Two-Stage Deep Anomaly Detection With Heterogeneous Time Series Data

Two-Stage Deep Anomaly Detection With Heterogeneous Time Series Data

We introduce a data-driven anomaly detection framework using a manufacturing dataset collected from a factory assembly line. Given <italic>heterogeneous</italic> time series data consisting of operation cycle signals and sensor signals, we aim at discovering abnormal events. Motivated by...

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Bibliographic Details
Main Authors: Kyeong-Joong Jeong, Jin-Duk Park, Kyusoon Hwang, Seong-Lyun Kim, Won-Yong Shin
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Anomaly detection
operation cycle
sensor
time series data
two-stage detection
Online Access:https://ieeexplore.ieee.org/document/9695481/

Internet

https://ieeexplore.ieee.org/document/9695481/

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