Optimization of room-temperature TCR of polycrystalline La0.9-xSrxK0.1MnO3 ceramics by Sr adjustment

High-density La_0.9-xSr_xK_0.1MnO₃ ceramics (LSKMO, A-site = La, Sr and K, 0 ≤ x ≤ 0.25) are successfully fabricated by using facile sol-gel method. Electrical properties are performed by using combination of phenomenological percolation (PP) model, double exchange (DE) mechanism, and Jahn-Teller (JT) effect. Moreover, X-ray diffraction and scanning electron microscopy are employed to analyze the structure and morphology of LSKMO ceramics. Valence states and ionic stoichiometry are assessed by using X-ray photoemission spectrometry. Results reveal that Sr²⁺ ions, substituting La³⁺ ions, significantly influenced DE mechanism and JT effect. In addition, Sr-doping plays essential role in improving electrical properties of LSKMO ceramics. At optimal doping content of x = 0.09, peak temperature coefficient of resistance (TCR) of the resistivity is found to be 11.56% K^?1 at 297.15 K, which is optimal TCR for A-site K-occupied perovskite manganese oxides. These results confirm that polycrystalline LSKMO ceramics render high room-temperature TCR values due to Sr-doping.     

Application of differential evolution for cascaded multilevel VSI with harmonics elimination PWM switching

Harmonic elimination pulse width modulation (HEPWM) method has been widely applied to multilevel voltage source inverter (MVSI) to remove low frequency harmonics from its output voltage. However, the computation of the HEPWM switching angles for MVSI is very challenging due to several constraints, namely angle sequencing, very tight angular spacing and the numerous possibilities of angles distribution ratio. Realizing the potential of Differential Evolution (DE) to handle complex problems, this work proposes its application to solve the HEPWM problem for cascaded MVSI. Its emphasis is on improving the availability of HEPWM for higher output voltage by extending the maximum range of modulation index (M). It also removes the discontinuities in the switching angles and reduces the number of distribution ratio required to obtain the required solution. Compared to the most advanced (similar) work, i.e., 7-level MVSI with seventeen switching angles, DE covers a wider range of M; the maximum achievable M is 2.80. Furthermore, it exhibits very low second order distortion factor (DF₂): for the worst case, the value of DF₂ is 0.0014%. To verify the viability of the proposed algorithm, simulation is carried out and hardware prototype is constructed. Both results show very good agreement with the theoretical prediction.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

双丝三电弧焊中熔滴过渡及焊缝成形机理

为了验证双丝三电弧焊接过程中M弧不同的电流、脉冲频率对其熔滴过渡行为的影响;试验搭建了双丝三电弧焊的焊接系统以及高速摄像与波形同步采集系统.结果表明,熔滴过渡行为变化的主要原因是在M弧作用下熔滴的受力变化.其次,熔滴过渡行为和M弧电流的变化存在着对应关系:随着M弧电流增大,熔滴过渡行为依次为焊缝成形最佳的短路过渡+射流过渡、以及成形依次变差的大滴过渡、射滴过渡、射流过渡.随着M弧脉冲频率增加,熔滴过渡行为依次为一脉多滴、一脉一滴、多脉一滴三个阶段;其中焊接成形最理想的为一脉一滴的熔滴过渡阶段.     

基于全寿命周期成本的配电网蓄电池储能系统的优化配置

蓄电池储能具有效率高、使用寿命长、对地理条件要求低等优点,其额定功率和额定容量可以独立配置。以配电网中蓄电池储能系统全寿命周期内总的净收益最大为目标,研究配电网中蓄电池的配置和各时段充/放电值的优化,综合考虑了储能套利收入、政府电价补贴收入、减少电能转运费、延缓电网升级以及全寿命周期成本等因素。建立了蓄电池储能系统配置的混合优化模型,提出一种基于差分进化和预测-校正内点法的混合算法并进行求解。最后,算例测试比较了钠硫电池、全钒液流电池、多硫化物/溴液流电池、铅酸电池和锂离子电池的配置和净收益,分析了影响经济效益的指标,为蓄电池的配置规划提出了建议,并验证了所建模型和求解算法的可行性。     

A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter

Stock market prediction is of great interest to stock traders and investors due to high profit in trading the stocks. A successful stock buying/selling generally occurs near price trend turning point. Thus the prediction of stock market indices and its analysis are important to ascertain whether the next day's closing price would increase or decrease. This paper, therefore, presents a simple IIR filter based dynamic neural network (DNN) and an innovative optimized adaptive unscented Kalman filter for forecasting stock price indices of four different Indian stocks, namely the Bombay stock exchange (BSE), the IBM stock market, RIL stock market, and Oracle stock market. The weights of the dynamic neural information system are adjusted by four different learning strategies that include gradient calculation, unscented Kalman filter (UKF), differential evolution (DE), and a hybrid technique (DEUKF) by alternately executing the DE and UKF for a few generations. To improve the performance of both the UKF and DE algorithms, adaptation of certain parameters in both these algorithms has been presented in this paper. After predicting the stock price indices one day to one week ahead time horizon, the stock market trend has been analyzed using several important technical indicators like the moving average (MA), stochastic oscillators like K and D parameters, WMS%R (William indicator), etc. Extensive computer simulations are carried out with the four learning strategies for prediction of stock indices and the up or down trends of the indices. From the results it is observed that significant accuracy is achieved using the hybrid DEUKF algorithm in comparison to others that include only DE, UKF, and gradient descent technique in chronological order. Comparisons with some of the widely used neural networks (NNs) are also presented in the paper.     

CIE DE2000在彩色扫描仪特征化色差评价中的应用

采用支持向量回归机(SVR)建立了RGB色空间到CIE Lab色空间的转换模型,分别采用CIE DE2000与CIE 1976L*a*b*色差公式对模型精度进行色差计算。采用CIE DE2000色差公式得到的测试组色差平均值、最大和最小值分别为2.659 7,5.219 4和0.206 5,采用CIE 1976L*a*b*色差公式得到的测试组色差平均值、最大和最小值分别为2.865 6,5.879 1和0.376 9。实验结果表明,CIE DE2000与CIE 1976L*a*b*色差公式计算的色差值基本一致,均符合彩色扫描仪特征化精度要求,可将CIE DE2000色差公式用于扫描仪特征化管理中。     

基于微分进化算法的电路模型匹配技术

根据电路模型单元库实现装备数学模型和物理模型的映射匹配,是基于模型的装备快速测试中的一项关键技术.电路模型匹配技术是进行基于装备物理模型进行故障诊断的基础.对模拟电路中的基本数学模型单元和物理模型单元进行了总结,建立了相应的模型库,针对装备中最基本的单元——可观测的模拟电路系统,提出了利用微分进化算法进行模拟电路模型匹...     

不同材料外推模型的精冲有限元模拟对比

将35铜的应力应变曲线用VOSS模型、Ludwik模型外推并插入到DEFROM2D中,对精冲过程进行有限元模拟,对比了VOSS模型、Ludwik模型及DEFORM自带材料模型的计算结果,表明DEFORM自带材料模型与VOSS模型计算结果相近,DEFORM自带材料模型在大塑性应变下仍具有可靠性。