输电线路覆冰图像边缘提取方法研究

A new method of measuring the icing thickness of transmission lines on-line is proposed in this paper.In this method,the pictures of transmission lines which are photoed by the camera on the iron tower are processed immediately to extract the edges of the transmission line conductor and transmission line insulators.The icing thickness can be gained by comparing the edges of the iced transmission line and the uniced one.Two icing image edge extraction methods are described in detail,that is,a method based on the combination of the wavelet transform and the floating threshold method and a method based on the combination of the optimal threshold method and the mathematical morphology transform.The icing images from the artificial climatic chamber and transmission lines are used to test the methods above.The results show that the method based on the wavelet transform and the floating threshold method does well in the extraction of relatively smooth edges,such as glaze icing on conductor and icing on the insulator;meanwhile,the method based on the optimal threshold method and the mathematical morphology transform does well in the edge extraction of icing on the conductor,especially the opaque rime icing on the conductor with complicated edges.     

临近高压电气设备电缆局部放电脉冲的鉴别方法

On-line partial discharge(PD)diagnostics data are corrupted by various noise sources and this makes it more challenging to extract the PD signal contained in the raw data.Though the noise sources can be filtered out using signal processing techniques,PDs from neighboring cables and other high voltage equipment make the de-noising process more difficult due to the similar features of these signals with the PD signal of interest.Proposed in this paper is a double-ended partial discharge diagnostic system with dual sensors at each end which uses wireless time triggering using global time reference with the aid of global positioning system(GPS).Using the time of arrival method based on the velocity of propagation on the data,PD pulses originating from other sources can be discarded which reduces the volume of data to be stored and would eventually also reduce the hardware and software requirements of the denoising process thereby improving de-noising efficiency.System design,laboratory tests and on-site measurements are discussed.     

Improved Location Algorithm of VIRE Based on RFiD

Using linear interpolation method, VIRE algorithm simply treats the signal strength value and distance of the reference tag as a linear relationship, leading to the inaccuracy of signal strength value for virtual reference tags. The threshold in VIRE algorithm is a fixed value that needs repeatedly adjustment through experiments, which results in the complicated algorithm. To solve these problems, an improved algorithm is proposed in this paper, including nonlinear interpolation algorithm, dynamic threshold setting and tag self-correction of fuzzy map, which builds an indoor positioning system based on reference tags. The experimental results show that the improved algorithm can improve the position- ing accuracy and improve the stability of positioning results under bad environmental conditions with- out increasing the number of reference tags.     

交直流复合电压下电晕放电实验研究(英文)

Converter transformers are one of the most important electrical apparatuses in the ultra high voltage(UHV) DC transmission systems.The valve side and the low voltage(LV) bushing are stressed by long-term AC and DC composite voltage leading to significant partial discharge(PD) and posing great danger to the insulation system.In this paper AC and DC composite voltage is applied on a metal needle-plate model to produce PD signal sequences,and then the pulse waveshape and frequency spectrum are analyzed and compared with PD signals under conventional AC or DC voltage.In the end,the phase-resolved distribution is analyzed to depict the new characteristics of PD under this composite voltage.     

油纸绝缘电介质响应低频弥散的极化机理(英文)

Both the real part and imaginary part of complex permittivity approximately have a log-linear frequency dependency at low fre- quencies, especially at ultra-low frequencies under conditions of different moisture concentrations and temperatures, which is recognized as the low frequency dispersion (LFD). In order to explain this dispersion, a new mechanism of dielectric response of LFD of oil-paper insula- tion is proposed. A simplified one-dimensional mathematical model of concentration polarization carrier caused by slow migration is developed and solved, which indicates that ion mobility is closely related to the size of gap and the adsorption capacity of cellulose molecu- lar chains to ions. A stochastic statistical model of the carrier mobility induced LFD is also developed. Moreover, actual tests under 50 °C and 2% moisture content were put forward, as well as simulations with according current waveforms. The simulation results agreed well with the experimental data in that concentration polarization of carriers caused by slow migration is the probable cause of low frequency dispersion of dielectric response for oil-paper insulation diagnosis.     

