Spatial and Temporal Distribution of Different Grades of Short-time Precipitation in Xining City

Based on the hourly precipitation data from 4 observation stations of Xining City from June to September during 2005-2011,the temporal and spatial distribution characteristics of short-time precipitation were analyzed.The results show that the precipitation distribution in Xining region exhibited the less-more-less trend from southwest to northeast,while the torrential rain gradually increased from the northwest and southwest to the middle.The hourly general precipitation in Xining region had obviously seasonal characteristics,and its annual distribution showed wavy changes,but the annual variation of short-time heavy precipitation and rainstorm was very obvious.Furthermore,short-time heavy precipitation was concentrated from 18:00 to 24:00,followed by 03:00-07:00 on the following day.The occurrence time of short-time rainstorm accorded with short-time heavy precipitation.It offers a useful reference for the accurate and timely short-term forecast.

Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network

With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.

Microstructural evolution in Al–Zn–Mg–Cu–Sc–Zr alloys during short-time homogenization

Abstract： Microstructural evolution in a new kind of aluminum （A1） alloy with the chemical composition of AI-8.82Zn-2.08Mg- 0.80Cu-3.31Sc-0.3Zr was investigated. It is found that the secondary phase MgZn2 is completely dissolved into the matrix during a short homogenization treatment （470℃, 1 h）, while the primary phase A13（Sc,Zr） remains stable. This is due to Sc and Zr additions into the A1 al- loy, high Zn/Mg mass ratio, and low Cu content. The experimental findings fit well with the results calculated by the homogenization diffusion kinetics equation. The alloy shows an excellent mechanical performance after the short homogenization process followed by hot-extrusion and T6 treatment. Consequently, a good combination of low energy consumotion and favorable mechanical properties is obtained.

Characteristics of Radar Echo Parameters and Microphysical Structure Simulation of a Short-Time Heavy Precipitation Supercell

By using the conventional observations, radar data, NCEP/NCAR FNL 1°×1° reanalysis data and numerical simulation data and with the construction and calculation of radar echo parameters, this paper presents the structural characteristics and physical processes of a short-time heavy precipitation supercell that occurred in the squall line process in Shanxi Province on 24 June 2020. The results show that this squall line event occurred in front of a surface cold front,combined with infiltration of low-level cold air and continuous increase of near-surface humidity in the afternoon. The surface mesoscale convergence line and mesoscale dew point front contributed to the development and systemization of the squall line by a large degree. The short-time extremely heavy precipitation in Pingshun County was caused by the development of a supercell from thunderstorm cells on the front side of the squall line. The characteristics of sharp increase in vertical integral liquid water content, persistent increase in reflectivity factor and continuous rise in the echo top height appeared about 23 min earlier than the severe precipitation, which has qualitative indicating significance for the nowcasting of short-time heavy precipitation. A quantitative analysis of the radar echo parameters suggests that the“sudden drop”of FV40was a precursor signal of cells’ coalescence and rapid development to the mature stage. The areal change of the echo core at the 6 km height was highly subject to the merging and developing of cells, the rapid change of hydrometeor particles in clouds and the precipitation intensity. Changes in the cross-sectional area of convective cells at different heights can indirectly reflect the changes of liquid particles and ice particles in clouds, which is indicatively meaningful for predicting the coalescing and developing-to-maturing of cells and heavy precipitation 30-45 min earlier.A comprehensive echo parameter prediction model constructed by the random forest principle can predict the magnitude of short-time heavy precipitation 40-50 min in advance. Numerical simulation reveals that large amounts of water vapor existed in the near-surface atmosphere, and that the cells rapidly obtained moisture from the ambient atmosphere and developed rapidly through maternal feeding. The cold cloud zone was narrow, upright and had a high stretch height. The upward motion in clouds was strong and deep, and very rich in liquid water content. The graupel particles had a large vertical distribution range, the coexistence area of graupel and snow was large, the height of raindrops was close to the surface with a wide horizontal scale, and the precipitation efficiency was high. These may be the important elements responsible for the occurrence of the short-time heavy precipitation that exceeded historical extreme values. On the basis of the above analyses, a comprehensive parameter(CP) prediction model is worked out, which can estimate the developing trend of supercells and the intensity of short-time heavy precipitation about 1 h in advance.

