Dynamic Displacement Estimation from Acceleration Measurements Using a Wireless Smart Sensor

2013 ◽  
Vol 558 ◽  
pp. 227-234
Author(s):  
Jong Woong Park ◽  
Sung Han Sim ◽  
Hyung Jo Jung ◽  
Billie F. Spencer
Keyword(s):  
Large Scale ◽  
Low Frequency ◽  
Estimation Algorithm ◽  
Reference Points ◽  
Displacement Measurement ◽  
Frequency Drift ◽  
Smart Sensor ◽  
Civil Structures ◽  
Dynamic Displacement ◽  
Displacement Estimation

A displacement measurement provides useful information for structural health monitoring (SHM) as it is directly related to stiffness of the structure. Most existing methods of direct measurement such as the Laser Doppler Vibrometer (LDV) and the Liner Variable Differential Transformer (LVDT) are known to have accurate performance but have difficulties particularly in the use of large-scale civil structures as the methods rely on fixed reference points. Alternatively, indirect methods have been developed and widely used methods are Global Positioning System (GPS), vision-based displacement measurement system and displacement estimation from acceleration record. Among the indirect method, the use of accelerometer provides simple and economical in term of both hardware installation and operation. The major problem using acceleration based displacement estimation is low frequency drift caused by double integration. Recently, dynamic displacement estimation algorithm that addresses low-frequency drift problem has been developed. This study utilizes Wireless Smart Sensor (WSN) for estimating dynamic displacement from acceleration measurement in combination with the recently developed displacement estimation algorithm. Integrated into WSN that are low-cost, wireless, compatible with accelerometers, and capable of onboard computation, the displacement can be measured without limit of location on large-scale civil structures. Thus, this approach has the significant potential to impact many applications that require displacement measurements. With the displacement estimation algorithm embedded, the WSN performs in-network data processing to estimate displacements at each distributed sensor location wirelessly using only measured acceleration data. To experimentally validate the performance of displacement estimation using WSN for the use in structures with multiple-degree of freedom, the random vibration test is conducted on the three-story shear building model. The estimated displacement is compared with the reference displacements measured from the laser displacement sensor and the result shows good agreement.

scholarly journals Dynamic Displacement Estimation for Long-Span Bridges Using Acceleration and Heuristically Enhanced Displacement Measurements of Real-Time Kinematic Global Navigation System

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5092
Author(s):  
Kiyoung Kim ◽  
Hoon Sohn
Keyword(s):  
Kalman Filter ◽  
Large Scale ◽  
Reduction Method ◽  
Estimation Method ◽  
Sampling Frequency ◽  
Displacement Measurement ◽  
Dynamic Displacement ◽  
Displacement Estimation ◽  
Gnss Receiver ◽  
Civil Infrastructures

In this paper, we propose a dynamic displacement estimation method for large-scale civil infrastructures based on a two-stage Kalman filter and modified heuristic drift reduction method. When measuring displacement at large-scale infrastructures, a non-contact displacement sensor is placed on a limited number of spots such as foundations of the structures, and the sensor must have a very long measurement distance (typically longer than 100 m). RTK-GNSS, therefore, has been widely used in displacement measurement on civil infrastructures. However, RTK-GNSS has a low sampling frequency of 10–20 Hz and often suffers from its low stability due to the number of satellites and the surrounding environment. The proposed method combines data from an RTK-GNSS receiver and an accelerometer to estimate the dynamic displacement of the structure with higher precision and accuracy than those of RTK-GNSS and 100 Hz sampling frequency. In the proposed method, a heuristic drift reduction method estimates displacement with better accuracy employing a low-pass-filtered acceleration measurement by an accelerometer and a displacement measurement by an RTK-GNSS receiver. Then, the displacement estimated by the heuristic drift reduction method, the velocity measured by a single GNSS receiver, and the acceleration measured by the accelerometer are combined in a two-stage Kalman filter to estimate the dynamic displacement. The effectiveness of the proposed dynamic displacement estimation method was validated through three field application tests at Yeongjong Grand Bridge in Korea, San Francisco–Oakland Bay Bridge in California, and Qingfeng Bridge in China. In the field tests, the root-mean-square error of RTK-GNSS displacement measurement reduces by 55–78 percent after applying the proposed method.

scholarly journals Research on 5G Millimeter Wave Channel Estimation Algorithm

2019 ◽  
pp. 74-77
Author(s):  
Xu Shuang
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Large Scale ◽  
Low Frequency ◽  
Estimation Algorithm ◽  
Simulation Research ◽  
Wave Technology ◽  
Wave Channel ◽  
Mimo Technology

With the explosive growth in the number of communication users and the huge demand for data from users, Limited low-frequency resources have been far from being satisfied by users. The combination of Massive MIMO technology and millimeter-wave technology has brought new hope to users. In this paper, several basic algorithms are placed under the millimeter wave large-scale antenna channel for simulation research.