Short Term Load Forecast Using Wavelet Neural Network

This paper presents a wavelet neural network (WNN) model combining wavelet transform and artificial neural networks for short term load forecast (STLF). Both historical load and temperature data having important impacts on load level were used in the proposed forecasting model. The model used the three-layer feed forward network trained by the error back-propagation algorithm. To enhance the forecasting accuracy by neural networks, wavelet multi-resolution analysis method was introduced to pre-process these data and reconstruct the predicted output. The proposed model has been evaluated with actual data of electricity load and temperature of Hunan Province. The simulation results show that the model is capable of providine a reasonable forecasting accuracy in STLF.     

Multimodal Medical Image Fusion Based on Parameter Adaptive PCNN and Latent Low-rank Representation

Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment planning. Aiming at the problem of insufficient protection of image contour and detail information by traditional image fusion methods, a new multimodal medical image fusion method is proposed. This method first uses non-subsampled shearlet transform to decompose the source image to obtain high and low frequency subband coefficients, then uses the latent low rank representation algorithm to fuse the low frequency subband coefficients, and applies the improved PAPCNN algorithm to fuse the high frequency subband coefficients. Finally, based on the automatic setting of parameters, the optimization method configuration of the time decay factor 𝛼𝑒 is carried out. The experimental results show that the proposed method solves the problems of difficult parameter setting and insufficient detail protection ability in traditional PCNN algorithm fusion images, and at the same time, it has achieved great improvement in visual quality and objective evaluation indicators.     

基于IEC 61850-9-2的智能合并单元关键技术研究(英文)

A realization scheme of merging unit(MU) for electronic current transformers(ECT) and electronic voltage transformers(EVT) based on single field-programmable gate array(FPGA) and IEC 61850-9-2 protocol is given in this paper.The MU is divided into three modules: sampling pulse synchronization module,sampled values processing module and data frames transmission module.A two-stage synchronization scheme is proposed to compensate the data latency.In the first stage,the phase angle of the sampled signal is shifted forward in a large range by employing the digital phase-shifter.In the second stage,a fine adjustment for the signal phase angle is carried out in a small range by using the dynamic second-order Lagrange interpolation algorithm.This scheme can achieve SMV packet’s highly accurate time synchronization in process bus.Tests about the basic bus data accuracy,performance of the temperature diversification and performance of the multi-channel signal in real-time communication show the testing is within the limits of the accuracy class 0.2 s in IEC 60044.The communication characteristics test proves the frame is fully comply with the format of IEC 61850-9-2.This series of tests demonstrate the utility and flexibility of the MU which can be applied in the digital substation based on IEC 61850.     

地电波方法在金属封闭式开关柜放电故障诊断中的应用(英文)

In order to solve the problems of TEV(transient earth voltage) utilization,such as single judgment criterion and low reliability of PD detection in HV switchboard,this paper discussed the method on how to make a better utilization of TEV in PD detection of metal-enclosed switchgears.Through discussing the relationship among the temporal phase,number of pulses and threshold of measuring and extracting the features corresponding to different typical defects,test results showed that the needle discharge distributed in 0°～90°and 200°～340°with low appearance probability above high measurement threshold;internal discharge distributed in 0°～90°and 270°～315°,and showed a similar decreasing trend under increasing of the threshold in the two regions;suspended discharge distributed in 0°～135°and 180°～315°where the PD in negative half periods decreased more seriously than those in positive half with increasing threshold.These results followed the doctrine of consistency with the conclusions that were obtained by using the traditional pulse current method.The possibility of using TEV method to make identification of PD defects has been proved to prepare for further research.     

