Shenyang Institute of Automation,Chinese Academy Of Sciences
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Fast actuator and sensor fault estimation based on adaptive unknown input observer
No full textThis study evaluates the robust fault estimation problem of systems with actuator and sensor faults though the simultaneous use of unknown input disturbances and measurement noise. Specifically, an augmented descriptor system is preliminarily developed by creating an augmented state consisting of system states and sensor faults. Next, a novel fast adaptive unknown input observer (FAUIO) is proposed for the system to enhance its fault estimation performance. The existence condition of the novel FAUIO is then introduced for linear time-invariant systems with unknown input disturbances. Furthermore, the proposed FAUIO is extended to a class of Lipschitz nonlinear systems with unknown input disturbances and measurement noise to investigate the robust fault estimation problem. Accordingly, an H∞ performance index is employed to attenuate the influence of disturbances on fault estimation. Moreover, the linear matrix inequality (LMI) technique is applied to solve the designed FAUIO. Finally, the effectiveness of the developed FAUIO is validated via the simulation of two examples.</p
Detection Methods in Smart Meters for Electricity Thefts: A Survey
No full textFor accommodating rapidly increasing power demands, power systems are transitioning from analog systems to systems with increasing digital control and communications. Although this modernization brings many far-reaching benefits, the hardware and software newly incorporated into the power systems also incur many vulnerabilities. By taking advantage of these vulnerabilities, adversaries can launch various cyber/physical attacks to tamper with electricity meter readings, i.e., to steal electricity. It is reported that total worldwide annual economic losses caused by electricity theft reached up to almost one hundred billion dollars in recent years. With methods to tamper with meter readings becoming more versatile, secret, and flexible, electricity theft tends to get even more serious in modernized power systems. For preventing adversaries from stealing electricity, researchers have done a lot of works. Although some related surveys on these works exist, they are not updated or just discuss electricity theft in a specific region. This survey aims to gain a comprehensive and in-depth understanding of the electricity theft issue. After investigating how adversaries tamper with meter readings, we systematically survey all existing detection methods up to date, which is classified into machine learning- and measurement mismatch-based methods. Adverse effects and political and socioeconomic factors of electricity theft are also provided. This survey can help relevant researchers to shape future research directions, especially in the area of developing new effective electricity theft detection methods
内部水压均衡的水导激光加工头
No full text本发明涉及水导激光加工领域，具体地说是一种内部水压均衡的水导激光加工头，包括壳体、聚焦镜、透光窗口和喷嘴，所述壳体一端设有入射口，且所述入射口内设有聚焦镜和透光窗口，所述壳体另一端设有喷嘴，且激光经过所述聚焦镜聚焦于所述喷嘴处，所述壳体内设有均压环，且所述均压环设于所述透光窗口和喷嘴之间，所述均压环内部设有供激光穿过的通孔腔，所述均压环外侧与壳体之间形成液压均衡腔，所述均压环的环壁内均布有限流孔，且所述液压均衡腔通过各限流孔与所述通孔腔连通，所述壳体上设有与所述液压均衡腔连通的入水孔。本发明利用均压环实现高压水的压力和流量均匀分布，从而解决了喷嘴附近水压与流量不均衡影响水射流稳定长度的问题
超高压输电线路绝缘子检测机器人
No full text本实用新型涉及绝缘子检测技术领域，特别涉及一种超高压输电线路绝缘子检测机器人。包括控制箱体、自适应导向模块、环抱导向执行机构、环抱导向驱动机构、移动机构、检测夹爪机构、绝缘子电阻检测仪及电源，其中自适应导向模块与移动机构设置于控制箱体的顶部；环抱导向执行机构为两组且对称设置于控制箱体两侧；环抱导向驱动机构设置于控制箱体端部，用于驱动环抱导向执行机构张开或闭合；绝缘子电阻检测仪和电源设置于环抱导向执行机构上；检测夹爪机构为两组，一组固定于控制箱体顶部，另一组设置于移动机构上，两对检测夹爪机构用于爬行及绝缘子串电阻检测。本实用新型结构简单，行走连续，爬行平稳，检测效率高，安全可靠
一种混合动力倾转旋翼无人飞行器
No full text本发明涉及无人飞行器技术领域，特别涉及一种混合动力倾转旋翼无人飞行器。包括机身及设置于机身上的尾翼和两个机翼，其中机身的前端下部设有涵道风扇；机翼包括内翼段和倾转外翼段，内翼段的一端与机身固定连接，另一端与倾转外翼段转动连接，尾翼为V型结构。本发明的机身前下部装有涵道风扇，可提供升力，并且能显著的提升飞行器的纵向配平特性；该飞行器可垂直起降，不受限于场地即可起飞降落，同时可长航时高速巡航，满足测绘、巡逻、运输、警用等需求
基于机器学习方法的点阵模型增材制造的自适应填充方法
No full text本发明涉及一种适用于点阵模型增材制造加工的自适应填充方法，包括：根据学习样本对待填充的几何特征进行分类；选用适宜的填充路径对各个待加工子区域进行填充；确定各个子区域的加工次序，将各个子区域的填充轨迹进行连接。本发明方法对复杂点阵模型采用基于机器学习的自适应路径选择规划方式及无交叉轨迹连接方法，提高了加工的均匀性及光顺性；提高了加工效率和质量；采用根据机器学习对几何特征进行分类的加工区域归类方法，获得了适宜采用等距轮廓偏置、双螺旋轨迹及基于直骨架路径填充方式的的加工区域分类结果，实现了加工轨迹的光顺性和高效性；基于旅行商问题的连接路径，将使得轨迹连接没有交叉，实现高效的填充次序规划
Isolation method of Saccharomyces cerevisiae from red blood cells based on the optically induced dielectrophoresis technique for the rapid detection of fungal infections
