Average Speed in Projectile Motion and in General Motion of a Particle

We calculate the average speed of a projectile in the absence of air resistance, a quantity that is missing from the treatment of the problem in the literature. We then show that this quantity is equal to the time-average instantaneous speed of the projectile, but different from its space-average instantaneous speed. It is then shown that this behavior is shared by general motion of all particles regardless of the dimensionality of motion and the nature of the forces involved. The equality of average speed and time-average instantaneous speed can be useful in situations where the calculation of one is more difficult than the other. Thus, making it more efficient to calculate one by calculating the other.

The Relation between Freeway Average Speed and Speed Noise

Many factors affect the vehicular fuel consumption rate. The most significant traffic-related ones are speed, number of stops, speed noise, and acceleration noise (acceleration standard deviation). Fuel consumption models for both urban and highway traffic are used to evaluate the effect of these factors. Previous literature shows the speed and the acceleration of vehicles as well as the aerodynamic effects are the most commonly used variables in the highway fuel consumption mo dels. However, most existing models are based on the average or cruising speed and the effect of speed variation is by-and-large ignored. Incorporating the speed noise as a variable in the prediction models seems impractical because measuring it is cumbersome. However, knowing the relation between speed and speed noise may allow including the effect of speed noise in the model indirectly. To that end, this study examines the relation between speed and speed noise. The resulting mathematical relation is used to incorporate the speed noise effects in the fuel consumption model.

Safety Impact of Average Speed Control in the UK

There is considerable safety potential in ensuring that motorists respect the speed limits. High speeds increase the number and severity of accidents. Technological development over the last 20 years has enabled the development of systems that allow automatic speed control. The first generation of automatic speed control was point-based, but in recent years a potentially more effective alternative automatic speed control method has been introduced. This method is based upon records of drivers’ average travel speed over selected sections of the road and is normally called average speed control or section control. This article discusses the different methods for automatic speed control and presents an evaluation of the safety effects of average speed control, documented through changes in speed levels and accidents before and after the implementation of average speed control at selected sites in the UK. The study demonstrates that the introduction of average speed control results in statistically significant and substantial reductions both in speed and in number of accidents. The evaluation indicates that average speed control has a higher safety effect than point-based automatic speed control.

Research on Instantaneous Angular Speed Signal Separation Method for Planetary Gear Fault Diagnosis

Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation of equipment. Existing methods for damage perception of planetary gear trains mainly rely on linear vibration analysis. However, these methods based on linear vibration signal analysis face challenges such as rich vibration sources, complex signal coupling and modulation mechanisms, significant influence of transmission paths, and difficulties in separating damage information. This paper proposes a method for separating instantaneous angular speed (IAS) signals for planetary gear fault diagnosis. Firstly, this method obtains encoder pulse signals through a built-in encoder. Based on this, it calculates the IAS signals using the Hilbert transform, and obtains the time-domain synchronous average signal of the IAS of the planetary gear through time-domain synchronous averaging technology, thus realizing the fault diagnosis of the planetary gear train. Experimental results validate the effectiveness of the calculated IAS signals, demonstrating that the time-domain synchronous averaging technology can highlight impact characteristics, effectively separate and extract fault impacts, greatly reduce the testing cost of experiments, and provide an effective tool for the fault diagnosis of planetary gear trains.

A Study of Wind Statistics Through Auto-Regressive and Moving-Average (ARMA) Modeling

Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simulated results of the Auto-Regressive (AR), Moving-Average (MA), and/ or Auto-Regressive and Moving-Average (ARMA) models is studied. Predictions of the 25-year extreme wind speeds based upon the augmented data are compared with the original series. Based upon the results, predictions of the 50- and 100-year extreme wind speeds are then made.

Patterns of Nutrient Intake among Male and Female High School-Aged Cross-Country Skiers and Speed Skaters

This study aimed to determine the appropriate nutritional intakes and dietary habits of high school-aged cross-country skiers and speed skaters. The subjects, all high school students from N Prefecture, included 18 male cross-country skiers, 5 male speed skaters, 10 female cross-country ski players and 4 female speed skaters. Physical measurements, food intake frequency survey results, bone mineral density and exercise stress test outcomes, and lactic acid measurements were evaluated. Female athletes in both sports had higher body fat percentages relative to the average range stated for female athletes. Male speed skaters had a significantly higher maximum oxygen in-take than that male cross-country skiers did. By contrast, this parameter did not differ significantly among female athletes. A negative correlation was observed between the fat free mass and muscle mass, and a positive correlation was observed among the body fat percentage, fat percentage, and fat mass. Both male and female athletes had protein intake ratios within the reference ranges. All athletes except male speed skaters had lipid energy ratios that were higher than the upper limit of the reference value. Both male and female athletes also reported carbohydrate energy ratios within the reference ranges, but had cereal energy ratios below the reference values. Athletes should pay attention to the ingestion of various nutrients to ensure a sufficient energy intake. Accordingly, adolescent athletes should consume daily meals containing a good balance of staple foods, main dishes, side dishes, milk and other dairy products, and fruits.