Adaptive Short-Time Fractional Fourier Transform Based on Minimum Information Entropy

Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order to overcome the shortcomings,the STFrFT method with adaptive window function is proposed.In this method,the window function of STFrFT is ad-aptively adjusted by establishing a library containing multiple window functions and taking the minimum information entropy as the criterion,so as to obtain a time-frequency distribution that better matches the desired signal.This method takes into account the time-frequency resolution characteristics of STFrFT and the excellent characteristics of adaptive adjustment to window func-tion,improves the time-frequency aggregation on the basis of eliminating cross term interference,and provides a new tool for improving the time-frequency analysis ability of complex modulated sig-nals.

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20 - 30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23 - 24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16 - 18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

Short-Time Dynamics of the Random n-Vector Model

Short-time critical behavior of the random n-vector model is studied by the theoretic renormalization-group approach.Asymptotic scaling laws are studied in a frame of the expansion in e = 4 - d for n ≠ 1 and for n = 1respectively.In d ＜ 4,the initial slip exponents θ′ for the order parameter and θ for the response function are calculated up to the second order in e ＝ 4 - d for n ≠ 1 and for n ＝ 1 at the random fixed point respectively.Our results show that the random impurities exert a strong influence on the short-time dynamics for d ＜ 4 and n ＜ nc.

Application of short-time Fourier transform to high-rise frame structural-health monitoring based on change of inherent frequency over time

The high-rise frame structure has become more and more widespread, like its damage from the complication of the environment. The traditional method of damage detection, which is only suitable for the stationary signal, does not apply to a high-rise frame structure because its damage signal is non-stationary. Thus, this paper presents an application of the short-time Fourier transform(STFT) to damage detection of high-rise frame structures. Compared with the fast Fourier transform, STFT is found to be able to express the frequency spectrum property of the time interval using the signal within this interval. Application of STFT to analyzing a Matlab model and the shaking table test with a twelve-story frame-structure model reveals that there is a positive correlation between the slope of the frequency versus time and the damage level. If the slope is equal to or greater than zero, the structure is not damaged. If the slope is smaller than zero, the structure is damaged, and the less the slope is, the more serious the damage is. The damage results from calculation based on the Matlab model are consistent with those from the shaking table test, demonstrating that STFT can be a reliable tool for the damage detection of high-rise frame structures.

Comparative Analysis of Two Short-time Strong Precipitation Processes

By means of conceptual model prediction, two short-time strong precipitation processes in Xiamen on June 12th and 14th, 2008 were analyzed from the aspects of real precipitation, weather situation, physical parameter and radar echo. The results showed that two short-time strong precipitation processes had complete different weather backgrounds, so physical quantities which could reflect atmospheric thermal and dynamic characteristic were different, as well as the characteristic and evolution process of radar echo, and it revealed that two short-time strong precipitation processes in Xiamen had various formation mechanisms and evolution processes. Therefore, many data should be combined to grasp different vantage points in precipitation forecast.

Comparative Analysis of Climate Characteristics of Extremely Short-Time Severe Precipitation in Guizhou Based on Two Types of Rainfall Data

In order to fill the gaps of the research on the data of automatic weather stations(referred to as automatic stations)not used for the climate characteristics of extremely short-time severe precipitation in Guizhou Province,the climate characteristics of extremely short-time severe precipitation in Guizhou Province were compared and analyzed based on the hourly precipitation data of the automatic stations and the national weather stations(referred to as the national stations)from April to September during 2010-2019.The results show that the average state of maximum hourly precipitation of all stations(the automatic stations and the national stations)and national stations both are representative,but the data of all stations are more representative when the maximum hourly precipitation is extreme.The 99.5 th quantile is the most reasonable threshold of extremely short-time severe precipitation in each station.The spatial distribution of extremely short-time severe precipitation intensity in all stations and national stations is generally that the southern region is stronger than the northern region,and the intensity values are concentrated in the range of 40-50 mm/h.All stations data can better reflect the distribution characteristics of<40 and≥50 mm/h.The national stations data underestimates the precipitation intensity in the southern and northeastern marginal areas of Guizhou,and slightly exaggerates the precipitation intensity in the northern part of Guizhou.The monthly and diurnal variations of the frequency of extremely short-time severe precipitation in all stations and national stations are very obvious and the variation trend is the same,but the intensity of extremely short-time severe precipitation has no obvious monthly variation characteristics.There is no significant diurnal variation in the intensity of extremely short-time severe precipitation in all stations,but the diurnal variation in the data of national stations is significant.Since the frequency of extremely short-time severe precipitation in national stations is less,the diurnal variation in the intensity of extremely short-time severe precipitation in all stations is more statistically significant.