No full textSaccharomyces cerevisiae (S. cerevisiae) has been classically used to treat diarrhea and diarrhea-related diseases. However, in the past two decades, fungal infections caused by S. cerevisiae have been increasing among immunocompromised patients, and it takes too long to isolate S. cerevisiae from blood to diagnose it in time. In this paper, a new method for the isolation and selection of S. cerevisiae from red blood cells (RBC) is proposed by designing a microfluidic chip with an optically-induced dielectrophoresis (ODEP) system. It was verified by theory and experiments that the magnitude and direction of the dielectrophoresis force applied on RBCs and S. cerevisiae are different, which determine that the S. cerevisiae can be isolated from RBCs by the ODEP system. By designing the specific light images and the dynamic separation mode, the optimal operating conditions were experimentally achieved for acquiring higher purity of S. cerevisiae. The purity ranges were up to 95.9%-97.3%. This work demonstrates a promising tool for efficient and effective purification of S. cerevisiae from RBCs and provides a novel method of S. cerevisiae isolation for the timely diagnosis of fungal infections
APAN: Across-Scale Progressive Attention Network for Single Image Deraining
No full textRecent single image deraining works have achieved significant improvement using convolutional neural networks. However, the rain streaks in the rain image share similar patterns with its multi-scale versions, which are not fully exploited in recent works. In this paper, we propose an Across-scale Progressive Attention Network (i.e., APAN) to explore the multi-scale collaborative representation for single image deraining. Specifically, we represent each rainy image via a multi-scale module. An across-scale attention module is then used to capture long-range feature correspondences from multi-scale features, which can model the rain streaks at an enlarging feature dimension. Afterwards, we construct a pyramid structure and further predict the rain streak progressively, which also guides the across-scale attention module to refine the feature representation from coarse to fine. The proposed model exploits self-similarity of features via an across-scale attention between different scales, which can well model the rain streak with long-range information. Experiments on several datasets show that our model achieves significant improvement compared with most state-of-the-art deraining models
Microstructure and Properties of WC Particles Reinforced 316L Stainless Steel Composites Prepared by Additive and Subtractive Manufacturing
No full text基于自主研发的增减材复合工艺技术与装备,探索了激光功率和WC颗粒质量分数对316L不锈钢复合材料致密度、组织演变和表面耐磨性能的影响规律.结果表明:随着WC质量分数的增加,试样致密度呈现先升高后降低的趋势,而硬度和耐磨性能均逐渐提高,过多的WC颗粒会使工件内部产生热裂纹,同时降低了工件的表面质量;当激光功率由270 W提高到330 W时粉末充分熔化,凝固后未熔合缺陷明显减少.当WC颗粒质量分数为5%、激光功率为330 W时,增材件的致密度最高达到99.6%;相比未添加WC颗粒的工件,力学性能、耐磨性能和表面质量等指标均有明显提高.</p
Adaptive output-Feedback asymptotic tracking control for a class of nonlinear systems with actuator failure
No full textThis study deals with the output-feedback asymptotic tracking control problem for a class of nonlinear strict-feedback systems with actuator loss of effectiveness failure. To handle with the output-feedback control issue in the presences of nonlinearities, a new reduced-order observer design is presented, by utilizing the dynamic gain technique, which not only eliminates the limitation that the Lipchitz coefficients are required to be known in the existing output-feedback results, but makes full use of the measurable information. Furthermore, a new failure compensation mechanism is proposed to erase the effect of actuator failure, by introducing a cubic absolute-value Lyapunov function method and a novel (σ,σf)-modification technique. Compared with the existing output-feedback failure compensation results, our proposed method can not only relax the assumption requirement on nonlinear function, i.e., the nonlinear function with respect to output y can be extended to the nonlinear one with respect to state variable χ¯i in the means of asymptotic tracking, but also avoid the issue that the estimate for actuator efficiency indicator drifts to a large value suddenly. Further, within the framework of backstepping design, a new high-gain reduced-order observer based adaptive output-feedback failure compensation control is developed. Then, with the aid of Lyapunov analysis method, it is shown that all the signals in the closed-loop system are globally bounded, and the system output can asymptotically track a given reference signal. Finally, a simulation example is given to illustrate the efficiency of the proposed techniques.</p