Monitoring interstory drift in buildings under seismic loading using MEMS inclinometers

Hou, Shuang; Zeng, Chuangshuo; Zhang, Haibin; Ou, Jinping

doi:10.1016/j.conbuildmat.2018.07.087

Cited by 31 publications

(18 citation statements)

References 21 publications

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“…The method in paper [15] will be a good choice for rapid residual displacement measurement after seismic events, while it is a static measurement method rather than continuous measurement. The method in paper [16] could describe the deformation condition along a column. However, it needs 8 MEMS inclinometers in one column, thus the cost will increase.…”

Section: Sensor Comparisonmentioning

confidence: 99%

“…The essence of interstory drift monitoring is to monitor relative displacement between ceiling and floor. There are many relative displacement monitoring methods, such as a linear variable differential transmitter (LVDT) [11], double numerical integration of acceleration data [11][12][13][14], the photogrammetry-assisted Augmented Reality (AR) technique [15], Micro Electro Mechanical Systems (MEMS) inclinometers [16], and the machine vision method [17].…”

Section: Introductionmentioning

confidence: 99%

“…Dai et al [15] proposed a photogrammetry assisted AR technique using a consumer-grade digital SLR camera to measure interstory drift, which could be used after seismic events. Hou et al [16] calculated the relationship between interstory drift ratio and rotation of a column in both elastic and elastoplastic stages and used 8 MEMS inclinometers in one column to verify the feasibility of the method. The results turned out that the mean percent error was 7.6%.…”

Section: Introductionmentioning

confidence: 99%

“…The photogrammetry assisted AR technique [15] is a static measurement, and it had not been tested in full-scale experiments. Using inclinometers [16] to monitoring interstory drift will require eight sensors in one column, which will increase the cost. Besides, the machine vision method [17] needs normal light and cannot be used in darkness.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Method of Interstory Drift Monitoring Using a Smartphone and a Laser Device

Xie

Zhao

2020

Sensors

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Interstory drift is an important engineering parameter in building design and building structural health monitoring. However, many problems exist in current interstory drift monitoring methods. The traditional method is imprecise—double numerical integration of acceleration data—and other direct monitoring methods need professional equipment. This paper proposes a method to solve these problems by monitoring the interstory drift with a smartphone and a laser device. In this method, a laser device is installed on the ceiling while a smartphone is fixed on a steel projection plate on the floor. Compared with a reference sensor, the method designed in this study shows that a smartphone is competent in monitoring the interstory drift. This method utilizes a smartphone application (APP) named D-Viewer to implement monitoring and data storage just in one place, which is also inexpensive. The results showed that this method has an average percent error of 3.37%, with a standard deviation of 2.67%. With the popularization of the smartphone, this method is promising in acquiring large amounts of data, which will be significant for building assessment after an earthquake.

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Section: Sensor Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Method of Interstory Drift Monitoring Using a Smartphone and a Laser Device

Xie

Zhao

2020

Sensors

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“…Due to their low cost, small size, high durability, low power consumption, and easy installation [1], micro-electro-mechanical system (MEMS) accelerometer-based inclinometers have been widely applied in civil engineering, such as for deformation measurements of bridges [2] and buildings [3], for soil stability monitoring of embankments [4] and landslides [5], and for performance evaluations of underground structures [6]. In these cases, MEMS inclinometers are used to measure both angular deformations and displacements.…”

Section: Introductionmentioning

confidence: 99%

An Improved Calibration Technique for MEMS Accelerometer-Based Inclinometers

Zhu

Wang

Huang

et al. 2020

Sensors

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Micro-electro-mechanical system (MEMS) accelerometer-based inclinometers are widely used to measure deformations of civil structures. To further improve the measurement accuracy, a new calibration technique was proposed in this paper. First, a single-parameter calibration model was constructed to obtain accurate angles. Then, an image-processing-based method was designed to obtain the key parameter for the calibration model. An ADXL355 accelerometer-based inclinometer was calibrated to evaluate the feasibility of the technique. In this validation experiment, the technique was proven to be reliable and robust. Finally, to evaluate the performance of the technique, the calibrated MEMS inclinometer was used to measure the deflections of a scale beam model. The experimental results demonstrate that the proposed technique can yield accurate deformation measurements for MEMS inclinometers.

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Robust adaptive Kalman filter for structural performance assessment

Yi,

Su,

Tang

2024

Intl J Robust & Nonlinear

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SummaryStructural performance assessment is a critical stage in the health monitoring for the maintenance and risk management of engineering structures, in which the interstory drift is a key indicator. In this paper, a robust adaptive Kalman filter is proposed for an interstory drift estimation problem to show the health condition of steel structures in the case that the statistics or internal dynamics describing the signals and measurements are not known precisely. More precisely, we build an adaptive current Jerk model (ACJM) where the model parameters are updated in each time step to presuppose the statistics characterization of the steel dynamic, while the unknown measurement noise covariance is adapted based on a fixed‐lag innovation with respect to measurements. Moreover, a robust adaptive Kalman filter is designed for the modelling uncertainties in each time increment by solving a minimax game: one player tries to select an “actual” model far from the proposed ACJM with an exponential decay tolerance, while its “hostile” player, namely, the optimum filter, is designed by minimizing the estimation error according to the selected “actual” model. Finally, some simulation and experimental results show the effectiveness of the proposed algorithm.

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Monitoring interstory drift in buildings under seismic loading using MEMS inclinometers

Cited by 31 publications

References 21 publications

A Method of Interstory Drift Monitoring Using a Smartphone and a Laser Device

A Method of Interstory Drift Monitoring Using a Smartphone and a Laser Device

An Improved Calibration Technique for MEMS Accelerometer-Based Inclinometers

Robust adaptive Kalman filter for structural performance assessment

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