EQUIPMENT DIAGNOSIS SYSTEM AND METHOD BASED ON DEEP LEARNING

An equipment diagnosis system and method, which use abnormal data and normal data of equipment and accurately and effectively perform diagnosis on the equipment, are provided. The equipment diagnosis system includes a data acquisition unit to acquire time series data of equipment, a preprocessing unit convert the time series data into frequency data including a temporal component through a Fourier transform, a deep learning unit to perform deep learning through a convolution neural network (CNN) by using the frequency data, and a diagnosis unit to determine a state of the equipment to be a normal state or a breakdown state based on the deep learning.