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This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

The proposal is to answer the following question: based on previous studies, which are the new paths and challenges related to the circular economy (CE) and Industry 4.0 (I4.0)? To answer this question, the research objective is to analyze studies approaching the interface between CE and I4.0.

A systematic literature review (SLR) was conducted on previously published studies pertaining to Scopus and Web of Science bases, and 63 articles were found.

The authors present five new paths and challenges amid the relationship between CE and I4.0: applying those technologies to clean production, using blockchain and big data in the circular supply chain, raising additive manufacturing impact on the CE, seek for a better understanding on how I4.0 technologies can properly support the CE in the stakeholders' view and discerning the factors for implementing those theoretical fields onto supply chains.

Previous studies' sample basis is still recent, lacking research depth. Search strings might have minimized the number of selected studies: there could be a bigger sample.

Practical contributions of this study lay on the applicability of the raised propositions into several sectors' industries.

The authors suggest a transition agenda towards CE, using I4.0 technologies for operational, tactical and strategic personnel within organizations, as well as potential utilization strategies in specific study fields, like supply chain management and product manufacturing per se.

The study presents new paths and challenges amid technologies pertaining to I4.0 and its interfaces with the CE. In the result presentation and analysis, the existing interfaces are described.

The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments.

Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle.

The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development.

Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Temperature is an important load for a ballastless track. However, little research has been conducted on the dynamic responses when a train travels on a ballastless track under the temperature gradient. The dynamic responses under different temperature gradients of the slab are theoretically investigated in this work.

Considering the moving train, the temperature gradient of the slab, and the gravity of the slab track, a dynamic model for a high-speed train that runs along the CRTS III slab track on subgrade is developed by a nonlinear coupled way in Abaqus.

The results are as follows: (1) The upward transmission of the periodic deformation of the slab causes periodic track irregularity. (2) Because of the geometric constraint of limiting structures, the maximum bending stresses of the slab occur near the end of the slab under positive temperature gradients, but in the middle of the slab under negative temperature gradients. (3) The periodic deformation of the slab can induce periodic changes in the interlayer stiffness and contact status, leading to a large vibration of the slab. Because of the vibration-reduction capacity of the fastener and the larger mass of the concrete base, the accelerations of both the slab and concrete base are far less than the acceleration of the rail.

This study reveals the influence mechanism of temperature gradient-induced periodic deformation in the dynamic responses of the train-track system, and it also provides a guide for the safe service of CRTS III slab track.

This paper aims to propose an enhanced densely dehazing network to suit railway scenes’ features and improve the visual quality degraded by haze and fog.

It is an end-to-end network based on DenseNet. The authors design enhanced dense blocks and fuse them in a pyramid pooling module for visual data’s local and global features. Multiple ablation studies have been conducted to show the effects of each module proposed in this paper.

The authors have compared dehazed results on real hazy images and railway hazy images of state-of-the-art dehazing networks with the dehazed results in data quality. Finally, an object-detection test is taken to judge the edge information preservation after haze removal. All results demonstrate that the proposed dehazing network performs better under railway scenes in detail.

This study provides a new method for image enhancing in the railway monitoring system.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.

First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.

This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.

The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.

This study aims to address the problem of low-temperature wave soldering in industry production with Sn-9Zn-2.5 Bi-1.5In alloys and develop qualified process parameters. Sn–Zn eutectic alloys are lead-free solders applied in consumer electronics due to their low melting point, high strength, and low cost. In the electronic assembly industry, Sn–Zn eutectic alloys have great potential for use.

This paper explored developing and implementing process parameters for low-temperature wave soldering of Sn–Zn alloys (SN-9ZN-2.5BI-1.5 In). A two-factor, three-level design of the experiments experiment was designed to simulate various conditions parameters encountered in Sn–Zn soldering, developed the nitrogen protection device of waving soldering and proposed the optimal process parameters to realize mass production of low-temperature wave soldering on Sn–Zn alloys.

The Sn-9Zn-2.5 Bi-1.5In alloy can overcome the Zn oxidation problem, achieve low-temperature wave soldering and meet IPC standards, but requires the development of nitrogen protection devices and the optimization of a series of process parameters. The design experiment reveals that preheating temperature, soldering temperature and flux affect failure phenomena. Finally, combined with the process test results, an effective method to support mass production.

In term of overcome Zn’s oxidation characteristics, anti-oxidation wave welding device needs to be studied. Various process parameters need to be developed to achieve a welding process with lower temperature than that of lead solder(Sn–Pb) and lead-free SAC(Sn-0.3Ag-0.7Cu). The process window of Sn–Zn series alloy (Sn-9Zn-2.5 Bi-1.5In alloy) is narrow. A more stringent quality control chart is required to make mass production.

In this research, the soldering temperature of Sn-9Zn-2.5 Bi-1.5In is 5 °C and 25 °C lower than Sn–Pb and Sn-0.3Ag-0.7Cu(SAC0307). To the best of the authors’ knowledge, this work was the first time to apply Sn–Zn solder alloy under actual production conditions on wave soldering, which was of great significance for the study of wave soldering of the same kind of solder alloy.

Low-temperature wave soldering can supported green manufacturing widely, offering a new path to achieve carbon emissions for many factories and also combat to international climate change.

There are many research papers on Sn–Zn alloys, but methods of achieving low-temperature wave soldering to meet IPC standards are infrequent. Especially the process control method that can be mass-produced is more challenging. In addition, the metal storage is very high and the cost is relatively low, which is of great help to provide enterprise competitiveness and can also support the development of green manufacturing, which has a good role in promoting the broader development of the Sn–Zn series.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.