정렬불량 진단을 위한 유전알고리듬 기반 특징분석

Feature Analysis based on Genetic Algorithm for Diagnosis of Misalignment
  • 하정민; 
  • 안병현; 
  • 유현탁; 
  • 최병근

초록

An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.

키워드

유전 알고리듬; 정렬 불량; 특징 분석; 주파수 분석; Genetic Algorithms; Misalignment; Features Analysis; Frequency Analysis
제목
정렬불량 진단을 위한 유전알고리듬 기반 특징분석
제목 (타언어)
Feature Analysis based on Genetic Algorithm for Diagnosis of Misalignment
저자
하정민; 안병현; 유현탁; 최병근
DOI
10.5050/KSNVE.2017.27.2.189
발행일
2017
저널명
한국소음진동공학회논문집
권
27
호
2
페이지
189 ~ 194