A wireless sensor with data-fusion algorithm for structural tilt measurement

Jian Zhang,Dan Li,Guangwei Zhang,Ziyang Su 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.3

Tilt is a key indicator of structural safety. Real-time monitoring of tilt responses helps to evaluate structural condition, enable cost-effective maintenance, and enhance lifetime resilience. This paper presents a prototype wireless sensing system for structural tilt measurement. Long range (LoRa) technology is adopted by the sensing system to offer long-range wireless communication with low power consumption. The sensor integrates a gyroscope and an accelerometer as the sensing module. Although tilt can be estimated from the gyroscope or the accelerometer measurements, these estimates suffer from either drift issue or high noise. To address this challenging issue and obtain more reliable tilt results, two sensor fusion algorithms, the complementary filter and the Kalman filter, are investigated to fully exploit the advantages of both gyroscope and accelerometer measurements. Numerical simulation is carried out to validate and compare the sensor fusion algorithms. Laboratory experiment is conducted on a simply supported beam under moving vehicle load to further investigate the performance of the proposed wireless tilt sensing system.

APPLICATION OF THE SEGUE STELLAR PARAMETER PIPELINE TO LAMOST STELLAR SPECTRA

Lee, Young Sun,Beers, Timothy C.,Carlin, Jeffrey L.,Newberg, Heidi J.,Hou, Yonghui,Li, Guangwei,Luo, A.-Li,Wu, Yue,Yang, Ming,Zhang, Haotong,Zhang, Wei,Zhang, Yong IOP Publishing 2015 The Astronomical journal Vol.150 No.6

The Study of Services Management Based on the Network Environment

Xuemin Zhang,Zenggang Xiong,Guangwei Wang,Conghuan Ye,Fang Xu 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.5

Service-Oriented Architecture (SOA) constructs applications by publishing services in an open network environment. In network environment individual service changes highly dynamically, it is required the system based on services to adapt to this change. But the current service management in network environment doesn’t have a good, unified management mode, management mechanism, service and quality control system, and lacks of theoretical foundation to express formal service system. In this paper, a service management framework is designed. A mechanism and method based on strategy and dynamic network environment service management are proposed. The method can effectively solve the problem of dynamic service management in network environment, and is widely used in dynamic service management based on Web services.

Quantitative Study of the Reformation of Excess Sludge by Intense Aeration Under Nutrient-poor Conditions

Shuting Zhang,Guangwei Li,Liming Chen,Kiyoshi Toda 한국생물공학회 2004 Biotechnology and Bioprocess Engineering Vol.9 No.6

In the course of anaerobic storage of excess sludge, odors due to chemicals such as hydrogen sulfide are produced. These odors cause many problems. Many methods have been developed to eliminate odors, but all current methods are not only costly, but also largely ineffective. In this paper, we investigate the process of transformation of sludge microorganism cultures through intense aeration under nutrient-poor conditions, in terms of the selective adjustment and control of microorganism culture. The aerated sludge is subsequently returned to the adjusting pool, where the microorganisms inhibit odors, thus the excess sludge itself will act as an odor inhibitor. The process can be verified in terms of viability, in that the degradation capacity of the sludge was maintained after the intensely-aerated sludge was returned to the treatment system.

Developing efficient model updating approaches for different structural complexity - an ensemble learning and uncertainty quantifications

Yi Zhang,Guangwei Lin,Qinzhuo Liao 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.2

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the lowdimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

An ensemble learning based Bayesian model updating approach for structural damage identification

Yi Zhang,Guangwei Lin,Enjian Cai,Taisen Zhao,Zhaoyan Li 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.32 No.1

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.

