基于CATIA/CAA飞机蒙皮边缘连接孔最小边距快速检测方法

在新机研制阶段,设计部门提供的工程数据集可能存在连接孔边距不符合规范要求,也可能出现连接孔进入零件的R区等现象.通过对边距的检测可以检查连接孔边距的缺陷,因此边距的快速检测是一个重要问题.提出了边距提取和最小边距快速检测的算法,利用CAA/CATIA开发平台,开发了蒙皮边缘孔最小边距的快速检测软件可快速筛选不符合要求的蒙皮边缘孔并标注出来,减少了飞机生产过程中不必要的浪费,提高了生产效率.     

A pre-generated matrix-based method for real-time robotic drilling chatter monitoring

Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression.     

Multi-block SSD based on small object detection for UAV railway scene surveillance

A method of multi-block Single Shot MultiBox Detector (SSD) based on small object detection is proposed to the railway scene of unmanned aerial vehicle surveillance. To address the limitation of small object detection, a multi-block SSD mechanism, which consists of three steps, is designed. First, the original input images are segmented into several overlapped patches. Second, each patch is separately fed into an SSD to detect the objects. Third, the patches are merged together through two stages. In the first stage, the truncated object of the sub-layer detection result is spliced. In the second stage, a sub-layer suppression and filtering algorithm applying the concept of non-maximum suppression is utilized to remove the overlapped boxes of sub-layers. The boxes that are not detected in the main-layer are retained. In addition, no sufficient labeled training samples of railway circumstance are available, thereby hindering the deployment of SSD. A two-stage training strategy leveraging to transfer learning is adopted to solve this issue. The deep learning model is preliminarily trained using labeled data of numerous auxiliaries, and then it is refined using only a few samples of railway scene. A railway spot in China, which is easily damaged by landslides, is investigated as a case study. Experimental results show that the proposed multi-block SSD method produces an overall accuracy of 96.6% and obtains an improvement of up to 9.2% compared with the traditional SSD.     

The update of BDS-2 TGD and its impact on positioning

Timing group delay (TGD) is an important parameter that affects the positioning performance of global navigation satellite systems (GNSS). The BeiDou navigation satellite system (BDS) broadcasts TGD corrections from B3I frequency to B1I and B2I frequencies, namely TGD₁ and TGD₂. On July 21, 2017, BDS updated TGD values with a maximum change of more than 4 ns. In this contribution, we explain the motivation for the BDS TGD update, which is due to the systematic bias between narrowly correlated and widely correlated pseudo-ranges in BDS monitoring receivers. To investigate the impact of the updated TGD, BDS signal-in-space range error (SISRE) and user positioning performance regarding single point positioning (SPP) and precise point positioning (PPP) are analyzed. Results show that after the update of TGD, the difference between the new TGD and multi-GNSS experiment (MGEX) differential code bias (DCB) decreases from 1.38 ns to 0.29 ns on TGD₁ and from 0.40 ns to 0.25 ns on TGD₂. With the contribution of more accurate TGD, the systematic bias of BDS radial SISRE no longer exists, and the overall BDS SISRE also reduces from 1.33 m to 0.87 m on B1I/B2I frequency, from 1.05 m to 0.89 m on B1I frequency, from 0.92 m to 0.91 m on B2I frequency, respectively, which proves the similar precision of BDS TGD and MGEX DCB. One week of statistical results from 28 globally distributed MGEX stations shows that the SPP performance improves on non-B3I frequencies after the TGD update, with a maximum improvement of more than 22% for the B1I/B2I or B1I/B3I combination. The new TGD mainly reduces SPP positioning bias in the East component. The updated TGD also slightly improves the PPP convergence performance for the B1I/B3I combination, but mostly contributes to a more accurate estimation of the receiver clock and ambiguities.     

A novel range-Doppler imaging algorithm with OFDM radar

Traditional pulse Doppler radar estimates the Doppler frequency by taking advantage of Doppler modulation over different pulses and usually it requires a few pulses to estimate the Doppler frequency. In this paper, a novel range-Doppler imaging algorithm based on single pulse with orthogonal frequency division multiplexing(OFDM) radar is proposed, where the OFDM pulse is composed of phase coded symbols. The Doppler frequency is estimated using one single pulse by utilizing Doppler modulation over different symbols, which remarkably increases the data update rate. Besides, it is shown that the range and Doppler estimations are completely independent and the well-known range-Doppler coupling effect does not exist. The effects of target movement on the performances of the proposed algorithm are also discussed and the results show that the algorithm is not sensitive to velocity. Performances of the proposed algorithm as well as comparisons with other range-Doppler algorithms are demonstrated via simulation experiments.     

单视角立体成像技术研究

立体成像是获取目标三维轮廓信息的有效方法。目前,在航天航空领域立体成像方法主要包括：基于立体视觉原理的三线阵成像方法和主动式激光测距立体成像方法。这两种成像方式由于对平台要求较高或者无法得到目标的灰度图像而存在相应的缺陷。文章研究了一种新的单视角立体成像技术。通过对该技术的研究认为,单视角立体成像技术能够实现单台相机单...     

预腐蚀疲劳缺口系数(英文)

对在EXCO溶液中预腐蚀后的LC4CS光滑试件和缺口试件进行疲劳试验,得到不同预腐蚀时间的S-N曲线及预腐蚀疲劳缺口系数。通过分析腐蚀过程,阐述了腐蚀对疲劳缺口系数的影响机理,建立了描述预腐蚀疲劳缺口系数的两参数模型,并进行了试验验证。结果表明:LC4CS材料的疲劳缺口系数随预腐蚀时间呈现出先降后升的变化趋势,其拐点出现在剥蚀开始阶段。     

基于模糊理论的图像边缘检测算法研究与实现

针对模糊边缘检测算法迭代次数过多、计算量过大、实时性不好等缺陷,提出一种快速改进图像边缘检测算法,包括定义隶属函数、模糊增强处理、模糊平滑及模糊边缘检测,通过实验,改进算法速度快,性能好,效率高。     

刷毛翼型尾缘噪声控制实验研究

利用具有全消声环境的低速开口风洞研究了采用翼型尾缘刷毛来控制翼型噪声的方法,研究了不同迎角情况下不同长度和间距刷毛对翼型远声场气动噪声的影响以及翼型表面压力的影响,并把该方法与锯齿尾缘降噪方法对比,研究了不同工况下两种降噪方案对降噪效果的影响。实验结果表明,翼型尾缘附加刷毛是一种可行的降噪方案,尤其对中低频段具有比较明显的降低效果;降噪效果与刷毛的间距和长度有关;尾缘刷毛与锯齿尾缘相比具有更优的降噪效果。附加刷毛对翼型壁面动态压力载荷的影响较小。