Remote Fault Diagnosis System for Marine Power Machinery System

Data Mining ◽  
2013 ◽  
pp. 2174-2192
Author(s):  
Chengqing Yuan ◽  
Xinping Yan ◽  
Zhixiong Li ◽  
Yuelei Zhang ◽  
Chenxing Sheng ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Heavy Load ◽  
Diagnosis System ◽  
Power Machinery ◽  
Diagnosis Method ◽  
On Line ◽  
Identification Approach ◽  
Fault Diagnosis System ◽  
Machinery System ◽  
Remote Fault Diagnosis

Marine power machinery parts are key equipments in ships. Ships always work in rigorous conditions such as offshore, heavy load, et cetera. Therefore, the failures in marine power machinery would badly threaten the safety of voyages. Keeping marine power machineries running reliably is the guarantee of voyage safety. For the condition monitoring and fault diagnosis of marine power machinery system, this study established the systemic condition identification approach for the tribo-system of marine power machinery and developed integrated diagnosis method by combining on-line and off-line ways for marine power machinery. Lastly, the remote fault diagnosis system was developed for practical application in marine power machinery, which consists of monitoring system in the ship, diagnosis system in laboratory centre, and maintenance management & maintenance decision support system.

Remote Fault Diagnosis System for Marine Power Machinery System

2013 ◽  
pp. 292-311
Author(s):  
Chengqing Yuan ◽  
Xinping Yan ◽  
Zhixiong Li ◽  
Yuelei Zhang ◽  
Chenxing Sheng ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Heavy Load ◽  
Diagnosis System ◽  
Power Machinery ◽  
Diagnosis Method ◽  
On Line ◽  
Identification Approach ◽  
Fault Diagnosis System ◽  
Machinery System ◽  
Remote Fault Diagnosis

Marine power machinery parts are key equipments in ships. Ships always work in rigorous conditions such as offshore, heavy load, et cetera. Therefore, the failures in marine power machinery would badly threaten the safety of voyages. Keeping marine power machineries running reliably is the guarantee of voyage safety. For the condition monitoring and fault diagnosis of marine power machinery system, this study established the systemic condition identification approach for the tribo-system of marine power machinery and developed integrated diagnosis method by combining on-line and off-line ways for marine power machinery. Lastly, the remote fault diagnosis system was developed for practical application in marine power machinery, which consists of monitoring system in the ship, diagnosis system in laboratory centre, and maintenance management & maintenance decision support system.

Remote Fault Diagnosis System of Ultrahigh Speed Grinding Based on Multi-Agent

2009 ◽  
Vol 76-78 ◽  
pp. 67-71
Author(s):  
Wan Shan Wang ◽  
Tian Biao Yu
Keyword(s):  
Fault Diagnosis ◽  
Theoretical Research ◽  
Case Based Reasoning ◽  
Diagnosis System ◽  
Knowledge Reasoning ◽  
Diagnosis Method ◽  
Multi Agent ◽  
Fault Diagnosis System ◽  
Set Up ◽  
Remote Fault Diagnosis

A remote fault diagnosis method for ultrahigh speeding grinding based on multi-agent is presented. The general faults of ultrahigh speed grinding are analyzed and diagnosis model based on multi-agent is established, the dialogue layer, problem decomposition layer, control layer and problem solving layer in the process of diagnosis are studied and the knowledge reasoning model of fault diagnosis is set up based case-based reasoning (CBR) combining rule-based reasoning (RBR). Based on theoretical research, a remote fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running prove the theory is correctness and the technology is feasibility.

