Thesis Chapters by Chandan Nagaraja
TECHNISCHE HOCHSCHULE INGOLSTADT, 2016
Structural health monitoring (SHM), an emerging technique developed from Non Destructive Testing(... more Structural health monitoring (SHM), an emerging technique developed from Non Destructive Testing(NDT), combines advanced sensor technology with intelligent algorithms to interrogate the structural ‘health’ conditions. SHM performs the real-time and on-line damage detection with the help of in-situ sensors. The potential benefits of implementing SHM in automotive sector includes improving reliability, reducing life-cycle costs and high safety factor to improve the design of automotive components. For these purposes, a car has been fitted with measuring equipment’s: strain gauge and
accelerometer to record the measuring drives in the present work.
The aim of the work is to investigate the measured strain signals, suggestions for improvement and optimization identified based on the theories of signal conditioning and signal analysis and computationally implemented for a SHM system. The thesis work majorly deals with signal monitoring, damage monitoring and fatigue life monitoring in a SHM system. The measured strain signal is generated from hardware embedded platform and it deals with several practical issues. The measured signal has a disturbance superimposed on the good data. This disturbance can mask some important fatigue features of the stress or strain signals. One of the goal in this study includes an implementation and evaluation methods for noise suppression and drift removal of the signal. Hence several digital filters are designed and applied for the signals. Filter efficiency was checked, compared and recommended with a focus on setting-up a processed signal for next signal analysis step with amplitude based methods.
A car is subjected to a large number of highly variable loads, but fatigue life prediction is typically based on constant amplitude fatigue behaviour. Therefore counting method was used for describing variable amplitude signals as a collection of constant amplitude cycles with predominantly using Rainflow analysis. The rainflow matrix and load spectrum are obtained for vehicle structure signals. An assessment of the remaining service life of a car structure is carried out by a simplified version of the linear damage accumulation hypothesis according to Palmgren-Miner rules and derivation of S-N curve which relates the stresses to the number of cycles to failure.
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Thesis Chapters by Chandan Nagaraja
accelerometer to record the measuring drives in the present work.
The aim of the work is to investigate the measured strain signals, suggestions for improvement and optimization identified based on the theories of signal conditioning and signal analysis and computationally implemented for a SHM system. The thesis work majorly deals with signal monitoring, damage monitoring and fatigue life monitoring in a SHM system. The measured strain signal is generated from hardware embedded platform and it deals with several practical issues. The measured signal has a disturbance superimposed on the good data. This disturbance can mask some important fatigue features of the stress or strain signals. One of the goal in this study includes an implementation and evaluation methods for noise suppression and drift removal of the signal. Hence several digital filters are designed and applied for the signals. Filter efficiency was checked, compared and recommended with a focus on setting-up a processed signal for next signal analysis step with amplitude based methods.
A car is subjected to a large number of highly variable loads, but fatigue life prediction is typically based on constant amplitude fatigue behaviour. Therefore counting method was used for describing variable amplitude signals as a collection of constant amplitude cycles with predominantly using Rainflow analysis. The rainflow matrix and load spectrum are obtained for vehicle structure signals. An assessment of the remaining service life of a car structure is carried out by a simplified version of the linear damage accumulation hypothesis according to Palmgren-Miner rules and derivation of S-N curve which relates the stresses to the number of cycles to failure.
accelerometer to record the measuring drives in the present work.
The aim of the work is to investigate the measured strain signals, suggestions for improvement and optimization identified based on the theories of signal conditioning and signal analysis and computationally implemented for a SHM system. The thesis work majorly deals with signal monitoring, damage monitoring and fatigue life monitoring in a SHM system. The measured strain signal is generated from hardware embedded platform and it deals with several practical issues. The measured signal has a disturbance superimposed on the good data. This disturbance can mask some important fatigue features of the stress or strain signals. One of the goal in this study includes an implementation and evaluation methods for noise suppression and drift removal of the signal. Hence several digital filters are designed and applied for the signals. Filter efficiency was checked, compared and recommended with a focus on setting-up a processed signal for next signal analysis step with amplitude based methods.
A car is subjected to a large number of highly variable loads, but fatigue life prediction is typically based on constant amplitude fatigue behaviour. Therefore counting method was used for describing variable amplitude signals as a collection of constant amplitude cycles with predominantly using Rainflow analysis. The rainflow matrix and load spectrum are obtained for vehicle structure signals. An assessment of the remaining service life of a car structure is carried out by a simplified version of the linear damage accumulation hypothesis according to Palmgren-Miner rules and derivation of S-N curve which relates the stresses to the number of cycles to failure.