计算机与现代化 ›› 2010, Vol. 1 ›› Issue (6): 144-0146.doi: 10.3969/j.issn.1006-2475.2010.06.041
• 计算机控制 • 上一篇 下一篇
张 宇,罗长更
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ZHANG Yu, LUO Chang-geng
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摘要： 设计一种基于图形化开发环境LabVIEW DSP模块的风机故障诊断系统开发方案。方案以32位浮点DSP芯片TMS320C6713为核心，采集风机噪声信号并利用信号的功率谱重心、A声级和小波分解相关频段的能量构成故障诊断的特征向量，以BP网络作为故障的智能分类器，建立起智能诊断系统。实验结果表明，以噪声信号作为诊断对象，采用提升小波和神经网络相融合的诊断与识别技术具有良好的特征提取能力和自适应学习能力，可以准确地识别设备状态。
关键词: 声级, 故障诊断, DSP, 提升小波, BP网络
Abstract: The article designs a kind of fan fault diagnosis system based on LabVIEW DSP module. Relying on the noise signal of the fan collected by TMS320C6713, the recognition system utilizes power spectrum gravity center, sound level, wavelet frequency segment power of the signal as feature vectors, and a BP network as classifier for fault diagnosis. The experimental results show that it is effective to extract fault information by the combination of lifting wavelet and neural network. The entire system has adaptability and feature extraction capability. The diagnose results are reliable and accurate.
Key words: sound level, fault diagnosis, DSP, lifting wavelet, BP network
中图分类号:
TP373
张宇;罗长更. 一种基于LabVIEW DSP模块的风机故障诊断系统[J]. 计算机与现代化, 2010, 1(6): 144-0146.
ZHANG Yu;LUO Chang-geng. Fan Fault Diagnosis System Based on LabVIEW DSP Module[J]. Computer and Modernization, 2010, 1(6): 144-0146.
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链接本文: http://www.c-a-m.org.cn/CN/10.3969/j.issn.1006-2475.2010.06.041
http://www.c-a-m.org.cn/CN/Y2010/V1/I6/144
