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Artificial Neural Network (ANN) Approach for Predicting Concrete Compressive Strength by SonReb 基于SonReb的人工神经网络(ANN)混凝土抗压强度预测方法
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/SDHM.2021.015644
M. Bonagura, L. Nobile
The compressive strength of concrete is one of most important mechanical parameters in the performance assessment of existing reinforced concrete structures. According to various international codes, core samples are drilled and tested to obtain the concrete compressive strengths. Non-destructive testing is an important alternative when destructive testing is not feasible without damaging the structure. The commonly used non-destructive testing (NDT) methods to estimate the in-situ values include the Rebound hammer test and the Ultrasonic Pulse Velocity test. The poor reliability of these tests due to different aspects could be partially contrasted by using both methods together, as proposed.in the SonReb method. There are three techniques that are commonly used to predict the compressive strength of concrete based on the SonReb measurements: computational modeling, artificial intelligence, and parametric multi-variable regression models. In a previous study the accuracy of the correlation formulas deduced from the last technique has been investigated in comparison with the effective compressive strengths based on destructive test results on core drilled in adjacent locations. The aim of this study is to verify the accuracy of Artificial Neural Approach comparing the estimated compressive strengths based on NDT measured parameters with the same effective compressive strengths. The comparisons show the best performance of ANN approach.
混凝土抗压强度是现有钢筋混凝土结构性能评价中最重要的力学参数之一。根据各种国际规范,钻取岩心样品并进行测试,以获得混凝土抗压强度。当破坏性检测无法在不损坏结构的情况下进行时,无损检测是一种重要的替代方法。目前常用的无损检测方法有回弹锤法和超声脉冲速度法。由于不同方面的原因,这些测试的可靠性较差,可以通过将两种方法结合使用来部分对比。在SonReb方法中。有三种技术通常用于基于SonReb测量来预测混凝土的抗压强度:计算建模、人工智能和参数多变量回归模型。在之前的研究中,将最后一种技术推导出的相关公式的准确性与基于相邻位置岩心的有效抗压强度破坏性试验结果进行了比较。本研究的目的是验证人工神经方法的准确性,将基于无损检测测量参数的估计抗压强度与相同的有效抗压强度进行比较。比较表明,人工神经网络方法的性能最好。
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引用次数: 9
A TimeImageNet Sequence Learning for Remaining Useful Life Estimation of Turbofan Engine in Aircraft Systems 基于TimeImageNet序列学习的飞机涡扇发动机剩余使用寿命估计
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/sdhm.2021.016975
S. Kalyani, K. Venkata Rao, A. Mary Sowjanya
Internet of Things systems generate a large amount of sensor data that needs to be analyzed for extracting useful insights on the health status of the machine under consideration. Sensor data of all possible states of a system are used for building machine learning models. These models are further used to predict the possible downtime for proactive action on the system condition. Aircraft engine data from run to failure is used in the current study. The run to failure data includes states like new installation, stable operation, first reported issue, erroneous operation, and final failure. In the present work, the non-linear multivariate sensor data is used to understand the health status and anomalous behavior. The methodology is based on different sampling sizes to obtain optimum results with great accuracy. The time series of each sensor is converted to a 2D image with a specific time window. Converted Images would represent the health of a system in higher-dimensional space. The created images were fed to Convolutional Neural Network, which includes both time variation and space variation of each sensed parameter. Using these created images, a model for estimating the remaining life of the aircraft is developed. Further, the proposed net is also used for predicting the number of engines that would fail in the given time window. The current methodology is useful in avoiding the health index generation for predicting the remaining useful life of the industrial components. Better accuracy in the classification of components is achieved using the TimeImagenet-based approach.
