Although the Transformer model has outperformed traditional sequence-To-sequence model in a variety of natural language processing (NLP) tasks, it still suffers from semantic irrelevance and repetition for abstractive...
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With the advances in new-generation information technologies, smart process planning is becoming the focus for smart process planning with less time and lower cost. Big data-based reusing and evaluating the multi-dime...
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With the advances in new-generation information technologies, smart process planning is becoming the focus for smart process planning with less time and lower cost. Big data-based reusing and evaluating the multi-dimensional process knowledge is widely accepted as an effective strategy for improving competitiveness of enterprises. However, there was little research on how to reuse and evaluate process knowledge with dynamical changing machining status. In this paper, we propose a novel digital twin-based approach for reusing and evaluating process knowledge. First, the digital twin-based process knowledge model which contains the geometric information and real-time process equipment status is introduced to represent the purpose and requirement of machining planning. Second, the process big data is constructed based on the three-layer and its association rules for accumulating process knowledge. Moreover, the similarity calculation algorithm of the scene model is proposed to filter the unmatched process knowledge. For accurately reusing the process knowledge, the process reusability evaluation approach of the candidate knowledge set is presented based on the real-time machining status and the calculated confidence. Finally, the diesel engine parts are applied in the developed prototype module to verify the effectiveness of the proposed method. The proposed method can promote the development and application of the smart process planning.
The influence of transient heat transfer in different condensation condition was investigated experimentally in the present paper. Getting condensation heat and mass transfer regularity and characteristics in space ca...
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The influence of transient heat transfer in different condensation condition was investigated experimentally in the present paper. Getting condensation heat and mass transfer regularity and characteristics in space can provide theoretical basis for thermodynamic device such as heat pipes, loop heat pipes and capillary pumped loops as well as other fluid management engineering designing. In order to study the condensation process in space, an experimental study has been carried out on the ground for space experiment. The results show that transit heat transfer coefficient of film condensation is related to the condensation film width, the flow condition near the two phase interface and the pressure of the vapor and non-condensable gas in chamber. On the ground, the condensation heat flux on vertical surface is higher than it on horizontal surface. The transit heat flux of film condensation is affected by the temperature of superheated vapor, the temperature of condensation surface and non-condensable gas pressure. Condensation heat flux with vapor forced convection is many times more than it with natural convection. All of heat flux for both vapor forced convection and natural convection condensation in limited chamber declines dramatically over time. The present experiment is preliminary work for our future space experiments of the condensation and heat transfer process onboard the Chinese Spacecraft "TZ-1" to be launched in 2016.
As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant ...
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ISBN:
(纸本)9780769551203
As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.
In this paper, we investigate the problem of code acquisition for band-limited direct-sequence spread-spectrum (DSSS) systems in the presence of sampling offset. By analyzing the detection output property of the tradi...
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In this paper, we investigate the problem of code acquisition for band-limited direct-sequence spread-spectrum (DSSS) systems in the presence of sampling offset. By analyzing the detection output property of the traditional noncoherent detection scheme with and without the existence of sampling offset, an improved acquisition scheme that utilizes two decision variables for joint detection is proposed. Numerical results show that the proposed scheme can offer better performance and is more robust to the variation of the sampling offset than the traditional scheme.
Welding process, as one of the crucial industrial technologies in ship construction, accounts for approximately 70% of the workload and costs account for approximately 40% of the total cost. The existing welding quali...
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Welding process, as one of the crucial industrial technologies in ship construction, accounts for approximately 70% of the workload and costs account for approximately 40% of the total cost. The existing welding quality prediction methods have hypothetical premises and subjective factors, which cannot meet the dynamic control requirements of intelligent welding for processing quality. Aiming at the low efficiency of quality prediction problems poor timeliness and unpredictability of quality control in ship assembly-welding process, a data and model driven welding quality prediction method is proposed. Firstly, the influence factors of welding quality are analyzed and the correlation mechanism between process parameters and quality is determined. According to the analysis results, a stable and reliable data collection architecture is established. The elements of welding process monitoring are also determined based on the feature dimensionality reduction method. To improve the accuracy of welding quality prediction, the prediction model is constructed by fusing the adaptive simulated annealing, the particle swarm optimization, and the back propagation neural network algorithms. Finally, the effectiveness of the prediction method is verified through 74 sets of plate welding experiments, the prediction accuracy reaches over 90%.
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