Defect Diagnostics of Rolling Element Bearing Using Fuzzy Dichotomy Technique

スポンサーリンク

概要

• 論文の詳細を見る

• The monitoring and diagnostics of the bearing have been received considerable attention for many years because the majority of problems in rotating machines are caused by faulty bearings. The malfunction of rotating machinery in plants due to some defects may cause shutdown of the plants, resulting in high maintenance cost. Overly generalized predictions are problematic due to concept classification. In particular, the boundaries among classes are not always clearly defined. To avoid such problems, the idea of fuzzy classification was proposed. In this paper, in order to automatize the diagnosis of a rolling element bearing using the fuzzy classification along with their construction algorithm, the fuzzy dichotomy techique as an acquisition of structured knowledge from held case history data is used for validating the diagnosis capability.

• 一般社団法人日本機械学会の論文
• 2000-06-15

著者

• Lim Dons-soo

  School Of Mechanical Engineering Pukyong National University

• YANG Bo-Suk

  School of Mechanical Engineering, Pukyong National University

• JO Young-Chun

  School of Mechanical Engineering, Pukyong National University

• Jo Young-chun

  School Of Mechanical Engineering Pukyong National University

• Yang Bo-suk

  School Of Mechanical Engineering Pukyong National University

• Yang Bo-suk

  School Of Mechanical Engineering Pukong National University

• Lim Dong-Soo

  School of Mechanical Engineering, Pukyong National University

関連論文

• Defect Diagnostics of Rolling Element Bearing Using Fuzzy Dichotomy Technique
• 206 FAULT DIAGNOSIS SYSTEM OF INDUCTION MOTORS USING FEATURE EXTRACTION, FEATURE SELECTION AND CLASSIFICATION ALGORITHM(General Session I)
• Fault Diagnosis System of Induction Motors Using Feature Extraction, Feature Selection and Classification Algorithm(Advanced Technology of Vibration and Sound)
• Support Vector Machine for Machine Fault Diagnosis and Prognosis

スポンサーリンク