scholarly journals Reference-Free Displacement Estimation of Bridges Using Kalman Filter-Based Multimetric Data Fusion

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Soojin Cho ◽  
Jong-Woong Park ◽  
Rajendra P. Palanisamy ◽  
Sung-Han Sim
Keyword(s):  
Kalman Filter ◽  
Data Fusion ◽  
Structural Integrity ◽  
State Space Model ◽  
Reference Points ◽  
Displacement Measurement ◽  
Displacement Estimation ◽  
Relative Characteristic ◽  
Crucial Information ◽  
Measurement Approach

Displacement responses of a bridge as a result of external loadings provide crucial information regarding structural integrity and current conditions. Due to the relative characteristic of displacement, the conventional measurement approach requires reference points to firmly install the transducers, while the points are often unavailable for bridges. In this paper, a displacement estimation approach using Kalman filter-based data fusion is proposed to provide a practical means for displacement measurement. The proposed method enables accurate displacement estimation by optimally utilizing acceleration and strain in combination that have high availability and are free from reference points for sensor installation. The Kalman filter is formulated using a state-space model representing the double integration of acceleration and model-based strain-displacement relationship. The validation of the proposed method is conducted successfully by a numerical simulation and a field experiment, which shows the efficacy and accuracy of the proposed approach in bridge displacement measurement.

scholarly journals Single-Camera-Based Bridge Structural Displacement Measurement with Traffic Counting

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4517
Author(s):  
Zulhaj Aliansyah ◽  
Kohei Shimasaki ◽  
Taku Senoo ◽  
Idaku Ishii ◽  
Shuji Umemoto
Keyword(s):  
Motion Capture ◽  
Displacement Measurement ◽  
Single Camera ◽  
Motion Capture System ◽  
Side View ◽  
Civil Structures ◽  
Counting System ◽  
Front View ◽  
Dynamic Displacement ◽  
Measured Displacement

Vision-based structural displacement methods allow convenient monitoring of civil structures such as bridges, though they are often limited due to the small number of measurement points, constrained spatial resolution, and inability to identify the acting forces of the measured displacement. To increase the number of measurement points in vision-based bridge displacement measurement, this study introduces a front-view tandem marker motion capture system with side-view traffic counting to identify the force-inducing passing vehicles on the bridge’s deck. The proposed system was able to measure structural displacement at submillimeter resolution on eight measurement points at once at a distance of 40.8–64.2 m from a front-view camera. The traffic counting system with a side-view camera recorded the passing vehicles from two opposing lanes. We conducted a 35-min experiment for a 25 m-span steel road bridge with hundreds of cars passing over it and confirmed dynamic displacement distributions with amplitudes of several millimeters when large vehicles passed.

scholarly journals Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

2021 ◽  
Vol 11 (9) ◽  
pp. 3868
Author(s):  
Qiong Wu ◽  
Hairui Zhang ◽  
Jie Lian ◽  
Wei Zhao ◽  
Shijie Zhou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Cantilever Beam ◽  
Large Scale ◽  
Low Frequency ◽  
Vibration Energy ◽  
Random Wave ◽  
Periodic Signal ◽  
Vibration Energy Harvesting ◽  
Motion Activity

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1474
Author(s):  
Ruben Tapia-Olvera ◽  
Francisco Beltran-Carbajal ◽  
Antonio Valderrabano-Gonzalez ◽  
Omar Aguilar-Mejia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Large Scale ◽  
Short Circuit ◽  
Dynamic Performance ◽  
Low Frequency ◽  
Electric Power System ◽  
Design Stage ◽  
Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

scholarly journals Optimizing the Frequency Capping: A Robust and Reliable Methodology to Define the Number of Ads to Maximize ROAS

2021 ◽  
Vol 11 (15) ◽  
pp. 6688
Author(s):  
Jesús Romero Leguina ◽  
Ángel Cuevas Rumin ◽  
Rubén Cuevas Rumin
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Low Frequency ◽  
Digital Marketing ◽  
Optimal Frequency ◽  
Novel Technique ◽  
Maximum Threshold

The goal of digital marketing is to connect advertisers with users that are interested in their products. This means serving ads to users, and it could lead to a user receiving hundreds of impressions of the same ad. Consequently, advertisers can define a maximum threshold to the number of impressions a user can receive, referred to as Frequency Cap. However, low frequency caps mean many users are not engaging with the advertiser. By contrast, with high frequency caps, users may receive many ads leading to annoyance and wasting budget. We build a robust and reliable methodology to define the number of ads that should be delivered to different users to maximize the ROAS and reduce the possibility that users get annoyed with the ads’ brand. The methodology uses a novel technique to find the optimal frequency capping based on the number of non-clicked impressions rather than the traditional number of received impressions. This methodology is validated using simulations and large-scale datasets obtained from real ad campaigns data. To sum up, our work proves that it is feasible to address the frequency capping optimization as a business problem, and we provide a framework that can be used to configure efficient frequency capping values.

Sign in / Sign up

Export Citation Format

Share Document