A Multi-Expert System for chlorine electrolyzer monitoring

The Chlor-Alkali production is one of the largest industrial scale electro-synthesis in the world. Plants with more than 1000 individual reactors are common, where chlorine and hydrogen are only separated by 0.2 mm thin membranes. Wrong operating conditions can cause explosions and highly toxic gas releases, but also irreversible damages of very expensive cell components with dramatic maintenance costs and production loss. In this paper, a Multi-Expert System based on first-order logic rules and Decision Forests is proposed to detect any abnormal operating conditions of membrane cell electrolyzers and to advice the operator accordingly. Robustness to missing data – which represents an important issue in industrial applications in general – is achieved by means of a Dynamic Selection strategy. Experiments performed with real-world electrolyzer data indicate that the proposed system can significantly detect the different operating modes, even in the presence of high levels of missing data – or “wrong” data, as a consequence of maloperation –, which is essential for precise fault detection and advice generation.

► A Multi-Expert System is proposed to detect any abnormal operating conditions of membrane cell electrolyzers.
► In order to correct anomalies, a set of helpful recommendations is provided to the operator.
► Robustness to missing data is achieved by means of a Dynamic Selection strategy.
► The system significantly detects the eight different electrolyzer operating modes.