Transmissibility as a Differential Indicator of Structural Damage

Johnson, Timothy J.; Adams, Douglas E.

doi:10.1115/1.1500744

Cited by 119 publications

(91 citation statements)

References 6 publications

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“…Johnson and Adams [22] showed that transmissibility functions could be used to effectively detect and locate structural changes. Transmissibility functions only contain the zeros, and not the poles, of discrete frequency response functions (FRF), and therefore, contain information about more localized regions of structures.…”

Section: Damage Locationmentioning

confidence: 99%

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Time and frequency domain nonlinear system characterization for mechanical fault identification

Haroon

Adams

2007

Nonlinear Dyn

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Mechanical systems are often nonlinear with nonlinear components and nonlinear connections, and mechanical damage frequently causes changes in the nonlinear characteristics of mechanical systems, e.g. loosening of bolts increases Coulomb friction nonlinearity. Consequently, methods which characterize the nonlinear behavior of mechanical systems are wellsuited to detect such damage. This paper presents passive time and frequency domain methods that exploit the changes in the nonlinear behavior of a mechanical system to identify damage.In the time domain, fundamental mechanics models are used to generate restoring forces, which characterize the nonlinear nature of internal forces in system components under loading. The onset of nonlinear damage results in changes to the restoring forces, which can be used as indicators of damage. Analogously, in the frequency domain, transmissibility (output-only) versions of auto-regressive exogenous input (ARX) models are used to locate and characterize the degree to which faults change the nonlinear correlations present in the response data. First, it is shown that damage causes changes in the restoring force characteristics, which can be used to detect damage. Second, it is shown that damage also alters the nonlinear correlations in the data that can be used to locate and track the progress of damage. Both restoring forces and auto-regressive transmissibility methods utilize operational response data for damage identification. Mechanical faults in ground vehicle suspension systems, e.g. loosening of bolts, are identified using experimental data.

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Section: Damage Locationmentioning

confidence: 99%

“…When the transmissibility version of the ARX models is used, they can help to detect and locate damage. The reason for this dual capability is that transmissibility functions contain only the transmission zeros of the system and, hence, are more sensitive to local changes in system characteristics [21,22].…”

Section: Introductionmentioning

confidence: 99%

Time and frequency domain nonlinear system characterization for mechanical fault identification

Haroon

Adams

2007

Nonlinear Dyn

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“…In [15], transmissibility functions, which only depend on the zeros of the system, are shown to be more sensitive to localized damages than other methods, such as modal analysis, which only monitor the poles (global properties) of the system. The use and the performance of transmissibility functions for damage localization have been investigated also in [16] for chain-like mass-spring systems.…”

Section: Related Workmentioning

confidence: 99%

Structural Health Monitoring in Wireless Sensor Networks by the Embedded Goertzel Algorithm

Bocca

Toivola

Eriksson

et al. 2011

2011 IEEE/ACM Second International Conference on Cyber-Physical Systems

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Abstract-Structural health monitoring aims to provide an accurate diagnosis of the condition of civil infrastructures during their life-span by analyzing data collected by sensors. To this purpose, detection and localization of damages are fundamental tasks. This paper introduces a wireless sensor network for structural damage detection and localization in which the sensor nodes, in order to estimate the energies of specific frequency bands, process the acceleration data locally in real-time using the Goertzel algorithm. The nodes then share their results inside the network and exploit them to compute transmissibility functions, which can be exploited as damage indicators and for correctly localizing damages within the monitored structure. The use of the embedded Goertzel algorithm prevents the nodes from transmitting large volumes of acceleration data to the sink node for off-line analysis, reducing the latency and increasing the life time of the cyber-physical system by 80 % and 52 %, respectively. The tests performed on a truss structure confirm the capability of the distributed approach in correctly detecting and localizing structural damages.

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“…Therefore if we compute the transmissibility functions between consecutive locations, defined on the damaged structure and subtract the same transmissibility functions of the undamaged structure, the damage location should come up with the biggest value of the indicator. Johnson and Adams [6] have also posed a similar indicator:…”

Section: Damage Indicatorsmentioning

confidence: 99%

“…In previous work [5,6] it was shown that the use of transmissibility func-tions for damage detection seems promising. Techniques based on comparing two sets of transmissibility functions of the undamaged and damaged structure have been developed.…”

Section: Introductionmentioning

confidence: 99%

Structural Health Monitoring in Changing Operational Conditions Using Tranmissibility Measurements

Devriendt

Presezniak

Sitter

et al. 2010

Shock and Vibration

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Abstract. This article uses frequency domain transmissibility functions for detecting and locating damage in operational conditions. In recent articles numerical and experimental examples were presented and the possibility to use the transmissibility concept for damage detection seemed quite promising. In the work discussed so far, it was assumed that the operational conditions were constant, the structure was excited by a single input in a fixed location. Transmissibility functions, defined as a simple ratio between two measured responses, do depend on the amplitudes or locations of the operational forces. The current techniques fail in the case of changing operational conditions. A suitable operational damage detection method should however be able to detect damage in a very early stage even in the case of changing operational conditions. It will be demonstrated in this paper that, by using only a small frequency band around the resonance frequencies of the structure, the existing methods can still be used in a more robust way. The idea is based on the specific property that the transmissibility functions become independent of the loading condition in the system poles. A numerical and experimental validation will be given.

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Transmissibility as a Differential Indicator of Structural Damage

Cited by 119 publications

References 6 publications

Time and frequency domain nonlinear system characterization for mechanical fault identification

Time and frequency domain nonlinear system characterization for mechanical fault identification

Structural Health Monitoring in Wireless Sensor Networks by the Embedded Goertzel Algorithm

Structural Health Monitoring in Changing Operational Conditions Using Tranmissibility Measurements

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