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| 小波技术在高耸构筑物安全性评价中的应用 |
| Application of Wavelet Technology in the Safety Evaluation of Topping Structures |
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| DOI：10.3969/j.issn.1671-5322.2010.02.003 |
| 中文关键词: 安全监测 小波多尺度 小波神经网络 数据去噪 预测模型 |
| 英文关键词: security monitoring wavelet mult-scale wavelet neural network data de-noising prediction model |
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| 中文摘要: |
| 高耸构筑物施工风险大,安全监测至关重要.然而,复杂的环境因素使构筑物的原型观测数据包含强烈的噪声,严重干扰构筑物的受力分析和预测.为此,综合运用小波多尺度技术和小波神经网络技术分别对原始监测数据进行去噪处理和预测模型的建立.研究结果表明:经小波去噪后的数据更好地反映构筑物真实受力状态;基于RBF神经网络方法预测效果较好,具有很好的工程应用前景. |
| 英文摘要: |
| Topping structures faces to big risk in the process of construction,so security monitoring is very important.However,the measured data affected by many complicated environmental factors usually include strong noises,which badly disturbes force analysis and predication for construction.Therefore,both wavelet mult-scale technology and wavelet neural network technology are respectively used to eliminate the noises from measured data and set up prediction model.The results show that measured data after wavelet de-noising reflect practical force state,the prediction effect based on RBF neural network is better,and it has a good future in the field of engineering application. |
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