An integrated trade-off design of observer based fault detection systems

Automatica ◽  
2008 ◽  
Vol 44 (7) ◽  
pp. 1886-1894 ◽  
Author(s):  
Ping Zhang ◽  
Steven X. Ding
Keyword(s):  
Fault Detection ◽  
Trade Off ◽  
Detection Systems

Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes

2021 ◽  
Author(s):  
Seshapalli Sairam ◽  
Subathra Seshadhri ◽  
Giancarlo Marafioti ◽  
Seshadhri Srinivasan ◽  
Geir Mathisen ◽  
...  
Keyword(s):  
Fault Detection ◽  
Photovoltaic Panels ◽  
Detection Systems ◽  
Edge Based

scholarly journals A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 629 ◽  
Author(s):  
Junaid Arshad ◽  
Muhammad Ajmal Azad ◽  
Roohi Amad ◽  
Khaled Salah ◽  
Mamoun Alazab ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Resource Constraints ◽  
Extensive Study ◽  
Intrusion Detection Systems ◽  
Detection Accuracy ◽  
Trade Off ◽  
Detection Systems ◽  
Computational Overhead ◽  
Significant Research ◽  
And Performance

Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.

Gradient-based fuzzy fault isolation in residual-based fault detection systems

2014 ◽  
Author(s):  
Francisco Serdio ◽  
Edwin Lughofer ◽  
Kurt Pichler ◽  
Thomas Buchegger ◽  
Markus Pichler ◽  
...  
Keyword(s):  
Fault Detection ◽  
Fault Isolation ◽  
Detection Systems ◽  
Gradient Based

Robust fault detection of dynamic systems via genetic algorithms

1997 ◽  
Vol 211 (5) ◽  
pp. 357-364 ◽  
Author(s):  
R J Patton ◽  
J Chen ◽  
G P Liu
Keyword(s):  
Genetic Algorithm ◽  
Fault Detection ◽  
Flight Control ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Performance Indices ◽  
Frequency Distributions ◽  
Modelling Uncertainty ◽  
Detection Systems ◽  
Robust Fault Detection

This paper presents a new approach to the design of robust fault detection systems via a genetic algorithm. To achieve robustness, a number of performance indices are introduced, which are expressed in the frequency domain to account for the frequency distributions of incipient faults, noise and modelling uncertainty. All objectives are then reformulated into a set of inequality constraints on performance indices. A genetic algorithm is thus used to search an optimal solution to satisfy these inequality constraints. The approach developed is applied to a flight control system example and results show that incipient sensor faults can be detected reliably in the presence of modelling uncertainty.

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