储能科学与技术 ›› 2025, Vol. 14 ›› Issue (4): 1654-1656.doi: 10.19799/j.cnki.2095-4239.2025.0327

• 储能测试与评价 • 上一篇    下一篇

储能技术在电动机负载波动下的故障预测精度提升策略

宋文乐(), 王磊, 张烨, 倪伟强   

  1. 国网河北省电力有限公司沧州供电分公司,河北 沧州 061001
  • 收稿日期:2025-04-02 修回日期:2025-04-17 出版日期:2025-04-28 发布日期:2025-05-20
  • 通讯作者: 宋文乐 E-mail:songwenle2024@163.com
  • 作者简介:宋文乐(1987—),男,硕士,高级工程师,主要研究方向为新能源并网技术、逆变器变换控制技术和电能质量等,E-mail:songwenle2024@163.com
  • 基金资助:
    国网河北省电力有限公司科技项目(kj2022-007)

Strategies for improving fault prediction accuracy of energy storage technology under motor load fluctuations

Wenle SONG(), Lei WANG, Ye ZHANG, Weiqiang NI   

  1. State grid cangzhou electric supply company, Cangzhou 061001, Hebei, China
  • Received:2025-04-02 Revised:2025-04-17 Online:2025-04-28 Published:2025-05-20
  • Contact: Wenle SONG E-mail:songwenle2024@163.com

摘要:

电动机作为现代工业中不可或缺的驱动设备,其稳定运行对于生产效率和安全性至关重要。然而,电动机在运行过程中常常受到负载波动的影响,这可能导致设备故障和性能下降。为了提升电动机故障预测的精度,本文探讨了储能技术在电动机负载波动下的应用策略。通过收集和分析电动机的运行数据,结合储能技术的特性,提出了一系列故障预测模型和优化方法,旨在实现电动机故障的早期预警和精准预测。

关键词: 电动机, 负载波动, 故障预测

Abstract:

As an indispensable driving equipment in modern industry, the stable operation of electric motors is crucial for production efficiency and safety. However, electric motors are often affected by load fluctuations during operation, which may lead to equipment failures and performance degradation. In order to improve the accuracy of motor fault prediction, this article will explore the application strategy of energy storage technology under motor load fluctuations. By collecting and analyzing operational data of electric motors, combined with the characteristics of energy storage technology, a series of fault prediction models and optimization methods have been proposed, aiming to achieve early warning and accurate prediction of electric motor faults.

Key words: electric motor, load fluctuation, fault prediction

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