Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Fritzen, Claus‐Peter; Bohle, Karsten

doi:10.1006/mssp.2002.1546

Cited by 14 publications

(5 citation statements)

References 7 publications

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“…It is perhaps most obviously needed in the case of finite element (FE) updating methods (Mottershead & Friswell 1993;Friswell & Mottershead 1995), a class of algorithms that have proved successful at the higher levels of damage identification, i.e. in the location and quantification of damage ( Fritzen & Bohle 2003;Goerl & Link 2003). The FE updating methodology is based on the construction of a highfidelity FE model of the structure of interest in its normal condition.…”

Section: Axiom IImentioning

confidence: 99%

The fundamental axioms of structural health monitoring

et al. 2007

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Based on the extensive literature that has developed on structural health monitoring over the last 20 years, it can be argued that this field has matured to the point where several fundamental axioms, or gen eral principles, have emerged. The intention of this paper is to explicitly state and justify these axioms. In so doing, it is hoped that two subsequent goals are facilitated. First, the statement of such axioms will give new researchers in the field a starting point that alleviates the need to review the vast amounts of literature in this field. Second, the authors hope to stimulate discussion and thought within the community regarding these axioms.

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Section: Axiom IImentioning

confidence: 99%

The fundamental axioms of structural health monitoring

et al. 2007

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“…The second FE study was provided by Fritzen and Bohle [4]. This was also an updating strategy with the potential to reach level 3 in Rytter's hierarchy.…”

Section: The Steelquake Structurementioning

confidence: 99%

Discussion and Conclusions for Working Group 2 Benchmarks

Worden

2003

Mechanical Systems and Signal Processing

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“…stiffness matrix, modal parameters, etc.). These approaches deal with deterministic models on which all the parameters are considered as “measurable” and different uncertainties are not represented for the model directly (Fritzen and Li, 2009; Fritzen and Bohle, 2003; Holnicki-Szulc, 2008).…”

Section: Introductionmentioning

confidence: 99%

Damage detection in aerostructures from strain measurements

Sierra-Pérez

Güemes

2016

Aircraft Eng & Aerospace Tech

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Purpose The purpose of this paper is to study techniques of pattern recognition in the strain field as structural health monitoring tools. The changes in the strain field may be very intense at the tip of a crack but smooth out very quickly. So trying to get information about damage occurrence from strain measurements is a difficult task, as the detected strain changes may be very small and masked by temperature drifting, load changes or any other environmental factor. Design/methodology/approach It drives to the need to include a large sensor array into the structure, which is not difficult when using optical fiber sensors. Experiments were done on a simple cantilever beam, instrumented with 32 sensors and submitted to loads and progressive damage conditions. The same approach was applied to a more complex structure, the wing of an unmanned air vehicle (UAV) made in composite materials. Findings Algorithms based on principal component analysis (PCA), damage indices and damage thresholds were used and shown to be simple and robust enough for this task. Originality/value The data treatment was done in a fully automated approach; an algorithm to compare and extract information from the multiple strain measurements was developed for this task.

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Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Cited by 14 publications

References 7 publications

The fundamental axioms of structural health monitoring

The fundamental axioms of structural health monitoring

Discussion and Conclusions for Working Group 2 Benchmarks

Damage detection in aerostructures from strain measurements

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