Study of Remote Fault Diagnosis System to Wind Generator Gearbox Based on DSP

2012 ◽  
Vol 566 ◽  
pp. 568-571 ◽  
Author(s):  
Hong Xia Pan ◽  
Yang Gao
Keyword(s):  
Fault Diagnosis ◽  
Mobile Communications ◽  
Digital Signal ◽  
Fault Classification ◽  
Diagnosis System ◽  
Wind Generator ◽  
Fault Type ◽  
On Line ◽  
Fault Diagnosis System ◽  
Remote Fault Diagnosis

In order to meet the wind generator gearbox remote condition monitoring and fault diagnosis requirements, using TI's C2000 series DSP-TMS320F2812 processor as its core, the wind generator gearbox remote fault diagnosis system was designed, in this paper. The use of TMS320F2812-rich peripheral modules to build the system's hardware architecture, including the analog signals, frequency signals, digital signal data acquisition, and has Ethernet, GSM mobile communications. For wind generator gearbox bearings and gears common faults, using FIR digital filter, FFT Fourier transform, cepstrum, detailed spectral analysis and other methods to extract the fault characteristic information. The combination of extracted feature vectors, input to BP neural network trained for fault classification and identification, derived fault type, location and extent. Tests show that the system can go a long on-line monitoring, and can correctly identify the fault. It has small size, multi-functional, practical and strong features, particularly suitable for wind generator remote on-line monitoring and fault diagnosis.

Fault Diagnosis System Based on Fuzzy Theory of Vehicle Air Conditioner

2013 ◽  
Vol 329 ◽  
pp. 324-328
Author(s):  
Ying Hui Wang ◽  
Shu Sheng Xiong ◽  
Wen Lang ◽  
Yi Tian Tang
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Theory ◽  
Air Conditioner ◽  
Diagnosis System ◽  
Diagnosis Method ◽  
Fault Diagnosis System

To maintain the vehicle air conditioner efficiently, a fault diagnosis system based on fuzzy theory is prospected in this paper. A fault diagnosis method based on fuzzy theory was given. And according to the method, a fault diagnosis program was written with labview. Experiments proved that the fault diagnosis program was stable and functional. The accuracy of this fault diagnosis system is more than 80%. The system can be used to diagnosed the malfunction of vehicle air conditioner efficiently and discover the potential fault in time, helping to eliminate hidden dangers.

The Developmental Research on Fault Diagnosis System of Mine Fan Based on Grey Theory

2011 ◽  
Vol 105-107 ◽  
pp. 656-659 ◽  
Author(s):  
Dong Chen Li
Keyword(s):  
Fault Diagnosis ◽  
Data Storage ◽  
Grey Theory ◽  
Developmental Research ◽  
Software Platform ◽  
Diagnosis System ◽  
Fault Monitoring ◽  
On Line ◽  
Fault Diagnosis System

The system uses GRAP in Grey Theory to conduct fault diagnosis of fan and chooses LabWEV for software platform, developing a set of system aiming at fault monitoring on line and diagnosis of mine fan in order to guarantee the running state of fan continuously and efficiently . This system has functions of monitoring on line,fault diagnosis,fault warning,data storage, history inquiry and so on.

Fuzzy Diagnosis of Tapping Process Fault

2009 ◽  
Vol 626-627 ◽  
pp. 207-212 ◽  
Author(s):  
H.L. Xue ◽  
Le Wang ◽  
Xue Yong Chen ◽  
Gui Cheng Wang
Keyword(s):  
Experimental Study ◽  
Fault Diagnosis ◽  
Fuzzy Theory ◽  
Weight Matrix ◽  
Diagnosis System ◽  
Process Failure ◽  
Diagnosis Method ◽  
Fault Diagnosis System ◽  
Fuzzy Diagnosis ◽  
Types Of Faults

Based on analyzing the problem of tap worn and broken in the tapping process, the faults in tapping process are classified into four types: tap worn, chips jamming, uneven hardness of material and the tapping process failure; According to the fuzzy theory, this paper describes the torque characteristic of the four types of faults, ascertains the characteristic vector of fault, presents the weight matrix among faults, puts forward the judgment method of system faults and establishes the fuzzy fault diagnosis system in tapping process. The experimental study shows that the fuzzy diagnosis method can effectively identify the four types of faults in tapping process and guard against tap broken.

scholarly journals Design of Remote Fault Diagnosis System for Medium and Small-sized Enterprises

2011 ◽  
Vol 24 ◽  
pp. 48-52
Author(s):  
Jianwei Li ◽  
Zhihua Yuan ◽  
Hui Tian ◽  
Aiqin Liang
Keyword(s):  
Fault Diagnosis ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
Remote Fault Diagnosis
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