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.

Differentially Expressed Proteome of Microcystis under Short-time Ultrasonic Stress

This study was conducted to explore the regulation mechanism for key protein expression. The Microcystis treated by short-time ultrasonic wave was select-ed to analyze the total protein based on 2-DE. The results showed that there were 71 up-regulated protein spots, 56 down-regulated protein spots, 54 new protein spots and 21 protein spots disappeared under short-time ultrasonic stress. Eight dif-ferential proteins were chosen for further MALDI-TOFTOF/MS analysis, and the re-sults showed that 2 unknown proteins and 6 functional proteins were detected. These proteins were relevant to some physiological processes, such as antioxidation and anti-inflammatory process, phosphate synthesis and electron transfer, which is beneficial to the metabolic balance and self-protection under short-time ultrasonic stress.

Analysis of superheater's pipe wall overtemperature by fault tree diagnose

After research on a 2000t/h subcritical forced-circulation balanced ventilation were applied boiler and the structure and operation of its auxiliary system builds up this heat transfer model of a superheater's pipe wall and analyze the effect of primary factors on the overtemperature of the pipe wall. Fault tree structure was used to uncover the multiplayer logic between the overtemperature of the superheater's pipe wall and the faults.

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.

An HHT-based method to eliminate short-time strong disturbance from measured signals of bridge

According to the characteristic that Hilbert-Huang transform （HHT） can detect abnormity in signals, an HHT-based method to eliminate short-time strong disturbance was proposed. The signal with short-time strong disturbance was decomposed into a series of intrinsic mode functions （IMFs） and a residue by the empirical mode decomposition （EMD）. The instantaneous amplitudes and frequencies of each IMF were calculated. And at abnormal section, instantaneous amplitudes and frequencies were fired according to the data at normal section, replacing the fitted data for the original ones. A new set of IMFs was reconstructed by using the processed instantaneous amplitudes and frequencies. For the residue, abnormal fluctuations could be directly eliminated. And a new signal with the short-time strong disturbance eliminated was reconstructed by superposing all the new IMFs and the residue, The numerical simulation shows that there is a good correlation between the reconstructed signal and the undisturbed signal, The correlation coefficient is equal to 0.999 1. The processing results of the measured strain signal of a bridge with short-time strong disturbance verify the practicability of the method.

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.

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 Decoherence of Solid-State Qubit at Optimal Operation Points

We investigate the short-time decoherence of a solid-state qubit under Ohmic noise at optimal operation points. The decoherence is analyzed by maximum norm of the deviation density operator. It is shown that at the temperature T = 3 mK, the loss of the fidelity due to decoherence is much smaller than the DiVincenzo low decoherence criterion, which means that the mode/may be an optimal candidate of qubit for quantum computation.

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.

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.

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 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.

超临界W型火焰锅炉结构效应导致前墙水冷壁温差偏大问题的研究与治理

为解决某锅炉前墙水冷壁温差偏大导致水冷壁频繁超温爆管的问题,从管外传热和管内吸热两方面对热偏差进行分析,发现采用内螺纹管技术的水冷壁管具有自补偿特性,通过数值模拟试验发现结构效应带来温度场和气流场的变化对热偏差影响显著,是造成水冷壁变形和泄漏的主要原因,进而提出二次风差异配风、水冷壁前墙喷涂绝热涂料和优化卫燃带等治理方案,成功治理了水冷壁超温爆管问题.

过温淬火+低温回火20Cr13锻造剥皮齿的热处理工艺研究

以20Cr13不锈钢锻造的剥皮齿为研究对象,对比传统热处理工艺,提出了一种过温淬火和低温回火的热处理工艺方法。结果表明,在盐浴炉里进行热处理试验,得到的剥皮齿硬度值范围为48.0~49.5 HRC,比淬火加热到1000℃的同等条件,剥皮齿硬度值提高了5.3%。金相组织为低温回火马氏体和残余奥氏体,满足剥皮齿47~51 HRC的安全硬度值要求。后经不同设备网带炉验证,得到的剥皮齿硬度值范围为47.5~51.0 HRC,金相组织同为低温回火马氏体和残余奥氏体。经实际工作环境验证,所提出的工艺加工的剥皮齿满足安全工作的硬度要求。

阻性回路温升特性与超温故障特征信号分析

阻性回路长时超温故障特征信号的有效识别与分析,是表征电气火灾的关键性技术手段之一。通过三相四线制低压AC 220 V配电端纯阻性负载温升实验,制造了阻性回路的故障温升过程,高频多点采集了线路超温故障形成过程中的温度、电流、电压信号,探究了不同电流强度下的阻性回路温度变化时空分布,分析了超温故障状态下温度与电压本征信号、电压谐波信号的关系。通过回路电位分析发现了超温故障状态下回路压降与温度的线性关系,通过傅里叶分析总结出了阻性回路超温故障的电压频谱特征。实验结果分析表明,阻性回路温升过程伴随着显著的温度时空分布信号特征、压降信号特征和电压谐波信号特征,具备对超温故障的表征能力,可以为电气火灾的预防提供一种新的技术手段。

有源医疗器械超温试验检测研究

本文参照GB 9706.1—2020《医用电气设备第1部分:基本安全和基本性能的通用要求》和GB 4793.1—2007《测量、控制和实验室用电气设备的安全要求第1部分:通用要求》,结合超温试验自身特点,对标准条款进行了梳理,总结出有源医疗器械超温试验的检测重点,以供相关人员参考。

SRMD:Sparse Random Mode Decomposition

Signal decomposition and multiscale signal analysis provide many useful tools for timefrequency analysis.We proposed a random feature method for analyzing time-series data by constructing a sparse approximation to the spectrogram.The randomization is both in the time window locations and the frequency sampling,which lowers the overall sampling and computational cost.The sparsification of the spectrogram leads to a sharp separation between time-frequency clusters which makes it easier to identify intrinsic modes,and thus leads to a new data-driven mode decomposition.The applications include signal representation,outlier removal,and mode decomposition.On benchmark tests,we show that our approach outperforms other state-of-the-art decomposition methods.

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.