基于分形维数的高速铁路地震预警系统地震P波震相识别方法

为更好保障高速铁路的运营安全,高速铁路地震预警系统的实施十分必要。5级以下的小震事件占据地震事件的95%以上,提高高速铁路预警系统在小震震相识别的速度与精度能有效保障高铁安全运营。提出一种基于分形维数的地震震相识别算法,优化传统分形维数的计算方法,提高分形维数的计算速度。引入分形斜率曲线并划分为4个阶段,分析临界点的分形斜率特征,通过识别分形斜率极值时刻判断地震波精准到达时刻。提出的算法平均误差达到0.006 3 s,标准差达到0.043 8 s,满足高速铁路地震预警系统的时效性和准确度要求。

Reliability ensemble averaging reduces surface wind speed projection uncertainties in the 21st century over China

Accurate prediction of future surface wind speed(SWS)changes is the basis of scientific planning for wind turbines.Most studies have projected SWS changes in the 21st century over China on the basis of the multi-model ensemble(MME)of the 6th Coupled Model Intercomparison Project(CMIP6).However,the simulation capability for SWS varies greatly in CMIP6 multi-models,so the MME results still have large uncertainties.In this study,we used the reliability ensemble averaging(REA)method to assign each model different weights according to their performances in simulating historical SWS changes and project the SWS under different shared socioeconomic pathways(SSPs)in 2015-2099.The results indicate that REA considerably improves the SWS simulation capacity of CMIP6,eliminating the overestimation of SWS by the MME and increasing the simulation capacity of spatial distribution.The spatial correlations with observations increased from 0.56 for the MME to 0.85 for REA.Generally,REA could eliminate the overestimation of the SWS by 33%in 2015-2099.Except for southeastern China,the SWS generally decreases over China in the near term(2020-2049)and later term(2070-2099),particularly under high-emission scenarios.The SWS reduction projected by REA is twice as high as that by the MME in the near term,reaching-4%to-3%.REA predicts a larger area of increased SWS in the later term,which expands from southeastern China to eastern China.This study helps to reduce the projected SWS uncertainties.

变转速工况下基于快速谱平均峭度图的列车轮对轴承故障诊断

由于受到轮轨激励的干扰,轮对轴承故障特征易被背景噪声所淹没,且在变转速模式下故障特征具有时变性,进一步加剧了提取难度。为此,提出一种基于快速谱平均峭度图的列车轮对轴承故障特征提取方法。根据频谱趋势将频谱划分为若干子带,采用Meyer小波构造带通滤波器,计算每个窄带滤波信号的平均峭度并构造快速谱平均峭度图;选取最优频带进行解调,消除背景噪声的影响;通过相位函数对滤波信号进行迭代广义解调,解决时变故障冲击间隔带来的频谱模糊问题。仿真和试验分析结果表明所提方法有效克服了强背景噪声和时变故障特征的干扰,为变转速工况下轮对轴承故障特征提取提供了新的解决策略。

塔影效应对平均风速和湍流强度影响的外场试验研究

风场的准确测量在风工程中意义重大。测风塔是最常用的风场观测平台,而塔影效应是测风精度评估中需主要考虑的因素。基于我国3个不同区域测风塔1年的外场数据,研究了塔影效应对平均风速、湍流强度的影响,通过塔影效应影响因子(Tower Distortion Factor,TDF)和离散因子(Scatter Factor,SCF)量化分析了塔影效应的平均值和离散度。结果表明:塔体对下游气流影响明显,塔影效应可使平均风速降低15.5%、湍流强度增大26.1%;塔体对上游气流的阻挡效应弱于塔影效应,可使平均风速降低2.2%、湍流强度增大0.4%。塔影效应与平均风速、湍流强度的关系为负相关,相关系数为–0.864,线性拟合的斜率为–0.443。塔影效应对湍流强度的影响更显著,是对平均风速影响的2.257倍。在平均值上,平均风速TDF、湍流强度TDF的分布范围分别为0.0141~0.0314、0.0214~0.0385,塔影效应对平均风速和平均湍流强度影响的贡献分别为34.6%、49.0%;在离散度上,平均风速SCF、湍流强度SCF的分布范围分别为0.0179~0.0240、0.0648~0.0845,塔影效应对平均风速和平均湍流强度影响的贡献分别为10.5%、10.8%。塔影效应对平均湍流强度的影响高于对平均风速的影响,对二者离散程度造成的影响接近。

