Papers by Author: Yi Qing Ni

Abstract: The data management system (DMS) is an essential part for long-term structural health monitoring (SHM) systems, which stores a pool of monitoring data for various applications. A robust database within a DMS is generally used to archive, manage and update life-cycle information of civil structures. However, many applications especially those to large-scale structures provide little support for visualizing the long-term monitoring data. This paper presents the development of an efficient visualized DMS by integrating 4-dimension (4D) model technology, nested relational database, and virtual reality (VR) technology. Spatial data of the 4D model are organized in nested tables, while real-time (temporal) monitoring data are linked to the 4D model. The model is then reconstructed by use of an OpenSceneGraph 3D engine. A user interface is developed to query the database and display the data via the 4D model. To demonstrate its efficiency, the proposed method has been applied to the Canton Tower, a supertall tower-like structure instrumented with a long-term SHM system

Abstract: Based on the dynamic characteristics analysis results of a precise three-dimensional finite element model, the earthquake responses of the bridge are analyzed in this paper. The influences of cable local modes and stabilizing cables on the seismic response are investigated by using different mode combinations and different models. It is found that the influence of cable local modes is negligible on the side towers while significant and not negligible on the main tower; the influence of the stabilizing cables is significant and not negligible on side towers, while minor and negligible on the main tower. As for the deck displacements, the influence of cable local modes is minor and negligible, while that of longitudinal stabilizing cables is significant and not negligible.

Abstract: A long-term structural health monitoring (SHM) system consisting of more than 600 sensors has been designed and is being implemented by The Hong Kong Polytechnic University to the Guangzhou New TV Tower (GNTVT) of 610 m high. This monitoring system is one of few SHM practices that integrate in-construction monitoring and in-service monitoring. It is also designed to perform a special function of verifying the effectiveness of vibration control devices to be installed on the tower. The sensory system for in-construction monitoring includes a weather station, a total station, anemometers, zenithal telescopes, level sensors, theodolites, global positioning systems, vibrating wire gauges, thermometers, digital video cameras, and accelerometers (for ambient vibration monitoring at several construction stages), and the sensory system for in-service monitoring includes a weather station, anemometers, wind pressure sensors, vibrating wire gauges, thermometers, global positioning systems, digital video cameras, accelerometers, a seismograph, corrosion sensors, tiltmeters, and fiber optic sensors (for dynamic strain and temperature monitoring). The strain and temperature at the inner structure during construction are continuously monitored by a wireless data acquisition system. This paper outlines the design and implementation of this SHM system.

Abstract: Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST) and the International Society for Structural Health Monitoring of Intelligent Infrastructure (ISHMII), a structural health monitoring benchmark problem for highrise slender structures is being developed by taking the instrumented Guangzhou New Television Tower as a test bed. The benchmark problem consists of the following four tasks: (i) output-only modal identification and finite element model updating, (ii) damage detection using simulated data, (iii) optimal sensor placement for structural health monitoring, and (iv) damage detection using field measurement data. This paper will address some key issues related to the development of this first benchmark problem for high-rise structures. More details of the study can be found in the website: http://www.cse.polyu.edu.hk/benchmark/index.htm

Abstract: A method for probabilistic fatigue life assessment of steel bridges by using long-term monitoring data is proposed and applied for fatigue reliability analysis of the suspension Tsing Ma Bridge. In this method, the daily number of cycles for each stress range is obtained from the measured stress history and its probability distribution is estimated based on statistical analysis of long-term measurement data. The statistics obtained for all concerned stress ranges is combined with the S−N relationships stipulated in specifications to conduct a probabilistic assessment of fatigue life with the use of the Palmgren-Miner rule, from which the mean value and standard deviation of the fatigue life as well as the failure probability and reliability index versus fatigue life are obtained. The proposed method is illustrated by using 80-day strain measurement data from the suspension Tsing Ma Bridge which is instrumented with a long-term structural health monitoring system.

Abstract: In this paper a method for safety and condition assessment of bridge components based on long-term monitoring data and reliability analysis is proposed with the target to provide quantitative information to bridge managers for decision making on optimizing and prioritizing bridge inspection and maintenance. In the proposed method, the probability density function (PDF) of the load effect is obtained directly from continuous strain measurement, while the PDF of the resistance is determined using the material strength and its variation coefficient prescribed in provisions or obtained by material tests, and further revised with the damage identification results. Then the safety indices of structural components are estimated using the first-order reliability method (FORM), which can be readily used to decide bridge inspection/maintenance strategy because the correspondence between the safety index and the required maintenance action has been established. This method can incorporate the identified structural damage in a probabilistic manner into the safety index evaluation. Case studies of two truss bridge structures have been provided to illustrate the proposed method.