Stochastic automata for outdoor semantic mapping using optimised signal quantisation

Caponetti, Fabio; Blas, Morten Rufus; Blanke, Mogens

doi:10.1016/j.conengprac.2010.11.010

Cited by 2 publications

(2 citation statements)

References 18 publications

(14 reference statements)

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“…The overall aim, and the main contribution, is to demonstrate how a set of general methods may be combined into a complete methodology in order to solve a real industrial problem, in this case, the challenging problem of automotive engine FDI (Nyberg and Stutte, 2004). In this sense, this work serves as an illustration of the state-of-practice in model-based FDI, and in particular sequential residual generation, e.g., Staroswiecki and Declerck (1989); Cassar and Staroswiecki (1997); Staroswiecki (2002); Pulido and Alonso-González (2004); Ploix et al (2005); Travé-Massuyès et al (2006); Blanke et al (2006) ;Svärd 3 and Nyberg (2010), and statistical residual evaluation, e.g., Willsky and Jones (1976); Gertler (1998); Basseville and Nikiforov (1993); Peng et al (1997); AlSalami et al (2006); ; Wei et al (2011);Svärd et al (2011b); Caponetti et al (2011). Moreover, as a secondary contribution, the usefulness and properties of the specific methods described in Svärd and Nyberg (2010); Svärd et al (2011a,b); Svärd (2012) are illustrated and discussed.…”

Section: Introductionmentioning

confidence: 99%

Automotive engine FDI by application of an automated model-based and data-driven design methodology

Svärd

Nyberg

Frisk

et al. 2013

Control Engineering Practice

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Fault detection and isolation (FDI) in automotive diesel engines is important in order to achieve and guarantee low exhaust emissions, high vehicle uptime, and efficient repair and maintenance. This paper illustrates how a set of general methods for model-based sequential residual generation and data-driven statistical residual evaluation can be combined into an automated design methodology. The automated design methodology is then utilized to create a complete FDI-system for an automotive diesel engine. The performance of the obtained FDI-system is evaluated using measurements from road drives and engine testbed experiments. The overall performance of the FDI-system is good in relation to the required design effort. In particular no specific tuning of the FDI-system, or any adaption of the design methodology, were needed. It is illustrated how estimations of the statistical powers of the fault detection tests in the FDI-system can be used to further increase the performance, specifically in terms of fault isolability.

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Section: Introductionmentioning

confidence: 99%

Automotive engine FDI by application of an automated model-based and data-driven design methodology

Svärd

Nyberg

Frisk

et al. 2013

Control Engineering Practice

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“…Several aspects of control and diagnosis of complex systems appeared in [1]. Applications are plenty and to mention a few from recent years, omitting many important contributions: [8], [65], [46], [84], [93], [44], [13], [17].…”

Section: Introductionmentioning

confidence: 99%

Diagnosis for Control and Decision Support for Autonomous Vehicles

Blanke

Hansen

Blas³

2016

Complex Systems

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Abstract. Diagnosis and, when possible, prognosis of faults are essential for safe and reliable operation. The area of fault diagnosis has emerged over three decades. The majority of studies are related to linear systems but real-life systems are complex and nonlinear. The development of methodologies coping with complex and nonlinear systems have matured and even though there are many unsolved problems, methodology and associated tools have become available in the form of theory and software for design. Genuine industrial cases have also become available. Analysis of system topology, referred to as structural analysis, has proven to be unique and simple in use and a recent extension to active structural techniques have made fault isolation possible in a wide range of systems. Following residual generation using these topology-based methods, deterministic and statistical change detection has proven very useful for online prognosis and diagnosis. For complex systems, results from nonGaussian detection theory have been employed with convincing results. The chapter presents the theoretical foundation for design methodologies that now appear as enabling technology for a new area of design of systems that are reliable in practise. Yet they are also affordable due to the use of fault-tolerant philosophies and tools that make engineering efforts minimal for their implementation. The chapter includes examples for an autonomous aircraft and a baling system for agriculture to illustrate the generic design procedures and real life results.

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Stochastic automata for outdoor semantic mapping using optimised signal quantisation

Cited by 2 publications

References 18 publications

Automotive engine FDI by application of an automated model-based and data-driven design methodology

Automotive engine FDI by application of an automated model-based and data-driven design methodology

Diagnosis for Control and Decision Support for Autonomous Vehicles

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