Volume Flow Rate Optimization of an Axial Fan by Artificial Neural Network and Genetic Algorithm

The present study is to improve the volume flow rate of an axial fan through optimizing the blade shape under the demand for a specified static pressure. Fourteen design variables were selected to control the blade camber lines and the stacking line and the values of these variables were determined by using the experimental design method of the Latin Hypercube Sampling (LHS) to generate forty designs. The optimization was carried out using the genetic algorithm (GA) coupled with the artificial neural network (ANN) to increase the volume flow rate of the axial fan under the constraint of a specific motor power and a required static pressure. Differences in the aerodynamic performance and the flow characteristics between the original model and the optimal model were analyzed in detail. The results showed that the volume flow rate of the optimal model increased by 33%. The chord length, the installation angle and the cascade turning angle changed considerably. The forward leaned blade was beneficial to improve the volume flow rate of the axial fan. The axial velocity distribution and the static pressure distribution on the blade surface were improved after optimization.

RESEARCH ON THE PACKING ALGORITHM FOR ANTI-SEU OF FPGA BASED ON TRIPLE MODULAR REDUNDANCY AND THE NUMBERS OF FAN-OUTS OF THE NET

Static Random Access Memory(SRAM) based Field Programmable Gate Array(FPGA) is widely applied in the field of aerospace, whose anti-SEU(Single Event Upset) capability becomes more and more important. To improve anti-FPGA SEU capability, the registers of the circuit netlist are tripled and divided into three categories in this study. By the packing algorithm, the registers of triple modular redundancy are loaded into different configurable logic block. At the same time, the packing algorithm considers the effect of large fan-out nets. The experimental results show that the algorithm successfully realize the packing of the register of Triple Modular Redundancy(TMR). Comparing with Timing Versatile PACKing(TVPACK), the algorithm in this study is able to obtain a 11% reduction of the number of the nets in critical path, and a 12% reduction of the time delay in critical path on average when TMR is not considered. Especially, some critical path delay of circuit can be improved about 33%.

Aerodynamic design of transonic fan/compressor by 3D viscous RNS combined with genetic algorithms

This paper presents an aerodynamic design of a small transonic fan by 3D viscous RNS solver combined with genetic algorithms.The aerodynamic design system based on the 3D viscous RNS solver reduces the dependency on the design experience for designers.Furthermore the optimum with genetic algorithms is an effective method for improving the transonic fan performance as a part of the design system.The design result showed that the transonic fan designed by this method reaches the design requirement even with more efficiency value.

基于FAN算法的串扰时延故障的测试矢量生成

串扰噪声已成为在深亚米工艺下造成电路功能错误的一个主要原因,对串扰时延测试已成为一个迫切的问题。利用FAN算法完成串扰时延故障的测试矢量生成,并且利用其多路回退和回溯等主要特色,来提高测试生成算法的效率。

Stability of multiple fans in mine ventilation networks

In large mines,single fan is usually not enough to ventilate all the working areas.Single mine-fan approach cannot be directly applied to multiple-fan networks because the present of multiple pressures and air quantities associated with each fan in the network.Accordingly,each fan in a multiple-fan system has its own mine characteristic curve,or a subsystem curve.Under some consideration,the conventional concept of a mine characteristic curve of a single-fan system can be directly extended to that of a particular fan within a multiple-fan system.In this paper the mutual effect of the fans on each other and their effect on the stability of the ventilation network were investigated by Hardy Cross algorithm combined with a switching-parameters technique.To show the validity and reliability of this algorithm,the stability of the ventilation system of Abu-Tartur Mine(one of the largest underground mine in Egypt)has been studied.

利用FAN算法进行组合电路的等价性检验

讨论了组合电路的等价性检验方法,分析了FAN算法的关键技术。利用该算法进行了组合电路的等价性检验,实验结果表明了该方法的有效性。

Image Reconstruction from Fan-Beam Projections without Back-Projection Weight in a 2-D Dynamic CT: Compensation of Time-Dependent Rotational, Uniform Scaling and Translational Deformations

In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.

