Condition-Based Maintenance of an Anaerobic Reactor Using Artificial Intelligence

This paper proposes a condition-based maintenance system based on artificial intelligence for an online monitoring of the support bed expansion in 30-liter pilot-scale inverse fluidized reactor (IFBR). The main scope is to achieve strategy using single-level sensor biofilm fluidizing as source virtual sensors. implementation neural network was performed embedded electronic (Raspberry Pi 4), both working together real time. signals estimated by are compared against measured hardware sensors and, case detecting failure physical measurement system, intelligence-based then uses signal maintain correct operation IFBR. estimate COD concentration effluent and biogas production flow bioreactor, from pH, influent, inflow bioreactor coming each conductivity installed inside reactor, which provide information about media reactor. In addition, fuzzy PI controller presented, implemented Raspberry card, regulate used study.