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论文:2012,Vol:30,Issue(3):466-471 |
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引用本文： |
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王国庆, 牛伟, 成娟, 翟正军, 郭阳明 . 基于阶次小波包与Markov链模型的转子早期故障诊断[J]. 西北工业大学 |
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Wang Guoqing, Niu Wei, Cheng Juan, Zhai Zhengjun, Guo Yangming. A New and Effective Early Fault Diagnosis of Rotor Using Order Wavelet Packet and Markov Chain Model[J]. Northwestern polytechnical university |
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| 基于阶次小波包与Markov链模型的转子早期故障诊断 |
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| 王国庆1, 牛伟1, 成娟2, 翟正军1, 郭阳明 1 |
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1. 西北工业大学 计算机学院,陕西 西安 710072;
2. 西安应用光学研究所,陕西 西安 710065 |
| 摘要: |
| 针对转子启动过程中振动信号表现为非平稳、非高斯特征及传统诊断方法精度不高的现状,将阶次小波包和 Markov 链模型引入转子的早期故障诊断中, 提出了一种新的自适应故障诊断模型。首先利用阶次跟踪算法对瞬态振动信号重采样, 得到等角度分布诊断信号; 其次采用小波包对该信号分解—重构, 提取其在各频带的能量特征向量, 通过 Markov 链模型对其进行预测; 最后通过故障实例验证, 结果表明: 将阶次小波包变换和 Markov 链模型相结合进行故障诊断是可行而有效的。 |
| 关键词:
阶次跟踪
小波包
Markov 链模型
粒子群算法
故障诊断
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| A New and Effective Early Fault Diagnosis of Rotor Using Order Wavelet Packet and Markov Chain Model |
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| Wang Guoqing1, Niu Wei1, Cheng Juan2, Zhai Zhengjun1, Guo Yangming1 |
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1. Department of Computer Science and Engineering,Northwestern Polytechnical University,Xi'an 710072,China;
2. Xi'an Institute of Applied Optics,Xi'an 710065,China |
| Abstract: |
| The vibration signals at the start-up stage are non-stationary and non-Gaussian,and their diagnosis pre-cision obtained with traditional diagnosis methods is not good. So we introduce the order wavelet packet and theMarkov chain model that is based on particle swarm optimization into the early fault diagnosis of a rotor, thus propo-sing a new adaptive model of fault diagnosis. Sections 1 through 3 explain the early fault diagnosis mentioned in thetitle,which we believe is new and effective. Their core consists of: (1) we use the order tracking algorithm to car-ry out the resampling of the transient vibration signal,thus obtaining the diagnosis signal with equal angle distribu-tion; (2) with the order wavelet packet,we decompose and reconstruct the equal angle distribution diagnosis sig-nals and then extract their energy feature vectors at every frequency band; section 3 gives a five-step procedure forpredicting the vectors with the Markov chain model. Section 4 conducts experiments on the early fault diagnosis ofthe rotor which uses vibration signals as its state signals; the experimental results,given in Tables 2 and 3,andtheir analysis show preliminarily that the short-term prediction results with our fault diagnosis model are very closeto the actual values and have good prediction accuracy. |
| Key words:
algorithms
diagnosis
efficiency
error analysis
experiments
feature extraction
Markov processes
models
particle swarm optimization (PSO)
rotors
transfer matrix method
vibrations(mechani-cal)
wavelet transforms;fault diagnosis
Markov chain model
order tracking algorithm
order wave-let packet
vibration signal
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| 收稿日期: 2011-06-10
修回日期:
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| DOI: |
| 基金项目: 国家自然科学基金(61001023，61101004)；陕西省自然科学基金(2010HQ8005)；航空科学基金(2010ZD53039)资助 |
| 通讯作者:
Email： |
| 作者简介: 王国庆(1956-),西北工业大学教授、博士,主要从事嵌入式系统、航空电子系统综合化技术研究。
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| 作者相关文章 |
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| 王国庆 在本刊中的所有文章 |
| 牛伟 在本刊中的所有文章 |
| 成娟 在本刊中的所有文章 |
| 翟正军 在本刊中的所有文章 |
| 郭阳明 在本刊中的所有文章 |
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