Verification of a model-based diagnosis system for on-line detection of the moisture content of power transformer insulations using finite element calculations

2008 ◽  
Author(s):  
Wolfgang Hribernik ◽  
Bernhard Kubicek ◽  
Gert Pascoli ◽  
Klaus Frohlich
Keyword(s):  
Finite Element ◽  
Moisture Content ◽  
Power Transformer ◽  
Line Detection ◽  
Diagnosis System ◽  
Model Based ◽  
Finite Element Calculations ◽  
On Line

Study and Analysis of On-Line Detection and Fault Diagnosis System of Rolling Bearing

2013 ◽  
Vol 443 ◽  
pp. 218-222
Author(s):  
Jing Zi Wei ◽  
Ran Zhang
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Fault Detection And Diagnosis ◽  
Detection Methods ◽  
Line Detection ◽  
Diagnosis System ◽  
Bearing Fault ◽  
On Line ◽  
Fault Diagnosis System

This paper first of all gives an introduction to the structure of rolling bearing, development stage of fault and the main fault types; then, it makes an analysis of the common detection methods and the technologies involved in rolling bearing fault; at last, based on the emphasis on the rolling bearing on-line detection and fault diagnosis system of acoustic emission technology, it elaborates the basic principles of acoustic emission, rolling bearing fault detection and diagnosis system experiment setting. Meanwhile, it introduces modern signal processing technology into acoustic emission information feature extraction and state recognition, such as wavelet analysis and wavelet packet analysis.

A Model Based Computationally Efficient Method for On-Line Detection of Chatter in Milling

2013 ◽  
Author(s):  
Lei Ma ◽  
Shreyes Melkote ◽  
James Castle
Keyword(s):  
Efficient Method ◽  
Chip Thickness ◽  
Line Detection ◽  
Chatter Detection ◽  
Computationally Efficient ◽  
Model Based ◽  
Force Signal ◽  
On Line ◽  
Regeneration Effect ◽  
Milling Chatter

This paper presents a model-based computationally efficient method for detecting milling chatter in its incipient stages. Based on a complex exponentials model for the dynamic chip thickness, the chip regeneration effect is amplified and isolated from the cutting force signal for early chatter detection. The proposed method is independent of the cutting conditions. With the aid of a one tap adaptive filter, the proposed method is also found to be able to distinguish between chatter and the dynamic transients in the cutting forces due to sudden changes in workpiece geometry and tool entry/exit. The proposed method is experimentally validated.

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