定性モデルにもとづくラフ集合の決定ルールを利用したビル空調設備異常検知方法

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2018/12/01

タイトル(英語): Fault Detection Method with Decision Rule of Rough Set based on Qualitative Model in Building Air-conditioning System

著者名: 湯本　真樹（近畿大学理工学部電気電子工学科）

著者名(英語): Masaki Yumoto (Department of Electric and Electronic Engineering, Faculty of Science and Engineering, Kindai University)

キーワード: ビル空調システム，異常検知，測定値時系列データ，定性モデル，決定ルール，データセット　　building air-conditioning system，fault detection，measured time-series data，qualitative model，decision rule，data set

要約(英語): In a building air-conditioning system, measured time-series data is observed from many kinds of sensors. It is difficult to detect the fault by the administrators because only the limited experts can diagnose the unusual system. Thus, a new method is required, which can detect faults from measured data using computers automatically. This paper proposes the method of fault detection with rough set based on qualitative model of measured time-series data in building air- conditioning system. First, the proposal method converts target measured time-series data into data set based on target qualitative model. Next, this method constructs the decision rule of a rough set by comparison of the data set for every block. Finally, this method detects fault through comparison of evaluation values. Through practical experiments, it is confirmed that the proposal method can detect faults without expert knowledge in a building air-conditioning system.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.138 No.12 （2018） 特集：電気・電子・情報関係学会東海支部連合大会

本誌掲載ページ: 1613-1624 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/138/12/138_1613/_article/-char/ja/