Application of Oil Analysis to the Condition Monitoring of Large Engineering Machinery

被引：0

作者：

He, Qingfei ^{[1
]}

Chen, Guiming ^{[1
]}

Chen, Xiaohu ^{[1
]}

Yao, Chunjiang ^{[1
]}

机构：

[1] Xian Res Inst High Tech, Sect 501, Xian, Peoples R China

来源：

PROCEEDINGS OF 2009 8TH INTERNATIONAL CONFERENCE ON RELIABILITY, MAINTAINABILITY AND SAFETY, VOLS I AND II: HIGHLY RELIABLE, EASY TO MAINTAIN AND READY TO SUPPORT | 2009年

关键词：

Oil analysis; large engineering machinery; condition monitoring; spectroscopic analysis; ferrography analysis;

D O I：

暂无

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The running condition of large engineering machine is evaluated by physical and chemical analysis, spectroscopic analysis, ferrography analysis and oil contaminated analysis. According to the questions that occur in the running equipment, the paper proposes some feasible suggestions and measures. Monitoring examples demonstrate that it is effective application of oil analysis to the condition monitoring and fault diagnosis.

引用

页码：1100 / 1103

页数：4

共 50 条

[31] A machine learning approach for the condition monitoring of rotating machinery [J].

Kateris, Dimitrios ;

Moshou, Dimitrios ;

Pantazi, Xanthoula-Eirini ;

Gravalos, Ioannis ;

Sawalhi, Nader ;

Loutridis, Spiros .

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2014, 28 (01) :61-71

[32] Canonical correlation analysis of dimension reduced degradation feature space for machinery condition monitoring [J].

Li, Xiaomeng ;

Wang, Yi ;

Tang, Baoping ;

Qin, Yi ;

Zhang, Guangyao .

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 182

[33] An Application of Feature Engineering and Machine Learning Algorithms on Condition Monitoring of SiC Converters [J].

Toussi, Afshin Loghmani Moghaddam ;

Bahman, Amir Sajjad ;

Iannuzzo, Francesco ;

Blaabjerg, Frede .

2021 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), 2021, :3652-3658

[34] The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery [J].

Loutas, T. H. ;

Roulias, D. ;

Pauly, E. ;

Kostopoulos, V. .

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (04) :1339-1352

[35] Condition Monitoring with Prediction Based on Diesel Engine Oil Analysis: A Case Study for Urban Buses [J].

Raposo, Hugo ;

Farinha, Jose Torres ;

Fonseca, Inacio ;

Ferreira, L. Andrade .

ACTUATORS, 2019, 8 (01)

[36] Gearbox Non-ferrous Metal Bearing Wear Condition Monitoring Based on Oil Analysis [J].

Jiang, Xufeng ;

Liu, Fang ;

Zhao, Pengcheng .

APPLIED MECHANICS, MATERIALS, INDUSTRY AND MANUFACTURING ENGINEERING, 2012, 164 :73-+

[37] Oil analysis cost-effective machine condition monitoring technique [J].

Newell, GE .

INDUSTRIAL LUBRICATION AND TRIBOLOGY, 1999, 51 (03) :119-124

[38] Study on Condition Monitoring in Petrochemical Equipment Using Oil Analysis Technology [J].

Xie, Xiaopeng ;

Feng, Wei ;

Liao, Qiansheng .

ADVANCED TRIBOLOGY, 2009, :942-946

[39] Low-cost condition monitoring sensor for used oil analysis [J].

Raadnui, S ;

Kleesuwan, S .

WEAR, 2005, 259 :1502-1506

[40] Condition Monitoring on Complex Machinery for Predictive Maintenance and Process Control [J].

Dai, Yuan ;

Chen, C. L. Philip ;

Xu, Xiao-Yan ;

Hu, Peng .

2008 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), VOLS 1-6, 2008, :3594-+

← 1 2 3 4 5 →