Long-term structural performance monitoring system for the Shanghai Tower

Su, Jia Zhan; Xia, Yong; Chen, Lu; Zhao, Xin; Zhang, Qi Lin; Xu, You Lin; Ding, Jie; Xiong, Hai Bei; Jin, Ru; Lv, Xi Lin; Chen, Ai Rong

doi:10.1007/s13349-012-0034-z

Cited by 82 publications

(45 citation statements)

References 14 publications

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“…The building is divided into nine zones along its height separated by eight independent strengthening floors [see Figure 1 (a)]. The Shanghai Tower adopts a mega-frame core-wall structural system, which comprises a core wall inner tube, an outer mega-frame, and a total of six levels of outriggers between the tube and the frame, as shown in Figure 2 (Su et al 2013). The core wall inner tube is square-shaped with dimensions of 30 m × 30 m divided into nine cells at the bottom of the building.…”

Section: Project Overviewmentioning

confidence: 99%

Settlement Monitoring of a Supertall Building Using the Kalman Filtering Technique and Forward Construction Stage Analysis

Xia

et al. 2014

Advances in Structural Engineering

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Excessive and unexpected settlement of supertall buildings during the construction stage may affect structural safety. Floor settlement monitoring is imperative during the structural construction. The current practice is to measure floor settlement within a specific time frame and then compensate for the elevation error in the next construction stage. This posterior manner is inaccurate because it does not take account of measurement error and the real settlement in the next construction stage. This paper presents a Kalman filter based settlement monitoring approach with the aid of forward construction stage analysis. The settlement of floors in the next stage is predicted with the forward construction stage analysis. Consequently the elevation of the floor to be constructed can be pre-determined. The proposed method is demonstrated through construction settlement monitoring of the 632-m tall Shanghai Tower. The structure will be the tallest supertall building of China upon completed in 2014. It shows that this method can improve the accuracy of pre-determined elevation of supertall buildings.

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Section: Project Overviewmentioning

confidence: 99%

Settlement Monitoring of a Supertall Building Using the Kalman Filtering Technique and Forward Construction Stage Analysis

Xia

et al. 2014

Advances in Structural Engineering

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“…For structures in which relatively large mega columns have been used, the safety of the members are managed during construction through structural health monitoring (SHM) using various sensors, including axial strain sensors [3–5]. Various sensing methods have been developed for field measurements of strains in buildings and infrastructures [6–10].…”

Section: Introductionmentioning

confidence: 99%

A Practical Data Recovery Technique for Long-Term Strain Monitoring of Mega Columns during Construction

Choi

Kwon

Kim

et al. 2013

Sensors

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A practical data recovery method is proposed for the strain data lost during the safety monitoring of mega columns. The analytical relations among the measured strains are derived to recover the data lost due to unexpected errors in long-term measurement during construction. The proposed technique is applied to recovery of axial strain data of a mega column in an irregular building structure during construction. The axial strain monitoring using the wireless strain sensing system was carried out for one year and five months between 23 July 2010 and 22 February 2012. During the long-term strain sensing, three different types of measurement errors occurred. Using the recovery technique, the strain data that could not be measured at different intervals in the measurement were successfully recovered. It is confirmed that the problems that may occur during long-term wireless strain sensing of mega columns during construction could be resolved through the proposed recovery method.

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“…A total of 432 sensors of 11 different types are installed in the Shanghai Tower [27], and these sensors are vertically expressed as the number of sensors of each sensor type as a function of the elevation of the building in a manner similar to the Guangzhou New TV Tower. In addition, the monitoring zone in the Shanghai Tower is divided vertically, and each zone is classified from the ground to the top by a series of numbers.…”

Section: Introductionmentioning

confidence: 99%

Symbolic and Graphical Representation Scheme for Sensors Deployed in Large-Scale Structures

Park

Shin

Choi

et al. 2013

Sensors

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As wireless sensor network (WSN)-based structural health monitoring (SHM) systems are increasingly being employed in civil infrastructures and building structures, the management of large numbers of sensing devices and the large amount of data acquired from WSNs will become increasingly difficult unless systematic expressions of the sensor network are provided. This study introduces a practical WSN for SHM that consists of sensors, wireless sensor nodes, repeater nodes, master nodes, and monitoring servers. This study also proposes a symbolic and graphical representation scheme (SGRS) for this system, in which the communication relationships and respective location information of the distributed sensing components are expressed in a concise manner. The SGRS was applied to the proposed WSN, which is employed in an actual large-scale irregular structure in which three types of sensors (75 vibrating wire strain gauges, 10 inclinometers, and three laser displacement sensors) and customized wireless sensor nodes are installed. The application results demonstrate that prompt identification of sensing units and effective management of the distributed sensor network can be realized from the SGRS. The results also demonstrate the superiority of the SGRS over conventional expression methods in which a box diagram or tree diagram representing the ID of sensors and data loggers is used.

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Long-term structural performance monitoring system for the Shanghai Tower

Cited by 82 publications

References 14 publications

Settlement Monitoring of a Supertall Building Using the Kalman Filtering Technique and Forward Construction Stage Analysis

Settlement Monitoring of a Supertall Building Using the Kalman Filtering Technique and Forward Construction Stage Analysis

A Practical Data Recovery Technique for Long-Term Strain Monitoring of Mega Columns during Construction

Symbolic and Graphical Representation Scheme for Sensors Deployed in Large-Scale Structures

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