• Title/Summary/Keyword: Noise Identification

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Extending the SRIV Identification Algorithm to MIMO LMFD Models

  • Akroum, Mohamed;Hariche, Kamel
    • Journal of Electrical Engineering and Technology
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    • 제4권1호
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    • pp.135-142
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    • 2009

  • In this paper the Simplified Refined Instrumental Variable (SRIV) identification algorithm for SISO systems is extended to MIMO systems described by a Left Matrix Fraction Description (LMFD). The performance of the extended algorithm is compared to the well-known MIMO four-step instrumental variable (IV4) algorithm. Monte Carlo simulations for different signal to noise ratios are conducted to assess the performance of the algorithm. Moreover, the algorithm is applied to a simulated quadruple tank process.

  • https://doi.org/10.5370/JEET.2009.4.1.135 인용 PDF KSCI

THE PROBLEMS OF MODELLING AND IDENTIFICATION OF SOURCES OF NOISE IN MACHINES

  • Zbigniew Dabrowski;Stanilaw Radkowski
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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    • pp.758-763
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    • 1994

  • The work discusses the problems of modelling of the process of acoustic signal generation in machines. We have pointed out that in the task of minimizing of both moise and vibration, the key problem is identification of sources and paths of propagation, both in terms of their location and of definition of their characteristic features. Properly conducted identification makes possible the use of relatively simple mathematical models and this fact is particularly important for a broad application of the proposed methods in practice.

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