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Article
Publication date: 8 February 2021

Yu Luo, Xiangdong Jiao, Zewei Fang, Shuxin Zhang, Xuan Wu, Dongyao Wang and Qin Chu

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance…

234

Abstract

Purpose

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance of subsea pipeline.

Design/methodology/approach

Based on the analysis of the cross-section of the fillet weld, the multi-layer and multi-pass welding path planning of the submarine pipeline sleeve fillet weld is studied, and thus a multi-layer and multi-pass welding path planning strategy is proposed. A welding seam filling method is designed, and the end position of the welding gun is planned, which provides a theoretical basis for the motion control of the maintenance system.

Findings

The trajectory planning and adjustment of multi-layer and multi-pass fillet welding and the motion stability control of the rotating mechanism are realized.

Research limitations/implications

It provides the basis for the prototype design of the submarine pipeline maintenance and welding robot system, and also lays the foundation for the in-depth research on the intelligent maintenance system of submarine pipeline.

Originality/value

The maintenance of diverless subsea pipeline is a new type of maintenance method, which can solve the problem of large amount of subsea maintenance work with high efficiency.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 3 May 2016

Jun Qin, Shuxin Bai, Weijun Zhang, Zhuofeng Liu and Hailiang Wang

The purpose of this paper is to characterize and understand the effects of polymer binder, thixotropic agent, solvent and organic medium content on the rheological properties of…

409

Abstract

Purpose

The purpose of this paper is to characterize and understand the effects of polymer binder, thixotropic agent, solvent and organic medium content on the rheological properties of silver pastes for screen printing front electrode films of solar cells.

Design/methodology/approach

Dispersions of silver particles (surface modified with oleic acid) in ethyl cellulose (EC) polymer solutions with and without thixotropic agent were prepared, and yield stress values were measured by setting shear stress to characterize the inter-particle interaction strength of pastes. Steady-state flow, three interval thixotropy shear test and oscillatory measurements were conducted to study the effect of EC polymer and thixotropic agent on viscosity, structure rebuilding and viscoelastic properties of electrode pastes. The effect of solvent was studied by investigating the steady viscosity of cellulose acetate butyrate (CAB) polymer solutions and Ag dispersions.

Findings

Weak flocculation network of silver particles was produced because of depletion flocculation. Besides the interaction between thixotropic agent micelles, EC polymer also has a significant interaction with thixotropic agent. Merely increasing EC polymer or thixotropic agent content is not the best way to prevent the layer printed from laying down. The effect of solvent on the viscosity of paste is mainly attributed to the difference of hydromechanics radius and configuration of CAB polymer in solvents. With the increase of organic medium content, the properties of electrode pastes were converted from rigidity to flexibility.

Originality/value

It is still a challenge to obtain high-quality front electrode films for crystalline silicon solar cells by screen printing, because of the difficulty in reducing shadowing losses while ensuring a low series resistance and high filling factor. The paste rheological properties are the key properties related to the paste’s passing ability through the meshes and resistance of paste spreading on the substrate. Organic medium as an important component of the paste is acknowledged to be used to tailor the paste’s rheological properties and have a great role in screen printing.

Details

Circuit World, vol. 42 no. 2
Type: Research Article
ISSN: 0305-6120

Keywords

Available. Open Access. Open Access
Article
Publication date: 13 September 2023

Rongsheng Wang, Tao Zhang, Zhiming Yuan, Shuxin Ding and Qi Zhang

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information…

789

Abstract

Purpose

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Design/methodology/approach

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

Findings

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

Originality/value

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

Available. Open Access. Open Access
Article
Publication date: 9 May 2024

Yanhao Sun, Tao Zhang, Shuxin Ding, Zhiming Yuan and Shengliang Yang

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to…

330

Abstract

Purpose

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

Design/methodology/approach

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

Findings

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

Originality/value

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Details

Railway Sciences, vol. 3 no. 3
Type: Research Article
ISSN: 2755-0907

Keywords

Available. Open Access. Open Access
Article
Publication date: 13 September 2023

Shuxin Ding, Tao Zhang, Kai Sheng, Yuanyuan Chen and Zhiming Yuan

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command…

958

Abstract

Purpose

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

Design/methodology/approach

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

Findings

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

Originality/value

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Available. Open Access. Open Access
Article
Publication date: 2 July 2024

Qingyun Fu, Shuxin Ding, Tao Zhang, Rongsheng Wang, Ping Hu and Cunlai Pu

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on…

406

Abstract

Purpose

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

Design/methodology/approach

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

Findings

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

Originality/value

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

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Article
Publication date: 11 October 2024

Tanish Mavi, Dev Priya, Rampal Grih Dhwaj Singh, Ankit Singh, Digvijay Singh, Priyanka Upadhyay, Ravinder Singh and Akshay Katyal

This paper aims to develop a real-time pothole detection system to improve mapping, localization and path planning, reducing vehicle instability and accident risks. Efficient…

22

Abstract

Purpose

This paper aims to develop a real-time pothole detection system to improve mapping, localization and path planning, reducing vehicle instability and accident risks. Efficient mapping, accurate localization and optimal path planning stand as prerequisites to realizing accident-free navigation. Despite their significance, existing literature often overlooks the real-time detection of potholes, which poses a considerable risk, particularly during nighttime operations. Potholes contribute to vehicle imbalance, trajectory tracking errors, abrupt braking, wheel skidding, jerking and steering overshoot, all of which can lead to accidents.