基于云边协同的通用板级自动测试系统方案设计

针对当前数字电路自动测试领域,对通用板级自动测试系统进行了设计,完成了系统方案的设计开发和测试验证。为了解决通用板级自动测试系统的测试数据量大、本地存储容量不足、测试向量与被测试目标无法自动化匹配、无法进行批量快速测试等问题,采用云边协同架构设计了通用板级自动测试系统,避免了大量数据传输和数据集中式处理,使得云端计算资源能够集中解决关键数据处理任务。为了提高板级测试平台的通用性,使平台适配不同接口的电路板,同时具有高速网络数据处理能力,系统选用精简命令集处理器和现场可编程门阵列(Advanced RISC machines,Filed programmable gate array,ARM+FPGA)的异构计算平台作为边缘设备。为了提高系统的测试效率,采用模块化的设计思想,系统硬件测试平台设计了多总线分布式结构。系统采用扇出导向(Fan-out-oriented,FAN)算法生成测试向量,并基于浏览器/服务器(Brower/Server,B/S)架构设计了用户操作界面,用户可通过浏览器进行测试操作,完成板级自动故障测试,并自动生成故障诊断报告。实验结果表明,对两个待测板卡进行测试验证,通用板级自动测试系统可以自动识别目标板卡,自动匹配测试向量,进行自动测试,生成测试报表。基于云边协同的通用板级自动测试系统提高了测试效率,满足数字电路板卡出厂前批量测试的需求,具有实际应用价值。

基于遗传算法与Hardy-Cross方法的矿井通风机控制

针对矿井通风机系统控制的复杂问题,提出了一种遗传算法与Hardy-Cross方法相结合的矿井通风控制,强化了其在处理离散变量和非凸搜索空间中寻找全局最优解的能力。通过数学形式化定义问题并结合基尔霍夫定律,确立了通风机网络的优化模型。根据实际用风情况智能调节通风机的供风量,以实现能源节约和安全生产的目标。通过对某煤矿的通风案例深入研究和验证,风扇的配置在优化气流方面表现出了卓越性能。该研究不仅为矿山工程领域提供了新的优化思路和方法,也为通风机系统的管理提供了重要参考。

暖通空调小流量风机机械振动信号自适应采集研究

当暖通空调小流量风机运行时,频繁产生的脉冲噪声增加了信号采集的复杂性并引入了干扰,使得采集到的振动信号含有大量不必要的噪声成分,降低了采集精度和准确性。为此,提出暖通空调小流量风机机械振动信号自适应采集方法。使用经验模态分解方法对振动信号进行处理,获得信号在时域和频域上的特征信息。根据振动信号的频率特征,设计自适应变采样算法在不同的时间段内动态地调整采样率,采集风机振动信号。使用数学形态滤波器调整信号的形状,去除脉冲干扰以提高采集信号的精度,并进一步优化信号的质量。实验结果表明,所提方法的振动信号自适应采集精度高,且采集时间短。

Adaptive Real-Coded Genetic Algorithm for Identifying Motor Systems

In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical and electrical equations. The real-coded genetic algorithm (RGA) is adopted to identify all parameters of motors, and the standard genetic algorithm (SRGA) and various adaptive genetic algorithm (ARGAs) are compared in the rotational angular speeds and fitness values, which are the inverse of square differences of angular speeds. From numerical simulations and experimental results, it is found that the SRGA and ARGA are feasible, the ARGA can effectively solve the problems with slow convergent speed and premature phenomenon, and is more accurate in identifying system’s parameters than the SRGA. From the comparisons of the ARGAs in identifying parameters of motors, the best ARGA method is obtained and could be applied to any other mechatronic systems.

基于WOA-RF的船用风机故障诊断

针对船用风机典型故障诊断问题,利用鲸鱼优化算法优化随机森林(random forest optimized bywhale optimization algorithm,WOA-RF)对故障进行诊断,并通过实验验证该方法的准确性。实验模拟包括正常工况和5种异常工况在内的6种工况。采集所有不同工况下的振动信号,分别提取时域、频域下的特征参数构建第一特征向量。通过传统随机森林筛选得到具有更优分类效果的第二特征向量,再输入WOA-RF中完成故障识别。实验结果表明,本文提出的方法能够有效识别故障模式,平均预测准确率超99%。与其他算法对比,这种基于信息融合和WOA-RF的船用风机故障诊断方法准确性更高。

基于YOLOv3的风机叶片故障检测模型

针对风机工作中由于高海拔地理位置、恶劣天气等因素的影响,致使风机叶片出现裂纹、沙眼等缺陷故障,提出基于YOLOv3算法的风机叶片故障检测模型。将风机叶片缺陷区域具有YOLO格式的数据集划分为训练集与测试集,输入YOLOv3模型进行实验,结果表明:YOLOv3模型与YOLOv2模型相比,精度提升3.7%,达到了90.6%;召回率提升3.2%,达到了90.5%;精度平均值提升4.8%,达到了76.2%。

