Integrating model checking with HiP-HOPS in model-based safety analysis

Sharvia, Septavera; Papadopoulos, Yiannis

doi:10.1016/j.ress.2014.10.025

Cited by 52 publications

(27 citation statements)

References 20 publications

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“…Model-based safety analysis has been developed during the last years to help the analysis of complex systems, taking as a central element the model and automating the analysis of extended fault models [19]. This new approach intends to overcome the limitations mentioned in Section 2.2.…”

Section: State Of the Art Of Model-based Fault Modes And Effects Analmentioning

confidence: 99%

“…Among others, from the railway traction application point of view, the HiP-HOPS methodology and its associated tools are the most interesting ones [19,22]. This tool, implemented as a Matlab/Simulink tool, allows the analyst to define Figure 3.…”

Section: Failure Logic Modeling Approachmentioning

confidence: 99%

“…Nevertheless, as it was mentioned in [18], the main limitation that FLM techniques have to face is the lack of tools to analyze the dynamic behavior of the system. They do not consider the changes in the states of a system and are not able to model its dynamic or temporal behavior [19]. A common framework to present the structure and analyze the propagation of the system is defined, but the information about the dynamic behavior of the system (operation modes, reaction to faults, etc.)…”

Section: Failure Logic Modeling Approachmentioning

confidence: 99%

See 2 more Smart Citations

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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Fault analysis in industrial equipment has been usually performed using classical techniques such as failure modes and effects analysis (FMEA) and fault tree analysis (FTA). Model-based fault analysis has been used during the last several years in order to overcome the limitations of classical methods when complex industrial equipment has to be analyzed. In railway and automotive sectors, the development and validation of new products are based on hardware-in-the-loop (HIL) platforms. In this chapter, a methodology to enhance classical FMEAs is presented. Based on HIL simulations, the objective is to improve the results of the fault analysis with quantitative information about the effects of each fault mode. In this way, the impact of the fault analysis in the design of the traction system, the development of new diagnostic functionalities and in the maintenance tasks will increase.

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Section: State Of the Art Of Model-based Fault Modes And Effects Analmentioning

confidence: 99%

Section: Failure Logic Modeling Approachmentioning

confidence: 99%

Section: Failure Logic Modeling Approachmentioning

confidence: 99%

See 1 more Smart Citation

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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“…This framework is implemented in the ESSaRel (Embedded Systems Safety and Reliability Analyser) tool. Last, (Bozzano et al 2015) proposes recently to check properties of AltaRica OCAS models by using the NuSMV verification tool while (Sharvia and Papadopoulos 2015) focuses on verification of HiP-HOPS models with the same tool. Despite their interest, none of these works has addressed models for dynamic, repairable, and reconfigurable systems.…”

Section: Introductionmentioning

confidence: 99%

Formal Verification of Safety Analysis Models of Repairable and Reconfigurable Systems

2017

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This paper proposes a method to formally check whether formal properties hold on a dynamic model which has been designed by experts for Model Based Safety Analysis/Assessment. As repairable and reconfigurable systems are considered, this model is assumed to be described in the Generalized Boolean-logic Driven Markov Processes (GBDMP) modelling framework. Translation rules are given to obtain a formal model that describes correctly the evolution of the initial model with the semantics of the verification tool. The approach is exemplified on a simple case of standby redundancy.

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“…With the increasing of system scale and the growing of functional requirements, the complex large-scale systems gradually tend to be highly integrated and employ complex architectures coupling hardware with software, where numerous embedded components are usually adopted [1]. Classical safety analysis techniques, such as Failure Mode and Effects Analysis (FMEA) [2], Fault Tree Analysis (FTA) [3] and Hazard and Operability Analysis (HAZOP) [4], which depend mainly on analysts' personal skills, experiences and active status, have gradually had difficulty to adapting to this new situation.…”

Section: Introductionmentioning

confidence: 99%

A fault propagation modeling and analysis method based on model checking

Jiao

Fan

et al. 2016

2016 Annual Reliability and Maintainability Symposium (RAMS)

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& CONCLUSIONSFault propagation identification is an indispensable task in complex system safety analysis. With the growing of system scale and complexity, it is hard for the traditional safety analysis techniques, which depend mainly on analysts' personal skills and experiences, to keep completeness and timeliness; moreover, some failure modes may be neglected and failure effects misjudged during the analysis. Formal science provides a new way to solve this problem, where formal verification method such as model checking can automatically validate whether the system design satisfies the given safety requirements, which can reduce an analysts' repetitive work and design cost, and improve the efficiency and quality of safety analysis. However, there is lack of a deliberate and reasonable way to build system models because of the diversity and flexibility of languages used for model checking, which results in that it is difficult to specify and model system quickly and accurately, and leads to some deviation in model checking.In this paper, a system modeling and safety property specifying approach using symbolic language SMV is proposed, including guidance on the mapping relationships between the formal language elements and system functions, architecture and failure modes; moreover, how to define system specifications and safety requirements using temporal logic formulas is discussed as well. Finally, a case study about airborne system safety analysis is provided, in which the counter-examples that do not meet system specifications can be identified automatically using model checker NuSMV to find out fault events and their propagation that can result in accidents.

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Integrating model checking with HiP-HOPS in model-based safety analysis

Cited by 52 publications

References 20 publications

Model-Based Fault Analysis for Railway Traction Systems

Model-Based Fault Analysis for Railway Traction Systems

Formal Verification of Safety Analysis Models of Repairable and Reconfigurable Systems

A fault propagation modeling and analysis method based on model checking

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