Abstract Details
  1. Home
  2. Abstract List
  3. Abstract Details
256 / 2021-11-07 16:31:27
Motor Bearing Fault Diagnosis Method Based on Wavelet Decomposition and SSA-BP
Sparrow search algorithm; Neural network; Fault diagnosis; Genetic algorithm; Particle swarm optimizationey
AI-driven technology > Intelligent Anomaly Detection, Fault Diagnosis and Prognostics
Draft Rejected
Zhe Cheng / Guilin University Of Electronic Technology
针对神经网络在断层诊断中应用过度拟合现象的缺陷，结合运动数学模型和常见故障机制的分析，提出了神经网络麻雀搜索算法优化方法，实现电机轴承故障的实时检测。首先，波莱特包用于分解和重建断层信号，第三层8个节点的能量值作为电子发生器输入神经网络。结果表明，对于运动轴承的常见故障，SSA-bp的故障诊断测试率为98.24%，分别比传统粒子群优化神经网络和遗传算法优化神经网络高5.14%和6.23%，收敛速度较快，适合运动轴承断层诊断。
Important Date

  • Conference Date

    Jul 11

    2023

    to

    Aug 18

    2023

  • Nov 10 2021

    Draft paper submission deadline

  • Dec 10 2021

    Registration deadline

  • Dec 11 2021

    Contribution Submission Deadline

Sponsored By
IEEE IAS
Organized By
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST
Contact Information
Login to view full contact details
Previous Conferences