On-line valve monitoring and diagnosis

1990 ◽  
Vol 3 (1) ◽  
pp. 25-29
Author(s):  
J. Schreurs ◽  
F. Bednar
Keyword(s):  
Monitoring And Diagnosis ◽  
On Line

Evaluation of On-Line Signals for Roundness Monitoring

2012 ◽  
Vol 498 ◽  
pp. 85-90
Author(s):  
Eustaquio García Plaza ◽  
Pedro Jose Núñez López ◽  
A.R. Martin
Keyword(s):  
Cutting Forces ◽  
Mechanical Vibration ◽  
Acoustic Emissions ◽  
Machining Process ◽  
Roundness Error ◽  
Monitoring And Diagnosis ◽  
Orthogonal Components ◽  
On Line ◽  
Cutting Processes ◽  
Machining Operations

The cutting forces, mechanical vibration and acoustic emission signals obtained using dynamometer, accelerometer, and acoustic emissions sensors have been extensively used to monitor several aspects of the cutting processes in automated machining operations. This study assesses the significance of these on-line signals for the real-time monitoring and diagnosis of the roundness error in automated cylindrical turning processes. The system developed is based on predictive models obtained by regression techniques employing the orthogonal components of the cutting forces, mechanical vibration and acoustic emissions, and combines all three types of sensors into one system. This monitoring system enables the on-line monitoring and diagnosis of roundness error by registering, visualizing, and characterizing the signals obtained during the machining process.

An Efficient Diagnosis Technique for Variations of Shaft-Bow and Unbalance

2009 ◽  
Author(s):  
Tachung Yang ◽  
Ming-Wei Hsu
Keyword(s):  
Power Plants ◽  
Search Strategy ◽  
Search Results ◽  
Monitoring And Diagnosis ◽  
Turbine Generators ◽  
Vibration Responses ◽  
On Line ◽  
The Common ◽  
Types Of Faults ◽  
Diagnosis Technique

This paper focuses on the diagnosis of two types of faults, unbalance and shaft-bow, which are the common faults occurring in rotating machines. An efficient fault diagnostic method is proposed to identify the locations and amounts of faults based on the vibration responses of the rotor without prior knowledge of the numbers and locations of the faults. The proposed method achieves fast diagnosis by orderly searching the possible locations of faults, avoiding exploring all possible combinations of faults, and fully utilizing previous search results. Based on the unique search strategy, the proposed method is suitable for on-line monitoring and diagnosis of the gradual variations of shaft-bow and unbalance of large rotating machinery of fixedly rotating speeds, like steam turbine-generators of power plants.

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