Unsupervised Anomaly Detection of Reciprocating Compressors using Auto-Encoder

Min-Ha Kim; Jaehoon Shim; Juwon Lee; JongHyun Shin; Jung-Ik Ha

doi:10.1109/ecce55643.2024.10861618

ScienceGate Book Chapters

JOURNAL ARTICLE

Unsupervised Anomaly Detection of Reciprocating Compressors using Auto-Encoder

Min-Ha Kim Jaehoon Shim Juwon Lee JongHyun Shin Jung-Ik Ha

Year: 2024 Pages: 5762-5767

DOI: 10.1109/ecce55643.2024.10861618

Get Full-Text PDF Get Analytical Report

Keywords:

Anomaly detection Reciprocating compressor Computer science Encoder Autoencoder Anomaly (physics) Artificial intelligence Gas compressor Pattern recognition (psychology) Engineering Physics Aerospace engineering Artificial neural network

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.30

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Cyclone Separators and Fluid Dynamics

Physical Sciences → Engineering → Computational Mechanics

Refrigeration and Air Conditioning Technologies

Physical Sciences → Engineering → Mechanical Engineering

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Unsupervised Anomaly Detection of Reciprocating Compressors using Auto-Encoder

Metrics

Topics

Related Documents

Unsupervised Anomaly Detection Using Variational Auto-Encoder based Feature Extraction

Unsupervised Anomaly Detection in Flight Data Using Convolutional Variational Auto-Encoder

An intelligent unsupervised anomaly detection in videos using inception capsule auto encoder

Anomaly Detection in IoT Sensor Data Using Auto Encoder-Based Unsupervised Learning

ANOMALY DETECTION OF REVETMENT BY UNSUPERVISED DEEP LEARNING USING VARIATIONAL AUTO-ENCODER