Condition Assessment of Air Cooled Electric Generators With EMI Diagnostics

2013 ◽  
Author(s):  
James E. Timperley
Keyword(s):  
Case Studies ◽  
Electromagnetic Interference ◽  
Condition Assessment ◽  
Mechanical Condition ◽  
Data Comparison ◽  
On Line ◽  
Electric Generators

Since 1980 EMI (electromagnetic interference) Diagnostics has provided information on the electrical and mechanical condition of several hundred electric generators. This on-line technique has been applied to many sizes and designs of 2-pole and 4-pole steam and combustion turbines, air cooled and hydrogen cooled generators. This paper provides several case studies of electrical and mechanical deterioration identified with EMI Diagnostics for air cooled machines. Several methods that enhance analysis of EMI Diagnostics are presented, such as trending, data comparison at different loads as well as data comparison on-line and off-line but energized.

Generator Condition Assessment Through EMI Diagnostics

2008 ◽  
Author(s):  
James E. Timperley
Keyword(s):  
Radio Frequency ◽  
Electromagnetic Interference ◽  
Good Condition ◽  
Condition Assessment ◽  
Current Transformer ◽  
Stator Winding ◽  
Electrical Systems ◽  
On Line ◽  
Line Test ◽  
Frequency Current

EMI (electromagnetic interference) Diagnostics is an on-line test that can detect a wide variety of defects in generators and associated electrical systems. Trending data is not necessary to develop maintenance recommendations. This paper provides examples of generators in good condition as well as some that need maintenance. Verification of generator maintenance is also presented. Photo 1 shows the preferred RFCT (radio frequency current transformer) location to collect generator data. This conduit goes from the stator winding neutral to a grounding transformer. The split core RFCT is temporally placed around the conduit while data is collected and is then removed.

RECYCLED WATER RISK PERCEPTION - A COMPARISON OF TWO CASE STUDIES

2007 ◽  
Vol 2 (4) ◽  
Author(s):  
A. Hurlimann
Keyword(s):  
Risk Perception ◽  
Case Studies ◽  
Perceived Risk ◽  
Capital City ◽  
Recycled Water ◽  
Urban Centre ◽  
On Line ◽  
Line Survey ◽  
Water Uses

This paper reports results from a study comparing perceived risk associated with various recycled water uses in two Australian locations, both in the state of Victoria: the capital city Melbourne, and Bendigo a regional urban centre. Both locations are experiencing ‘drought’, but Bendigo is experiencing this in a more acute manner. A case study is used in each location. Both case studies involve future use of recycled water in new commercial buildings. An on-line survey was used to measure attitudes to recycled water of the future occupants of both buildings. The study found perceived risk associated with 11 uses of recycled water increased as the use became increasingly personal. Interestingly, no difference in perceived risk associated with 11 uses of recycled water was found between locations. Prior experience (use) of recycled water was found to be a significant and positive factor in reducing risk perception. Various attitudinal variables were found to be significant influences on perceived risk. Results indicate that reducing perceived risk of recycled water use may increase satisfaction with its use.

An Adaptive State Filtering Algorithm for Systems With Partially Known Dynamics

2002 ◽  
Vol 124 (3) ◽  
pp. 364-374 ◽  
Author(s):  
Alexander G. Parlos ◽  
Sunil K. Menon ◽  
Amir F. Atiya
Keyword(s):  
Neural Networks ◽  
Case Studies ◽  
Feedforward Neural Networks ◽  
Complex Case ◽  
State Equations ◽  
Estimation Errors ◽  
Filter Performance ◽  
On Line ◽  
Noise Statistics ◽  
On Line Learning

On-line filtering of stochastic variables that are difficult or expensive to directly measure has been widely studied. In this paper a practical algorithm is presented for adaptive state filtering when the underlying nonlinear state equations are partially known. The unknown dynamics are constructively approximated using neural networks. The proposed algorithm is based on the two-step prediction-update approach of the Kalman Filter. The algorithm accounts for the unmodeled nonlinear dynamics and makes no assumptions regarding the system noise statistics. The proposed filter is implemented using static and dynamic feedforward neural networks. Both off-line and on-line learning algorithms are presented for training the filter networks. Two case studies are considered and comparisons with Extended Kalman Filters (EKFs) performed. For one of the case studies, the EKF converges but it results in higher state estimation errors than the equivalent neural filter with on-line learning. For another, more complex case study, the developed EKF does not converge. For both case studies, the off-line trained neural state filters converge quite rapidly and exhibit acceptable performance. On-line training further enhances filter performance, decoupling the eventual filter accuracy from the accuracy of the assumed system model.

