e-journal

Monitoring for Nonlinear Multiple Modes Process Based on LL-SVDD-MRDA

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This study proposes an online monitoring technique for nonlinear multiple-mode problems in industrial processes. The contributions of the proposed technique are summarized as follows: 1) Lazy learning (LL), a new adaptive local modeling method, is introduced for multiple-mode process monitoring. In
this method, multiple modes are separated and accurately modeled online, and the between-mode dynamic process is considered. 2) The modified receptor density algorithm (MRDA) exhibiting superior nonlinear ability is introduced to analyze the residuals between the actual system output and the model-predicted output. The simulation of the Tennessee Eastman process with multiple operation modes shows that compared with other techniques mentioned in this study, the proposed technique performs more
accurately and is more suitable for nonlinear processes with multiple operation modes.
Note to Practitioners—This paper wasmotivated by the problem of fault detection of chemical process. Most chemical processes are nonlinear processes. Especially in the multiple-mode process, nonlinear is more significant, making the process more difficult to monitor. In this paper, we modify the receptor density algorithm (MRDA) and combine it with support vector data description (SVDD) and LL algorithm to monitor nonlinear multiple operation modes chemical processes. In LL-SVDD-MRDA, LL is introduced to solve multiple operation modes, SVDD is adopted to construct one-dimensional distance statistics to reflect the change in high-dimensional data and MRDA is used for nonlinear data monitoring. Our simulation demonstrates that LL-SVDD-MRDA is a highly competitive method for handling nonlinear multiple operation modes chemical processes monitoring.
Index Terms—Between-mode dynamic process, lazy learning (LL), modified receptor density algorithm (MRDA), multiple operationmodes, nonlinear, support vector data description (SVDD).

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Informasi Detail

Judul Seri

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING

No. Panggil

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Penerbit

New York : IEEE., 2014

Deskripsi Fisik

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 11, NO. 4, OCTOBER 2014

Bahasa

English

ISBN/ISSN

1545-5955

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

VOL. 11, NO. 4, OCTOBER 2014

Subjek

TEKNIK

Info Detail Spesifik

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Pernyataan Tanggungjawab

Yuli/Agus

Versi lain/terkait

Lampiran Berkas

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