Reliability Analysis of CAN nodes under Electromagnetic Interference

Chen, Juexiao; Luo, Feng; Sun, Zhonghui

doi:10.1109/icves.2006.371617

Cited by 7 publications

(1 citation statement)

References 3 publications

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“…These aspects are mostly specified at the level of communication protocol. Accordingly, in many applications the protocol rules should provide the basic information to derive an explicit expression for the functions in (9).…”

Section: Detailed Analysis Of Net_ber Computationmentioning

confidence: 99%

A System-Level Protocol-Based Methodology for Noise Analysis of Digital Networked Systems

Vece¹,

Mazza²,

Conti³

2014

JNW

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Reliability and noise tolerance represent important requirements for electronic systems and in particular for networked systems, especially in critical working conditions. Reliability and noise tolerance mostly concern the communication tasks between the network nodes, which are implemented complying with formal protocol rules. The challenging target for a reliability analysis is to provide comprehensive evaluations and acceptably accurate results. However, the current complexity of the protocol and the complexity of the networks with many nodes make it very difficult to achieve this target. This paper presents a novel system-level methodology for noise analysis of digital networked systems. The methodology is based on a simulation and analytical approach capable to address a fast and comprehensive study of the reliability properties complying with the protocol specifications. As a test case, the MOST 150 protocol has been considered. MOST 150 protocol is currently widely used for multimedia networks in automotive applications.

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Section: Detailed Analysis Of Net_ber Computationmentioning

confidence: 99%

A System-Level Protocol-Based Methodology for Noise Analysis of Digital Networked Systems

Vece¹,

Mazza²,

Conti³

2014

JNW

View full text Add to dashboard Cite

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Electric Vehicle Automation through a Distributed Control System for Search and Rescue Operations

Cruz-Ramos

Hassard

Gordillo

2013

Advances in Artificial Intelligence

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Anomaly Detection for Controller Area Network in Braking Control System With Dynamic Ensemble Selection

Yang

Wang

et al. 2019

IEEE Access

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The controller area networks (CAN) in the braking control system of metro trains are used to transmit the important control instruction and condition information, whose anomaly will endanger the security of trains running seriously. Due to the harsh work environment, there are various known and previously unknown fault types, current scheduled maintenance cannot detect early anomaly in time, and constructing an accurate and stable anomaly detector is a challenging task. In this paper, an anomaly detection approach is proposed to detect anomaly based on a dynamic ensemble selection system (DESS) without the expert knowledge, which involves two-class and one-class classifiers, and the base classifiers are trained with the network features extracted from the physical-layer information. To conduct the fusion, the support function of ''distance-based'' classifier is redefined as a class-conditional probability density function, and the source competence of base classifier is estimated by the entropy-based method in validate space and extended to entire decision space using the normalized Gaussian potential function. For different fault types, the competence classifiers are selected and the anomaly detection result is finally achieved by weighted majority voting. The comparative experiments are included in this paper to demonstrate the effectiveness and robustness in anomaly detection, including varying fault types.

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Reliability Analysis of CAN nodes under Electromagnetic Interference

Cited by 7 publications

References 3 publications

A System-Level Protocol-Based Methodology for Noise Analysis of Digital Networked Systems

A System-Level Protocol-Based Methodology for Noise Analysis of Digital Networked Systems

Electric Vehicle Automation through a Distributed Control System for Search and Rescue Operations

Anomaly Detection for Controller Area Network in Braking Control System With Dynamic Ensemble Selection

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