Shenyang Institute of Automation,Chinese Academy Of Sciences
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Cloud Computing Based Demand Response Management Using Deep Reinforcement Learning
No full textDemand response is an effective way for ensuring safety and stabilization of power grid by maintaining the balance between the supply and the demand of power grid, and this article focuses on using electric water heaters for demand response. In addition to considering comfort and price factors as did in previous works, this article considers the overshoot temperature and its influence on demand response. First, a theoretical model of the heating and cooling processes of the electric water heater is established; second, the demand response process using electric water heaters is analyzed, including the influences of the physical parameters and the settings of electric water heaters on the demand response process; third, a model is established considering the demand response requirement, the comfort of owners of electric water heaters, and the electricity price, simultaneously; fourth, an optimization method based on deep reinforcement learning is proposed for demand response using electric water heaters. Meanwhile, the influence of parameters on the results of demand response is discussed in details. Experimental results show the effectiveness of the proposed method
Dsa-PAML: a parallel automated machine learning system via dual-stacked autoencoder
No full textFinding a high-performance machine learning pipeline (ML pipeline) for a supervised learning task takes much time. It requires many choices, including preprocessing datasets, selecting algorithms, tuning hyperparameters, and ensembling candidate models. With increasing pipelines arises a combination explosion problem. This work presents a new automated machine learning (AutoML) system called Dsa-PAML to address this challenge by recommending, training, and ensembling suitable models for supervised learning tasks. Dsa-PAML is a parallel automated system based on a dual-stacked autoencoder (Dsa). Firstly, meta-features of datasets and ML pipelines are used to alleviate cold-start recommendation problems. Secondly, a novel dual-stacked autoencoder is used to simultaneously learn the latent features of datasets and ML pipelines, efficiently learning collaborations of both datasets and ML pipelines and recommending suitable ML pipelines for a new dataset. Thirdly, Dsa-PAML can train the recommended ML pipelines on the new dataset in a parallel method, which substantially reduces the time complexity of the proposed method. Finally, a parallel selective ensemble system is embedded into Dsa-PAML. It selects base models from candidate ML pipelines according to their runtime, classification performance, and diversity on the validation set, enhancing Dsa-PAML's stability for most datasets. Amounts of experiments on 30 UCI datasets show that our approach outperforms current state-of-the-art methods
Study on Ore and Rock Movement Law in Open Pit Blasting Process Based on Inertial Navigation Technology
No full text针对露天矿爆破过程中矿岩空间运动轨迹难以准确获取的问题,本研究创新性地提出了利用高精度MEMS惯性导航传感器高频率采集爆破过程的矿岩运动数据来生成矿岩空间运动轨迹的方法,在惯性导航技术基础上对爆破过程中矿岩轨迹生成算法进行研究。最后利用MATLAB数学软件准确输出矿岩在爆破过程中的真实空间运动轨迹信息,为露天矿爆破过程中矿岩运动规律研究提供理论和技术依据。以鞍钢齐大山露天矿-105 m水平采区为例进行了现场试验,基于试验结果分析了压渣爆破的矿岩运动规律,为露天爆破效果智能评价提供参考依据。</p
Mechanism of Surface Subsidence Propagation Based on Structural Instability Characteristics of Combined Rock Strata
No full text将采场上覆岩层划分成若干组合岩层结构，通过组合岩结构失稳特征解析地表沉陷扩展机理.分析了组合岩层结构梁体和支撑体的破坏时序与地表沉陷扩展之间的内在联系，认为组合岩层结构后部支撑体破坏滑入采空区是造成地表沉陷扩展的根本原因.提出了组合岩层结构垮落至地表沉陷过程的量化方法，以煤岩体塑性软化及损伤为理论指导，推导了结构后部支撑体破坏宽度的计算公式.结合岩层垮落三带分布及岩体破坏膨胀规律可知组合岩层结构垮落扩展次数.根据沉陷扩展机理及量化公式对铁法晓楠矿SW4102和SW4103工作面进行工程实例计算.</p
A Generic View Planning System Based on Formal Expression of Perception Tasks†
