Method and device for detecting anomalies in window-based electrodialysis equipment.

Abstract

A method for detecting anomalies in window-based electrodialysis equipment, according to one embodiment, comprises the following steps: establishing an input window range for a control variable of the electrodialysis equipment; converting time series data of the control variable into continuous section unit data corresponding to the input window range; predicting a management variable corresponding to the control variable using an artificial intelligence model trained on the continuous section unit data; and comparing the predicted management variable with a reference value to detect whether anomalies exist in the electrodialysis equipment.