我国城市轨道交通运营线路旅行速度和速度效率分析

为衡量城市轨道交通线路的旅行速度所发挥的效率,提出速度效率的概念。基于我国170条城市轨道交通线路的运营数据,涵盖全封闭运行的地铁、轻轨、单轨等系统,只考虑站站停的列车运行模式,从平均站间距和线路设计速度两个方面对旅行速度和速度效率进行分析,结果表明:大部分线路(约64%)设计速度为80 km/h,平均站间距为1.0~2.5 km,其中约90%的线路旅行速度为30~40 km/h,速度效率为37.5%~50.0%。此外,量化分析旅行速度和平均站间距、设计速度正相关的变化关系,以及速度效率与平均站间距正相关、与设计速度负相关的变化关系。最后,基于实际数据拟合的旅行速度和速度效率公式,计算得到平均站间距、设计速度、旅行速度和速度效率的对应分布值,可为衡量城市轨道交通线路旅行速度和速度效率的合理范围提供参考。

不同长径比下真空电弧自由燃弧特性的研究

该文研究不同触头开距(g)与直径(D)比值(g/D)条件下真空电弧的自由燃弧特性,以为进一步研究电弧控制方法提供理论支撑。实验选用直径为42 mm、材料为CuCr50合金的平板触头,采用触发引弧的方式,分别观察12 mm(g/D=0.286)、24 mm(g/D=0.571)、36 mm(g/D=0.857)触头开距,2.4至5.2 kA电流峰值(Ipeak)条件下的真空电弧。结果表明:不同长径比真空电弧阴极斑点扩散速度与阴极斑点平均承载电流接近,阴极斑点扩散速度与电流峰值的平方根成正比;小长径比(g/D=0.286)真空电弧在电流峰值较大时(Ipeak>4 kA)会依次出现扩散电弧模式、点状阳极斑点模式、阳极斑点模式;大长径比(g/D=0.571、0.857)真空电弧中大量阴极斑点在初始扩散阶段结束后长期维持在阴极触头侧面,未观察到稳定的阳极斑点。结果表明:大长径比与小长径比真空电弧在形态以及阳极现象上存在较大的差异,涉及大长径比真空电弧时需要考虑电弧对于触头侧面烧蚀的问题。

矿井巷道风速智能感知技术研究进展

矿井通风系统智能化是推进智能矿山建设、保障矿井安全生产的关键环节,通风参数作为基础数据来源,是矿井通风系统智能化建设的重要保障。而矿井巷道风速智能感知技术发展过程中存在传感器精度及可靠性优化、传感器测风误差修正、平均风速智能快速预测、传感器布设优化等关键科学技术问题有待改善。综述了传感器技术、高精度智能风速预测等研究成果,总结了各项技术的优劣及适用范围,提出了基于PSO−GRU神经网络构建的巷道断面平均风速智能预测模型,该模型能够有效提高矿井巷道平均风速测算的精度,可为通风参数智能感知技术的发展提供理论参考。

基于磁编码器和窄带解调的太阳轮故障检测

绝对式磁编码器具有价格低、安装方便等优势,适合于工程应用,但在低转速工况下其角度信号受测量误差的影响较大,需要对角度信号进行拟合以消除测量误差带来的干扰。传统的分段拟合方法在分段点处易出现不连续现象,角度信号的不连续导致由其计算的瞬时角速度(instantaneous angular speed,简称IAS)信号中出现虚假冲击,并对基于IAS信号的故障特征提取造成干扰。针对此问题,提出一种基于绝对式磁编码器IAS估计和窄带解调的太阳轮故障检测方法。首先,为保证IAS信号的连续性与平滑性,提出基于最小二乘拟合与5次Hermite插值的方法,实现了对IAS信号的拟合估计和平滑处理;其次,结合窄带解调技术实现了对行星齿轮减速器太阳轮故障特征的有效提取;最后,通过对正常与故障太阳轮的绝对式磁编码器信号分析对比,验证了所提方法的有效性。

