变压器机组机械状态诊断的实验设计和数据分析及优化

IF 2.4 Q2 ENGINEERING, MECHANICAL
Bingshuang Chang, Jian Xin, Miaomiao Fu, Vishal Jagota, Mukesh Soni, Samrat Ray
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引用次数: 0

摘要

典型的电力变压器诊断方法精度不高、不稳定。提出了一种支持向量机分类算法,通过设计一种能够提高能量变压器诊断精度和速度的算法程序,采用小波包能谱信号处理方法提取了不同状态下的表面扭转振动信号,验证了振动仿真模型与实测数据的曲线相似度大于0.98,证明了仿真模型的有效性。从等效变压器模型出发,发展了在线短路电感的计算技术,仿真结果与实际变压器特性相比变化误差小于0.05%。所提出的状态诊断技术成功地弥补了电抗法无法检测和判断绕组轻微松动或故障的缺点。验证了该方法的准确性和优越性,以及该状态诊断系统的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental design and data analysis and optimization of mechanical condition diagnosis for transformer sets
Abstract The typical power transformer diagnosis approach is imprecise and unstable. A support vector machine classification algorithm is proposed, by designing an algorithm program that can improve the accuracy and speed of energy transformer diagnosis, the vibration signals of the surface twisting in different states are extracted by wavelet packet energy spectrum signal processing method, it is verified that the curve similarity between the vibration simulation model and the measured data is greater than 0.98, proving the simulation model’s validity. The calculation technique of online short circuit inductance is developed from the equivalent transformer model, and the variation error of simulation results is less than 0.05% when compared to the real transformer characteristics. The suggested state diagnostic technique successfully compensates for the drawbacks of the reactance method, which is incapable of detecting and judging the slightly loose or faulty winding. The method’s accuracy and superiority, as well as the practicability of the state diagnosis system, are demonstrated.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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