A Study on Fault Classification by EEMD Application of Gear Transmission Error

Sungho Park; Joo-Ho Choi

doi:10.7734/COSEIK.2017.30.2.169

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2017 Vol.30, Issue 2 Preview Page Next Page

A Study on Fault Classification by EEMD Application of Gear Transmission Error 전달오차의 EEMD적용을 통한 기어 결함분류연구

2017. pp. 169-177

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Abstract

In this paper, classification of spall and crack faults of gear teeth is studied by applying the ensemble empirical mode decomposition(EEMD) for the gear transmission error(TE). Finite element models of the gears with the two faults are built, and TE is obtained by simulation of the gears under loaded contact. EEMD is applied to the residuals of the TE which are the difference between the normal and faulty signal. From the result, the difference of spall and crack faults are clearly identified by the intrinsic mode functions(IMF). A simple test bed is installed to illustrate the approach, which consists of motor, brake and a pair of spur gears. Two gears are employed to obtain the TE for the normal, spalled, and cracked gears, and the type of the faults are separated by the same EEMD application process. In order to quantify the results, crest factors are applied to each IMF. Characteristics of spall and crack are well represented by the crest factors of the first and the third IMF, which are used as the feature signals. The classification is carried out using the Bayes decision theory using the feature signals acquired through the experiments.

Keywords

gear

fault diagnostics

transmission error

fault classification

EEMD

본 논문에서는 기어 전달오차의 EEMD 적용을 통한 기어 이빨의 박리결함과 균열결함의 분류법을 소개한다. 두 가지 결 함을 적용한 기어의 유한요소모델을 바탕으로 전달오차를 획득하고 전달오차에서 나타나는 두 가지 결함의 특징과 정상상 태의 전달오차와의 차이를 나타내는 RTE에서 나타나는 두 가지 결함의 특징을 확인했으며 유한요소해석 결과를 이용한 시 뮬레이션 신호를 구성하여 신호처리를 통한 RTE 획득과정을 구성하였다. 시뮬레이션 신호로부터 얻은 RTE의 EEMD 적용 을 통하여 박리과 균열의 신호가 각기 다른 IMF에서 비중이 크다는 것을 확인하였고, 이를 실험을 통해 검증하고자 하였다. 한 쌍의 기어와 서보모터, 파우더브레이크 그리고 기어의 회전량을 측정하기 위한 엔코더로 구성되어있는 테스트베드를 꾸 려 전달오차를 획득하였다. 두 개의 기어를 이용하여 정상, 박리, 균열 세가지 상황에 대한 전달오차를 획득하여 시뮬레이션 과 같은 과정을 거쳐 결함이 신호로 구분되는 것을 확인했다. 이를 정량화 하기위해 파고율을 각 IMF에 적용하였고 첫 번째 IMF와 세 번째 IMF의 파고율을 특징 신호로 선정하였다. 실험을 통해 확보된 데이터를 이용하여 Bayes decision 이론을 이 용하여 분류 방법을 제시하였다.

키워드

기어

고장진단

전달오차

결함분류

EEMD

References

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Information

Publisher :Computational Structural Engineering Institute of Korea
Publisher(Ko) :한국전산구조공학회
Journal Title :Journal of the Computational Structural Engineering Institute of Korea
Journal Title(Ko) :한국전산구조공학회 논문집
Volume : 30
No :2
Pages :169-177
Received Date : 2017-02-10
Revised Date : 2017-02-15
Accepted Date : 2017-02-27
DOI :https://doi.org/10.7734/COSEIK.2017.30.2.169

Journal of the Computational Structural Engineering Institute of Korea ISSN:1229-3059(Print) 2287-2302(Online) 한국전산구조공학회 논문집

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