Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.     

Solid state reactions between SiC and Ir

Reactivity between SiC and Ir as a function of SiC-crystallinity was investigated by diffusion bonding technique under a vacuum and over the temperature range of 1200–1450 °C. As reaction products, various Ir-silicides and free unreacted-C were detected. Reactivity is strongly affected by the temperature and SiC-crystallinity involving a series of interactions, from “no reaction” to “massive exothermic reactions”. In particular, interfacial phenomena are more pronounced by the presence of defects and grain boundaries.Solid state reactions result in formation of fine C-precipitates rearranged in a quasi-periodic microstructure. On the contrary, clustering of highly ordered C-precipitates (C-graphitized) occurs after “massive reactions” take place.A relationship between the degree of graphitization (from 1 to multi-layers of graphene), temperature and SiC crystallinity was found by Raman spectroscopy. 2D-layering phenomenon is enhanced in polycrystalline SiC at high temperature.     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

低觉醒脑电识别与唤醒的可穿戴系统研究

为智能化地识别警戒作业人员出现的低觉醒、注意力下降的生理状态，本文介绍了一种基于FPGA和脑电信号处理的低觉醒状态检测与唤醒系统，系统通过传感器从大脑头皮采集脑电信号，转换为数字信号，经傅里叶变换获取了脑电信号的θ相对能量、α相对能量、重心频率、谱熵等4个特征量，由4个特征量表征低觉醒状态并运用支持向量机对低警戒状态进行识别，当识别出低觉醒状态时采用声音报警模块发出声音，唤醒警戒作业人员。设计系统能够较好地识别出低觉醒状态，识别率达90.8%，可为提高警戒作业工作绩效提供一种可穿戴的智能装备。     

智能变电站设备管控大数据分析系统研究

结合数据挖掘、大数据技术在电力系统中的应用现状，分析和设计了一种智能变电站设备管控大数据分析系统。对变电站设备运行状态的大数据特征及基本框架进行了分析，并重点阐述了变电站设备运行状态大数据分析系统的数据集成与预处理、数据存储与处理、设备状态评估模型以及数据可视化展示。实验结果表明，所设计的大数据分析系统能够大幅度提升变电站设备数据分析智能化水平，为变电站管控稳定运行提供更加有效和实用性的技术支撑。     

Anticancer activity of flavonoids accompanied by redox state modulation and the potential for a chemotherapeutic strategy

Since researchers began studying the mechanism of flavonoids’ anticancer activity, little attention has been focused on the modulation of redox state in cells as a potential chemotherapeutic strategy. However, recent studies have begun identifying that the anticancer effect of flavonoids occurs both in their antioxidative activity which scavenges ROS and their prooxidative activity which generates ROS. Against this backdrop, this study attempts to achieve a comprehensive analysis of the individual and separate study findings regarding flavonoids’ modulation of redox state in cancer cells. It focuses on the mechanism behind the anticancer effect, and mostly on the modulation of redox potential by flavonoids such as quercetin, hesperetin, apigenin, genistein, epigallocatechin-3-gallate (EGCG), luteolin and kaempferol in both in vitro and animal models. In addition, the clinical applications of and bioavailability of flavonoids were reviewed to help build a treatment strategy based on flavonoids’ prooxidative potential.     

小微数据包高效无线传输技术的发展和趋势

5G-NR和B5G系统都需能高效地支持小微数据包(块)的传输,且在不同的无线传输技术(如宽带或超低时延)之间快速灵活地切换。系统梳理和比较和小微数据包(块)相关的多种无线传输技术,如两步RACH、预配置授权和公共资源竞争等,分析它们对3GPP各个系统和各个RAN协议的影响和复杂度优劣等,并进一步展望其未来发展和应用趋势。     

Enhanced transduction coefficient in piezoelectric PZT ceramics by mixing powders calcined at different temperatures

Large transduction coefficient ($d_{33}\times g_{33}$) is difficult to obtain in piezoelectric ceramics because these two parameters show opposite trends with compositional modifications. Herein, the Pb(Zr_0.53Ti_0.47)O₃ ceramic powders were calcinated under different temperatures (A:830 °C, B:860 °C, and C:890 °C), and then mixed together according to different weight ratios (1A:1B:1C, 1A:2B:1C, 1A:2B:3C and 3A:2B:1C) for ceramics preparation. Both d₃₃ and g₃₃ are improved successfully, and the transduction coefficient with the weight ratio of 1A:2B:3C reaches up to 17,500 × 10⁻¹⁵ m²/N, which is 60 % higher than that with the powders calcinated under 830 °C, and at least twice those of commercial PZT-4, PZT-5A and PZT-8 ceramics. The improved transduction coefficient is owing to the enhanced piezoelectric constant and spontaneous polarization resulted from the increased grain size, relative density and the fraction of tetragonal phase. These results indicate that this is a simple but effective way to tailor the transduction coefficient in piezoelectric ceramics.