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Design of an enhanced visual odometry by building and matching compressive panoramic landmarks online

Wei LU,Zhi-yu XIANG,Ji-lin LIU

《信息与电子工程前沿（英文）》 2015年 第16卷 第2期   页码 152-165 doi: 10.1631/FITEE.1400139

摘要： Efficient and precise localization is a prerequisite for the intelligent navigation of mobile robots. Traditional visual localization systems, such as visual odometry (VO) and simultaneous localization and mapping (SLAM), suffer from two shortcomings: a drift problem caused by accumulated localization error, and erroneous motion estimation due to illumination variation and moving objects. In this paper, we propose an enhanced VO by introducing a panoramic camera into the traditional stereo-only VO system. Benefiting from the 360° field of view, the panoramic camera is responsible for three tasks: (1) detecting road junctions and building a landmark library online; (2) correcting the robot’s position when the landmarks are revisited with any orientation; (3) working as a panoramic compass when the stereo VO cannot provide reliable positioning results. To use the large-sized panoramic images efficiently, the concept of compressed sensing is introduced into the solution and an adaptive compressive feature is presented. Combined with our previous two-stage local binocular bundle adjustment (TLBBA) stereo VO, the new system can obtain reliable positioning results in quasi-real time. Experimental results of challenging long-range tests show that our enhanced VO is much more accurate and robust than the traditional VO, thanks to the compressive panoramic landmarks built online.

关键词： Visual odometry     Panoramic landmark     Landmark matching     Compressed sensing     Adaptive compressive feature    

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Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariateadaptive regression spline

Ali Reza GHANIZADEH, Morteza RAHROVAN

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 787-799 doi: 10.1007/s11709-019-0516-8

摘要： The recycled layer in full-depth reclamation (FDR) method is a mixture of coarse aggregates and reclaimed asphalt pavement (RAP) which is stabilized by a stabilizer agent. For design and quality control of the final product in FDR method, the unconfined compressive strength of stabilized material should be known. This paper aims to develop a mathematical model for predicting the unconfined compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariate adaptive regression spline (MARS). To this end, two different aggregate materials were mixed with different percentages of RAP and then stabilized by different percentages of Portland cement. For training and testing of MARS model, total of 64 experimental UCS data were employed. Predictors or independent variables in the developed model are percentage of RAP, percentage of cement, optimum moisture content, percent passing of #200 sieve, and curing time. The results demonstrate that MARS has a great ability for prediction of the UCS in case of soil-RAP blend stabilized with Portland cement ( is more than 0.97). Sensitivity analysis of the proposed model showed that the cement, optimum moisture content, and percent passing of #200 sieve are the most influential parameters on the UCS of FDR layer.

关键词： full-depth reclamation     soil-reclaimed asphalt pavement blend     Portland cement     unconfined compressive strength     multivariate adaptive regression spline    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 61-79 doi: 10.1007/s11709-020-0684-6

摘要： Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

关键词： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive strength    

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基于Wilkinson矩阵提升稀疏自适应匹配追踪重构效率 None

Rasha SHOITAN, Zaki NOSSAIR, I. I. IBRAHIM, Ahmed TOBAL

《信息与电子工程前沿（英文）》 2018年 第19卷 第4期   页码 503-512 doi: 10.1631/FITEE.1601588

摘要： 稀疏自适应匹配追踪（sparsity adaptive matching pursuit，SAMP）是压缩感知信号的一种贪婪重构算法。将块压缩感知（block compressive sensing，BCS）思想与SAMP技术结合，以提高SAMP技术性能。

关键词： 块压缩传感；稀疏自适应匹配追踪；贪婪算法；Wilkinson矩阵    

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The ITZ microstructure, thickness, porosity and its relation with compressive and flexural strength of

《结构与土木工程前沿（英文）》 2022年 第16卷 第2期   页码 191-201 doi: 10.1007/s11709-021-0792-y

摘要： A new insight into the interfacial transition zone (ITZ) in cement mortar specimens (CMSs) that is influenced by cement fineness is reported. The importance of cement fineness in ITZ characterizations such as morphology and thickness is elucidated by backscattered electron images and by consequences to the compressive (Fc) and flexural strength (Ff), and porosity at various water/cement ratios. The findings indicate that by increasing the cement fineness the calcium silicate hydrate formation in the ITZ is favored and that this can refine the pore structures and create a denser and more homogeneous microstructure. By increasing cement fineness by about 25% of, the ITZ thickness of CMSs was reduced by about 30% and Fc was increased by 7%–52% and Ff by 19%–40%. These findings illustrate that the influence of ITZ features on the mechanical strength of CMSs is mostly related to the cement fineness and ITZ microstructure.