Design/methodology/approach

Unmanned vehicles constitute a critical domain within robotics research, necessitating reliable autonomous navigation for their optimal functioning. This research paper addresses the gap in current methodologies by leveraging a Convolutional Neural Network (CNN)-based approach to detect potholes, facilitating the generation of an efficient environmental map. Furthermore, a hybrid solution is proposed, integrating an improved Ant Colony Optimization (ACO) algorithm with modified Bezier techniques, complementing the CNN approach for accident-free and time-efficient unmanned vehicle navigation. The conventional Bezier technique is enhanced by incorporating new control points near sharp turns, mitigating rapid trajectory convergence and ensuring collision-free paths.

Findings

The hybrid solution, combining CNN with path smoothing techniques, is rigorously tested in various real-time scenarios. Experimental results demonstrate that the proposed technique achieves a 100% reduction in collisions in favorable conditions, a 4.5% decrease in path length, a 100% reduction in sharp turns and a significant 23.31% reduction in total time lag compared to state-of-the-art techniques such as conventional ACO, ACO+ Bezier and ACO+ midpoint Bezier, Improved ACO, hybrid ACO+ A*.

Originality/value

The proposed technique provides a proficient solution in the field of unmanned vehicles for accident-free time efficient navigation in an unstructured environment.

Details

Robotic Intelligence and Automation, vol. 45 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

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Article
Publication date: 14 January 2025

Xiaoyang Zhao, Runwen Liu and Shuxin Zhong

Existing research suggests a positive relationship between firms’ research and development investments (RDIs) and their patenting performance (PP) according to assumptions of…

10

Abstract

Purpose

Existing research suggests a positive relationship between firms’ research and development investments (RDIs) and their patenting performance (PP) according to assumptions of linear productivity and homogeneous behavior. This study unravels the RDI–PP relationship by taking a strategic view to reveal its underlying mechanisms.

Design/methodology/approach

We study the effects of firms’ RDI on PP in the context of China’s listed firms in 16 patent-intensive industries, including the pharmaceutical, computer communication, electronic equipment and electrical machinery and equipment manufacturing industries. To test our hypotheses, we use panel data from 2010 to 2017. We apply generalized estimating equations to estimate our models.

Findings

The study finds an inverted U-shaped relationship between RDI and PP that arises from the transition of innovation portfolios and the strategic balancing of patenting costs and benefits. The study further examines two contingencies: (1) top management team (TMT) education level and (2) TMT compensation. It shows the turning point of the inverted U-shape shifts to the right when TMT education level is high; the curve flattens when TMT education level and TMT compensation are high.

Originality/value

We contribute to literature on innovation and appropriability strategy in three ways: First, we reveal the underlying mechanisms of the inverted U-shaped relationship between RDI and PP. Second, because previous research on appropriability strategies pays little attention to how innovation portfolios influence patenting decisions at the firm level, we provide evidence and insights on how the tension between exploitative and explorative innovations affects appropriability strategies. Third, we connect appropriability strategy literature with two streams of literature: corporate governance and upper-echelon theory.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

Available. Content available
Article
Publication date: 21 June 2024

Shuxin Huang, Hui Huang, Shaoyao He and Xiaoping Yu

This study aims to examine the effects of technology-, organisation- and environment-readiness, smart economic development, change valence, social cohesion and quality of life on…

185

Abstract

Purpose

This study aims to examine the effects of technology-, organisation- and environment-readiness, smart economic development, change valence, social cohesion and quality of life on citizenship in the context of smart cities.

Design/methodology/approach

The study employed a customized questionnaire which was completed by 280 residents of China’s first-tier cities. This study tested the framework using the partial least squares structural equation modelling (PLS-SEM) technique.

Findings

The results indicated that smart economy development, social cohesion, change valence, technological readiness, organizational readiness and environmental readiness have a significant impact on the quality of life. Quality of life has a positive impact on citizenship.

Originality/value

This study adds new insights to smart city academic discussions. The study addresses a critical gap identified in existing literature which urges the need for a balance between user-centric, organization-centric and technology-centric approaches. It offers a fresh perspective on how the smart economy, social cohesion and readiness factors are interlinked. These elements together shape urban living experiences. For policymakers and urban planners, our findings provide clear guidance. They highlight the complex dynamics that must be considered to build more unified, inclusive and sustainable smart cities.

Details

Open House International, vol. 50 no. 1
Type: Research Article
ISSN: 0168-2601

Keywords

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Article
Publication date: 17 September 2024

Yu Xia and Shuxin Guo

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

52

Abstract

Purpose

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

Design/methodology/approach

We use the ratio of the recent closing price to its historical high in the previous 12–60 months (anchoring-high-price ratio) to study its impact on the market timing of SEOs.

Findings

Empirical results show that the anchoring-high-price ratio significantly and positively affects the probability of additional stock issuances. Contrary to the USA market, the Chinese stock market reacts negatively to the SEOs at historical highs. Moreover, the anchoring-high-price ratio exacerbates the negative effect of announcements and leads to long-term underperformance. Finally, we investigate the impact of the anchoring-high-price ratio on a company’s capital structure, showing that the additional issuance anchoring on historical highs reduces the company’s leverage ratio in the long run. Overall, our findings support the anchoring theory and can help understand better the anchoring behavior of managers and the company’s decision on additional stock issuances.

Originality/value

We are the first to use the anchoring-high-price ratio to study the timing of SEOs. We find that the anchoring-high-price ratio positively affects the probability of SEOs. Unlike the USA, the Chinese stock market reacts negatively to SEOs at high prices. SEOs anchoring on historical highs reduce a firm’s leverage ratio in the long run. Finally, our results support the anchoring theory.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

Keywords

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