Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints
Abstract Addressing the issues of inadequate information exchange among subsequences in the operational time series of water injection pumps, leading to low accuracy and high false alarm rates in anomaly detection, this paper proposes a multidimensional time series anomaly detection method for water...
Saved in:
Main Authors: | Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-85436-x |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Method for detecting anomalies in geomagnetic field variations
based on artificial neural network
by: Imashev, Sanjar A.
Published: (2024-12-01) -
Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation
by: Zhan Wang, et al.
Published: (2025-01-01) -
Multidimensional time series classification with multiple attention mechanism
by: Chen Liu, et al.
Published: (2024-11-01) -
Anomaly detection of adversarial cyber attacks on electric vehicle charging stations
by: Sagar Babu Mitikiri, et al.
Published: (2025-03-01) -
A State-Supervised Model and Novel Anomaly Index for Gas Turbines Blade Fault Detection Under Multi-Operating Conditions
by: Yuan Xiao, et al.
Published: (2025-01-01)