Environmental Effects on Torsional Vibration Feature Health Monitoring

2012 ◽  
pp. 313-322
Author(s):  
Mitchell S. Lebold ◽  
Jonathan P. Bednar ◽  
Martin W. Trethewey
Keyword(s):  
Environmental Effects ◽  
Health Monitoring ◽  
Torsional Vibration

Continuous structural health monitoring of the Sayano-Shushenskaya Dam using off-site seismic station data accounting for environmental effects

2019 ◽  
Vol 31 (1) ◽  
pp. 015801
Author(s):  
Ting-Yu Hsu ◽  
Arygianni Valentino ◽  
Aleksei Liseikin ◽  
Dmitry Krechetov ◽  
Chun-Chung Chen ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Environmental Effects ◽  
Health Monitoring ◽  
Seismic Station ◽  
Structural Health ◽  
Station Data

scholarly journals Bridge Health Monitoring with Consideration of Environmental Effects

2012 ◽  
Vol 32 (6) ◽  
pp. 648-660 ◽  
Author(s):  
Yuhee Kim ◽  
Hyunsoo Kim ◽  
Soobong Shin ◽  
Jong-Chil Park
Keyword(s):  
Environmental Effects ◽  
Health Monitoring ◽  
Bridge Health Monitoring

Thermal Environmental Effects on Modal Parameters and Health Monitoring of Bridge Structures

2009 ◽  
Vol 96 (10) ◽  
pp. 21-30
Author(s):  
Mahendra P. Singh ◽  
Harsh Nandan ◽  
Surot Thangjitham
Keyword(s):  
Environmental Effects ◽  
Health Monitoring ◽  
Modal Parameters ◽  
Bridge Structures

Improving Turbomachinery Health Monitoring Using Advanced Shaft Telemetry System

2017 ◽  
Author(s):  
S. H. Hesler ◽  
C. A. Suprock
Keyword(s):  
Power Systems ◽  
Health Monitoring ◽  
Torsional Vibration ◽  
High Reliability ◽  
Turbine Generator ◽  
Blade Vibration ◽  
Widespread Application ◽  
High Data ◽  
Vibration Data ◽  
Technical Features

Turbine-generator shaft systems used in power generation applications are exposed to degradation mechanisms that could result in high consequence failures if not discovered prior to damage accumulation. Grid-induced torsional vibration, growth of cracks in the shaft forging, and large blade vibration are some examples of degradation that remains unmonitored in most commercial plants today. In many cases, the sensing and subsequent trending of high-quality vibration data obtained directly from the shaft surface can be the basis for a decision to continue to operate versus inspect or repair. Detection of small changes in torsional and lateral vibration mode properties can be sensed at a single shaft location and trended using techniques such as Advanced Pattern Recognition to reveal the very early signs of rotor distress. Contemporary barriers to widespread application of wireless shaft vibration measurements for health monitoring were studied and addressed in the development of the Turbine Dynamics Monitoring System (TDMS). The resulting design evolved around the industry need for low sensor maintenance, high reliability, ease of installation, and high data quality to enable early detection of critical component changes. These improvements capitalized on advances in strain gage and accelerometer technology, micro-telemetry, radio-frequency power systems, and advanced adhesives for installation. The new system has been successfully applied in the field on large steam turbine-generators to detect grid-induced torsional vibration. The paper will describe background of turbine-generator torsional vibration as well as the technical features of this advanced telemetry application with examples of field data.

scholarly journals Damage identification using inverse methods

2006 ◽  
Vol 365 (1851) ◽  
pp. 393-410 ◽  
Author(s):  
Michael I Friswell
Keyword(s):  
Inverse Problems ◽  
Damage Detection ◽  
Environmental Effects ◽  
Health Monitoring ◽  
Damage Identification ◽  
Inverse Methods ◽  
Damage Localization ◽  
Uncertain Parameters ◽  
Vibration Data ◽  
Modelling Error

This paper gives an overview of the use of inverse methods in damage detection and location, using measured vibration data. Inverse problems require the use of a model and the identification of uncertain parameters of this model. Damage is often local in nature and although the effect of the loss of stiffness may require only a small number of parameters, the lack of knowledge of the location means that a large number of candidate parameters must be included. This paper discusses a number of problems that exist with this approach to health monitoring, including modelling error, environmental effects, damage localization and regularization.

Imaging molecules adsorbed onto electrodes under potential control by scanning probe microscopy

1991 ◽  
Vol 49 ◽  
pp. 376-377 ◽  
Author(s):  
N.J. Tao ◽  
J.A. DeRose ◽  
P.I. Oden ◽  
S.M. Lindsay
Keyword(s):  
Surface Charge ◽  
Environmental Effects ◽  
Scanning Probe Microscopy ◽  
Statistical Significance ◽  
Electrochemical Methods ◽  
Surface Structures ◽  
Scanning Probe ◽  
Potential Control ◽  
Afm Imaging ◽  
Special Circumstances

Clemmer and Beebe have pointed out that surface structures on graphite substrates can be misinterpreted as biopolymer images in STM experiments. We have been using electrochemical methods to react DNA fragments onto gold electrodes for STM and AFM imaging. The adsorbates produced in this way are only homogeneous in special circumstances. Searching an inhomogeneous substrate for ‘desired’ images limits the value of the data. Here, we report on a reversible method for imaging adsorbates. The molecules can be lifted onto and off the substrate during imaging. This leaves no doubt about the validity or statistical significance of the images. Furthermore, environmental effects (such as changes in electrolyte or surface charge) can be investigated easily.

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