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A New Online Structural Health Monitoring Technique to Detect Subtle Damage Considering Environmental Variability



Detecting damage at the earliest possible stage is the most desirable feature of any structural health monitoring scheme, for its successful practical implementation in the field. Particularly, for a small damage in its incipient stage, the minor changes in the dynamic characteristics of the structures, alter only some specific modal responses. Hence the damage features present in the modal response of only some limited modes due to the minor incipient damage will not get highlighted in the measured raw dynamic signatures. Also, the presence of environmental variability (EOV), which alter the dynamic characteristics and signature, mask the existence of the minor incipient damage from diagnosis, while using conventional damage diagnostic algorithms. In this paper, a new online health monitoring technique is proposed to handle the EOV and locate the minor damage in the structure. In the proposed online SHM scheme, we use the cointegration technique to handle the EOV. During online monitoring, the cointegrating vectors are obtained from the recent healthy data denoted as ‘baseline data’, collected from the structure. Subsequently, these vectors are used to filter out the confounding effects of EOV of the current data. During damage diagnosis with the current data, if the state of the structure is found to be healthy, then the ‘baseline data’ is updated with the current data along with their corresponding freshly evaluated cointegrating vectors. We later employ the blind source separation (BSS) technique on the cointegrated time series, free from EOV, to decompose the dynamic response into modal responses. Then we employ an automated algorithm proposed in this paper, on the decomposed signals (i.e. modal responses) in order to identify and isolate the modal responses with the damage features. Finally, the location of the damage is identified using a damage index, formulated with the isolated modal responses. Numerical simulation studies and experimental studies are carried out to test and evaluate the proposed online damage diagnostic technique and their capability in identifying minor/incipient damage like small cracks considering environmental variability with measurement noise.


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