Performance improvement of glass fiber mat reinforced polypropylene composites

Thesis (doctoral)--서울대학교 대학원 :공업화학과,1999.Docto

딥러닝을 이용한 발전소 회전체 진단 시스템: 스펙트럼, 스펙트로그램, 오빗의 앙상블 모델

MasterThe Prognosis and Health Management (PHM) research field is rising in modern industry to minimize the down-time of a mechanical system. In the power plant, the needs in PHM for the rotating machinery in the power plant are increasing since rotating machinery such as a generator, turbine, and pump are carried out an important role. However, a complicated sensory system for diagnosing rotating equipment in power plants is scarcely established. Although the plant could stop running due to a malfunction in rotating equipment, rotating equipment in power plants usually lacks a real-time machine condition monitoring system. For this reason, it is hard to detect the fault of equipment in advance. Therefore, establishing a diagnosis system for rotating equipment is essential to minimize the downtime in the operation process in power plants. The proposed fault diagnosis system aims to enhance the diagnosis performance by combining multi-classifier. Spectrum analysis, spectrogram analysis, and orbit analysis are used to conduct a single network. These are the most commonly used analysis techniques for vibration data. Deep ensemble learning networks and combination networks are used to improve the diagnosis performance

원심력을 이용한 에폭시탄소섬유 경사형 복합재료의 제조 및 물성 특성

학위논문(석사)--서울대학교 대학원 :공업화학과,1995.Maste

Vibration Data Augmentation Technique for Improving Rotor Diagnosis Accuracy

2

Analysis of rotating machinery diagnosis based on explainable deep learning technology

2

Deep Learning Technique for Diagnosis of Rotating Machinery using Orbit Shape and Scale

2

규칙 기반과 딥러닝을 동시에 활용한 앙상블 회전체 이상 진단

2

Remote machine mode detection in cold forging using vibration signal

1

Detection of process variation in a cold forging process through smart manufacturing

1