No full textView planning (VP) is a technique that guides the adjustment of the sensor’s postures in multi-view perception tasks. It converts the perception process into active perception, which improves the intelligence and reduces the resource consumption of the robot. We propose a generic VP system for multiple kinds of visual perception. The VP system is built on the basis of the formal description of the visual task, and the next best view is calculated by the system. When dealing with a given visual task, we can simply update its description as the input of the VP system, and obtain the defined best view in real time. Formal description of the perception task includes the task’s status, the objects’ prior information library, the visual representation status and the optimization goal. The task’s status and the visual representation status are updated when data are received at a new view. If the task’s status has not reached its goal, candidate views are sorted based on the updated visual representation status, and the next best view that can minimize the entropy of the model space is chosen as the output of the VP system. Experiments of view planning for 3D recognition and reconstruction tasks are conducted, and the result shows that our algorithm has good performance on different tasks. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.</p
Study of multi-electrode excitation mode for 3D electrical resistance tomography
No full textMulti-electrode excitation is an effective way to improve the performance of 3D electrical tomography (ET) system compared with single electrode excitation. This paper systematically discusses various sensing strategies for multi-electrode excitation with different combinations in radial and axial directions. A typical 3 x 8 3D ERT sensor is adopted to analyze the influence of different excitation modes on performance indexes, such as number of independent measurements, dynamic range of measurements, sensitivity distribution and correlation coefficient of image reconstruction. On the basis of radial rotation angle between the excitation electrodes mapped to the same plane and whether the excitation electrodes are located in the same axial layer, five typical electrode combination modes are designed under dual-electrode excitation and single-electrode measurement protocol. The results show that the variation trend of different indexes influenced by excitation mode is inconsistent. The entropy-based method is applied to comprehensively evaluate the different excitation modes with the selected multiple performance indexes. Among all above modes, the mode in which excitation electrodes are vertically aligned is better universal one. The experimental results show that the position characteristics of the preferable mode can obtain better image reconstruction quality in different distribution models. Furthermore, the better excitation mode will provide guidance for design of other multi-electrode excitation in 3D ET systems with different structures
一种在空间任意约束下的软连续型机器人的控制方法
No full text本发明属于软连续型机器人控制领域，具体说是一种在空间任意约束下的软连续型机器人的控制方法。包括以下步骤：首先建立软连续型机器人能量的变分，然后基于最小能量法建立平衡方程，采用有限差分法为微分形式进行离散，获得封闭的非线性方程组。然后建立机器人与约束面接触位置的平衡方程，采用不等式描述空间约束，限定机器人的运动空间。采用拉格朗日乘子法和非线性最小二乘法对模型进行求解。通过模型求解，得到软连续型机器人上每个驱动杆的长度。通过调节驱动杆的长度，以控制软连续型机器人动作。本发明基于采用拉格朗日乘子法和Levenberg‑Marquardt算法进行求解，保证了计算每个驱动杆的长度的结果的收敛性和稳定性
一种壳聚糖基三维多孔导电海绵及其制备方法与应用
No full text本发明公开了一种壳聚糖基三维多孔导电海绵及其制备方法与应用，涉及多孔材料技术领域。本发明所述壳聚糖基三维多孔导电海绵的制备方法为：首先以导电填充剂填充壳聚糖，然后加入致孔剂以形成孔隙结构，进一步增大海绵体的比表面积，最后加入碳纤维丝提高孔与孔之间的连通性，同时进一步提高材料的导电性。以本发明所述方法制备的壳聚糖基三维多孔导电海绵具有良好的生物相容性以及较高的比表面积，可以为微生物提供更多的附着位点，另外，碳纤维丝的加入可以增强材料的弹性和强度，可以改善材料的稳定性
可调四点夹持的绝缘子夹持机构
No full text本实用新型涉及绝缘子夹持设备，特别涉及一种可调四点夹持的绝缘子夹持机构。包括双向驱动直线模组、左夹爪及右夹爪，其中左夹爪和右夹爪设置于双向驱动直线模组上，双向驱动直线模组驱动左夹爪和右夹爪反向运动；左夹爪和右夹爪均包括支架及设置于支架上的两指夹持结构，左夹爪和右夹爪通过两指夹持结构四点夹持绝缘子。本实用新型设置有左右两夹爪，两个夹爪构成四点夹持，确保夹持机构的夹持效果，绝缘子不易脱落和滑动
水下变结构机器人
No full text1.本外观设计产品的名称：水下变结构机器人。2.本外观设计产品的用途：用于完成各种水下探测以及作业任务。3.本外观设计产品的设计要点：在于形状。4.最能表明设计要点的图片或照片：立体图