关键词： cement fineness     interfacial transition zone     compressive and flexural strength    

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自适应多小波基函数构造与机械故障诊断应用研究

何正嘉,孙海亮,訾艳阳

《中国工程科学》 2011年 第13卷 第10期   页码 83-92

摘要：

设备在运行中萌生的故障(即早期故障)，特征信息微弱且往往被机械设备运行过程的强噪声所淹没，给故障诊断与预示带来困难，已成为国内外此领域研究的热点和难点。文章深入研究了机械故障动态信号与基函数的内积变换原理；提出了若干自适应多小波基函数构造方法；改进了几种多小波邻域区间和局部阈值降噪方法。利用典型的工程案例分析和阐述了重油催化裂化装置、连铸连轧机组、空分机、电力机车和船载卫星通信地球站传动系统在运行状态下，微弱动态信号的特征增强和复合故障特征提取的工程应用实效。

关键词： 机械故障诊断     内积变换原理     自适应基函数     多小波降噪     故障特征提取    

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Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

《结构与土木工程前沿（英文）》   页码 901-914 doi: 10.1007/s11709-023-0915-8

摘要： The integrity and bearing capacity of segment joints in shield tunnels are associated closely with the mechanical properties of the joints. This study focuses on the mechanical characteristics and mechanism of a bolted circumferential joint during the entire bearing process. Simplified analytical algorithms for four stress stages are established to describe the bearing behaviors of the joint under a compressive bending load. A height adjustment coefficient, α, for the outer concrete compression zone is introduced into a simplified analytical model. Factors affecting α are determined, and the degree of influence of these factors is investigated via orthogonal numerical simulations. The numerical results show that α can be specified as approximately 0.2 for most metro shield tunnels in China. Subsequently, a case study is performed to verify the rationality of the simplified theoretical analysis for the segment joint via numerical simulations and experiments. Using the proposed simplified analytical algorithms, a parametric investigation is conducted to discuss the factors affecting the ultimate compressive bending capacity of the joint. The method for optimizing the joint flexural stiffness is clarified. The results of this study can provide a theoretical basis for optimizing the design and prediciting the damage of bolted segment joints in shield tunnels.

关键词： shield tunnel     segment joint     joint structural model     failure mechanism    

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Optimizing the compressive strength of concrete containing micro-silica, nano-silica, and polypropylene

Fatemeh ZAHIRI, Hamid ESKANDARI-NADDAF

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 821-830 doi: 10.1007/s11709-019-0518-6

摘要： Many studies have evaluated the effects of additives such as nano-silica (NS), micro-silica (MS) and polymer fibers on optimizing the mechanical properties of concrete, such as compressive strength. Nowadays, with progress in cement industry provides, it has become possible to produce cement type I with strength classes of 32.5, 42.5, and 52.5 MPa. On the one hand, the microstructure of cement has changed, and modified by NS, MS, and polymers; therefore it is very important to determine the optimal percentage of each additives for those CSCs. In this study, 12 mix designs containing different percentages of MS, NS, and polymer fibers in three cement strength classes(CSCs) (32.5, 42.5, and 52.5 MPa) were designed and constructed based on the mixture method. Results indicated the sensitivity of each CSCs can be different on the NS or MS in compressive strength of concrete. Consequently, strength classes have a significant effect on the amount of MS and NS in mix design of concrete. While, polymer fibers don’t have significant effect in compressive strength considering CSCs.

关键词： mixture method     compressive strength     nano-silica     micro-silica     polypropylene fibers    

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基于质量感知的水下图像自适应压缩方法 Regular Papers

Ya-qiong CAI, Hai-xia ZOU, Fei YUAN

《信息与电子工程前沿（英文）》 2019年 第20卷 第5期   页码 716-730 doi: 10.1631/FITEE.1700737

摘要： 水下图像压缩是水声图像传输系统中必不可少并且至关重要的一个环节，有效的预测感知压缩图像的质量能使系统在压缩过程更好的调整压缩率，提高图像传输通信系统的效率。本文首先分别对压缩感知和嵌入式编码两种压缩策略下的水下压缩图像进行质量感知，然后利用图像活动性IAM（Image Activity Measurement）与BPP-SSIM（Bits Per Pixel and Structural SIMilarity）曲线间的映射进行建模并获得模型参数，从而根据图像的空域活动性、压缩率和压缩策略预测图像的压缩质量。实验结果表明本文所建立的模型能有效拟合水下图像的压缩质量曲线，根据模型中参数所具有的规律性能在小误差范围内预测出水下压缩图像的感知质量。本文所提出的方法能够有效的预测感知水下图像的压缩质量，并有效权衡压缩率与压缩质量之间的关系，减小发送端的数据缓存压力，提高水下图像通信系统的效率。

