SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK
A damage detection method based on wavelet packet transform and replicator neural networks is proposed to carry out real-time damage detection of structures. Firstly,wavelet packet transform is used to decompose original vibration response signals to calculate the relative band energy of each band....
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2020-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.03.001 |
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| _version_ | 1841535792167518208 |
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| author | ZHANG Xiang CHEN RenWen |
| author_facet | ZHANG Xiang CHEN RenWen |
| author_sort | ZHANG Xiang |
| collection | DOAJ |
| description | A damage detection method based on wavelet packet transform and replicator neural networks is proposed to carry out real-time damage detection of structures. Firstly,wavelet packet transform is used to decompose original vibration response signals to calculate the relative band energy of each band. The distribution of relative band energy reflects the characteristics of the structure to be detected. Secondly,the relative energy from healthy structure is taken as input to training replicator neural networks. Finally,the trained networks are used for damage detection in real-time. Experiments showed that the proposed method can detect single-position damage even under noise interference. |
| format | Article |
| id | doaj-art-89448be211b14a47b4925abc190c9ef9 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-89448be211b14a47b4925abc190c9ef92025-01-15T02:27:45ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692020-01-014250951530607788SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORKZHANG XiangCHEN RenWenA damage detection method based on wavelet packet transform and replicator neural networks is proposed to carry out real-time damage detection of structures. Firstly,wavelet packet transform is used to decompose original vibration response signals to calculate the relative band energy of each band. The distribution of relative band energy reflects the characteristics of the structure to be detected. Secondly,the relative energy from healthy structure is taken as input to training replicator neural networks. Finally,the trained networks are used for damage detection in real-time. Experiments showed that the proposed method can detect single-position damage even under noise interference.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.03.001Replicator Neural Network（RNN）Wavelet packet transformRelative band energyDamage detection |
| spellingShingle | ZHANG Xiang CHEN RenWen SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK Jixie qiangdu Replicator Neural Network（RNN） Wavelet packet transform Relative band energy Damage detection |
| title | SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK |
| title_full | SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK |
| title_fullStr | SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK |
| title_full_unstemmed | SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK |
| title_short | SINGLE-POSITION DAMAGE DETECTION BASED ON WAVELET PACKET TRANSFORM AND REPLICATOR NEURAL NETWORK |
| title_sort | single position damage detection based on wavelet packet transform and replicator neural network |
| topic | Replicator Neural Network（RNN） Wavelet packet transform Relative band energy Damage detection |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.03.001 |
| work_keys_str_mv | AT zhangxiang singlepositiondamagedetectionbasedonwaveletpackettransformandreplicatorneuralnetwork AT chenrenwen singlepositiondamagedetectionbasedonwaveletpackettransformandreplicatorneuralnetwork |