Samsung Electronics Co., Ltd.

Seoul National University

Young-il Jang

Won-ki Park

Ho-youl Lee

Byoung-Tak Zhang

Kyoung-whan Oh

Kyoung-Whan Oh

Jong-hwi Seo

Seong-Ho Choi

Yong-Won Choi

Yeon-Woo Choi

Ha-nock Kwak

Won-Yup Ko

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.

Equipment diagnosis system and method based on deep learning

A method for determining a position of a fault of equipment includes receiving a plurality of sound source signals from a plurality of sound source inputting apparatuses, determining an abnormal operation of the equipment by analyzing at least one sound source signal among the sound source signals, and extracting abnormal sound source signals from the sound source signals. The abnormal sound source signals are indicative of abnormal operation of the equipment. The method further includes determining a position of the abnormal operation based on a time difference between the abnormal sound source signals.

Method of determining position of fault of equipment using sound source inputting apparatus and system of determining position of fault of equipment for performing the same

Growing community of inventors

Yongin-si, South Korea

Young-il Jang