Damage localization in civil engineering structures using dynamic strain measurements

monitoring of civil engineering structures in order to locate small damages automatically. A

review of the very wide literature on Structural Health Monitoring (SHM) points first out that

the methods can be grouped in four categories based on their need or not of a numerical model,

as well as their need or not of information of the damaged structure to be applied. This state

of the art of the SHM methods highlights the requirement to reach each levels of SHM, which

is in particular for the localization of small damages in civil engineering structures the needs

for a non-model based output-only damage sensitive feature extraction technique. The origin of

the local sensitivity of strains to damages is also analyzed, which justifies their use for damage

localization.

A new method based on the modal filtering technique which consists in combining linearly

the sensor responses in a specific way to mimic a single degree of freedom system and which

was previously developed for damage detection is proposed. A very large network of dynamic

strain sensors is deployed on the structure and split into several independent local sensor networks.

Low computational cost and fast signal processing techniques are coupled to statistical

control charts for robust and fully automated damage localization.

The efficiency of the method is demonstrated using time-domain simulated data on a simply

supported beam and a three-dimensional bridge structure. The method is able to detect and

locate very small damages even in the presence of noise on the measurements and variability

of the baseline structure if strain sensors are used. The difficulty to locate damages from acceleration

sensors is also clearly illustrated. The most common classical methods for damage

localization are applied on the simply supported beam and the results show that the modal filtering

technique presents much better performances for an accurate localization of small damages

and is easier to automate.

An improvement of the modal filters method referred to as adaptive modal filters is next

proposed in order to enhance the ability to localize small damages, as well as to follow their

evolution through modal filters updating. Based on this study, a new damage sensitive feature

is proposed and is compared with other damage sensitive features to detect the damages with

modal filters to demonstrate its interest. These expectations are verified numerically with the

three-dimensional bridge structure, and the results show that the adaptation of the modal filters

increases the sensitivity of local filters to damages.

Experimental tests have been led first to check the feasibility of modal filters to detect damages

when they are used with accelerometers. Two case studies are considered. The first work

investigates the experimental damage detection of a small aircraft wing equipped with a network

of 15 accelerometers, one force transducer and excited with an electro-dynamic shaker. A

damage is introduced by replacing inspection panels with damaged panels. A modified version

of the modal filtering technique is applied and compared with the damage detection based principal

component analysis of FRFs as well as of transmissibilities. The three approaches succeed

in the damage detection but we illustrate the advantage of using the modal filtering algorithm as

well as of the new damage sensitive feature. The second experimental application aims at detecting

both linear and nonlinear damage scenarios using the responses of four accelerometers

installed on the three-storey frame structure previously developed and studied at Los Alamos

National Labs. In particular, modal filters are shown to be sensitive to both types of damages,

but cannot make the distinction between linear and nonlinear damages.

Finally, the new method is tested experimentally to locate damages by considering cheap

piezoelectric patches (PVDF) for dynamic strain measurements. Again, two case studies are investigated.

The first work investigates a small clamped-free steel plate equipped with 8 PVDFs sensors, and excited with a PZT patch. A small damage is introduced at different locations by

fixing a stiffener. The modal filters are applied on three local filters in order to locate damage.

Univariate control charts allow to locate automatically all the damage positions correctly.

The last experimental investigation is devoted to a 3.78m long I-steel beam equipped with 20

PVDFs sensors and excited with an electro-dynamic shaker. Again, a small stiffener is added to

mimic the effect of a small damage and five local filters are defined to locate the damage. The

damage is correctly located for several positions, and the interest of including measurements

under different environmental conditions for the baseline as well as overlapping the local filters

is illustrated.

The very nice results obtained with these first experimental applications of modal filters

based on strains show the real interest of this very low computational cost method for outputonly

non-model based automated damage localization of real structures.