物联网系统产生大量的传感器数据,需要对这些数据进行分析,以提取有关所考虑的机器健康状态的有用见解。系统所有可能状态的传感器数据用于构建机器学习模型。这些模型进一步用于预测系统条件下主动操作的可能停机时间。本研究使用的是飞机发动机从运行到故障的数据。运行到故障的数据包括新安装、稳定运行、首次报告的问题、错误操作和最终故障等状态。在本工作中,非线性多变量传感器数据用于了解健康状态和异常行为。该方法基于不同的采样大小,以获得精度高的最佳结果。将每个传感器的时间序列转换为具有特定时间窗的二维图像。转换后的图像将表示高维空间中系统的健康状况。将生成的图像输入到卷积神经网络中,卷积神经网络中包含了每个被测参数的时空变化。利用这些生成的图像,开发了估算飞机剩余寿命的模型。此外,所提出的网络还用于预测在给定时间窗口内将发生故障的发动机数量。目前的方法有助于避免生成健康指数来预测工业部件的剩余使用寿命。使用基于timeimagenet的方法可以提高组件分类的准确性。
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引用次数: 0
Digital Twin-Driven Intelligent Construction: Features and Trends 数字孪生驱动的智能建筑:特点与趋势
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/sdhm.2021.018247
Hao Zhang, Yongqi Zhou, Huaxin Zhu, D. Sumarac, Maosen Cao
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引用次数: 6
Experimental and Numerical Assessment on Seismic Performance of Earth Adobe Walls 土坯墙抗震性能试验与数值评价
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/SDHM.2021.011193
Zele Li, Mohammad N. Noori, Wael A. Altabey
Earth buildings are common types of structures in most rural areas in all developing countries. Catastrophic failure and destruction of these structures under seismic loads always result in loss of human lives and economic losses. Wall is an important load-bearing component of raw soil buildings. In this paper, a novel approach is proposed to improve the strength and ductility of adobe walls. Three types of analyses, material properties, mechanical properties, and dynamic properties, are carried out for the seismic performance assessment of the adobe walls. These performed studies include that, material properties of the earth cylinder block, mechanical properties of adobe walls under quasi-static loads, and dynamic performance of adobe walls excited by seismic waves. On investigation of material properties, eighteen cylindrical specimens with a diameter of 100 mm and a height of 110 mm were divided into three groups for compressive, tensile, and split pull strength tests, respectively. The results of the three groups of tests showed that the yield strength ratios of compressive, tensile, and shear strength were about 1:0.3:0.2. In order to study the performance of structural components, three 1/3 scale model raw soil walls with a dimension of 1,200 mm in width, 1,000 mm in height, and 310 mm in thickness were tested under cyclic loading. The average wall capacity of the wall obtained by the test was about 13.5 kN and the average displacement angle was about 1/135. The numerical simulation experiment is used to explore the mechanism of structural failure. A three-dimensional finite element model is established by choosing the material parameters based on the above test outcomes. The accuracy of the numerical simulation experiment is verified by simulation and comparison of the above quasi-static test results. Further, the collapse process of raw soil wall under a seismic wave is simulated for exploring the response and damage mechanism of structure. Based on those systematically analyzed, some useful suggested guidelines are provided for improving the seismic performance of raw soil buildings.
