基于自适应阈值活动语音检测和最小均方误差对数谱幅度估计的低信噪比降噪算法

针对低信噪比(SNR)环境下传统方法对声信号降噪的局限性，提出了一种联合自适应阈值活动语音检测（VAD）算法和最小均方误差对数谱幅度估计（MMSE-LSA）的实时降噪算法。首先，在VAD算法中通过基于能量概率最大值的概率统计来对背景噪声进行估计，对得到的背景噪声进行实时更新并保存；然后，将实时更新的背景噪声作为MMSE-LSA的参考噪声，并对噪声幅度谱进行自适应更新，最后进行降噪处理。通过在真实场景中对四类声信号进行实验，结果表明，该算法在保证对低SNR声信号的实时处理的情况下，相较于传统MMSE-LSA算法，降噪信号的SNR能够提高10~15 dB，且不存在信号过减的情况，可应用于实际工程。     

双离心机法线加速度计动态校准中三参数余弦算法实现及应用

在双离心机的线加速度计动态校准中,三参数余弦算法贯穿在幅频特性、相频特性以及幅值线性度的整个测试中。本文详细描述了三参数余弦算法的概念和推导过程,以及在双离心机线加速度计动态校准数据处理过程中三参数余弦算法的程序实现;介绍了在幅频特性和相频特性中关于采集点的选取方式,降低由于采集点选择方式不同对数据拟合精度造成的影响。选取某型线加速度计为例,利用双离心机进行动态校准,对采集得到的数据点进行曲线拟合并得到测试结果,验证了所编写的三参数余弦算法程序的可行性。     

Genetic algorithm to simultaneously optimise stope sequencing and equipment dispatching in underground short-term mine planning under time uncertainty

ABSTRACT

The main issue in short-term planning optimisation for underground mining is organising the mining process with limited resources in the form of equipment and materials to satisfy production targets and stable feed grade requirements. In this paper, an integrated optimisation model is proposed based on an individual generation algorithm and an improved Genetic Algorithm to simultaneously optimise stope extraction sequencing and timing, extracted ore grade and equipment dispatching. The model objectives are to shorten the time gap between the stope mining processes and the overall working time. When the uncertainty of equipment working time is taken into account in a short-term scheduling model, the Monte Carlo simulation is applied to evaluate the risk of not meeting the production target. A modification strategy is defined to evaluate equipment failure. Consequently, any available equipment is automatically reassigned to the mining site to replace the broken-down equipment. A case study is used to validate the model in the Sanshandao gold mine of China to formulate an optimal monthly schedule. Compared with the conventional approach, the new model could reduce the variance of ore tonnage and feed grade and improve the equipment allocation efficiency. Discussions are presented to address the uncertainty.     

Shape optimization of bi-directional flow passage components based on a genetic algorithm and computational fluid dynamics

The inlet/outlet is an important part of a water conveyance system in a pumped storage power station (PSPS). Its hydraulic characteristics are directly related to the operation and economic benefit of the PSPS. Frequent changes between inflow and outflow operations pose significant challenges in the design of the inlet/outlet diffusion segment shape. In this study, an effective optimization method, including three-dimensional parametric modelling, computational fluid dynamics and a genetic algorithm, is introduced and coupled to the design of the diffusion segment shape. The hydraulic characteristics of bi-directional flow, including the head loss, velocity uneven distribution and uneven discharge distribution, are selected as the objective function in the optimization method. Using this method, the recommended shape of the inlet/outlet is studied and its hydraulic characteristics are discussed. The results indicate that the optimized inlet/outlet has better performance.     

On the approximation of the canard explosion point in singularly perturbed systems without an explicit small parameter

A canard explosion is the dramatic change of period and amplitude of a limit cycle of a system of nonlinear ODEs in a very narrow interval of the bifurcation parameter. It occurs in slow–fast systems and is well understood in singular perturbation problems where a small parameter epsilon defines the time-scale separation. We present an iterative algorithm for the determination of the canard explosion point which can be applied for a general slow–fast system without an explicit small parameter. We also present assumptions under which the algorithm gives accurate estimates of the canard explosion point. Finally, we apply the algorithm to the van der Pol equations, a Templator model for a self-replicating system and a model for intracellular calcium oscillations with no explicit small parameters and obtain very good agreement with results from numerical simulations.     

