1,721,012 research outputs found
Identification and fault diagnosis of nonlinear dynamic processes using hybrid models
No full textThis work addresses a novel approach for fault diagnosis of industrial processes using hybrid models. A nonlinear dynamic process can, in fact, be described as a composition of different affine submodels selected according to the process operating conditions. This paper concerns the identification of hybrid model parameters through input-output data affected by additive noise. The fault detection scheme adopted to generate residuals uses the estimated hybrid model. In order to show the effectiveness of the developed technique, the results obtained in the fault diagnosis of a real industrial plant are reported
Fuzzy system identification and fault diagnosis of industrial processes
No full textThis paper proposes a method for fault diagnosis of dynamic processes using the multiple model approach. The technique presented concerns the identification of a non-linear dynamic system based on Takagi-Sugeno (TS) fuzzy models. It can be shown that any non-linear dynamic process can, in fact, be described as a composition of several TS models selected according to process operating conditions. In particular, this work addresses a method for the identification and the optimal selection of the local TS models from a sequence of noisy input-output data acquired from the process. The diagnostic scheme exploits the TS fuzzy models to generate residuals. The developed technique was applied to the fault diagnosis of the input-output sensors of an industrial gas turbine and the results are also presented
Parameter identification for eigenstructure assignment in robust fault detection
No full textThe paper presents some results on parametric identification of linear systems applied to robust Fault Diagnosis schemes. In our approach, an equation error model is derived from input- output data. In particular, the error term takes into account disturbances (non measurable inputs), nonlinear and time-variant terms, measurement errors, etc. In this manner, state-space realization of the equation error model leads to define a disturbance distribution matrix related to the error term, and, thus, well-known eigenstructure assignment results for robust fault detection can be successfully applied. The proposed procedure has been tested on a industrial gas turbine prototype model in which a sensor fault is simulated. Results from this simulation campaign are also reported
Identification and Fault Diagnosis of nonlinear dynamic processes using hybrid models
No full textThis work addresses a novel approach for fault diagnosis of industrial processes using hybrid models. A nonlinear dynamic process can, in fact, be described as a composition of different affine sub-models selected according to the process operating conditions. This paper deals with the identification of hybrid model parameters through input-output data affected by additive noise. The fault detection scheme adopted to generate residuals uses the estimated hybrid model. In order to show the effectiveness of the developed technique, the results obtained in the fault diagnosis of a real industrial plant are reported
Parameter identification of piecewise affine dynamic models from input-output data
No full textThis paper addresses the identification of non-linear dynamic systems. A wide class of these systems can be described using non-linear time-invariant regression models, that can be approximated by means of piecewise affine prototypes with an arbitrary degree of accuracy. This work concerns the identification of piecewise affine model structure through input-output data acquired from a dynamic process. In order to show the effectiveness of the developed technique, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported
A low-cost home automation system based on power-line communication links
No full textIn this paper we present a feasible Home Automation
System scenario based on a very cheap distributed microcontroller
architecture, rather than on devices interconnected by an expensive
commercial bus. The means used for data communication is the
home powerline, so that the system doesn’t require placing other
cables in addition to standard electrical facilities
Noise rejection in parameters identification for piecewise linear fuzzy models
No full textThe fuzzy model identification problem from noisy data is addressed. The piecewise linear fuzzy model structure is used as a nonlinear prototype for a multi-input, single-output unknown system. The consequent of the fuzzy model is identified using noisy data, e.g. collected from experiments on a real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which has been modified and improved to be applied in fuzzy systems field
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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