在所有发展中国家的大多数农村地区,土楼是常见的结构类型。这些结构在地震荷载作用下的灾难性破坏往往会造成人员伤亡和经济损失。墙体是生土建筑的重要承重构件。本文提出了一种提高土坯墙体强度和延性的新方法。对土坯墙的抗震性能进行了材料性能、力学性能和动力性能三种类型的分析。这些研究包括土缸体的材料特性、准静态载荷作用下土坯墙的力学特性以及地震波作用下土坯墙的动力性能。在材料性能研究方面,将18个直径为100 mm、高度为110 mm的圆柱形试件分为三组,分别进行了抗压、拉伸和劈裂拉强度试验。三组试验结果表明,抗压、抗拉、抗剪强度的屈服强度比约为1:0.3:0.2。为了研究结构构件的性能,对3个尺寸为宽1200 mm、高1000 mm、厚310 mm的1/3比例尺模型原土墙进行了循环加载试验。试验得到的墙体平均承载力约为13.5 kN,平均位移角约为1/135。通过数值模拟试验,探讨了结构破坏的机理。根据上述试验结果,选择材料参数,建立三维有限元模型。通过对上述准静态试验结果的仿真和对比,验证了数值模拟实验的准确性。在此基础上,模拟了原土墙在地震波作用下的倒塌过程,探讨了结构的反应和破坏机理。在此基础上,提出了改善生土建筑抗震性能的建议。
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引用次数: 9
Experimental Study on Compressive Strength of Recycled Aggregate Concrete under High Temperature 再生骨料混凝土高温抗压强度试验研究
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/sdhm.2021.015988
M. Akhtar, Abdulsamee M. Halahla, Amin H. Almasri
This research aims to study the effect of elevated temperature on the compressive strength evolution of concrete made with recycled aggregate. Demolished building concrete samples were collected from four different sites in Saudi Arabia, namely from Tabuk, Madina, Yanbu, and Riyadh. These concretes were crushed and recycled into aggregates to be used to make new concrete samples. These samples were tested for axial compressive strength at ages 3, 7, 14, and 28 days at ambient temperature. Samples of the same concrete mixes were subjected to the elevated temperature of 300°C and tested for compressive strength again. The experimental result reveals that the recycled aggregate concrete samples have good quality at ambient and elevated temperatures and are considered fairly close to the concrete made with natural aggregate. However, recycled aggregate concrete at high temperatures showed higher strength degradation than natural aggregate concrete, but with differences that do not exceed 5% to 10%. The concrete samples made from recycled coarse aggregates also reached the design strength. It can be considered acceptable, considering the high variation in the concrete’s thermal response found in the literature.
本研究旨在研究高温对再生骨料混凝土抗压强度演变的影响。拆除的建筑混凝土样本从沙特阿拉伯的四个不同地点收集,即塔布克、麦地那、延布和利雅得。这些混凝土被碾碎并回收成集料,用于制作新的混凝土样品。这些样品在3、7、14和28天的环境温度下进行了轴向抗压强度测试。将相同的混凝土混合料试样进行300℃的高温试验,并再次进行抗压强度测试。试验结果表明,再生骨料混凝土试样在常温和高温条件下均具有良好的性能,与天然骨料混凝土性能相当接近。然而,高温下再生骨料混凝土的强度退化高于天然骨料混凝土,但差异不超过5% ~ 10%。回收粗骨料制成的混凝土样品也达到了设计强度。考虑到在文献中发现的混凝土热响应的高变化,它可以被认为是可以接受的。
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引用次数: 7
Fatigue Performance of Orthotropic Steel Decks in Super-Wide Steel Box Girder Considering Transverse Distribution of Vehicle Load 考虑车辆荷载横向分布的超宽钢箱梁正交各向异性钢桥面疲劳性能
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/sdhm.2021.017526
Xudong Wang, C. Miao, Mao Yang, You-liang Ding
This study presents an investigation on the fatigue analysis of four types of details on orthotropic steel decks (OSDs) for a cable-stayed super-wide steel box girder bridge based on finite-element analysis (FEA) with vehicle transverse distribution model (VTDM). A high-fidelity 3D FE model verified by the static load test is established to satisfy the fatigue analysis accuracy. The stress behavior of super-wide steel box girders under the vehicle load at different lane locations is investigated. Then, considering the effect of VTDM, the fatigue life analysis of four typical details is performed using the Miner cumulative damage rule. The results show that the vehicle transverse location has a great influence on the stress behavior of details with sharp influence surface, and the stress ranges in the outermost lane are larger than those in other lanes, indicating that the details of OSD in the outermost lane are prone to fatigue. The fatigue life analysis indicates that the diaphragm cutout is more prone to fatigue than other details, which should be carefully treated in bridge maintenance.
