A malfunction of a wastewater treatment plant is a major social and biological problem. Poorly treated waste water outside the plant could provoke dangerous consequences for human beings as well as the environment itself. The conventional control systems, that are usually applied in this field, have to cope with some difficulties: complexity of the system, an ill-structured domain, qualitative information, uncertainty or approximate knowledge, real-time dynamic system, ... This paper shows an application of artificial intelligence in order to help the operators of wastewater treatment plants in their task of process control. The main goal is to build a knowledge-based tool useful for the diagnosis and management of wastewater treatment plants. First, a survey of wastewater treatment plants describes the complexity of the system being modelled and outlines its difficulties. The development of the application, and the methodology employed in it, are discussed. A new methodology called LINNEO+ is introduced. It is used for the automatic knowledge acquisition process in order to build up a Knowledge Base. The prototype architecture constructed -DEPUR- is detailed, together with some obtained results. © 1994.
|Journal||Engineering Applications of Artificial Intelligence|
|Publication status||Published - 1 Jan 1994|
- environmental engineering
- knowledge acquisition tools
- Knowledge-based systems
- process diagnosis and management
- wasteweater treatment