Kunihiko Nabeshima

On-line reactor monitoring with neural network for RSG-GAS

The ANNOMA (artificial neural network of monitoring aids) system is applied to the condition monitoring and signal validation of multi purpose reactor (RSG-GAS) in Indonesia. The feedforward neural network in auto-associative mode learns reactors normal operational data, and models the reactor dynamics during the initial learning. The basic principle of the anomaly detection is to monitor the deviation between the process signals measured from the actual reactor and the corresponding values predicted by the reactor model, i.e., the neural networks. The pattern of the deviation at each signal is utilized for the identification of anomaly, e.g. sensor failure or system fault. The on-line test results showed that the neural network successfully monitored the reactor status during power increasing and steady state operation in real-time

New Control Theory and Its Application

The PID control system design method based on transfer functions was established in the 1950s and has since made contributions to automation processes in various industrial fields. Transfer functions have features that make you aware of rough characteristics of input–output responses based on the positioning of the poles and zero point and also discuss frequency responses and the stability of the control system using their Bode diagram. Now we will once again review the restrictions required to express dynamic characteristics of the control target with transfer functions.