The integration of flawidentification and flawindulgence is a crucial task in real-time monitoring of complex processes. This research proposes a control method using a three-layer neural network for realizing the integration of flawidentification and flawindulgence for a boiler sensor based on the internet. The proposed method determines the input mode pair and output mode pair by grouping voltage values collected from the sensor data. The grouped data is then used to train a neural network of a joint controller of a blurring cerebellum model, which carries out flawidentification and flawindulgence. This study also presents a control apparatus to realize the proposed method. The research is applicable to industrial fields such as underwater robots, chemical industries, and other areas where sensors are used.

Flaw Identification, Flaw Indulgence, Boiler Sensor, Three-Layer Neural Network, Real-time Monitoring, Internet