A Prognosis Method for Condenser Fouling Based on Differential Modeling

Abstract

Fouling in heat exchanger tubes is a common problem in the operation of condensers. The deposition of fouling can affect the thermal efficiency and safety of the condenser. Therefore, it is necessary to predict the impact of fouling on time and carry out scientific treatment. Firstly, fault prognosis methods require a significant amount of historical fault data, which is often lacking in practical applications. This paper proposes a method based on dynamically adjusting parameters of the fouling thermal resistance empirical equation to establish a fouling thermal resistance digital twin model. It is combined with simulation tools to rapidly generate a large amount of fault data for the research of prognosis methods. Secondly, in the research of fault prognosis methods, prognosis accuracy relies on establishing a reliable and accurate model that describes the behavior of faults. The uncertainty in the modeling process significantly affects the results. Classic modeling methods do not effectively quantify uncertainty. Therefore, this paper proposes a method that applies differential modeling to predict fouling faults in condensers, automatically obtaining uncertain parameters while establishing a reliable model. By calculating the performance evaluation indicator, the accuracy error indicator of the differential modeling-based prognosis method is further reduced to 0.35. The results demonstrate that this method can provide effective reference opinions for handling fouling faults in condensers.

Keywords

• condenser fouling
• prognosis
• differential modeling
• particle filter
• digital twin