Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.
Açıklama
2023 China Automation Congress, CAC 2023 -- 17 November 2023 through 19 November 2023 -- -- 198194
Anahtar Kelimeler
Anomaly Detection, Principle Of Justifiable Granularity, Probability Density Estimation, Time Series
Kaynak
Proceedings - 2023 China Automation Congress, CAC 2023
WoS Q Değeri
Scopus Q Değeri
N/A
