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1.
Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset. 相似文献
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In this paper, an adaptive control approach is designed for compensating the faults in the actuators of chaotic systems and maintaining the acceptable system stability. We propose a state‐feedback model reference adaptive control scheme for unknown chaotic multi‐input systems. Only the dimensions of the chaotic systems are required to be known. Based on Lyapunov stability theory, new adaptive control laws are synthesized to accommodate actuator failures and system nonlinearities. An illustrative example is studied. The simulation results show the effectiveness of the design method. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize frequency band location including a fault transient out of a full band spectrum, and thus fault diagnosis can suppress noise influence from other frequency components. Impulsiveness and cyclostationarity have been recently recognized as two distinctive signatures of a transient. Thus, many studies have focused on developing quantification metrics of the two signatures and using them as indicators to guide FBS. However, most previous studies almost ignore another aspect of FBS, i.e. health reference, which significantly affect FBS performance. To address this issue, this paper investigates importance of a health reference and recognize it as the third critical aspect in FBS. With help of the health reference, the frequency band where the fault transient exists could be located. A novel approach based on classification is proposed to integrate all three aspects (impulsiveness, cyclostationarity, and health reference) for FBS. Classification accuracy is developed as a novel indicator to select the most sensitive frequency band for rotating machinery fault diagnosis. The proposed method (coined by accugram) has been validated on benchmark and experiment datasets. Comparison results show its effectiveness and robustness over conventional envelope analysis, the kurtogram, and the infogram. 相似文献
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ABSTRACTImproving the hydration resistance of CaO particle in manufacturing and application of free CaO-containing materials has practical significance. In this study, CaO granules was made from Ca(OH)2 particles, which were fabricated by the granulation method. The results showed that the hydration resistance of the CaO granules which was prepared under 1700?r?min?1 was the best, the CaO granules was sintered well in calcination process, the shell of CaO granules was relatively dense, which improves the hydration resistance of CaO granules, and the rate of hydration weight increment was 0.58% after placed in the air for 20 days under a temperature of 10–14°C and a relative humidity of 57–81%. 相似文献
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四川盆地作为国内页岩气开发的重点区域,通过近几年的不断攻关和实践,机械钻速得到了提高,但由于受地层复杂、可钻性差、非均质性强等地质因素的影响,导致井下钻柱系统不良振动剧烈,容易出现钻头损坏严重、钻速较低等问题,严重影响了钻井时效。为了解决上述难题,以该盆地涪陵工区上二叠统龙潭组—中二叠统茅口组为例,采用井下振动高频测量工具的实测手段,测量了钻头—钻柱系统的动态振动加速度参数,结合地层的岩性和矿物组分分析,研究钻头失效原因与对策,并开展了现场试验。研究结果表明:①在非均质地层中钻进的钻头—钻柱系统产生了大于40 m/s~2的高幅值瞬时冲击振动,高幅值的瞬时冲击是导致钻头先期失效的主要原因;②提出了抑制高幅值的瞬时冲击振动采用"减振+增压"工具组合和避免井下工具共振的钻井参数;③采用钻井新参数的试验井比邻井的高幅值瞬时振动降低了17%,单只钻头进尺增加24%,钻头工作环境得到了较大的改善,钻头使用数量减少。结论认为,该研究成果能够有效地改善钻头—钻柱系统的振动状态,有利于达成延长钻头使用寿命的目标。 相似文献
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随钻扩眼工具及技术研究 总被引:1,自引:0,他引:1
基于随钻扩眼技术优势的分析,研究了机械式、液压式和偏心式随钻扩眼工具执行机构和扩眼总成的机构原理,并介绍了国内所开展的相关研究。文章提出应加强现有工具的适应性和匹配性研究,发掘各类工具的优势。优化执行机构、扩眼总成和水力机构、重视底部钻具组合力学特性的分析是今后发展和完善随钻扩眼工具及技术的几个重要内容。实践表明,随钻扩眼技术在处理井下复杂情况、降低钻井综合成本、提高钻井速度、提高建井质量和安全性等方面具有显著的优势,随钻扩眼工具也正逐渐成为一种重要的石油钻井配套工具。 相似文献
10.
径向基函数网络(RBFN)已广泛应用于参考腾发量预测等领域,但常用的K均值聚类和自组织特征映射等方法在求取径向基函数网络隐层节点中心时存在较大不足。针对这一问题,本文引入投影寻踪方法,在投影降维的基础上实现对大量高维数据的聚类,建立了基于投影寻踪的径向基函数网络模型,并将该模型应用于山西潇河灌区参考腾发量的预测,研究了不同气象因子输入对参考腾发量预测精度的影响。结果表明,基于投影寻踪的径向基函数网络具有较强的适用性,只需使用最高温度、最低温度、日照时数和旬序数作为输入因子,就能以较高的精度预测参考腾发量。 相似文献