Research graph
References from Drift-aware Whitening Residual Monitoring (DAWRM): An adaptive PCA-based framework for real-time fault detection and machine learning integration in industrial IoT systems. Local targets link to admitted publications; unresolved targets remain external evidence.
Industrial internet of things intelligence empowering smart manufacturing: a literature review
10.1109/jiot.2024.3367692 · 2024 · External reference
Edge-to-Cloud IIot for condition monitoring in manufacturing systems with ubiquitous smart sensors
10.3390/s22155901 · 2022 · External reference
Conceptual and empirical comparison of dimensionality reduction algorithms (pca, kpca, lda, mds, svd, lle, isomap, le, ica, t-sne)
10.1016/j.cosrev.2021.100378 · 2021 · External reference
Fault detection using correspondence analysis: application to tennessee eastman challenge problem
10.3182/20060402-4-br-2902.00705 · 2006 · External reference
A review on fault detection and process diagnostics in industrial processes
10.3390/pr8091123 · 2020 · External reference
Overview of principal component analysis algorithm
10.1016/j.ijleo.2016.01.033 · 2016 · External reference
Data dimensional reduction and principal components analysis
10.1016/j.procs.2019.12.111 · 2019 · External reference
Online monitoring for uneven length batch processes using function space principal component analysis
10.3182/20131216-3-in-2044.00058 · 2013 · External reference
Sensor data quality: a systematic review
10.1186/s40537-020-0285-1 · 2020 · External reference
Tutorial on PCA and approximate PCA and approximate kernel PCA
10.1007/s10462-022-10297-z · 2023 · External reference
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Concept drift detection based on deep neural networks and autoencoders
10.3390/app15063056 · 2025 · External reference
An improved plant-wide fault detection scheme based on PCA and adaptive threshold for reliable process monitoring: application on the new revised model of tennessee eastman process
10.1002/cem.2978 · 2018 · External reference
Learning under concept drift: a review
2018 · External reference
Integrated unfold-PCA monitoring application for smart buildings: an AHU application example
10.3390/en14010235 · 2021 · External reference
PCA-Based sensor drift fault detection with distribution adaptation in wastewater treatment process
2024 · External reference
A well-conditioned estimator for large-dimensional covariance matrices
10.1016/s0047-259x(03)00096-4 · 2004 · External reference
Statistical approaches and artificial neural networks for process monitoring
10.1016/bs.mcps.2022.04.003 · 2022 · External reference
An enhanced temporal algorithm-coupled optimized adaptive sparse principal component analysis methodology for fault diagnosis of chemical processes
10.1016/j.psep.2023.04.036 · 2023 · External reference
Fault diagnosis of time-varying processes using modified reconstruction-based contributions
10.1016/j.jprocont.2018.07.017 · 2018 · External reference
Integrating PCA and structural model decomposition to improve fault monitoring and diagnosis with varying operation points
10.1016/j.engappai.2023.106145 · 2023 · External reference
Dynamic transfer soft sensor for concept drift adaptation
10.1016/j.jprocont.2023.01.012 · 2023 · External reference
A novel multiple kernel learning method based on the kullback–leibler divergence
10.1007/s11063-014-9392-3 · 2015 · External reference
The deep kernelized autoencoder
10.1016/j.asoc.2018.07.029 · 2018 · External reference
Foundations and innovations in data fusion and ensemble learning for effective consensus
10.3390/math13040587 · 2025 · External reference
An improved SVM integrated GS-PCA fault diagnosis approach of tennessee eastman process
10.1016/j.neucom.2015.10.018 · 2016 · External reference
Explainability and interpretability in concept and data drift: a systematic literature review
10.3390/a18070443 · 2025 · External reference
Fault detection of non-stationary processes using a modified PCA approach
2021 · External reference
Enhancing fault detection with clustering and covariance analysis
10.1016/j.ifacol.2022.04.203 · 2022 · External reference
Self-Adaptive incremental PCA-Based DBSCAN of acoustic features for anomalous sound detection
10.1007/s42979-024-02844-y · 2024 · External reference
An adaptive mode identification and fault detection scheme for nonlinear multimode process monitoring using improved DPC-KPCA
10.1016/j.jtice.2024.105915 · 2025 · External reference
Estimation, forecasting, and anomaly detection for nonstationary streams using adaptive estimation
10.1109/tcyb.2021.3054161 · 2021 · External reference
Uncertainty-aware real-time visual anomaly detection with conformal prediction in dynamic indoor environments
10.1109/lra.2025.3552318 · 2025 · External reference
Conformal prediction for distribution-independent anomaly detection in streaming vessel data
2010 · External reference
Performance investigation of principal component analysis for intrusion detection system using different support vector machine kernels
10.3390/electronics11213571 · 2022 · External reference
Industrial fault detection employing meta ensemble model based on contact sensor ultrasonic signal
10.3390/s24072297 · 2024 · External reference
An integrated approach: a hybrid machine learning model for the classification of unscheduled stoppages in a mining crushing line employing principal component analysis and artificial neural networks
10.3390/s24175804 · 2024 · External reference
Application of PCA and SVM in fault detection and diagnosis of bearings with varying speed
2022 · External reference
Relevance of drift components and unit-to-Unit variability in the predictive maintenance of low-Cost electrochemical sensor systems in air quality monitoring
10.3390/s21093298 · 2021 · External reference
Coalitional bayesian autoencoders: towards explainable unsupervised deep learning with applications to condition monitoring under covariate shift
10.1016/j.asoc.2022.108912 · 2022 · External reference
Intrusion detection in the IoT under data and concept drifts: online deep learning approach
10.1109/jiot.2022.3167005 · 2022 · External reference
Online principal component analysis in high dimension: which algorithm to choose?
10.1111/insr.12220 · 2018 · External reference
High-dimensional covariance matrix estimation
10.1002/wics.1485 · 2020 · External reference
ANOMALY DETECTION IN CROWDS USING MULTI SENSORY INFORMATION
2018 · External reference
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