Yuri A. W. Shardt

Orcid: 0000-0002-9311-7739

According to our database1, Yuri A. W. Shardt authored at least 21 papers between 2011 and 2024.

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Bibliography

2024
Dynamic-controlled principal component analysis for fault detection and automatic recovery.
Reliab. Eng. Syst. Saf., January, 2024

2021
Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development.
IEEE Trans. Ind. Electron., 2021

A Just-In-Time-Learning-Aided Canonical Correlation Analysis Method for Multimode Process Monitoring and Fault Detection.
IEEE Trans. Ind. Electron., 2021

Graph neural network-based fault diagnosis: a review.
CoRR, 2021

2020
A KPI-Based Soft Sensor Development Approach Incorporating Infrequent, Variable Time Delayed Measurements.
IEEE Trans. Control. Syst. Technol., 2020

Fault Classification in Dynamic Processes Using Multiclass Relevance Vector Machine and Slow Feature Analysis.
IEEE Access, 2020

2019
Cost-sensitive large margin distribution machine for fault detection of wind turbines.
Clust. Comput., 2019

Optimization of Motion Control for a Variably Excited Linear Hybrid Stepper Motor.
Proceedings of the IEEE International Conference on Mechatronics, 2019

2018
A KPI-Based Probabilistic Soft Sensor Development Approach that Maximizes the Coefficient of Determination.
Sensors, 2018

A Comparison of Different Statistics for Detecting Multiplicative Faults in Multivariate Statistics-Based Fault Detection Approaches.
IEEE Access, 2018

Simultaneous Robust, Decoupled Output Feedback Control for Multivariate Industrial Systems.
IEEE Access, 2018

2017
Parameter Identification and Control Scheme for Monitoring Automatic Thickness Control System with Measurement Delay.
J. Control. Sci. Eng., 2017

Self-Adaptive Artificial Bee Colony for Function Optimization.
J. Control. Sci. Eng., 2017

Assessment of <i>T</i><sup>2</sup>- and <i>Q</i>-statistics for detecting additive and multiplicative faults in multivariate statistical process monitoring.
J. Frankl. Inst., 2017

Parameter-based conditions for closed-loop system identifiability of ARX models with routine operating data.
J. Frankl. Inst., 2017

2016
An Adaptive, Advanced Control Strategy for KPI-Based Optimization of Industrial Processes.
IEEE Trans. Ind. Electron., 2016

Estimating the unknown time delay in chemical processes.
Eng. Appl. Artif. Intell., 2016

A brief survey of different statistics for detecting multiplicative faults in multivariate statistical process monitoring.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
A New Soft-Sensor-Based Process Monitoring Scheme Incorporating Infrequent KPI Measurements.
IEEE Trans. Ind. Electron., 2015

2013
Data quality assessment of routine operating data for process identification.
Comput. Chem. Eng., 2013

2011
Closed-loop identification condition for ARMAX models using routine operating data.
Autom., 2011


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