The high porosity and amorphous content of APS YAG coatings can negatively impact their overall performance. Therefore, a laser remelting treatment was performed on the APS YAG coatings to reduce their porosity and improve their crystallinity. SEM and EDS were used to detect the micromorphology and composition of the coatings, and XRD and TEM were employed to detect the phase composition of the coatings. The results show that laser remelting eliminated the layered structure of the APS YAG coatings and significantly reduced the porosity and surface roughness of the coatings, from 6.9 % to 3.2 % and Ra = 8.5 +/- 0.6 mu m to Ra = 3.1 +/- 0.2 mu m, respectively, while increasing the overall crystallinity of the coatings to over 95 %. Finally, owing to the action of the laser, the APS YAG coatings changed from a two-layer structure to a four-layer structure consisting of a mixed-color layer, white layer, black layer and gray layer, and formed new phases, such as Y2Ti2O7, Al2Ti7O15, TiN, Ti2O, Ti4O7 and Al2O3-Y2Ti2O7 eutectic structure, etc.

Thermoplastic polypropylene cables feature low energy consumption in production, high operating temperatures, recyclability, and excellent electrical and mechanical properties. However, limited research exists on copper’s influence on the aging of polypropylene insulation in medium- and high-voltage cables. To investigate copper’s impact on polypropylene (PP) cable insulation performance during aging, accelerated thermal aging tests were conducted on medium-voltage polypropylene cable segments. The effects of copper on the aggregated structure of polypropylene insulation during thermal-oxidative aging were studied using techniques such as infrared spectroscopy, ultraviolet spectroscopy, scanning electron microscopy, and differential scanning calorimetry. Frequency-domain dielectric spectroscopy and tensile property tests examined copper’s effect on polypropylene insulation performance during thermal-oxygen aging. Results indicate that the thermal-oxidative aging process primarily affects the amorphous rubbery state of polypropylene insulation. Rubbery state molecular chains aggregate unevenly and undergo chemical structural changes upon oxygen exposure. Macro-scale properties show increased low-frequency dielectric loss and reduced mechanical strength due to thermal-oxidative aging. Copper plays a role in catalytic oxidation reactions in the process of thermal oxygen aging, accelerates the change of polypropylene chemical structure, and accelerates the formation of polar groups such as carbonyl groups. It aggravates the movement of rubbery state molecular chains, aggravates the change of phase structure and phase interface, significantly reduces the mechanical toughness of polypropylene, and aggravates the deterioration of polypropylene cables.

绝缘子或套管处产生的沿面放电是导致开关柜、环网柜绝缘失效的常见诱因,而传统局部放电在线检测和诊断方法难以准确评估放电发展阶段和危害程度.该文采用单光子固态光电传感技术,对绝缘子沿面放电发展过程中的多光谱脉冲特性及其演化规律进行了试验研究,并提出一种基于多光谱脉冲演化特性的沿面放电严重程度诊断方法.首先,搭建多光谱光电同步检测平台,实现了沿面放电过程中多个光谱波段光信号和电流信号的同步采集;然后,根据全波段光脉冲幅值及其导数变化规律对沿面放电发展过程进行了三阶段划分,并分别对沿面放电三阶段多光谱脉冲的相位统计和非相位统计特征进行分析,明确了特征量随放电发展阶段的演化规律;最后,基于深度神经网络算法建立沿面放电多光谱严重程度评估模型,结果显示该模型诊断准确率达到 96.75%,验证了多光谱诊断方法的可靠性.

Partial discharge is an important reason for the failure of GIS equipment, and its detection can determine the type and position of the defect in GIS. In the discharge inspection, accurate positioning of defects can provide an important reference for maintenance. In response to this, this paper proposes a discharge optical location method based on multi-normal photoelectric array. Based on the SiPM sensor, a multi-normal array is designed and built into the coaxial structure of GIS equipment. Measuring the responses of each unit in the array to get the response ratio of each element and calculate the direction of the discharge light in space. This paper firstly introduces the array structure, and proposes a solution algorithm in space, which uses the proportional relationship of multi-normal elements to solve the discharge direction. Secondly, the feasibility and error source of this method are verified in the simulation software. Finally, the application effect of this method in actual power equipment is verified by actual measurement, and the results show that this method can accurately locate the partial discharge in GIS.

The accurate identification and hazard assessment can effectively realize condition-based maintenance and equipment life cycle economic management. For this purpose, a novel discharge identification approach based on multi-physical information fusion is proposed considering practical applications in equipped engineering sites. Three typical discharge defect models are placed within the a SF6 gas-filled test chamber, where the high frequency current transformer (HFCT), ultra-high frequency (UHF) and acoustic emission (AE) methods-based sensors are placed for discharge pulse monitoring. Furthermore, the non-phase information of discharge pulse for each measurement are extracted by the developed host computer software, where the fingerprint characteristics, namely maximum pulse amplitude (MPA) and cumulative pulse amplitude (CPA) are further extracted. Finally, the extracted multi-physical characteristics are aggregated into feature matrix. The identification results indicated that diagnosis accuracy of the proposed model achieves an average accuracy of 99.33%, which demonstrates that the multi-physical information fusion can resulting in better diagnosis performance.