基于车辆横向分布模型(VTDM)的有限元分析方法,对某斜拉超宽钢箱梁桥正交各向异性钢桥面(OSDs)的四种结构细节进行了疲劳分析。通过静载试验,建立了满足疲劳分析精度的高保真三维有限元模型。研究了不同车道位置超宽箱梁在车辆荷载作用下的受力特性。然后,考虑VTDM的影响,采用Miner累积损伤规则对四个典型细部进行了疲劳寿命分析。结果表明:车辆横向位置对影响面尖锐的细节应力行为影响较大,且最外侧车道的应力范围大于其他车道,表明最外侧车道OSD细节容易发生疲劳;疲劳寿命分析表明,隔膜开孔是桥梁维修中最容易出现疲劳的部位,应慎重对待。
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引用次数: 3
Research on Reconstruction Technology of Flexible Structure Shape Based on FBG Sensor Array and Deep Learning Algorithm 基于FBG传感器阵列和深度学习算法的柔性结构形状重构技术研究
Q2 Engineering Pub Date : 2021-01-01 DOI: 10.32604/sdhm.2022.018202
K. Huang, Jie Yan, Lei Zhang, Faye Zhang, Mingshun Jiang, Q. Sui
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引用次数: 0
Finite Element Model Updating for Structural Health Monitoring 结构健康监测的有限元模型更新
Q2 Engineering Pub Date : 2020-01-01 DOI: 10.32604/sdhm.2020.08792
A. Haidarpour, K. Tee
This paper provides a model updating approach to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration responses. Research in vibration-based damage identification has been rapidly expanding over the last few decades. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause changes in the modal properties which could be obtained by structural health monitoring (SHM). Updating is a process fraught with numerical difficulties. These arise from inaccuracy in the model and imprecision and lack of information in the measurements, mainly taken place in joints and critical points. The motivation for the development of this technology is presented, methods are categorized according to various criteria such as the level of damage detection provided from vibration testing, natural frequency and mode shape readings are then obtained by using modal analysis techniques, which are used for updating structural parameters of the associated finite element model. The experimental studies for the laboratory tested bridge model show that the proposed model updating using ME’scope technique can provide reasonable model updating results.
本文提供了一种模型更新方法,通过检测测量振动响应的变化来检测、定位和表征结构和机械系统中的损伤。在过去的几十年里,基于振动的损伤识别研究得到了迅速的发展。该技术背后的基本思想是,模态参数(特别是频率、模态振型和模态阻尼)是结构物理特性(质量、阻尼和刚度)的函数。因此,物理性能的变化会引起模态性能的变化,这可以通过结构健康监测(SHM)获得。更新是一个充满数字困难的过程。这主要是由于模型的不精确和测量的不精确和信息的缺乏,主要发生在关节和临界点。提出了开发该技术的动机,根据各种标准对方法进行分类,例如从振动测试中提供的损伤检测水平,然后通过使用模态分析技术获得固有频率和模态振型读数,用于更新相关有限元模型的结构参数。对室内试验桥梁模型的实验研究表明,本文提出的模型修正方法能够提供合理的模型修正结果。
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引用次数: 9
Long-Term Bending Behaviour of Prestressed Glulam Bamboo-Wood BeamBased on Creep Effect 基于徐变效应的预应力胶合竹木梁长期弯曲性能
Q2 Engineering Pub Date : 2020-01-01 DOI: 10.32604/sdhm.2020.09104
Guo Nan, Huajing Xiong, Mingtao Wu, Hongliang Zuo, Feng Jiang, Xiaofeng Hou, D. Xin
: Creep is an important characteristic of bamboo and wood materials under long-term loading. This paper aims to study the long-term bending behaviour of prestressed glulam bamboo-wood beam (GBWB). For this, 14 pre-stressed GBWBs were selected and subjected to a long-term loading test for 60 days. Then, a comparative analysis was performed for the effects of pretension values, the number of pre-stressed wires, and long-term load on the stress variation of the steel wire and the long-term de fl ection of the beam midspan. The test results showed that with the number of prestressed wires increasing, the total stress of the steel wire in the beam midspan and the ratio of the long-term de fl ection to the total de fl ection decreases decreased, but when the number of steel wires exceeded 4, the total stress and long-term de fl ection was less in fl uenced; with the pre-tension value increasing, the ratio of the total stress of the steel wire in the beam midspan and the ratio of the long-term de fl ection to the total de fl ection also decreased, but when the prestress force was greater than 3.975 kN, the total stress and long-term de fl ection were less affected; with the other parameters unchanged, when the value of the long-term load increased, the total stress of the steel wire decreased, and the long-term de fl ection of the beam midspan increased, which shall be more signi fi cant with the long-term load greater than 30% of the standard ultimate bearing capacity. After the test, the experimental data were fi tted, and the creep coef fi cient was given. Finally, the long-term stiffness calculation formula of the pre-stressed GBWB based on creep effect was proposed. The research fi ndings have certain theoretical signi fi cance and engineering value.