遗传算法用于局部放电小波自适应阈值去噪

小波去噪用于局部放电信号在线监测具有良好的效果,阈值选取与局部放电去噪后信号的畸变具有紧密联系。为提高局部放电监测中小波去噪的自适应能力,并降低去噪信号的畸变率,提出一种小波自适应最优阈值去噪算法,用于变压器局部放电脉冲信号去噪。该方法采用小波对局部放电信号进行分解,在阈值选择时采用基于史坦无偏似然估计(SURE)的最优阈值自适应选择方法,并引入一种新的具有多阶导数的阈值函数,结合二进制遗传算法全局自适应搜索最优阈值,使最优阈值自适应寻优速度大大提高。对局部放电仿真信号和现场局部放电信号的去噪结果表明,该方法与Donoho阈值计算公式及标准软阈值法相比,能更好地去除局部放电信号中的白噪声,去噪信号失真度较小,具有良好的应用价值。     

粒子群优化小波自适应阈值法用于局部放电去噪

为了提高局部放电在线监测中小波去噪的自适应能力,并降低去噪信号的畸变率,提出了一种用于电力设备局部放电信号去噪的粒子群优化小波自适应阈值方法。该方法采用小波对局部放电信号进行分解,在阈值选择时采用基于SURE无偏估计的最优阈值自适应选择方法,结合粒子群优化算法进行全局自适应搜索最优阈值,使最优阈值自适应寻优速度大大提高。为了验证其去噪效果,还引入遗传算法对小波自适应阈值法进行优化计算。对局部放电仿真信号与实测局部放电信号的去噪结果表明,本文与标准软阈值法和遗传算法优化小波自适应阈值法相比,能更好地去除局部放电信号中的白噪声,计算速度更快,具有良好的去噪效果和应用价值。     

局部放电在线监测中小波阈值去噪法的最优阈值自适应选择

小波系数阈值是决定小波阈值去噪法处理后的去噪信号失真度及误差的关键因素。针对局部放电脉冲频谱特征,提出用于局部放电信号去噪的小波最优阈值选择方法,阐述了自适应阈值搜索中的尺度选择方案;采用四种人工模拟加噪信号和两种典型局部放电脉冲仿真信号对该方法的去噪效果进行了定量分析,并采用了自适应阈值法对实测局部放电信号进行了处理,结果表明,该方法在局部放电在线监测中具有良好的去噪效果和实用价值。     

用于提取PD信号的复小波簇消噪算法

因电气设备处在强烈电磁干扰环境中,常被噪声淹没,为了准确检测PD信号,需有效抑制其噪声干扰。根据PD信号和白噪干扰的复小波系数各有其特点和小波变换的本质是被分析信号和小波做内积运算,提出了从一簇复小波中逐层选择最优复小波并根据模极大值原理确定分解层数的方法即以阈值消噪法为基础的复小波簇消噪法。采用该方法对PD染噪信号进行去噪处理,并用去噪前后的信噪比(SNR)和波形相似性参数(NCC)对仿真PD信号的消噪结果进行评价。结果表明,复小波簇消噪法在满足SNR>10 dB的要求下,两个信号的NCC都>0.9,复小波簇消噪法从白噪干扰中提取PD信号的能力更强,在高SNR的情况下,信号的畸变也更小。     

一种基于复小波变换提取PD信号的分块自适应复阈值算法

基于复小波系数之间的相关性以及块阈值算法能充分利用周围小波系数的特点,创建一种用于复小波变换对PD信号的去噪的分块自适应复阈值算法,并与点自适应复阈值算法和分块自适应实阈值算法的去噪效果进行了对比.利用变化趋势参数(VTP)和波形相似性参数(NCC),并结合去噪前后的信噪比(SNR)对仿真PD信号的去噪效果进行综合评价.最后,将分块自适应复阈值技术用于对实验室实测的模拟GIS超高频PD信号的去噪.结果表明,采用分块自适应复阈值算法的复小波变换抑制白噪声效果更好,在保证高信噪比(SNR)或噪声抑制比(NRR)的情况下,对信号的畸变也更小.     