煤矿主通风机不停风倒机控制技术研究

针对煤矿通风系统主备风机传统倒机方式供风稳定性与连续性差、备用风机启动失败率高、存在通风失稳风险等问题,研究了煤矿主通风机稳风倒机技术,从煤矿通风系统大滞后、非线性特点的角度出发,提出了一种基于粒子群优化的模糊PID不停风倒机控制方案,并设计了相应系统。该系统通过优化算法自适应调节风门开合角度,可有效缩短倒机时间,提高备用风机启动成功率,实现倒机过程井下通风不中断,确保通风系统全过程安全稳定运行。

集成多方法的废酸装置风机K7200轴承故障诊断

在废酸装置风机K7200中,轴承作为重要的机械部件,准确判断其故障(健康状态、内圈故障、外圈故障和滚动体故障)可以提高维修效率。克服实际作业场景中人工诊断的缺点,提出了集成多方法的轴承故障诊断策略:分别采用K最近邻算法(简称KNN)、逻辑回归(简称LR)和决策树(简称DT)进行诊断,对结果进行投票集成。实验结果表明,采用集成多方法的故障诊断法较KNN、LR和DT算法,故障诊断的准确率分别提升了3.69%、5.03%、6.3%。

发动机滑油散热系统性能计算方法及其应用

讨论了安装鼓风机引起滑油附加温升的原因并提出了合理的计算模型,完善了滑油散热系统性能计算方法。研究表明,在建立良好的物理模型的基础上,应用遗传算法对模型结构参数进行优化,可以显著提高系统模型的精度,减小系统性能计算误差。应用本文的计算模型分析了温控活门对滑油温度的影响,并建立了预测燃、滑油瞬态温度值的方法,为发动机的安全运行提供了指导。本文方法的优点是只需少量滑油系统试验数据即可获得满意的模型拟合结果,从而大大节约了试验费用,提高了试验效率,并能有效预测试验难以达到的恶劣条件下的滑油散热性能。

基于无线传感网络的矿井局部通风机风量自动控制

针对通风机风量自动控制常出现超调现象、控制效果不佳的问题,提出基于无线传感网络的矿井局部通风机风量自动控制方案。根据实际情况搭建无线传感网络;利用无线传感网络采集与传输局部通风机的功率数据;采用最邻近值填补算法填补缺失数据值;根据功率、转速和风量之间的关系确定局部通风机的风量,并与所需风量作差,识别局部通风机的风量误差;利用模糊PID自适应控制算法分析风量误差,确定控制量;通过PID控制器调控局部通风机风量,以实现基于无线传感网络的矿井局部通风机风量自动控制。实验证明,设计方法的超调量在2%以下,且可以在3 s内使通风机的风量恢复稳定状态。

基于MAF模型的串扰时延故障的测试矢量生成

随着深亚微米技术,串扰噪声问题越来越严重。利用MAF模型的基本思想,探讨了一种串扰时延最大化算法,并且利用被修改的FAN算法,生成测试矢量。对于一条敏化通路,利用被修改的FAN算法适当地激活相应的攻击线和受害线,使电路在最恶劣情况下引起最大通路时延,从而实现更有效的时延测试。在标准电路ISCAS’85上进行实验验证,结果表明:该算法对于多攻击线的串扰时延故障的测试矢量产生是有效的。

多攻击线引起的串扰时延故障的TPG

探讨了一种串扰时延最大化算法,并且利用被修改的FAN算法,生成测试矢量.对于一条敏化通路,利用被修改的FAN算法适当地激活相应的攻击线和受害线,使电路在最恶劣情况下引起最大通路时延,从而实现更有效的时延测试.利用了FAN算法的多路回退和回溯等主要特色,提高了测试生成算法的效率.实验结果表明,沿着任何临界通路传播的受害线相耦合的攻击线被适当地激活,并且可以对一定规模的电路的串扰时延故障进行测试矢量生成.

高负荷低速轴流风扇数值优化设计与实验研究

应用基于自适应遗传算法和复合形法发展的混合遗传算法数值设计平台ADOP,对某高负荷低速轴流风扇TA36A实施气动数值优化。该风扇设计转速2.9kr/min,三维数值结果近设计点流量7.482kg/s,绝热效率为84.54%,失速裕度为16.38%;优化设计后风扇TA36B数值模拟结果失速裕度提高了1.6个百分点,气动效率为85.31%,比原型略有提高。气动性能试验风扇TA36B失速裕度达18.84%,具有较宽的稳定工作范围。