Anomaly detection and early warning model of high-frequency data based on local anomaly factor algorithm

Konferenz: MEMAT 2022 - 2nd International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology
07.01.2022 - 09.01.2022 in Guilin, China

Tagungsband: MEMAT 2022

Seiten: 4Sprache: EnglischTyp: PDF

Autoren:
Zhang, Xinyu; Xie, Wenjie; Wu, Ziyang (Wuhan University of Technology, Wuhan, China)

Inhalt:
In the era of rapid development of modern economy, to promote the high-quality development of production enterprises, the most fundamental bottom line is to ensure safety and prevent risks, and the data generated in the production process can reflect potential risks in real time. In this paper, the LOF algorithm is improved and the fault data monitoring model established can quickly and accurately find the fault location, give early warning and stop the loss in time, which is of great practical significance.