基于大数据分析的分布式MOLAP技术研究

在计算机系统运行以及研究环节中,会存在大量的规模效应,此类状况难以避免,要想有效解决此类问题,就需要利用分布式的处理方式,开展对文件系统的分析。文章对分布式多维联机分析过程(MOLAP)的数据模型进行了分析,从维编码的算法、映射归约(MapReduce)算法的实现、分析维的遍历算法等方面作深入探讨。     

具有外套管的释热元件表面温度求解

为进行具有外套管的释热元件的性能分析，需准确计算元件包壳外侧的温度分布。由于套管结构内外均存在流体，传热情况较为复杂，因此本文基于传热基本方程和能量守恒关系，设计开发了专用的迭代算法和计算程序求解该结构温度分布，并采用典型算例，将计算结果与Fluent软件仿真结果进行对比。结果表明，本文程序计算结果与Fluent软件仿真结果的相对误差小于5%。基于本算法编写的程序模块与燃料元件性能分析程序相耦合，可提高燃料性能分析流程的独立性。     

一种下肢运动意图识别算法性能实时测评系统* .txt

摘要：对腿部运动意图识别算法的实时性能进行综合可靠的评价是实现下肢假肢灵活稳定控制的前提。提出一种逐层分级的基于下肢运动意图识别算法的实时测评方法，对算法的可靠性、稳定性以及运动意图识别速度进行综合评价。利用开发的运动意图识别算法评测系统，对基于肌电信号源和机械信号源的两种运动意图识别算法进行了实时性能测试，发现肌电信号源的算法识别时间大于机械信号源算法，但是其算法稳定性优于机械信号源算法。进一步地，还利用该评测系统有效地区分出正常识别策略与异常识别策略，发现正常策略的动作识别稳定系数比异常策略高25%左右。因此，所提的基于下肢运动意图识别算法的实时测评方法，能够对不同信号源算法以及不同识别策略的实时性能进行有效评价，为智能下肢假肢控制系统开发提供可供参考的测试平台。 .txt     

Optimal design of Raman fibre amplifier based on terminal value optimization strategy and shuffled frog leaping algorithm

This paper introduces an evolutionary algorithm, Shuffled Frog Leaping Algorithm (SFLA), to solve the optimization problem in designing the multi-pumped Raman Fibre Amplifier (RFA). SFLA is a powerful optimizer tool because of its efficient mathematical expressions and global search capability. We utilize SFLA to determine the optimal pump wavelengths and pump powers by minimizing the gain ripple of RFA. To accelerate calculations, a terminal value optimization strategy (TVOS) is incorporated into the evolution of SFLA. This proposed strategy takes the terminal power values of pumps as the decision variables in optimization. Then, the optimal original power values of the pumps are obtained by solving the Power Coupled Equations once, without using the traditional method of repetitive guesses.The combination of SFLA and TVOS enhances the efficiency of optimization and accelerates calculation, while satisfying the design requirements of RFA.The simulation results show that nearly 65% of computational time has been saved compared with the traditional average power analysis. The 4-pumped C+L band of backward multi-pumped RFA with the average net gain of 0 dB, 1 dB and 2 dB are designed individually, where the gain ripple is less than 0.64 dB. The combination of SFLA and TVOS enhance the optimization efficiency and improve the performance of RFA with good gain profile.     

New empirical correlation for estimation of vaporization enthalpy of algerian saharan blend petroleum fractions

A Real-coded Genetic Algorithm has been used to develop a new correlation to estimate the enthalpy of vaporization for pure compounds and petroleum fractions as a function of the normal boiling point and specific gravity. In developing the correlation 80% of the data was used and the remaining are used for validation. The results of the proposed correlations are compared to others in literature. The comparison indicates that the proposed model is simple to use and more accurate than the most common correlations for predicting the enthalpy of vaporization of pure compounds and petroleum fractions.