New Insights in Fault Detection and Isolation Systems for Industry 4.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 2989

Special Issue Editors

Polytechnic Institute of Lisbon, Instituto Superior de Engenharia de Lisboa (ISEL), Lisbon, Portugal
Interests: control systems for renewable energies and energetic efficiency; wave energy converters; industry 4.0; digital factories; multi-agent system approaches in fault tolerant control systems; safety-fault detection and isolation systems and soft robotics
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IDMEC/ISEL - Instituto Superior de Engenharia de Lisboa, Departamento de Engenharia Mecânica, Instituto Politécnico de Lisboa, 1500-310 Lisboa, Portugal
Interests: fault detection and isolation; intelligent automatic control; collaborative systems; robotics
Special Issues, Collections and Topics in MDPI journals
Department of Engineering, University of Ferrara, Via Saragat 1E., 44122 Ferrara, FE, Italy
Interests: fault diagnosis and fault tolerant control of linear and nonlinear dynamic processes; system modelling; identification and data analysis; linear and nonlinear filtering techniques; fuzzy logic and neural networks for modelling and control; as well as the interaction issues among identification; fault diagnosis; fault tolerant and sustainable control; these techniques have been applied to power plants; renewable energy conversion systems; aircraft and spacecraft processes
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Special Issue Information

Dear Colleagues,

This Special Issue aims to investigate the currently available state of the art in fault detection and isolation, fault diagnosis, fault tolerance, and condition-based systems applied for industry 4.0 concepts implementation.

Today, the world is witnessing a digital transformation and the industry is also undergoing this revolution, which they called Industry 4.0. This Special Issue intends to compile new contributions from areas related to fault detection and isolation systems and fault tolerance for this transformation. What has been investigated and applied in these areas, in industry 4.0, in recent years and, for example, how the greater computing power (edge, fog and cloud) and industrial internet of things have contributed to improving this kind of systems and the availability of industrial assets, improving the processes efficiency.

Dr. Mário J. G. C. Mendes
Prof. Dr. João M. F. Calado
Dr. Silvio Simani
Guest Editors

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Keywords

  • fault detection and isolation systems
  • fault diagnosis systems
  • fault tolerance
  • condition-based maintenance systems
  • industry 4.0
  • power, energy and industry applications
  • industrial internet of things (IIoT)
  • digital twin

Published Papers (2 papers)

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Research

13 pages, 2751 KiB  
Article
Supervision System 4.0 for a Road Tanker Washing Robot Manipulator
by Luís Vicente, Fernando Carreira, Francisco M. Campos, Mário J. G. C. Mendes, João M. F. Calado and Gamboa Carvalho
Appl. Sci. 2023, 13(14), 8500; https://doi.org/10.3390/app13148500 - 23 Jul 2023
Viewed by 656
Abstract
The washing of road tankers is currently still a manual process that requires an operator to place the washing head into the tanks. To increase productivity and operator safety, it is essential to implement automated systems with Fault Detection and Isolation (FDI) capabilities. [...] Read more.
The washing of road tankers is currently still a manual process that requires an operator to place the washing head into the tanks. To increase productivity and operator safety, it is essential to implement automated systems with Fault Detection and Isolation (FDI) capabilities. On the other hand, the industry 4.0 paradigm promotes the use of collaborative systems that integrate with the other organization’s processes. Realizing this new vision requires Supervision, Control and Data Acquisition (SCADA) systems with FDI modules that integrate with collaborative systems and promote the digitalization of companies. This paper proposes a SCADA system for a new road tanker washing robot, aimed at integrating all systems and communication networks of the organization and future FDI modules. To this end, this paper proposes a communication architecture based on open protocols and a common database to connect SCADA to the lower and higher levels of automation. Furthermore, this paper describes the various aspects of SCADA system development, from synoptic design to validation. To support the development of the SCADA system, a Digital Twin (DT) of the road tanker washing robot was used, allowing to test and validate its functionality through this virtual prototype. The results show that the proposed SCADA system and underlying information architecture are suitable for supervision of a robotized wash operation and that the use of a Digital Twin facilitates SCADA system design and validation. Full article
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15 pages, 4170 KiB  
Article
Model-Based Fault Analysis and Diagnosis of PEM Fuel Cell Control System
by Byungwoo Kang, Wonbin Na and Hyeongcheol Lee
Appl. Sci. 2022, 12(24), 12733; https://doi.org/10.3390/app122412733 - 12 Dec 2022
Viewed by 1620
Abstract
This paper presents a systematic fault analysis and diagnosis method of a PEM fuel cell control system using a model-based approach. With a model-based approach, it is possible to analyze the causal relationship and effect of probable faults in the system, and to [...] Read more.
This paper presents a systematic fault analysis and diagnosis method of a PEM fuel cell control system using a model-based approach. With a model-based approach, it is possible to analyze the causal relationship and effect of probable faults in the system, and to diagnose them under the assumption that the model and the process are similar. With a model-based approach, it is possible to analyze the causal relationship and effect of probable faults in the system and diagnose them under the assumption that the model and the process are similar. In this work, a model-based approach was adopted for fault analysis and diagnosis, and its methods are suggested. A PEM fuel cell is mathematically modelled, analyzed, and verified for the analysis and simulations. Relationships among variables are shown using an incidence matrix and with a Dulmage–Mendelsohn decomposition of the matrix. When it is difficult to detect faults due to a deficient degree of redundancy, a bi-partite graph is used to analyze the effect of faults and to assess the possibility of fault detection through the appropriate redundant sensor placement. Thereafter, residuals are obtained based on analytical redundancies of the system, and a fault signature matrix is subsequently constructed. A fault detection and isolation (FDI) algorithm is developed based on a fault signature matrix that describes the connection between faults and residuals. The simulation results demonstrate the validity and effectiveness of the proposed FDI algorithm for diagnosing faults. With the proposed FDI algorithm, eight faults could be diagnosed by FDI algorithm with given sensors in the system. Full article
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