关键词： 水下图像压缩；SPIHT压缩；压缩感知；压缩质量预测    

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Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 829-839 doi: 10.1007/s11465-021-0652-4

摘要： Existing fault diagnosis methods usually assume that there are balanced training data for every machine health state. However, the collection of fault signals is very difficult and expensive, resulting in the problem of imbalanced training dataset. It will degrade the performance of fault diagnosis methods significantly. To address this problem, an imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning is proposed in this paper. Unsupervised autoencoder is firstly used to compress every monitoring signal into a low-dimensional vector as the node attribute in the SuperGraph. And the edge connections in the graph depend on the relationship between signals. On the basis, graph convolution is performed on the constructed SuperGraph to achieve imbalanced training dataset fault diagnosis for rotating machinery. Comprehensive experiments are conducted on a benchmarking publicized dataset and a practical experimental platform, and the results show that the proposed method can effectively achieve rotating machinery fault diagnosis towards imbalanced training dataset through graph feature learning.

关键词： imbalanced fault diagnosis     graph feature learning     rotating machinery     autoencoder    

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Time- and temperature-dependence of compressive and tensile behaviors of polypropylene fiber-reinforced

《结构与土木工程前沿（英文）》 2021年 第15卷 第4期   页码 1025-1037 doi: 10.1007/s11709-021-0741-9

摘要： The understanding of compressive and tensile behaviors of polypropylene fiber-reinforced cemented paste backfill (FR-CPB) play crucial roles in the successful implementation of reinforcement technique in underground mine backfilling operations. However, very limited studies have been performed to gain insight into the evolution of compressive and tensile behaviors and associated mechanical properties of FR-CPB under various curing temperatures from early to advanced ages. Thus, this study aims to investigate the time (7, 28, and 90 d)- and temperature (20°C, 35°C, and 45°C)-dependence of constitutive behavior and mechanical properties of FR-CPB. The obtained results show that pre- and post-failure behaviors of FR-CPB demonstrate strongly curing temperature-dependence from early to advanced ages. Moreover, the pseudo-hardening behavior is sensitive to curing temperature, especially at early ages. Furthermore, the mechanical properties including elastic modulus, material stiffness, strengths, brittleness, cohesion, and internal friction angle of FR-CPB show increasing trends with curing temperature as curing time elapses. Additionally, a predictive model is developed to capture the strong correlation between compressive and tensile strength of FR-CPB. The findings of this study will contribute to the successful implementation of FR-CPB technology.

关键词： cemented paste backfill     fiber reinforcement     constitutive behavior     temperature     tailings    

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Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

《能源前沿（英文）》 2020年 第14卷 第4期   页码 817-835 doi: 10.1007/s11708-020-0709-9

摘要： Since gas turbine plays a key role in electricity power generating, the requirements on the safety and reliability of this classical thermal system are becoming gradually strict. With a large amount of renewable energy being integrated into the power grid, the request of deep peak load regulation for satisfying the varying demand of users and maintaining the stability of the whole power grid leads to more unstable working conditions of gas turbines. The startup, shutdown, and load fluctuation are dominating the operating condition of gas turbines. Hence simulating and analyzing the dynamic behavior of the engines under such instable working conditions are important in improving their design, operation, and maintenance. However, conventional dynamic simulation methods based on the physic differential equations is unable to tackle the uncertainty and noise when faced with variant real-world operations. Although data-driven simulating methods, to some extent, can mitigate the problem, it is impossible to perform simulations with insufficient data. To tackle the issue, a novel transfer learning framework is proposed to transfer the knowledge from the physics equation domain to the real-world application domain to compensate for the lack of data. A strong dynamic operating data set with steep slope signals is created based on physics equations and then a feature similarity-based learning model with an encoder and a decoder is built and trained to achieve feature adaptive knowledge transferring. The simulation accuracy is significantly increased by 24.6% and the predicting error reduced by 63.6% compared with the baseline model. Moreover, compared with the other classical transfer learning modes, the method proposed has the best simulating performance on field testing data set. Furthermore, the effect study on the hyper parameters indicates that the method proposed is able to adaptively balance the weight of learning knowledge from the physical theory domain or from the real-world operation domain.

