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Open Access
Article
Publication date: 1 February 2018

Xuhui Ye, Gongping Wu, Fei Fan, XiangYang Peng and Ke Wang

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection…

1334

Abstract

Purpose

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

Design/methodology/approach

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Findings

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

Originality/value

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

Open Access
Article
Publication date: 24 January 2022

Ke Zhang, Almudena González del Valle-Brena, Ignacio Ramos Riera and Jingli Zhao

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route…

2373

Abstract

Purpose

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route heritage (CRH). The study intends to inspire further discussion on the theoretical and practical development of cultural routes since the development is still at a liminal stage in China.

Design/methodology/approach

A total of 253 research articles related to Chinese cultural rote heritage from major Chinese and English research databases China National Knowledge Infrastructure (CNKI), Web of Science (WOS) and Scopus have been comprehensively identified and reviewed for the purpose of the study.

Findings

Four major themes of research on Chinese CRH have been identified: conceptual evaluation, list of the routes and characteristics of the routes, conservation and utilization. The results revealed that China has very rich resources in CRH, many of which were formed a long time ago, which exist across vast geographic regions and have assumed multiple functions and undergone dynamic reciprocal exchanges among diverse cultures and ethnicities.

Practical implications

The paper summarizes some major obstacles faced by CRH in China and proposes a strategic model to address the need for a more sustainable development of CRH in the Chinese context.

Originality/value

The paper offers a comprehensive overview of CRH in China and discusses practical issues in management and development of heritage great in size, number and complexity.

Details

Journal of Cultural Heritage Management and Sustainable Development, vol. 14 no. 2
Type: Research Article
ISSN: 2044-1266

Keywords

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

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