An integral monitoring concept for data‐driven detection and localization of incipient leakages by fusion of process and environment data

• Published in: Journal of advanced manufacturing and processing 2022-07, Vol.4 (3), p.n/a
• Main Authors: Kasten, Kristian, Zhu, Caroline Charlotte, Birk, Joachim, Ding, Steven X.
• Format: Article
• Language: English
• Subjects: data‐driven fault detection; environment; gas detector; incipient fault; Industrial applications; Leakage; leakage detection; Localization; Monitoring; root cause
• ISSN: 2637-403X; 2637-403X
• DOI: 10.1002/amp2.10133

The risk of leakages in process industry is environmentally critical and potentially hazardous. Many technologies and schemes for process monitoring are theoretically developed and applied in an industrial context. Nevertheless, most approaches still focus on individual monitoring of a process and its environment. The major challenge is the lack of a priori knowledge about the leakage. This paper introduces a new approach combining monitoring of the environment and its embedded process. The application on an industrial use‐case in a real plant environment illustrates the success of this combined monitoring approach as well as a decision support to localize an incipient leakage. Leakage detection and localization is still a major challenge for science and industry because the lack of a priori knowledge. This article introduces a new approach; combining monitoring of the environment and its embedded process. The application on an industrial use‐case illustrates the success of this combined monitoring approach as well as an decision support to localize an incipient leakage.