Optimized Forecast Components-SVM-Based Fault Diagnosis With Applications for Wastewater Treatment
Process monitoring of wastewater treatment plant (WWTP) is a challenging industrial problem, due to its exposure to the hostile working environment and significant disturbances. This paper proposed a novel fault diagnosis method, termed as optimization forecast components-support vector machine (OFC...
Main Authors: | Hongchao Cheng, Yiqi Liu, Daoping Huang, Bin Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8822997/ |
Similar Items
-
Fault Diagnosis of Rolling Bearing Based on Probability box Theory and GA-SVM
by: Hong Tang, et al.
Published: (2020-01-01) -
SVM Based on Gaussian and Non-Gaussian Double Subspace for Fault Detection
by: Jinyu Guo, et al.
Published: (2021-01-01) -
A New Morphological Filter for Fault Feature Extraction of Vibration Signals
by: Jianbo Yu, et al.
Published: (2019-01-01) -
Inlet Water Quality Forecasting of Wastewater Treatment Based on Kernel Principal Component Analysis and an Extreme Learning Machine
by: Tingting Yu, et al.
Published: (2018-06-01) -
Open-circuit fault diagnosis of NPC inverter IGBT based on independent component analysis and neural network
by: Hailin Hu, et al.
Published: (2020-12-01)