...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Science, Measurement & Technology, IET >Gearbox fault diagnosis under fluctuating load conditions with independent angular re-sampling technique, continuous wavelet transform and multilayer perceptron neural network
【24h】

Gearbox fault diagnosis under fluctuating load conditions with independent angular re-sampling technique, continuous wavelet transform and multilayer perceptron neural network

机译：利用独立的角度重采样技术，连续小波变换和多层感知器神经网络在波动负载条件下进行变速箱故障诊断

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Most research efforts in gearbox fault diagnosis thus far have focused on diagnosing gearbox faults under stationary conditions. Efforts in diagnosing gearbox faults under non-stationary conditions have mostly involved an analysis of gearbox vibration signals under the speed-up or run-down processes. This paper attempts to diagnose faults in a single stage spur gearbox under non stationary conditions arising from fluctuating loads at the output of gearbox. The vibration signal corresponding to each independent revolution is synchronized from the revolution point of view by converting into the angular domain. This is accomplished experimentally by a simple process referred to as the independent angular re-sampling (IAR) technique. The IAR technique is accomplished by employing a multiple pulse tachometer arrangement. Through the IAR process, non-stationary signals in the time domain are converted into quasi-stationary signals in the angular domain. The angular domain signals, each representing one revolution of the gearbox drive shaft, are then decomposed with continuous wavelet transform. Optimal scales are identified based on superior energy-Shannon's entropy ratio of continuous wavelet coefficients (CWCs). The classification accuracy of a multilayer perceptron neural network is compared when CWCs from all scales and when CWCs from the optimal scales are fed to the neural network.
机译：迄今为止，变速箱故障诊断的大多数研究工作都集中于在固定条件下诊断变速箱故障。在非平稳状态下诊断变速箱故障的工作主要涉及分析加速或减速过程中的变速箱振动信号。本文尝试诊断非平稳工况下单级正齿轮箱的故障，该故障是由齿轮箱输出处的负载波动引起的。通过旋转到角域，从旋转的角度使与每个独立旋转相对应的振动信号同步。这是通过称为独立角度重采样（IAR）技术的简单过程通过实验完成的。 IAR技术是通过采用多脉冲转速计装置来实现的。通过IAR过程，将时域中的非平稳信号转换为角域中的准平稳信号。然后通过连续的小波变换分解角域信号，每个角域信号代表变速箱驱动轴的一转。基于连续小波系数（CWC）的优越能量-香农熵比率，确定最佳尺度。当所有尺度的CWC和最佳尺度的CWC馈入神经网络时，都会比较多层感知器神经网络的分类精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号