In general, the distance between the seismic stations is above 100 km and this distance is not small enough for monitoring the structural seismic response. As a result, crowdsourcing will be a good method to acquire the structural seismic response. Nowadays, the smartphone has been popularized and integrates different sensors. Based on the past work, a structure seismic response monitoring system named GroundEye based on smartphones is proposed. Here is the framework of the system. First, people can use software on the smartphone to acquire the structural seismic response parameters including acceleration, the inter-story drift, strain when the seismic comes. Beside the structural seismic response parameters mentioned above, the picture of the buildings and cracks after the seismic could also be taken so that the cracks could be recognized through the deep learning algorithms. Second, these data will be uploaded to the database to draw the intensity map. Third, these structural seismic response parameters monitored will be the database to assess the damage level of buildings. As mentioned above, the GroundEye can collect vast data in the earthquake monitoring fast within a large area with very low cost. And it will be very useful for identifying the health quality of the buildings.
Digital image correlation (DIC) is a non-contact, full-field optical measurement method that has been extensively used in various applications like structural health monitoring, material characterization, high temperature testing etc. However, most of the above applications are used in the laboratory, and rarely employed in the actual structure. This is mainly because of, firstly, DIC instruments are expensive and cannot be afforded by ordinary people. Secondly, the corresponding equipment is complicated to operate and cannot be widely used. The built-in camera of the smartphone is becoming more and more high-definition so that it has brought about an opportunity to solve this problem. From this point of view, this study monitored the deformation of compressive concrete blocks by smartphone and DIC technology, and analyzed the changes of displacement and strain field on the surface of concrete blocks under different loads. The location and shape of cracks in the displacement results were compared with those in the actual image as well. The results show the feasibility of using smartphones to monitor the strain of structures.
Earthquake can cause severe damage to structures, the assessment of structural performance, before, during, and after an extreme event, is critical for ensuring their safe operations and resiliency to potentially catastrophic events. However, the conventional monitoring methods need complicate sensors, acquisition devices and data transmission system, it’s difficult to obtain the real-time response of the structures during earthquake. Moreover, current damage assessment always relies on the numerical simulation, the monitoring data is rare to apply on the damage detection due to the difficult SHM system implementation during earthquake. Furthermore, the displacement was particular difficult to be monitored. In this work, the objective was to extract the damage features such as the modal frequencies variation and residual displacement using smartphone data in a three-story steel frame structure subjected to shaking table earthquake excitations, and study the acceleration integration method in frequency domain to obtain the displacement more convenient and quickly with higher precision. First, a discussion of experimental details, including test structure, test plan and damage cases was introduced. Then the modal frequencies variation and residual displacement in different cases were obtained with the conventional and smartphone monitoring data. Third, the integration techniques for obtaining displacements from acceleration raw data based on one-story measured displacement were investigated to reduce the errors caused by uncertain cut-off frequencies.
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