The use of recursive subspace-based identification methods is analyzed in the estimation of the most significant vibration frequencies along an elevated railroad segment of México City Metro Line 12 using ambient vibration measurements recorded from 2012, when the line was opened, to 2018. Due to the railroad characteristics, the use of high-order models and the systematic tuning of the methods are required to achieve low uncertainty in frequency estimation. A frequency history is generated using these high-order models in order to check for variations along the seven years where important events took place: two low- and one high-intensity earthquakes, paving, and construction of sidewalks and planters around the sensor station. Results are consistent for all methods under analysis in the identified frequencies, suggesting that the system has preserved its structural health. To produce independent results, spectral analysis was performed showing that the associated frequency history is again consistent with that generated with recursive subspace-based identification methods. Overall, results indicate that these subspace methods are suitable for frequency monitoring in the studied system offering, in the case of recursive N4SID, important advantages in terms of low computational cost, real-time implementation, and smaller uncertainty.

The seismic response of an instrumented 22-story rehabilitated building is presented. The building analyzed is as part of a complex (called CCUT) with three low-rise structures and a common basement founded on soft soil that was built in 1964. Since it was under construction until date, the building tower has experienced differential settlements and tilting. To mitigate such problems, the building has been subjected to several rehabilitations over the years. During the 1985 and 2017 high-intensity earthquakes in Mexico City, the tower suffered some damage. The aim of this article is to discuss the structural health monitoring system implemented for the tower and to describe the structure’s performance since the last rehabilitation in 2009. A monitoring methodology designed and implemented as a structural warning system based on five structural health indicators, two on seismic severity and three on structural performance, to automatically process seismic records, is presented. The results of the seismic response of the CCUT tower between 2011 and 2018 indicate that the structure had suffered moderate damage. Analysis of data, corroborated by building inspection, confirmed that the structure exhibited good performance during the 19 September 2017 Puebla-Morelos earthquake. The importance of the information obtained from the structural warning system is highlighted as a promissory tool for establishing a robust decision framework for occupants’ safety.

An on-line identification scheme for shear building models using recursive least squares with a matrix parameterized model is presented. Based on Gershgorin circles and tridiagonal matrices properties, the identified model stability is guaranteed in the presence of low excitation or low damping. Stability of the model helps in the design of more robust control laws. The scheme is evaluated in an experimental test-bed with a scaled five stories building where an on-line reduced order model is derived. Results indicate that when employing this matrix parametrization, a significant reduction in the number of calculations involved is achieved, when compared to the standard vector parametrization based schemes, such that real-time applications are feasible to implement. Moreover, the stability on the identified model is preserved.

No abstract

This article presents the most significant structural response parameters of a railway system analyzed with data gathered during 5 years. The structure is the instrumented curved portion of an elevated railroad that consists of a simply supported beam resting on cantilever columns on soft soil. A monitoring system was implemented to determine, within a few minutes, a preliminary structural state analyzing ambient vibration or seismic events. To assess the state of health of the structure, the response obtained from the seismic events, applying the proposed methodology, is compared with that obtained from controlled field tests conducted at the end of its construction and compared with design values. The monitoring system’s results showed minimal frequency variations caused by external works and a transitory variation of the fundamental frequencies during the 19 September 2017 great earthquake that, however, did not affect the structural integrity. The warning system showed acceptable performance, and only suggested checking the support beam-column condition.