:蠕变是竹木材料在长期荷载作用下的重要特性。本文旨在研究预应力胶合竹木梁的长期弯曲性能。为此,选取了14根预应力GBWBs进行了60天的长期加载试验。对比分析了预应力值、预应力筋数和长期荷载对预应力筋应力变化和梁跨中长期挠度的影响。试验结果表明:随着预应力筋数的增加,梁跨中钢丝的总应力和长期挠度占总挠度的比例减小,但当预应力筋数超过4根时,总应力和长期挠度受影响较小;随着预张力值的增大,梁跨中钢丝的总应力和长期挠度与总挠度之比也减小,但当预应力大于3.975 kN时,总应力和长期挠度受影响较小;在其他参数不变的情况下,当长期荷载值增大时,钢丝总应力减小,梁跨中长期挠度增大,当长期荷载大于标准极限承载力的30%时,挠度增大更为显著。试验结束后,对试验数据进行拟合,并给出了蠕变系数。最后,提出了基于蠕变效应的预应力GBWB长期刚度计算公式。研究成果具有一定的理论意义和工程价值。
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引用次数: 5
Research on Concrete Beam Crack Recognition Algorithm Based on BlockThreshold Value Image Processing 基于块阈值图像处理的混凝土梁裂缝识别算法研究
Q2 Engineering Pub Date : 2020-01-01 DOI: 10.32604/sdhm.2020.011479
Wenting Qiao, Xiaoguang Wu, Wen Sun, Qiande Wu
: To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven illumination and complex surface color of concrete structure, this paper has proposed a block segmentation method of maximum entropy threshold based on the digital image data obtained by the ACTIS automatic detection system. The steps in this research are as follows: 1. The crack digital images of concrete specimens with typical features were collected by using the Actis system of KURABO Co., Ltd., of Japan in the concrete beam bending test. 2. The images are segmented into blocks to distinguish backgrounds of different grayscale. 3. The maximum interclass average gray difference method is used to distinguish the sub-blocks and screen out the image blocks that need to be segmented. 4. Segmentation is made to the image with 2D maximum entropy threshold segmentation method to obtain the binary image, and the target image can be obtained by screening the connected domain features of the binary image. Results have shown that compared with other algorithms, the proposed method can effectively decrease the image over-segmentation and under segmentation rates, highlight the characteristics of the target cracks, solve the problems of excessive difference between the identi fi ed length and actual length of cracks caused by background gray level change and uneven illumination, and effectively improve the recognition accuracy of bridge concrete cracks.
针对混凝土结构在光照不均匀、表面颜色复杂的情况下,数字图像对混凝土结构裂缝的识别精度不高的问题,本文提出了一种基于ACTIS自动检测系统获取的数字图像数据的最大熵阈值分块方法。本研究的步骤如下:1。采用日本KURABO公司的Actis系统采集混凝土梁弯曲试验中具有典型特征的混凝土试件裂纹数字图像。2. 图像被分割成块,以区分不同灰度的背景。3.采用最大类间平均灰度差法区分子块,筛选出需要分割的图像块。4. 用二维最大熵阈值分割方法对图像进行分割得到二值化图像,通过筛选二值化图像的连通域特征得到目标图像。结果表明,与其他算法相比,所提方法能有效降低图像的过分割率和欠分割率,突出目标裂缝的特征,解决背景灰度变化和光照不均匀导致的裂缝识别长度与实际长度差距过大的问题,有效提高桥梁混凝土裂缝的识别精度。
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引用次数: 3
期刊
SDHM Structural Durability and Health Monitoring
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