变压器局部放电监测逐层最优小波去噪算法

针对用于局部放电监测的去除白噪声算法会造成去噪脉冲信号波形畸变,脉冲幅值等波形参数产生较大误差,不利于进一步采用脉冲波形分析去除脉冲干扰的问题。为此根据局部放电信号在小波域上的分布特点,提出了各尺度信号分解和重构的最优小波选择方法,并给出了各尺度小波阈值的计算方法。仿真信号的最优小波去噪结果显示去噪信号具有波形畸变率低和幅值误差小的特点;实测信号的最优小波去噪结果证明提出的最优小波去噪算法能有效去除局部放电监测信号中的噪声,在局部放电在线监测应用中具有良好的去噪效果。     

改进阈值函数的小波熵方法抑制局部放电白噪声的研究

针对传统硬阈值法和软阈值法的缺陷,提出了改进阈值函数的小波熵方法。该方法对含噪局放信号进行小波分解,基于小波熵自适应选取阈值,并引入一种改进阈值函数对小波系数进行处理,最后重构得到去噪后信号。典型仿真信号和实测信号的去噪结果表明,提出的方法能够有效去除局放信号中的白噪声。     

基于粒子群优化的最佳阈值法在局部放电信号去噪中应用

抑制白噪声干扰是局部放电（ Partial Discharge,PD）在线检测中的关键技术。提出一种基于粒子群优化的最优阈值选取去噪方法。该方法采用小波对局部放电信号进行分解,在选取阈值时建立广义交叉验证准则,以广义交叉验证准则作为适应度值函数,并结合粒子群优化算法自适应地确定出各分解层的最佳阈值。该方法不依赖任何先验知识,实现局部放电信号自适应去噪。对局部放电仿真信号和实测局部放电信号的去噪结果表明：本文提出的方法与标准阈值法相比,能更好地去除局部放电信号中的白噪声。     

基于时域能量与自适应奇异值阈值的改进局放信号去噪方法

局部放电(简称局放)检测是探测电力电缆绝缘缺陷的有效手段。针对传统短时奇异值分解(STSVD)白噪声抑制方法存在的不足,文中提出了一种基于时域能量与自适应奇异值阈值的局放信号白噪声抑制方法。该方法利用自适应奇异值阈值估计策略对重构奇异值个数进行准确估计,并在此基础上结合时域能量准则仅对局放脉冲区域进行去噪处理,从而极大地提升了算法的执行效率。对仿真和实测含噪局放信号进行处理,并将去噪结果与现有的自适应奇异值分解(ASVD)、传统STSVD及小波变换去噪结果进行对比。研究结果表明：相比于ASVD、小波变换去噪方法,文中所提去噪方法能够取得更好的去噪效果,去噪后波形误差更小;相比于传统STSVD,文中所提方法能够有效解决去噪后存在的毛刺干扰问题,且计算速率更快。     

基于经验模式分解的电晕放电辐射信号阈值降噪处理方法

随着输电电压等级的提高,电晕放电已成为影响高压、特高压输电线路安全稳定运行的重要因素。鉴于此,提出了基于经验模式分解（empirical mode decomposition,EMD）的电晕放电辐射信号阈值降噪处理方法,首先利用EMD算法对采集到的电晕放电辐射信号做分解处理,得到不同的基本模态分量,然后利用阈值函数和给定阈值对各分量做降噪处理,并对处理后的分量重构,得到降噪后的信号。研究结果表明：与小波降噪和EMD时空降噪相比,基于EMD的阈值降噪方法不存在基函数选取和分解层数选取等问题,其降噪过程是完全由信号特征决定的自适应降噪,同时该方法保留了小波降噪中对各分量进行阈值处理来降噪的优点,并且在对信号的降噪过程中去除了可能存在于信号中的趋势项干扰,因而该方法更有利于对电晕放电辐射信号的降噪处理。