平均降采样多周期微分均值的旋转部件故障特征增强方法

为解决编码器的瞬时角速度(Instantaneous Angular Speed,IAS)信号中旋转部件故障特征微弱的难题,本文提出一种平均降采样多周期微分均值(Average Down⁃Sampling Multi⁃period Differential Means,ADSMPDM)的故障特征增强方法。基于IAS信号的估计特性,开展了IAS信号的平均降采样研究,验证了平均降采样具有抑制随机噪声的特性;基于平均降采样抑制随机噪声特性、降低计算成本和减小存储空间的优势,结合多周期微分均值的累积特性,提出一种ADSMPDM算法对原始IAS信号中的旋转部件故障分量进行增强处理;通过阶次谱分析揭示故障特征。采用仿真数据和实验数据进行验证分析,并与快速谱峭度、可调整多点优化最小熵反卷积、离散随机分离和谱幅值调制算法进行对比,验证了ADSMPDM算法增强旋转部件故障特征的有效性和优势。

改进电机全速域无位置传感器转速控制系统研究

针对宽速电机的全速域应用场景,提出改进传统加权平均法,并利用改进后的中高速域滑模观测器法和低速域脉振高频注入法进行复合,实现精确的全速域无位置传感器控制。首先,针对滑模观测器法中符号函数导致的系统抖振,提出指数型复合函数用来替代原观测器中的符号函数;其次,针对脉振高频注入法中高频电流分量与注入信号的相位延迟,提出使用另一轴系高频电流替代注入信号;再次,针对加权平均法在过渡区域的权重分配不合理,提出新型指数型加权系数,同时为平稳过渡提出滞留缓冲带;最后,在MATLAB/Simulink仿真平台搭建基于滞留缓冲加权法的全速域转速控制系统,进行仿真验证。通过仿真结果,表明了改进后的全速域转速控制系统对转速误差和平稳过渡的优化效果。

基于自回归推广模型的海风预测方法分析

为准确预测海上风速和风向数据,提升船舶海上航行的安全性,针对现有海风预测方法存在的预测精度不高的问题,提出一种基于自回归(Auto-Regressive,AR)推广模型的海风预测方法。将风速和风向看作风矢量的2部分,在确定2组数据的依赖性之后,分别采用差分整合移动平均自回归(Auto-Regressive Integrated Moving Average,ARIMA)模型和向量自回归(Vector Auto-Regressive,VAR)模型这2种AR推广模型对风矢量进行预测。试验结果表明,VAR模型的预测结果中有34.17%的数据落在误差允许范围内,而ARIMA模型的预测结果中有61.25%的数据落在误差允许范围内,该方法可供海上风速和风向预测参考。

基于改进YOLOv5的镍板表面缺陷检测方法

针对镍板表面缺陷检测智能化程度低的问题,提出了一种基于改进YOLOv5的镍板表面缺陷检测方法。首先,对图像增强后的镍板数据集通过K-means++重新聚类锚框,提高锚框对本文数据集的适应度。其次,在主干网络Backbone中加入CBAM注意力机制,通过空间与通道信息融合来加强对感兴趣区域以及不清晰目标的特征识别。最后,在边界框回归时引入EIoU损失函数代替原CIoU损失函数,有效提高回归收敛速度,从而提高模型检测速度。实验结果表明,在自建的镍板缺陷数据集上,改进后的模型检测准确率高于Faster R-CNN、SSD、YOLOv3、YOLOv5等模型,其平均精度均值达81.4%,检测速度达61帧/s,模型在提高检测精度的同时也很好地满足了对检测速度的要求。

基于ARIMAX的风电功率预测研究

一次能源的波动特性给电网带来了许多麻烦,使得大量的风电、光伏都不能被充分利用,风电功率预测技术作为有效应对风电接入的关键技术之一,对指导系统调度运行、风电场生产安排具有十分重大的意义。基于ARIMAX建立了风电功率预测模型,并采用实测数据对模型有效性进行验证。研究结果表明,将风速作为外因变量,利用历史风电功率数据可以对未来短时风电功率进行较为准确的预测。

基于角域同步平均的高速列车车轮多边形检测方法

车轮多边形普遍存在于铁路车辆上,尤其是在高速情况下会对车辆和轨道产生强烈的周期性激励,影响车辆运行安全和乘客舒适性,因此研究车轮多边形的检测方法具有重要意义。采用轴箱垂向振动加速度信号作为检测数据,提出一种基于角域同步平均的高速列车车轮多边形检测方法。首先,结合一致相关系数,从滤波后的原始信号中提取相对稳定的短时时域信号。其次,将时域信号重采样到角域,再利用角域同步平均对角域信号进行去噪,得到特征向量。最后,根据特征向量计算反映车轮多边形状态的粗糙度水平和多边形阶次这两个参数,完成车轮多边形的准确估计。仿真分析和实例验证表明:该方法可以有效增强同步分量,去除速度因素以及轨道不平顺等偶然干扰因素的影响,完成高速列车车轮多边形的检测。