Detecting Enclosed Board Channel of Data Acquisition System Using Probabilistic Neural Network with Null Matrix

Autor:	Dapeng Zhang, Zhiling Lin, Zhiwei Gao
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	fault detection and diagnosis board channel probabilistic neural network Chemical technology TP1-1185
Zdroj:	Sensors, Vol 22, Iss 15, p 5559 (2022)
Druh dokumentu:	article
ISSN:	1424-8220
DOI:	10.3390/s22155559
Popis:	The board channel is a connection between a data acquisition system and the sensors of a plant. A flawed channel will bring poor-quality data or faulty data that may cause an incorrect strategy. In this paper, a data-driven approach is proposed to detect the status of the enclosed board channel based on an error time series obtained from multiple excitation signals and internal register values. The critical faulty data, contrary to the known healthy data, are constructed by using a null matrix with maximum projection and are labelled as training examples together with healthy data. Finally, the status of the enclosed board channel is validated by a well-trained probabilistic neural network. The experimental results demonstrate the effectiveness of the proposed method.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/1a9f8a2685ba465fb2b2d51cf8f31acb Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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