Autonomous Structural Health Monitoring—part Ii: Vibration-Based in-Operation Damage Assessment

Parloo, Eli; Verboven, Peter; Guillaume, Patrick; Overmeire, Marc Van

doi:10.1006/mssp.2002.1493

Cited by 32 publications

(19 citation statements)

References 11 publications

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“…where L is the differential operator and N (k) is the matrix of shape functions for element k. Using Equation (8), the following equation is obtained under modal coordinates:…”

Section: X(t)mentioning

confidence: 99%

“…Due to the increasing complexity and high reliability demand of those systems, damage and system performance degradation need to be quantified accurately for maintenance purposes [5,6]. To monitor the status of a target system, measurements of system condition variables are taken either by sensors installed on the system or field non-destructive inspections [7][8][9]. In particular, using smart sensors for structural health monitoring has drawn a lot of attention in the SHM community due to flexibility of smart sensors and advances in composite materials [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation

Zhou

Guan

et al. 2016

Preprint

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Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

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“…where L is the differential operator and N (k) is the matrix of shape functions for element k. Using Equation (8), the following equation is obtained under modal coordinates:…”

Section: X(t)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation

Zhou

Guan

et al. 2016

Preprint

View full text Add to dashboard Cite

show abstract

“…Thermal loads introduce stresses due to thermal expansion, which lead to changes in the modal properties. Thermal loads can also cause buckling and in some cases even lead to chaotic behaviour [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Damage Detections in Nonlinear Vibrating Thermally Loaded Plates

Manoach

Trendafilova

2010

Advanced Structured Materials

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“…The baseline of these techniques utiHze iterative algorithms to identify differences either in the stifi&iess matrix or in the flexibility matrix prior to and following damage. A review of these health monitoring methods can be found in reference [1] while some interesting results along with some generic issues and limitations are found in reference [2]. The lipiiting issues of all these techniques are related to the iterative algorithm and its numerical error that can overtake the small differences obtained between the update matrices and the baseline and thereby lowering the method sensitivity to damage.…”

Section: Introductionmentioning

confidence: 99%

Sensor Array Networks for Structural Integrity

Speyer¹

2004

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19b. TELEPHONE NUMBER (include arsacodeIn current technologies, given the high rehability required in almost all systems, the ability to detect a system fault at the earliest possible stage is of primary interest. The routine manual inspections required for structures in mechanical, civil and aerospace fields, significantly increase maintenance cost. Our objective is to develop and implement a selfdiagnostic tool that would reduce costs while also increasing system efiiciency and reducing risk. In addition, diagnostic tools can provide information on inaccessible parts in the structure. To provide the necessary architecture for this health maintenance, an array of sensor is used to monitor the system. Status of EffortDuring this grant, a fault detection filter was developed for structural health monitoring of a simply supported beam. More complex structtrres would be addressed later. The filter design is based on a mathematical model of the structure and rehes on foiu: measurements and one actuation point. Based on structural analysis, the structural damage is decomposed 1 and reduced to a fault direction vector that maintains a fixed direction in the detection space. We show that this fault detection vector can be detected and uniquely identified and thereby, the structural damage is detected and localized.3 Accomplishments/New Findings During this grant, robust fault detection filter based on a spectral design method is implemented for a simply supported beam and is shown to both identify and localize structural faults. See Appendix A for details. The algorithm is specifically accomplished using 4 sensors and 1 actuator and relays on a mathematical model of the structure. The detection filter design is based on fault direction vectors that can be uniquely associated with any structural fault occurring at the beam. At each damage locations the detection filter measurement residual vector produces a fibced direction independent of the fault (damage) size that can be uniquely identified. The numerical simulations are compared with experimental results produced by an aluminum simply supported beam and show good agreement. The measvirements and actuation of the beam are obtained with piezoelectric transducers that ensure a large operating bandwidth. Although the algorithm is designed specifically for 4 measurements, it can be adapted to virtually any number of sensors. This is a fundamental properties for structural health monitoring because, depending on structure complexity, the damage detection must be accomplished using the least number of sensors. The faultdetection filter methodology can also include sensors and actuator faults, as well as plant faults as addressed here. However, in this grant period, only structural faults are considered.For the implementation of the fault detection filter, the following equipments where utilized: 1) A Wavetek lOMHz DDs Mod. 29 function generator to produce the sinusoidal inputs for the actuator, 2) a low impedance Burleigh PZ 150M volt amplifier for the ampUfication of the ...

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Autonomous Structural Health Monitoring—part Ii: Vibration-Based in-Operation Damage Assessment

Cited by 32 publications

References 11 publications

Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation

Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation

Damage Detections in Nonlinear Vibrating Thermally Loaded Plates

Sensor Array Networks for Structural Integrity

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