Review on Machine Learning-based Defect Detection of Shield Tunnel Lining

At present, machine learning methods are widely used in various industries for their high adaptability, optimization function, and self-learning reserve function. Besides, the world-famous cities have almost built and formed subway networks that promote economic development. This paper presents the art states of Defect detection of Shield Tunnel lining based on Machine learning (DSTM). In addition, the processing method of image data from the shield tunnel is being explored to adapt to its complex environment. Comparison and analysis are used to show the performance of the algorithms in terms of the effects of data set establishment, algorithm selection, and detection devices. Based on the analysis results, Convolutional Neural Network methods show high recognition accuracy and better adaptability to the complexity of the environment in the shield tunnel compared to traditional machine learning methods. The Support Vector Machine algorithms show high recognition performance only for small data sets. To improve detection models and increase detection accuracy, measures such as optimizing features, fusing algorithms, creating a high-quality data set, increasing the sample size, and using devices with high detection accuracy can be recommended. Finally, we analyze the challenges in the field of coupling DSTM, meanwhile, the possible development direction of DSTM is prospected

Effects of Hybrid PVA–Steel Fibers on the Mechanical Performance of High-Ductility Cementitious Composites

Producing high-ductility cementitious composites (HDCC) increased in parallel with concrete demand in China recently. However, the high cost of manufacturing cementitious composites (HDCC) persists. To reduce the cost of HDCC, steel fibers, polyvinyl alcohol (PVA), and river sand were used to produce HDCC concrete in the present study. A total fiber content of 2% was formed with five different proportions of PVA fiber and steel fiber. Within the scope of the experimental studies, mechanical (workability, compressive strength, tensile, and bending properties), and microstructural (scanning electron microscopy) tests were carried out to investigate the properties of the hybrid fiber-reinforced composites. The results showed that the fluidity of HDCC increased with increasing steel fiber substitution. The compressive strength of the mixture containing 0.5% steel fiber and 1.5% PVA fiber exhibited a better compressive strength of 31.3 MPa. The tensile performance of the mixture was improved due to the incorporation of steel fiber. The initial cracking strength was about 2.32 MPa, 25.4% higher than that of the reference group, and the ultimate tensile strength was 3.36–3.56 MPa. However, reducing the content of PVA fiber impacts the flexural rigidity of the matrix

THE ENVIRONMENTAL CHALLENGE AND HEALTH SECURITY IN CHINA

China has achieved impressive rapid development over the past 30 years. But China also faces the challenge of environmental change resulting from rapid economic growth and the attendant risks to human health. In this paper we described the environmental change and health risk in China from evident fluctuation of China’s climate, major changes in natural hydrological condition, raw materials and energy demand, changes of disease epidemic pattern related to climate change and ecosystem damage, new health risk raised by rapid urbanization and rural environmental quality degradation. The suggestion and countermeasures were discussed

A Super-Resolution Reconstruction Driven Helmet Detection Workflow

The degrading of input images due to the engineering environment decreases the performance of helmet detection models so as to prevent their application in practice. To overcome this problem, we propose an end-to-end helmet monitoring system, which implements a super-resolution (SR) reconstruction driven helmet detection workflow to detect helmets for monitoring tasks. The monitoring system consists of two modules, the super-resolution reconstruction module and the detection module. The former implements the SR algorithm to produce high-resolution images, the latter performs the helmet detection. Validations are performed on both a public dataset as well as the realistic dataset obtained from a practical construction site. The results show that the proposed system achieves a promising performance and surpasses the competing methods. It will be a promising tool for construction monitoring and is easy to be extended to corresponding tasks

Effects of Hybrid PVA–Steel Fibers on the Mechanical Performance of High-Ductility Cementitious Composites

Producing high-ductility cementitious composites (HDCC) increased in parallel with concrete demand in China recently. However, the high cost of manufacturing cementitious composites (HDCC) persists. To reduce the cost of HDCC, steel fibers, polyvinyl alcohol (PVA), and river sand were used to produce HDCC concrete in the present study. A total fiber content of 2% was formed with five different proportions of PVA fiber and steel fiber. Within the scope of the experimental studies, mechanical (workability, compressive strength, tensile, and bending properties), and microstructural (scanning electron microscopy) tests were carried out to investigate the properties of the hybrid fiber-reinforced composites. The results showed that the fluidity of HDCC increased with increasing steel fiber substitution. The compressive strength of the mixture containing 0.5% steel fiber and 1.5% PVA fiber exhibited a better compressive strength of 31.3 MPa. The tensile performance of the mixture was improved due to the incorporation of steel fiber. The initial cracking strength was about 2.32 MPa, 25.4% higher than that of the reference group, and the ultimate tensile strength was 3.36–3.56 MPa. However, reducing the content of PVA fiber impacts the flexural rigidity of the matrix

Safety Helmet Detection Based on YOLOv5 Driven by Super-Resolution Reconstruction

High-resolution image transmission is required in safety helmet detection problems in the construction industry, which makes it difficult for existing image detection methods to achieve high-speed detection. To overcome this problem, a novel super-resolution (SR) reconstruction module is designed to improve the resolution of images before the detection module. In the super-resolution reconstruction module, the multichannel attention mechanism module is used to improve the breadth of feature capture. Furthermore, a novel CSP (Cross Stage Partial) module of YOLO (You Only Look Once) v5 is presented to reduce information loss and gradient confusion. Experiments are performed to validate the proposed algorithm. The PSNR (peak signal-to-noise ratio) of the proposed module is 29.420, and the SSIM (structural similarity) reaches 0.855. These results show that the proposed model works well for safety helmet detection in construction industries

Effects of Urbanization on Rural Drinking Water Quality in Beijing, China

Urbanization is an inevitable trend in historical development, but eco-environmental problems, including drinking water safety, have gradually become more and more outstanding during the process of rural urbanization. Ten districts in rural areas of Beijing, China were selected to study the effects of urbanization on drinking water quality. The relation between the urbanization index and drinking water quality indicators were explored. The influence of the urbanization process on drinking water quality showed that housing construction, population urbanization, energy consumption, and industrialization during urban development were closely related to drinking water quality. The paired t-test showed the total electricity consumption, living electricity consumption, tertiary industry, and the GDP growth rate had boundary (p = 0.06) or significantly positive (p < 0.05) relations with the qualified rate of rural drinking water. The grey correlation analysis showed that the growth rates of the value-added of housing construction areas were the most important factor affecting comprehensive water quality of Beijing rural areas, followed by the growth rates of the value-added by secondary industry and total electricity consumption, and then the growth rates of the value-added by the tertiary industry and GDP. Urbanization had a significant impact on individual water quality indicators. The results of this study provided some supports for drinking water security in the face of urbanization