Sodium potassium niobate (KNN) (K0.5Na0.5NbO3) nanopowder with a mean particle size of about 20 - 30 nm was synthesized by wet chemical route using Nb2O5 as Nb source. A solution of K, Na and Nb cations was prepared, ...Sodium potassium niobate (KNN) (K0.5Na0.5NbO3) nanopowder with a mean particle size of about 20 - 30 nm was synthesized by wet chemical route using Nb2O5 as Nb source. A solution of K, Na and Nb cations was prepared, which resulted in a clear gel after the thermal treatment. Phase analysis, microstructure and morphology of the powder were determined by X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Field Emission Scanning Electron Microscopy (FESEM). The obtained gel was first analyzed by Thermo Gravimetric Analyzer (TGA) and Differential Scanning Calorimetry (DSC), and then calcined at different temperatures of 400℃, 500℃, 600℃ and 700℃. The X-Ray Diffraction (XRD) patterns of the synthesized samples confirmed the formation of the orthorhombic crystal phase of K0.5Na0.5NbO3 at 500?C, a temperature significantly lower than that typically used in the conventional mixed oxide route. The process developed in this work is convenient to realize the mass production of KNN nanopowders at low cost and suitable for various industrial applications.展开更多
为了进一步提高工业机器人的故障状态监测精度,采用RV齿轮箱数据采集与监视控制系统(Supervisory Control And Data Acquisition,SCADA)进行数据采集测试,通过邻近算法(K-Nearest Neighbor,KNN)综合评价了RV齿轮箱故障状态下的全工况参...为了进一步提高工业机器人的故障状态监测精度,采用RV齿轮箱数据采集与监视控制系统(Supervisory Control And Data Acquisition,SCADA)进行数据采集测试,通过邻近算法(K-Nearest Neighbor,KNN)综合评价了RV齿轮箱故障状态下的全工况参数。以SPC方法与滑动窗口结合的方法获得异常率结果,实时监测齿轮箱的实际运行状态。研究结果表明:阈值介于0.1~0.2之间时,样本数目平缓减少,此时是比较优秀的。选择参数设置可以使得预测精度提高3.1%,优化14.1%运算效率。该研究有助于提高工业机器人的使用效率,具有很高的节能提效作用。展开更多
文摘Sodium potassium niobate (KNN) (K0.5Na0.5NbO3) nanopowder with a mean particle size of about 20 - 30 nm was synthesized by wet chemical route using Nb2O5 as Nb source. A solution of K, Na and Nb cations was prepared, which resulted in a clear gel after the thermal treatment. Phase analysis, microstructure and morphology of the powder were determined by X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Field Emission Scanning Electron Microscopy (FESEM). The obtained gel was first analyzed by Thermo Gravimetric Analyzer (TGA) and Differential Scanning Calorimetry (DSC), and then calcined at different temperatures of 400℃, 500℃, 600℃ and 700℃. The X-Ray Diffraction (XRD) patterns of the synthesized samples confirmed the formation of the orthorhombic crystal phase of K0.5Na0.5NbO3 at 500?C, a temperature significantly lower than that typically used in the conventional mixed oxide route. The process developed in this work is convenient to realize the mass production of KNN nanopowders at low cost and suitable for various industrial applications.
文摘为了进一步提高工业机器人的故障状态监测精度,采用RV齿轮箱数据采集与监视控制系统(Supervisory Control And Data Acquisition,SCADA)进行数据采集测试,通过邻近算法(K-Nearest Neighbor,KNN)综合评价了RV齿轮箱故障状态下的全工况参数。以SPC方法与滑动窗口结合的方法获得异常率结果,实时监测齿轮箱的实际运行状态。研究结果表明:阈值介于0.1~0.2之间时,样本数目平缓减少,此时是比较优秀的。选择参数设置可以使得预测精度提高3.1%,优化14.1%运算效率。该研究有助于提高工业机器人的使用效率,具有很高的节能提效作用。