不同充电条件下三元锂电池过充热失控研究

为了研究充电倍率以及充电倍率的调整方式对过充条件下三元锂电池热失控的影响,分别以0.5C、1.0C、1.5C充电倍率将锂电池过充至热失控。此外,以0.5C充至电池表面温度不再上升时,分别以0.5C和0.07C的幅度逐步调高充电倍率,直至发生热失控。结果表明:以0.5C过充时,在短时间内不会发生热失控;以1.0C和1.5C过充时,均会发生热失控,且1.5C下热失控所需时间更短,热失控的危害更大。相比于采用0.5C幅度提高充电倍率的调节方式,采用0.07C幅度的调节方式会显著提高临界充电倍率,从而降低热失控的风险;以0.07C逐步提高充电倍率的过程中存在一个拐点倍率,当充电倍率小于此拐点倍率时,充电倍率与其对应的峰值温度呈线性关系,而当充电倍率大于拐点倍率后,继续提高充电倍率会导致热失控;先以0.5C过充,而后提高充电倍率导致热失控,其热失控危害远低于1.0C和1.5C过充的危害。因此,应当在符合实际需求的前提下采取较低的充电倍率。如需增加充电倍率,采取缓慢增加的方式有助于降低电池发生热失控的风险。

储能锂离子电池高温诱发热失控特性研究

储能系统是新型电力系统的重要支撑,锂离子电池储能是当前主流发展方向之一。电池安全性是制约锂电储能系统的重要技术瓶颈。本文研究了锂离子电池高温诱发热失控的电热响应特性,设计了在自然对流换热情况下的逐级升温实验,基于谢苗诺夫理论对电池不同阶梯温度点的失效规律进行了分析,结合电池内部副反应探究了各温度区间的电压变化、电压平均下降率以及自生热特性。研究表明电池在140~160℃区间爆发热失控、最高温度达到464.6℃,热失控过程中的破裂漏气现象对最高温度有着显著影响;当电池荷电状态降低为50%时,电池可由热失控转为功能性失效。研究结论为进一步的安全管理与热失控抑制研究提供了基础。

基于混沌搜索的组合输变电设备过热检测仿真

输变电设备组经常处于发热状态会严重影响其生命周期,针对组合输变电设备发热检测准确性低下的问题,提出一种基于Tent混沌映射与种群演化相结合的参数优化算法,在SVM的基础上构建出MPTTE目标检测模型与CPTTE过热检测模型。首先通过图像灰度化、插值化与均值化处理,降低环境温度噪声与环境背景噪声;接着采用R-CNN算法对MPTTE类进行初识别,同时通过构建能量函数提取目标热特征,并将MPTTE数据集划分成训练集与测试集;然后利用Tent混沌映射算法提高种群演化算法后续参数寻优能力,对SVM的gamma和C参数进行最优解探寻,构建出SVM-MPTTE目标检测模型;最后采用Pearson相关系数分析与均值漂移聚类算法对MPTTE过热目标进行定位,构建出CPTTE过热检测模型。消融仿真结果表明,采用不同优化算法叠加后,MPTTE目标检测模型与CPTTE过热检测模型均产生了正向优化效果。对比仿真结果表明,所提构建的模型较其它三类基线算法相比,模型的综合性能提升了1.03%,且具有最高的精确性。本文提出的算法在设备发热检测上具有较高的精确度与稳定度。

Localization method of subsynchronous oscillation source based on high-resolution time-frequency distribution image and CNN

The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.

