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往复泵轴承故障诊断的神经网络方法

Neural Net Work Method of Reciprocating Pump Bearing Fault Diagnosis

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【作者】 张雷涛

【Author】 ZHANG Lei-tao (Engineering Department, LanZhou Teacher’s College, LanZhou, GanSu, China 730070)

【机构】 兰州师范高等专科学校工学系 甘肃兰州730070

【摘要】 研究了基于BP网络的往复泵轴承故障诊断方法.利用频域和倒频域进行特征提取,采用集成BP网络进行故障诊断和识别,解决了往复泵轴承故障特征提取困难、多故障识别困难的问题.试验结果表明,利用BP网络可以有效地诊断与识别往复泵轴承多故障模式,并且具有很高的成功率.

【Abstract】 This article studies the method of bearing trouble-shooting of reciprocating pump based on BP net work. The feature is extracted by using frequency and mel-frequency. Trouble-shooting and distinguishing are done by using integration BP net work. The difficulties of bearing fault feature extraction and of distinguishing multi-faults have been soled out in reciprocating pump. The experimental results have proved that BP network can efficiently diagnose and distinguish the multi-faults of bearing in reciprocating pump, and the successful rate is high.

  • 【文献出处】 河西学院学报 ,Journal of Hexi University , 编辑部邮箱 ,2005年02期
  • 【分类号】TE922
  • 【被引频次】7
  • 【下载频次】133
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