Fault Diagnosis of Active Magnetic Bearing-Rotor System via Vibration Images | |
Yan XS; Sun Z; Zhao JJ; Shi ZG; Zhang CA(张陈安) | |
Source Publication | SENSORS |
2019-01-02 | |
Volume | 19Issue:2Pages:AR244 |
ISSN | 1424-8220 |
Abstract | As important sources in fault diagnosis of rotary machinery, vibration signals are usually processed in the time or frequency domain as features to distinguish different classes of faults. However, these kinds of processing methods always ignore the corresponding relations among multiple signals, resulting in information loss. In this paper, a new fault description strategy named vibration image is proposed, based on which three new kinds of features are extracted, containing coupling information between different channels of vibration signals. Additionally, a new feature fusion method called two-layer AdaBoost is designed to train the fault recognition model, which avoids overfitting when the dataset is not large enough. Features based on vibration images combined with two-layer AdaBoost are adopted to diagnose faults of rotary machinery. Taking an active magnetic bearing-rotor system as the experimental platform, a dataset with four classes of faults is collected and our algorithm achieves good performance. Meanwhile, features based on vibration images and two-layer AdaBoost are both proved to be efficient separately. |
Keyword | fault diagnosis vibration signals active magnetic bearing rotary machinery AdaBoost |
DOI | 10.3390/s19020244 |
Indexed By | SCI ; EI |
Language | 英语 |
WOS ID | WOS:000458569300027 |
WOS Keyword | MACHINERY |
WOS Research Area | Chemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation |
WOS Subject | Chemistry ; Electrochemistry ; Instruments & Instrumentation |
Funding Organization | National Science and Technology Major Project of China [2011ZX069, 61305065] ; NSFC ; Strategic Priority Research Program of Chinese Academy of Sciences [XDA17030100] |
Classification | 二类/Q1 |
Ranking | 1 |
Contributor | Yan, XS ; 张陈安 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://dspace.imech.ac.cn/handle/311007/78511 |
Collection | 高温气体动力学国家重点实验室 |
Affiliation | 1.{Yan, Xunshi、Sun, Zhe、Zhao, Jingjing、Shi, Zhengang} Tsinghua Univ, Inst Nucl & New Energy Technol, Beijing 100084, Peoples R China 2.{Yan, Xunshi、Sun, Zhe、Zhao, Jingjing、Shi, Zhengang} Minist Educ, Key Lab Adv Reactor Engn & Safety, Beijing 100084, Peoples R China 3.{Yan, Xunshi、Sun, Zhe、Zhao, Jingjing、Shi, Zhengang} Collaborat Innovat Ctr Adv Nucl Energy Technol, Beijing 100084, Peoples R China 4.{Zhang, Chen-An} Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing 100190, Peoples R China |
Recommended Citation GB/T 7714 | Yan XS,Sun Z,Zhao JJ,et al. Fault Diagnosis of Active Magnetic Bearing-Rotor System via Vibration Images[J]. SENSORS,2019,19,2,:AR244. |
APA | Yan XS,Sun Z,Zhao JJ,Shi ZG,&Zhang CA.(2019).Fault Diagnosis of Active Magnetic Bearing-Rotor System via Vibration Images.SENSORS,19(2),AR244. |
MLA | Yan XS,et al."Fault Diagnosis of Active Magnetic Bearing-Rotor System via Vibration Images".SENSORS 19.2(2019):AR244. |
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