Shaking Table Model Test of Shanghai Tower

Lu, Xilin,Mao, Yuanjun,Lu, Wensheng,Kang, Liping Council on Tall Building and Urban Habitat Korea 2013 International journal of high-rise buildings Vol.2 No.1

Shaking table test is an important and useful method to help structural engineers get better knowledge about the seismic performance of the buildings with complex structure, just like Shanghai tower. According to Chinese seismic design guidelines, buildings with a very complex and special structural system, or whose height is far beyond the limitation of interrelated codes, should be firstly studied through the experiment on seismic behavior. To investigate the structural response, the weak storey and crack pattern under earthquakes of different levels, and to help the designers improve the design scheme, the shaking table model tests of a scaled model of Shanghai tower were carried out at the State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China. This paper describes briefly the structural system, the design method and manufacture process of the scaled model, and the test results as well.

Combining ICA and SVR in Times Series Predication

Wensheng Dai,Jui-Yu Wu,Chi-Jie Lu 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10

In this paper, a time series prediction approach by combing independent component analysis (ICA) and support vector regression (SVR)is proposed ICA is a novel statistical signal processing technique that was originally proposed to find the latent source signals from observed mixture signal without knowing any prior knowledge of the mixing mechanism. SVR is and artificial intelligence forecasting technique and has been widely applied in time series prediction problems. The proposed approach First uers ICA to the forecasting variables for generating the independent components(ICs). After identifying and removing the ICs containing the noise, the rest of the ICs are then used to reconstruct the forecasting variables which contain less noise. The SVR then uses the denoised forecasting variables to build the forecausting model. in order to evaluaate the performance of the proposed approach the TAIEX(Taiwan Stock Exchange Capitalization weighted Steock index) closing cash index is usde as the illusrtative example. Experimental results show that the proposed model outperforms the SVR model with mon ?filtered forecasting variables and random walk model

Application research of consumer credit Score model based on SVM and DEA

Wensheng Dai,Chi-Jie Lu 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10

Clustering and Classification are the most popular techniques in credit scoring. Most of the hybrid models are lack of revision abilities. To overcome this limitation, a two stages credit scoring model using SVM and DEA is proposed in this paper. Firstly constructing a SVM model and classifying all customs to two groups which are efficient and inefficient group, the performing DEA for those lower efficiency customers and proposing the way to improve their efficiency. This study also performs an empirical research based on the credit card database of a bank. The results show that the SVM has great ability to predict the efficiency and combined model can provide an indeed improvement for bank to improve the efficiency of non-efficient customer.

A cable tension identification technology using percussion sound

Qingzhao Kong,Guowei Wang,Wensheng Lu,Cheng Yuan 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.3

The loss of cable tension for civil infrastructure reduces structural bearing capacity and causes harmful deformation of structures. Currently, most of the structural health monitoring (SHM) approaches for cables rely on contact transducers. This paper proposes a cable tension identification technology using percussion sound, which provides a fast determination of steel cable tension without physical contact between cables and sensors. Notably, inspired by the concept of tensioning strings for piano tuning, this proposed technology predicts cable tension value by deep learning assisted classification of "percussion" sound from tapping a steel cable. To simulate the non-linear mapping of human ears to sound and to better quantify the minor changes in the high-frequency bands of the sound spectrum generated by percussions, Mel-frequency cepstral coefficients (MFCCs) were extracted as acoustic features to train the deep learning network. A convolutional neural network (CNN) with four convolutional layers and two global pooling layers was employed to identify the cable tension in a certain designed range. Moreover, theoretical and finite element methods (FEM) were conducted to prove the feasibility of the proposed technology. Finally, the identification performance of the proposed technology was experimentally investigated. Overall, results show that the proposed percussion-based technology has great potentials for estimating cable tension for <i>in-situ</i> structural safety assessment.

Comparison of semi-active and passive tuned mass damper systems for vibration control of a wind turbine

Eric R. Lalonde,Kaoshan Dai,Girma Bitsuamlak,Wensheng Lu,Zhi Zhao 한국풍공학회 2020 Wind and Structures, An International Journal (WAS Vol.30 No.6

Robust semi-active vibration control of wind turbines using tuned mass dampers (TMDs) is a promising technique. This study investigates a 1.5 megawatt wind turbine controlled by eight different types of tuned mass damper systems of equal mass: a passive TMD, a semi-active varying-spring TMD, a semi-active varying-damper TMD, a semi-active varying-damper-and-spring TMD, as well as these four damper systems paired with an additional smaller passive TMD near the mid-point of the tower. The mechanism and controllers for each of these TMD systems are explained, such as employing magnetorheological dampers for the varying-damper TMD cases. The turbine is modelled as a lumped-mass 3D finite element model. The uncontrolled and controlled turbines are subjected to loading and operational cases including service wind loads on operational turbines, seismic loading with service wind on operational turbines, and high-intensity storm wind loads on parked turbines. The displacement and acceleration responses of the tower at the first and second mode shape maxima were used as the performance indicators. Ultimately, it was found that while all the semi-active TMD systems outperformed the passive systems, it was the semi-active varying-damper-and-spring system that was found to be the most effective overall – capable of controlling vibrations about as effectively with only half the mass as a passive TMD. It was also shown that by reducing the mass of the TMD and adding a second smaller TMD below, the vibrations near the mid-point could be greatly reduced at the cost of slightly increased vibrations at the tower top.

Wind turbine testing methods and application of hybrid testing: A review

Eric R. Lalonde,Kaoshan Dai,Wensheng Lu,Girma Bitsuamlak 한국풍공학회 2019 Wind and Structures, An International Journal (WAS Vol.29 No.3

This paper presents an overview of wind turbine research techniques including the recent application of hybrid testing. Wind turbines are complex structures as they are large, slender, and dynamic with many different operational states, which limits applicable research techniques. Traditionally, numerical simulation is widely used to study turbines while experimental tests are rarer and often face cost and equipment restrictions. Hybrid testing is a relatively new simulation method that combines numerical and experimental techniques to accurately capture unknown or complex behaviour by modelling portions of the structure experimentally while numerically simulating the remainder. This can allow for increased detail, scope, and feasibility in wind turbine tests. Hybrid testing appears to be an effective tool for future wind turbine research, and the few studies that have applied it have shown promising results. This paper presents a literature review of experimental and numerical wind turbine testing, hybrid testing in structural engineering, and hybrid testing of wind turbines. Finally, several applications of hybrid testing for future wind turbine studies are proposed including multi-hazard loading, damped turbines, and turbine failure.