Wyniki wyszukiwania - BazTech

1

Analysis and experiments of embedded gripping mechanism used in large-scale tools holding up pile foundation in ocean

Wang Zhuo, Zhang Bo, Wang Tao

Polish Maritime Research

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2019

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nr 3

15--21

EN

With the rapid development of the marine economy and continuous improvement of the industry, the scale of the offshore engineering is increasing. This raises interest in studying, theoretically and experimentally, gripping and bearing mechanisms for large-scale holding and lifting tools used in foundation pile installations. In this paper, the embedded gripping mechanism is studied based on the theory of elastic-plastic mechanics. The embedded and bearing performance of the tooth is simulated and the influence factors are studied. In addition, the device used in the simplified embedded experiment on the tooth of the embedded block is designed. The relationship between embedded depth, load, and tooth profile angle is identified and validated. Meanwhile, the embedded performance of linear and ring type teeth is compared experimentally in order to select the suitable type of tooth for various situations. This comparison makes the basis for designing an upending gripper for the marine pile foundation, which can realize the operation of holding the pile to prevent its falling.

2

Fluidization characteristics and separation performance of mild-hot gas-solid fluidized bed

Lv Bo, Luo Zhenfu, Zhang Bo, Zhao Yuemin, Qin Yunfei

Physicochemical Problems of Mineral Processing

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2019

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Vol. 55, iss. 1

184--195

EN

In recent years, the mild-hot gas-solid fluidized bed had a crucial influence on wet-in-feed sorting when it comes to moist feed (e.g., lignite) because of its expanding sorting range. To explain the favorable sorting effect of the mild-hot gas-solid fluidized bed, the fluidization characteristics (e.g., the pressure drop, density, etc.) was studied under different work conditions. In addition, a high-speed dynamic camera was used in this study to compare the slumping behavior of the magnetite slag at different temperatures. The optimum conditions for coal separation was also studied by Design-Expert software. It was shown that the bed temperature of the fluidized bed has a particular effect on its stability when the bed temperature was below 120 °C, which had a great influence on the separation. Finally, the probable deviation E of the mild-hot gas-solid fluidized bed under optimum operation conditions could be as low as 0.09 g/cm3 which showed the good separation ability.

3

Flotation separation of enargite from complex copper concentrates by selective surface oxidation

Li Tangfei, Zhang Yansheng, Zhang Bo, Jiao Fen, Qin Wenqing

Physicochemical Problems of Mineral Processing

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2019

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Vol. 55, iss. 4

852--864

EN

In previous study, the promising results of separating enargite from non-arsenic copper sulfides were obtained using selective surface oxidation in pure mineral systems. However, this technology was not well understood in real ores or concentrates. In this study, the flotation separation of enargite from complex copper concentrates by selective surface oxidation was investigated. The effects of regrinding, pulp pH, NaClO concentration, conditioning time and flotation time on separation of enargite from NECu minerals were studied. The mineralogical characteristics of the flotation feed and products were showed as an instructive tool to understand the separation results. According to the results of EDTA extraction, the possible mechanism for separation of enargite from NECu minerals is that enargite is more resistant to oxidized compared to NECu minerals. The following order for the oxidation of NECu minerals and enargite is obtained: chalcopyrite (chalcocite, digenite)> enargite (covellite).

4

Automated characterization and classification of coronary atherosclerotic plaques for intravascular optical coherence tomography

Yang Jianli, Zhang Bo, Wang Hongrui, Lin Feng, Han Yechen, Liu Xiuling

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

719--727

EN

Identification of coronary atherosclerotic plaques and vulnerable plaques is of great clinical significance in the diagnosis and treatment of coronary artery diseases, such as myocardial infarction and sudden death. Optical coherence tomography (OCT) is a catheter-based intracoronary imaging technique with high resolution (<20 μm) adopted to study the morphology of atherosclerotic plaques and identification of the composition of plaques. Nevertheless, manual characterization and quantification of plaques by clinicians is a labor-intensive and subjective procedure. This study aimed to propose a novel plaque characterization algorithm to automatically characterize and classify the atherosclerotic plaques (fibrous, calcific, and lipid-rich). First, nongeometric features such as Fisher vector, principal component analysis, histogram of the oriented gradient, and local binary pattern were investigated and adapted to two geometric features (basic feature and texture feature) to characterize the plaques. Second, for automated classification of the plaques, a hard example mining strategy was introduced to train support vector machine classifier and improve the effectiveness of training data. Third, to demonstrate the relationship between the selected features and the plaque classification accuracy, different feature compositions and comparisons were presented. The contribution of key features to the final classification was revealed. Datasets from 20 OCT pullbacks of 9 patients were used in the training and testing using the proposed algorithm. The overall classification accuracy reached 96.8%, and that of fibrous, calcific, and lipid-rich plaques was 94%, 97.2%, and 99.2%, respectively.

5

A Method for Defect Detection of Yarn-Dyed Fabric Based on Frequency Domain Filtering and Similarity Measurement

Zhang Bo, Tang Chunming

Autex Research Journal

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2019

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Vol. 19, no. 3

257--262

EN

The detection of defects in yarn-dyed fabric is one of the most difficult problems among the present fabric defect detection methods. The difficulty lies in how to properly separate patterns, textures, and defects in the yarn-dyed fabric. In this paper, a novel automatic detection algorithm is presented based on frequency domain filtering and similarity measurement. First, the separation of the pattern and yarn texture structure of the fabric is achieved by frequency domain filtering technology. Subsequently, segmentation of the periodic units of the pattern is achieved by using distance matching function to measure the fabric pattern. Finally, based on the similarity measurement technology, the pattern’s periodic unit is classified, and thus, automatic detection of the defects in the yarn-dyed fabric is accomplished.