Rebuilding of a Large Single Hull Tank Barge into Double Hull

2005 ◽  
Author(s):  
Michael R. Kloesel ◽  
Robert J. Norton ◽  
Thomas R. Hagner
Keyword(s):  
Case Studies ◽  
Condition Assessment ◽  
Interesting Case ◽  
Assessment Program ◽  
Double Hull

This paper presents Maritrans’ groundbreaking experience in rebuilding very large single hull barges into OPA- 90 compliant double hull barges. Details of the process are described along with interesting case studies involving aspects of analysis and construction. The process by which the American Bureau of Shipping certified this barge to be a “Grade 1” under the ABS SafeHull Condition Assessment Program is described in detail. There is a brief discussion of extending this rebuild process to the double hulling of tankers.

Using the Asphalt Pavement Layer Condition Assessment Program: Case Studies

2003 ◽  
Vol 1860 (1) ◽  
pp. 66-75 ◽  
Author(s):  
Bing Xu ◽  
S. Ranji Ranjithan ◽  
Y. Richard Kim
Keyword(s):  
Case Studies ◽  
Asphalt Pavement ◽  
Compressive Strain ◽  
Dynamic Effect ◽  
Field Measurements ◽  
Condition Assessment ◽  
Base Layer ◽  
Element Analysis ◽  
Condition Indicators ◽  
Assessment Program

The Asphalt Pavement Layer Condition Assessment Program (APLCAP) is developed in this research to help highway agencies assess layer conditions of asphalt pavements. APLCAP implements a new integrated procedure for condition assessment from falling-weight deflectometer (FWD) deflections. The main components of this procedure include screening of FWD raw deflections, predictions of condition indicators from FWD measurements, structural adjustments for the predicted condition indicators, and layer condition evaluation based on the adjusted condition indicators. This procedure was developed on the basis of dynamic nonlinear finite element analysis and calibrated using field measurements. The three case studies presented show that the APLCAP algorithms can predict the asphalt concrete modulus, pavement critical strains, and strengths of the base and subgrade quite well, but not the compressive strain in the aggregate base layer. Although the APLCAP procedure includes the complicated dynamic effect of FWD loading and nonlinear behavior of unbound materials, the time to obtain results from this procedure is insignificant and therefore suitable for real-time evaluation of pavement conditions.

Power Transformer Condition Assessment by On-Line Monitoring and Trend Analysis

2012 ◽  
Author(s):  
Qijia Xie ◽  
Shengyou Gao ◽  
Hailong Zhang ◽  
Wen Dai ◽  
Ling Ruan ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Power Transformer ◽  
Condition Assessment ◽  
On Line

Verifying Suitability for Service With EMI Diagnostics

2008 ◽  
Author(s):  
James E. Timperley
Keyword(s):  
Electromagnetic Interference ◽  
Electrical Equipment ◽  
Current Transformer ◽  
Power Cables ◽  
Generator System ◽  
On Line ◽  
System Data ◽  
Line Test ◽  
Generator Stator ◽  
Frequency Current

This paper provides examples of conditions found with nuclear plant electrical equipment by the application of EMI (electromagnetic interference) Diagnostics. This is an on-line test that can detect a wide variety of defects in motors, generators, power cables transformers and isolated phase bus. There is no interruption to service and no risk to the system while data is collected. Photo 1 shows the temporary placement location of a RFCT (radio frequency current transformer) to collect EMI data from this CWP motor. Photo 2 shows the RFCT application on the generator stator grounding transformer. This is the preferred location to collect generator system data.

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