环氧玻璃钢(glass fiber reinforced plastic,GFRP)由于其优异的力学性能及绝缘强度,通常用作超导电缆终端的绝缘材料.但是在生产中不可避免地出现的气隙缺陷大大降低了其在低温下的绝缘寿命与机械性能.该文研究GFRP在低温下的降解过程,并对其降解机理进行深入探讨.通过比较不同温度下GFRP局部放电行为,可以发现低温下GFRP的局部放电受到抑制;同时,实验结果表明,低温下GFRP的劣化是空间电荷积聚以及力学性能下降共同作用的结果,化学腐蚀以及放电能量的释放对材料劣化影响较小.低温下局部放电带来的局部热积聚增加了材料内部的机械应力,同时空间电荷积聚导致了能量的瞬间释放,在材料力学性能下降的基础上,两者共同作用下材料裂纹快速扩展,加速了材料劣化.

气体绝缘开关设备内部的金属微粒在强电场作用下容易引起局部放电,威胁设备绝缘安全.为研究微粒放电的光学信号特征和光学诊断方法,该文搭建气体绝缘金属微粒放电光–电模拟实验系统,采用局部放电多光谱传感器对微粒引发的多光谱脉冲信号进行实验测量和统计分析.研究不同电压和数量下的粒形与线形微粒的放电多光谱相位图谱以及时序波形特征,并进一步获得多光谱脉冲信号统计演化规律和三元分布特征.结果表明,两类微粒放电在可见波段、紫外波段和红外波段的幅值大小关系保持一致,放电图谱均呈"双峰状"分布;多光谱脉冲强度与外施电压和微粒数量呈正相关,其中线形微粒光辐射强度大于粒形微粒,两者在多光谱三元空间中的统计分布和演化路径表现出明显差异.因此,利用多光谱演化路径和三元图谱分布可望实现微粒放电绝缘的危险性评价和粒形辨识.

对电力设备和线路外绝缘异常电晕放电的有效检测,是故障预防和运行维护的重要手段.日盲紫外成像是目前外绝缘电晕检测的常用手段,然而其检测仪器成本高、体积重量大、机载性能差,使得其难以在机载平台上大规模应用.该文提出一种基于朗伯散射原理的电晕放电溯源方法.首先,对光电传感器的辐照角响应特性进行分析,然后提出基于朗伯散射体原理和三维辐照平面的电晕放电溯源方法,并给出开放空间中放电源定向解析方法.为了验证该方法的可行性并对定位误差来源进行分析,该文设计具有多法向结构的三维光电传感阵列,通过光路仿真对其定位效果进行综合分析,结果显示定向平均误差角为3.7°.最后,依据仿真研制电晕定位装置样机,对其关键参数和定位性能进行实测,结果表明多组放电位置下的定位平均误差为4.59°,最大误差小于7°,定位距离偏差在0.4m以内,验证了基于朗伯散射原理的放电溯源方法的有效性.

In this article, a hypersensitive multispectral partial discharge (PD) optical sensor array was developed, by which the optical pulses in seven independent bands can be acquired simultaneously. By using this sensor array, the multispectral pulses for three typical PDs in gas insulated system were obtained experimentally and analyzed with phase-based (phase-resolved) and nonphase-based (spectral-ratio-based) multispectral characteristics, respectively. It indicates that the multispectral characteristics produced by a specific discharge defect provide unique spectral signatures in discharge mode as well as stage evolution. Based on the intrinsic relationship between the discharge feature and optical emission spectrum, we adopted the classification algorithms and spectral-ratio-reserved multispectral characteristics to implement pattern recognition as well as assessment on the three typical PDs, which obtained the hit ratios exceeding 91%. In principle, such detection approach also supports the phase-independent PD diagnosis especially for dc power equipment.

灵敏的信号感知和准确的故障诊断是局部放电光测法应用的关键,该文首先以单光子级固态光电器件为基础,研制多个独立光谱通道的微型传感装置,然后基于该装置对SF6中的典型局部放电进行多光谱同步测量,对光脉冲波形、序列、相基统计图谱等多方面进行分析,并提出基于三元图的多光谱数据分析方法,论证多光谱局部放电光学诊断技术的优势,提出该装置在GIS中可能的融合方法.结果表明,微型多光谱传感器能够有效探测不同波段下的局部放电光脉冲;多光谱脉冲的强度和比例与局部放电类型具有强相关性,并在统计图谱和三元图谱上表现出较明显的统计规律.相比传统局部放电诊断方法,多光谱检测能够提供更高维度的放电信息,为缺陷识别和危险性评估提供更丰富、更准确的判别依据,并且基本不受放电位置的影响.

机电故障是真空断路器开断异常、拒动或误动的主要原因,准确有效地掌握真空断路器机电状态对保障电网安全至关重要.该文以合闸线圈电流和行程信号为主要在线监测量,通过故障模拟试验,系统地分析了监测量在不同故障类型及严重程度下特征量的演变规律,提出一种基于三元图谱的实用化故障诊断模型.借助主成分分析(principal component analysis,PCA)方法,提取出具有正交贡献的三类主成分特征,并以此构建三元特征图谱,直观展示了不同故障下曲线的演变路径;在此基础上,采用局部加权回归给出故障边界方程,实现了故障的类型识别;最后,通过k-means聚类中心和欧式距离计算,提出了故障发展程度量化分析方法.试验结果表明,对于同型号设备,该方法在缺失刚分、刚合点的条件下,判断准确率达到97％以上,为真空断路器的在线诊断和故障预警提供了一种更为高效、直观和实用化的方法.