关键词： gas turbine     dynamic simulation     data-driven     transfer learning     feature similarity    

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Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

《结构与土木工程前沿（英文）》 2021年 第15卷 第2期   页码 520-536 doi: 10.1007/s11709-021-0689-9

摘要： This study aims to improve the unconfined compressive strength of soils using additives as well as by predicting the strength behavior of stabilized soils using two artificial-intelligence-based models. The soils used in this study are stabilized using various combinations of cement, lime, and rice husk ash. To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratory dataset comprising 137 soil specimens treated with different combinations of cement, lime, and rice husk ash is used. Two artificial-intelligence-based models including artificial neural networks and support vector machines are used comparatively to predict the strength characteristics of soils treated with cement, lime, and rice husk ash under different conditions. The suggested models predicted the unconfined compressive strength of soils accurately and can be introduced as reliable predictive models in geotechnical engineering. This study demonstrates the better performance of support vector machines in predicting the strength of the investigated soils compared with artificial neural networks. The type of kernel function used in support vector machine models contributed positively to the performance of the proposed models. Moreover, based on sensitivity analysis results, it is discovered that cement and lime contents impose more prominent effects on the unconfined compressive strength values of the investigated soils compared with the other parameters.

关键词： unconfined compressive strength     artificial neural network     support vector machine     predictive models     regression    

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Experimental study on the compressive performance of new sandwich masonry walls

Jianzhuang XIAO, Jie PU, Yongzhong HU

《结构与土木工程前沿（英文）》 2013年 第7卷 第2期   页码 154-163 doi: 10.1007/s11709-013-0203-0

摘要： Sandwich masonry wall, namely, multi-leaf masonry wall, is widely applied as energy-saving wall since the interlayer between the two outer leaves can act as insulation layer. New types of sandwich walls keep appearing in research and application, and due to their unique connection patterns, experimental studies should be performed to investigate the mechanical behavior, especially the compressive performance. 3 new types of sandwich masonry wall were investigated in this paper, and 3 different technical measures were considered to guarantee the cooperation between the two leaves of the walls. Based on the compression tests of 13 specimens, except for some damage patterns similar with the conventional masonry walls, several new failure patterns are found due to unique connection construction details. Comparisons were made between the tested compression capacity and the theoretical one which was calculated according to the Chinese Code for Design of Masonry Structures. The results indicate that the contributions of the 3 technical measures are different. The modification coefficient ( ) was suggested to evaluate the contribution of the technical measures on the compression capacity, and then a formula was proposed to evaluate the design compression capacity of the new sandwich masonry walls.

关键词： sandwich wall     insulation wall     connection     compressive performance     compression test    

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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

《信息与电子工程前沿（英文）》 2015年 第16卷 第3期   页码 227-237 doi: 10.1631/FITEE.1400217

摘要： We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sampling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By compositing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best performance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

关键词： Compressive sensing (CS)     Image fusion     Gradient-based image fusion     CS-based image fusion    

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标题 作者 时间 类型 操作

Design of an enhanced visual odometry by building and matching compressive panoramic landmarks online

Wei LU,Zhi-yu XIANG,Ji-lin LIU

期刊论文

Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariateadaptive regression spline

Ali Reza GHANIZADEH, Morteza RAHROVAN

期刊论文

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

期刊论文

基于Wilkinson矩阵提升稀疏自适应匹配追踪重构效率

Rasha SHOITAN, Zaki NOSSAIR, I. I. IBRAHIM, Ahmed TOBAL

期刊论文

The ITZ microstructure, thickness, porosity and its relation with compressive and flexural strength of

期刊论文

自适应多小波基函数构造与机械故障诊断应用研究

何正嘉,孙海亮,訾艳阳

期刊论文

Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

期刊论文

Optimizing the compressive strength of concrete containing micro-silica, nano-silica, and polypropylene

Fatemeh ZAHIRI, Hamid ESKANDARI-NADDAF

期刊论文

基于质量感知的水下图像自适应压缩方法

Ya-qiong CAI, Hai-xia ZOU, Fei YUAN

期刊论文

Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

期刊论文

Time- and temperature-dependence of compressive and tensile behaviors of polypropylene fiber-reinforced

期刊论文

Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

期刊论文

Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

期刊论文

Experimental study on the compressive performance of new sandwich masonry walls

Jianzhuang XIAO, Jie PU, Yongzhong HU

期刊论文

Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

期刊论文