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1 – 3 of 3Ge Xu, Shuyun Jiang, Chibin Zhang and Xiaohui Lin
The water-lubricated hydrodynamic herringbone groove journal bearing (HGJB) is capable of running at high speed. However, when running at a low speed, it suffers from a low…
Abstract
Purpose
The water-lubricated hydrodynamic herringbone groove journal bearing (HGJB) is capable of running at high speed. However, when running at a low speed, it suffers from a low load-carrying capacity due to the weak hydrodynamic effect. To overcome this problem, this study proposes a hybrid water-lubricated HGJB and aims to investigate its dynamic characteristics.
Design/methodology/approach
A hybrid lubrication model applicable to the hybrid water-lubricated HGJB is established based on the boundary fitted coordinate system, which considers the turbulent, thermal and tilting effects, and the finite difference method is used to calculate the dynamic characteristics of the hybrid water-lubricated HGJB.
Findings
The result shows that the hybrid HGJB has larger dynamic coefficients and better system stability compared with the hydrodynamic HGJB when running at low speed. Furthermore, the stiffness of hybrid HGJB are mainly governed by the hydrodynamic effect rather than the hydrostatic effect when running at high speed.
Originality/value
The proposed hybrid water-lubricated HGJB shows excellent dynamic characteristics at either low speed or high speed; and the hybrid water-lubricated HGJB has a large load-carrying capacity when running at low speed and has a good dynamic stability when running at high speed.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0233/
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Dan Feng, Zhenyu Yin, Xiaohui Wang, Feiqing Zhang and Zisong Wang
Traditional visual simultaneous localization and mapping (SLAM) systems are primarily based on the assumption that the environment is static, which makes them struggle with the…
Abstract
Purpose
Traditional visual simultaneous localization and mapping (SLAM) systems are primarily based on the assumption that the environment is static, which makes them struggle with the interference caused by dynamic objects in complex industrial production environments. This paper aims to improve the stability of visual SLAM in complex dynamic environments through semantic segmentation and its optimization.
Design/methodology/approach
This paper proposes a real-time visual SLAM system for complex dynamic environments based on YOLOv5s semantic segmentation, named YLS-SLAM. The system combines semantic segmentation results and the boundary semantic enhancement algorithm. By recognizing and completing the semantic masks of dynamic objects from coarse to fine, it effectively eliminates the interference of dynamic feature points on the pose estimation and enhances the retention and extraction of prominent features in the background, thereby achieving stable operation of the system in complex dynamic environments.
Findings
Experiments on the Technische Universität München and Bonn data sets show that, under monocular and Red, Green, Blue - Depth modes, the localization accuracy of YLS-SLAM is significantly better than existing advanced dynamic SLAM methods, effectively improving the robustness of visual SLAM. Additionally, the authors also conducted tests using a monocular camera in a real industrial production environment, successfully validating its effectiveness and application potential in complex dynamic environment.
Originality/value
This paper combines semantic segmentation algorithms with boundary semantic enhancement algorithms to effectively achieve precise removal of dynamic objects and their edges, while ensuring the system's real-time performance, offering significant application value.
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Esther Calderon-Monge, Vicente Ripollés-Matallana, Bruno Baruque-Zanón and Santiago Porras Alfonso
Wine is a complicated and difficult product to know, which makes it extremely difficult for people with little knowledge to choose the wine they want. This study aims to analyze…
Abstract
Purpose
Wine is a complicated and difficult product to know, which makes it extremely difficult for people with little knowledge to choose the wine they want. This study aims to analyze whether the vocabulary used in reviews on wine written by experts and amateurs on the specialized website is useful for those consumers who wish to search for information on this website to choose a wine.
Design/methodology/approach
The analysis combines text mining, Natural Language Processing and the Biterm Topic model applied to 25,847 reviews, evaluating a total of 13,263 Spanish wines made by 17 selected users of a specialized wine website.
Findings
The results show that wine consumers and users of the specialized wine website who write reviews can be divided into expert users and amateur users. Both experts and amateurs use a specific vocabulary related to the wines they review. Unlike amateurs, experts have a broader and more precise vocabulary, and greater consistency in the use of words with the aspects of the wine. For the revised wines, they address fewer and more specific aspects of wine (such as vintages), but they do so with more depth and rigor.
Originality/value
The originality and value of this research work lie in addressing two aspects that have hardly been analyzed: the reviews of experienced consumers and amateur consumers, and the textual information referring to the Spanish language, which distinguishes this analysis from other similar analyses carried out on the English language.
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