Lihui Wang, Chengshuai Qin, Yaoming Li, Jin Chen and Lizhang Xu
Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the…
Abstract
Purpose
Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.
Design/methodology/approach
To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.
Findings
Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.
Originality/value
In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.
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Keywords
Wei He, Yuanming Xu, Yaoming Zhou and Qiuyue Li
This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model.
Abstract
Purpose
This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model.
Design/methodology/approach
PSO was first used to identify the best group of trend functions and to optimize the correlation parameter thereafter.
Findings
The Kriging surrogate model was used to resolve the fuselage optimization of an unmanned helicopter.
Practical implications
The optimization results indicated that an appropriate PSO scheme can improve the efficiency of the Kriging surrogate model.
Originality/value
Both the STANDARD PSO and the original PSO algorithms were chosen to show the effect of PSO on a Kriging surrogate model.
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Yaoming Zhou, Yongchao Wang, Shunan Dou and Zhijun Meng
This paper aims to conduct soft fault diagnosis of dual-redundancy sensors. An innovative fault diagnosis method, which combines a tracking differentiator and a sequential…
Abstract
Purpose
This paper aims to conduct soft fault diagnosis of dual-redundancy sensors. An innovative fault diagnosis method, which combines a tracking differentiator and a sequential probability ratio test, is proposed.
Design/methodology/approach
First, two tracking differentiators are used to track and predict the two original signals, and determine their residuals. These residuals are used to calculate one quadratic residual. Then, a sequential probability ratio test is carried out on this quadratic residual to obtain log-likelihood ratio. A fault can be detected through comparing the log-likelihood ratio value with the threshold value. Finally, analyses of the difference in the residuals, which locates the fault, and of the difference in the original signals, which reveals the fault level and type, are completed successively.
Findings
Results from experimentation show that this method can realise soft fault diagnosis for dual-redundancy sensors.
Originality/value
The method proposed in the paper gives a new idea to study hybrid redundancy. The method provides a new application mode for tracking differentiators and sequential probability ratio test. The method can be used in robots, such as unmanned aerial vehicles and unmanned ground vehicles, to improve their fault tolerance. It can also be applied to the key parts of industrial production lines to decrease financial losses caused by sensor faults.
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Keywords
Abstract
This chapter outlines the philosophic underpinnings of the self-management paradigm developed over the past three decades by China’s Haier Group, a global leader in white goods. The successful transformation of Haier from a small resource-poor firm to a dominant global giant is often attributed to the self-management culture established in the company by its legendary leader Zhang Ruimin. This management paradigm is a function of the humbleness displayed by Mr. Zhang Ruimin and rooted in his strong belief in the traditional Chinese philosophy of I-Ching and Daoism. We show how the hexagram of Qian (“qian”: humbleness, modesty) from I-Ching is linked to Mr. Zhang’s humble approach and analyze how the six parts of the hexagram of Qian are related to the six development stages of the Haier Group. These insights are used to give some thoughts to the leadership challenge associated with the creation of a dynamic and responsive global organization.
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Liya Wang, Yang Zhao, Yaoming Zhou and Jingbin Hao
The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.
Abstract
Purpose
The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.
Design/methodology/approach
This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.
Findings
Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.
Research limitations/implications
The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.
Originality/value
This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.