnosis in other continuous plants, even in other domains. The main purpose of this paper is to illustrate how the basic tasks proposed are able to cope with supervision and diagnosis of a complex plant. Particularly significant are the separation of operation mode and diagnosis, and the approach of TURBOLID to diagnosis, that obtains on-line causal explanations for detected problems. TURBOLID is able to differentiate among competing hypotheses looking for historical data, current data and even future data, tracking the plant evolution. Results of the activity of the system during a working month are also presented.