管坯用圆钢12Cr1MoVG表面长裂纹原因分析及改进措施

按照GB/T 31212—2014标准对12Cr1MoVG管坯用圆钢进行了表面漏磁探伤,结果表明,深度>0.30 mm的长裂纹比例占15%左右,分析发现造成管坯用圆钢表面长裂纹的主要原因是铸坯角部裂纹。通过采取将中包钢水过热度由15~30℃提高到35~45℃,铸坯拉速由0.85 m/min提高到0.95 m/min,铸坯采取弱冷和均匀冷却等措施来解决了该问题。12Cr1MoVG管坯用圆钢长裂纹比例降到了3%以下。

基于多维监测数据的环网柜过热故障预测研究

随着配电网现代化的发展,作为其核心设备,环网柜过热故障的准确预测对保障供电系统的稳定运行至关重要。因此,提出一种基于多维监测数据的环网柜过热故障预测方法,旨在提升故障预警的准确性和及时性。通过引入温升、温差和相对温差等判别指标,结合深度学习技术,特别是基于长短期记忆(LSTM)网络的温度预测模型,克服了传统基于温度阈值的诊断方法的局限性。采用MATLAB平台进行模型仿真,所建模型融合历史温度、电流和环境温度等相关数据维度,提高了预测的精确度与稳定性。结果表明,与传统的BP神经网络相比,LSTM网络在环网柜过热故障趋势预测上具有更小的误差和更强的适应能力,提高了故障预测的准确性,为电网故障诊断和维护工作提供了科学依据,进一步保障了供电系统的可靠性。

车轮踏面温度实时监测系统

介绍了一种铁路工程车辆行车安全辅助系统——车轮踏面温度实时监测系统,并详细介绍了系统组成、工作原理及安装方式。该系统可实时监测车轮踏面温度,实现特定温度阈值报警等功能,且具有安装方便、成本低等特点,经过实车验证,系统可靠,适用于大多数铁路运行车辆。

基于改进支持向量机的配电电力变压器内部过热故障识别方法

为降低配电电力变压器内部过热故障识别误差较大的问题,提出基于改进支持向量机的配电电力变压器内部过热故障识别方法。该方法针对变压器内部过热故障展开分析,并基于分析结果,进行特征量的选择和归一化处理,以消除气体体积分值存在的差异,为确保后续识别结果的准确性奠定基础。然后通过跨子群交流策略和最优群体自变异策略改进蛙跳算法。最终基于改进后的混合蛙跳算法来进行实现支持向量机的改进,完成配电电力变压器内部过热故障识别。测试结果表示,采用所提方法进行配电电力变压器内部过热故障识别,其识别确率始终在95%以上,具有较强的应用性。

过充、过热及其共同作用下车用三元锂离子电池热失控特性

锂离子电池作为目前电动汽车的主要能源电池,其在外界滥用条件下的热失控问题受到广泛关注,研究不同滥用下尤其是多种滥用共同作用下的电池热失控特性可有效提高电池使用安全性。本工作以车用50 Ah方型动力三元锂离子电池单体作为研究对象,利用大功率充放电循环仪和电加热装置,进行了1 C倍率过充、150 W局部过热及其共同作用下的电池热失控实验。对不同工况下热失控实验现象、质量损失、温度变化、升温速率变化、升温部位和电压变化等实验结果进行对比分析,结果表明:过充过热共同作用下电池热失控具有更大危险性,电池热失控时间比单一滥用减少约35%,热失控时电池SOC比过充减小约35%,电池电压会出现“持续上升—突降至零”现象。本研究可为车用三元锂离子电池热管理系统安全设计提供参考。

氩气中长丝电爆炸沉积能量特性与演化过程分析

为研究氩气中长丝电爆炸沉积能量特性与空间形态演化过程,设计并搭建了铝丝电爆炸实验系统与光-电联合诊断平台。结果表明,丝长增加使电爆炸过程由直接击穿模式转变为电流暂停模式,电流暂停阶段磁压力消失是导致过热系数随丝长增加而减小的根本原因。丝长增加将导致残留丝核、弥散蒸汽层等径向不均匀现象以及分层结构等轴向不均匀现象的出现。提出了长丝电爆炸沉积能量提升措施与空间形态均匀性调控方法:增加充电电压可改善电爆炸模式、提升过热系数,是消除残留丝核的有效措施;增加气压可有效改善空间形态均匀性。研究结果对电爆炸法高效制备纳米粉体具有重要工程价值,对深入理解电爆炸物理机制具有重要学术意义。