3.8 Proceedings Paper

Exploring a Modular Architecture for Sensor Validation in Digital Twins

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model

Shohin Aheleroff et al.

Summary: Recent findings show that Digital Twin can provide services to multiple stakeholders, but a sophisticated reference architecture, suitable technologies, and a proper business model are needed. Most studies in the field focus on manufacturing, while empirical research on the relationship between Digital Twin and mass individualization is lacking. The study aims to identify suitable Industry 4.0 technologies and a comprehensive reference architecture model for challenging Digital Twin applications, indicating a significant relationship between Digital Twin capabilities as a service and mass individualization.

ADVANCED ENGINEERING INFORMATICS (2021)

Article Engineering, Electrical & Electronic

Sensor-Fault Detection, Isolation and Accommodation for Digital Twins via Modular Data-Driven Architecture

Hossein Darvishi et al.

Summary: This article introduces a machine-learning-based sensor validation architecture that uses neural network estimators and a classifier to detect and isolate faulty sensors for reliable digital twins. Results show that the proposed architecture performs well under different real-world datasets and synthetically-generated faults.

IEEE SENSORS JOURNAL (2021)

Article Engineering, Electrical & Electronic

Digital Moka: Small-Scale Condition Monitoring in Process Engineering

Siddanth N. Bairampalli et al.

Summary: The study proposes a data-driven condition-monitoring system for a moka pot aiming at anomaly detection in the coffee-preparation process. By describing the data-acquisition system and the comprehensive dataset generation process, supervised and unsupervised machine learning algorithms are trained and tested to detect anomalies in the process and demonstrate the relevance of the considered framework.

IEEE SENSORS LETTERS (2021)

Article Computer Science, Hardware & Architecture

Intelligent Digital Twin-Based Software-Defined Vehicular Networks

Liang Zhao et al.

IEEE NETWORK (2020)

Article Computer Science, Information Systems

A Machine-Learning-Based Technique for False Data Injection Attacks Detection in Industrial IoT

Mariam M. N. Aboelwafa et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Engineering, Electrical & Electronic

Fault Detection in Wireless Sensor Networks Through SVM Classifier

Salah Zidi et al.

IEEE SENSORS JOURNAL (2018)

Article Engineering, Aerospace

Air Data Sensor Fault Detection with an Augmented Floating Limiter

Fabio Balzano et al.

INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING (2018)

Article Automation & Control Systems

Sensor Failure Detection, Identification, and Accommodation Using Fully Connected Cascade Neural Network

Saed Hussain et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)

Proceedings Paper Energy & Fuels

Simulation of Sensor Fault Diagnosis for Wind Turbine Generators DFIG and PMSM Using Kalman Filter

R. Saravanakumar et al.

4 INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY RESEARCH (ICAER 2013) (2014)

Article Computer Science, Information Systems

Fault Diagnosis in Wireless Sensor Networks: A Survey

Arunanshu Mahapatro et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2013)

Article Automation & Control Systems

Fault Diagnosis and Fault-Tolerant Control in Linear Drives Using the Kalman Filter

Sunan Huang et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2012)

Article Telecommunications

Security framework for wireless sensor networks

Neeli R. Prasad et al.

WIRELESS PERSONAL COMMUNICATIONS (2006)

Article Automation & Control Systems

A method of sensor fault detection and identification

N Mehranbod et al.

JOURNAL OF PROCESS CONTROL (2005)