Design of Fan Performance Detection System Based on ARM Embedded System

Xiangdong Cai,Guangwei Ouyang,Xiaoqing Zhang 보안공학연구지원센터 2014 International Journal of Smart Home Vol.8 No.1

A deep and multiscale network for pavement crack detection based on function-specific modules

Allen A. Zhang,Guolong Wang,Kelvin C. P. Wang,Guangwei Yang 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.32 No.3

Using 3D asphalt pavement surface data, a deep and multiscale network named CrackNet-M is proposed in this paper for pixel-level crack detection for improvements in both accuracy and robustness. The CrackNet-M consists of four function-specific architectural modules: a central branch net (CBN), a crack map enhancement (CME) module, three pooling feature pyramids (PFP), and an output layer. The CBN maintains crack boundaries using no pooling reductions throughout all convolutional layers. The CME applies a pooling layer to enhance potential thin cracks for better continuity, consuming no data loss and attenuation when working jointly with CBN. The PFP modules implement direct down-sampling and pyramidal upsampling with multiscale contexts specifically for the detection of thick cracks and exclusion of non-crack patterns. Finally, the output layer is optimized with a skip layer supervision technique proposed to further improve the network performance. Compared with traditional supervisions, the skip layer supervision brings about not only significant performance gains with respect to both accuracy and robustness but a faster convergence rate. CrackNet-M was trained on a total of 2,500 pixel-wise annotated 3D pavement images and finely scaled with another 200 images with full considerations on accuracy and efficiency. CrackNet-M can potentially achieve crack detection in real-time with a processing speed of 40 ms/image. The experimental results on 500 testing images demonstrate that CrackNet-M can effectively detect both thick and thin cracks from various pavement surfaces with a high level of Precision (94.28%), Recall (93.89%), and F-measure (94.04%). In addition, the proposed CrackNet-M compares favorably to other well-developed networks with respect to the detection of thin cracks as well as the removal of shoulder drop-offs.

Effect of Bi(Zn1/2Nb2/5)O3 addition on phase transition and energy storage properties of BaTiO3 ceramics

Ma Cuiying,Zhang Ruiying,Zhang Guangwei,Du Huiling,Liu Jia,Liang Ruinan,Wang Zhaoguo 한국물리학회 2023 Current Applied Physics Vol.55 No.-

Bi(Zn1/2Nb2/5)O3-modified BaTiO3 ceramics were designed with formula (1‒x)BaTiO3‒xBi(Zn1/2Nb2/5)O3 (0 ≤ x ≤ 0.15) and fabricated using conventional solid-state route. With increasing Bi(Zn1/2Nb2/5)O3 concentration, grain volume increased and phase structure was transformed from tetragonal to pseudo-cubic. Dielectric properties changed from temperature-dependent to temperature-insensitive and curves were flattened. Additionally, higher pseudo-cubic phase content induced slim P-E loop and low Pr. Therefore, 0.94BaTiO3‒0.06Bi(Zn1/2Nb2/5)O3 ceramic achieved energy storage density of 1.85 J/cm3 and high energy efficiency of 91.2% under electric field of 230 kV/cm. This energy storage density was 5 times higher than that of pure BT ceramic. Meanwhile, energy storage properties of this ceramic exhibited excellent thermal stability in the range of 30–120 °C and good frequency stability over 10–100 Hz. This work provides promising alternative option in energy storage materials.

Design and Development of a Single-photon Laser and Infrared Common Aperture Optical System

Wu Hongbo,Zhang Xin,Tan Shuanglong,Liu Mingxin,Wang Lingjie,Yan Lei,Liu Yang,Shi Guangwei 한국광학회 2022 Current Optics and Photonics Vol.6 No.2

A single-photon laser and mid-wave infrared (MWIR) common aperture optical system was designed and developed to detect and range a long-distance civil aviation aircraft. The secondary mirror of the Ritchey-Chretien (R-C) optical system was chosen as a dichroic lens to realize the design of a common aperture system for the laser and MWIR. Point spread function (PSF) ellipticity was introduced to evaluate the coupling efficiency of the laser receiving system. A small aperture stop and narrow filter were set in the secondary image plane and an afocal light path of the laser system, respectively, and the stray light suppression ability of the small aperture stop was verified by modeling and simulation. With high-precision manufacturing technology by single point diamond turning (SPDT) and a high-efficiency dichroic coating, the laser/MWIR common aperture optical system with a φ300 mm aluminum alloy mirror obtained images of buildings at a distance of 5 km with great quality. A civil aviation aircraft detection experiment was conducted. The results show that the common aperture system could detect and track long-distance civil aviation aircraft effectively, and the coverage was more than 450 km (signal-tonoise ratio = 6.3). It satisfied the application requirements for earlier warning and ranging of long-range targets in the area of aviation, aerospace and ground detection systems.