M
Mattias Nyberg
Researcher at Royal Institute of Technology
Publications - 155
Citations - 2434
Mattias Nyberg is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Fault detection and isolation & Residual. The author has an hindex of 25, co-authored 151 publications receiving 2301 citations. Previous affiliations of Mattias Nyberg include Linköping University & Scania AB.
Papers
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An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis
TL;DR: A new algorithm for computing all minimal overconstrained subsystems in a model is proposed and it is shown that the time complexity under certain conditions is much better for the new algorithm.
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Model Based Diagnosis of the Air Path of an Automotive Diesel Engine
TL;DR: In this article, a model based diagnosis system for the airpath of a turbo-charged diesel engine with EGR is constructed, where the faults considered are air mass-flow sensor, intake manifold pressure sensor, air-leakage, and the EGR-valve stuck in closed position.
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Model-based diagnosis of an automotive engine using several types of fault models
TL;DR: It is shown how many different types of fault models can be used within one common diagnosis system, e.g., additive and multiplicative faults, and using the same underlying design principle.
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Brief A minimal polynomial basis solution to residual generation for fault diagnosis in linear systems
Erik Frisk,Mattias Nyberg +1 more
TL;DR: It is shown that the minimal polynomial basis approach can find all possible residual generators and explicitly those of minimal order.
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Residual Generators for Fault Diagnosis Using Computation Sequences With Mixed Causality Applied to Automotive Systems
Carl Svärd,Mattias Nyberg +1 more
TL;DR: A novel residual generation method that enables simultaneous use of integral and derivative causality, i.e., mixed causality and also handles equation sets corresponding to algebraic and differential loops in a systematic manner is presented.