1,618 research outputs found
A Topological-Based Method for Allocating Sensors by Using CSP Techniques
Model-based diagnosis enables isolation of faults of a system.
The diagnosis process uses a set of sensors (observations) and a model
of the system in order to explain a wrong behaviour. In this work, a
new approach is proposed with the aim of improving the computational
complexity for isolating faults in a system. The key idea is the addition of
a set of new sensors which allows the improvement of the diagnosability
of the system. The methodology is based on constraint programming
and a greedy method for improving the computational complexity of the
CSP resolution. Our approach maintains the requirements of the user
(detectability, diagnosability,. . .).Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
An Integration of FDI and DX Techniques for Determining the Minimal Diagnosis in an Automatic Way
Two communities work in parallel in model-based diagnosis:
FDI and DX. In this work an integration of the FDI and the DX communities
is proposed. Only relevant information for the identification of the
minimal diagnosis is used. In the first step, the system is divided into
clusters of components, and each cluster is separated into nodes. The
minimal and necessary set of contexts is then obtained for each cluster.
These two steps automatically reduce the computational complexity
since only the essential contexts are generated. In the last step, a signature
matrix and a set of rules are used in order to obtain the minimal
diagnosis. The evaluation of the signature matrix is on-line, the rest of
the process is totally off-line.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
Diagnosing Errors in DbC Programs Using Constraint Programming
Model-Based Diagnosis allows to determine why a correctly
designed system does not work as it was expected. In this paper, we propose
a methodology for software diagnosis which is based on the combination
of Design by Contract, Model-Based Diagnosis and Constraint
Programming. The contracts are specified by assertions embedded in the
source code. These assertions and an abstraction of the source code are
transformed into constraints, in order to obtain the model of the system.
Afterwards, a goal function is created for detecting which assertions or
source code statements are incorrect. The application of this methodology
is automatic and is based on Constraint Programming techniques.
The originality of this work stems from the transformation of contracts
and source code into constraints, in order to determine which assertions
and source code statements are not consistent with the specification.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
Applying Constraint Databases in the Determination of Potential Minimal Conflicts to Polynomial Model-Based Diagnosis
Model-based Diagnosis allows the identification of the parts
which fail in a system. The models are based on the knowledge of the
system to diagnose, and may be represented by constraints associated
to the components. The variables of these constraints can be observable
or non-observable, depending on the situation of the sensors. In order to
obtain the potential minimal diagnosis in a system, an important issue is
related to finding out the potential minimal conflicts in an efficient way.
We consider that Constraint Databases represent an excellent option in
order to solve this problem in complex systems.
In this work we have used a novel logical architecture of Constraint
Databases which has allowed obtaining these potential conflicts by means
of the corresponding queries. Moreover, we have considered Gröbner
Bases as a projection operator to obtain the potential minimal conflicts
of a system. The first results obtained on this work, which are shown in
a heat exchangers example, have been very promising.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
Developing a labelled object-relational constraint database architecture for the projection operator
Current relational databases have been developed in order to improve the handling of
stored data, however, there are some types of information that have to be analysed for
which no suitable tools are available. These new types of data can be represented and treated
as constraints, allowing a set of data to be represented through equations, inequations
and Boolean combinations of both. To this end, constraint databases were defined and
some prototypes were developed. Since there are aspects that can be improved, we propose
a new architecture called labelled object-relational constraint database (LORCDB). This provides
more expressiveness, since the database is adapted in order to support more types of
data, instead of the data having to be adapted to the database. In this paper, the projection
operator of SQL is extended so that it works with linear and polynomial constraints and
variables of constraints. In order to optimize query evaluation efficiency, some strategies
and algorithms have been used to obtain an efficient query plan.
Most work on constraint databases uses spatiotemporal data as case studies. However,
this paper proposes model-based diagnosis since it is a highly potential research area,
and model-based diagnosis permits more complicated queries than spatiotemporal examples.
Our architecture permits the queries over constraints to be defined over different sets
of variables by using symbolic substitution and elimination of variables.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-0
NMUS: Structural Analysis for Improving the Derivation of All MUSes in Overconstrained Numeric CSPs
Models are used in science and engineering for experimentation,
analysis, model-based diagnosis, design and planning/sheduling
applications. Many of these models are overconstrained Numeric Constraint
Satisfaction Problems (NCSP), where the numeric constraints
could have linear or polynomial relations. In practical scenarios, it is
very useful to know which parts of the overconstrained NCSP instances
cause the unsolvability.
Although there are algorithms to find all optimal solutions for this
problem, they are computationally expensive, and hence may not be applicable
to large and real-world problems. Our objective is to improve
the performance of these algorithms for numeric domains using structural
analysis. We provide experimental results showing that the use of
the different strategies proposed leads to a substantially improved performance
and it facilitates the application of solving larger and more
realistic problems.Ministerio de Educación y Ciencia DIP2006-15476-C02-0
Improving the Computational Efficiency in Symmetrical Numeric Constraint Satisfaction Problems
Models are used in science and engineering for experimentation,
analysis, diagnosis or design. In some cases, they can be considered
as numeric constraint satisfaction problems (NCSP). Many models
are symmetrical NCSP. The consideration of symmetries ensures that
NCSP-solver will find solutions if they exist on a smaller search space.
Our work proposes a strategy to perform it. We transform the symmetrical
NCSP into a newNCSP by means of addition of symmetry-breaking
constraints before the search begins. The specification of a library of possible
symmetries for numeric constraints allows an easy choice of these
new constraints. The summarized results of the studied cases show the
suitability of the symmetry-breaking constraints to improve the solving
process of certain types of symmetrical NCSP. Their possible speedup
facilitates the application of modelling and solving larger and more
realistic problems.Ministerio de Ciencia y Tecnología DIP2003-0666-02-
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