利用汛期三峡枢纽工程泄洪期间泄流荷载对左导墙产生的激励作用,对三峡左导墙结构进行了原型动力响应测试,分析了导墙泄洪振动动位移响应均方根的沿程分布特征;在此基础上,以泄流荷载为激励源,利用动力响应对导墙结构的工作模态参数进...利用汛期三峡枢纽工程泄洪期间泄流荷载对左导墙产生的激励作用,对三峡左导墙结构进行了原型动力响应测试,分析了导墙泄洪振动动位移响应均方根的沿程分布特征;在此基础上,以泄流荷载为激励源,利用动力响应对导墙结构的工作模态参数进行了动态识别;最后,综合导墙结构泄洪振动动位移原型观测、模态参数动态识别结果对三峡左导墙汛期的泄洪振动安全性进行了综合评估.结果表明,三峡左导墙泄洪振动安全,按M e ister感觉曲线标准,其泄洪振动响应属于"强烈地感觉到"阶段,但产生低阶共振可能性不大.展开更多
A novel noninvasive approach, based on flow-induced vibration, to the online flow regime identification for wet gas flow in a horizontal pipeline is proposed. Research into the flow-induced vibration response for the ...A novel noninvasive approach, based on flow-induced vibration, to the online flow regime identification for wet gas flow in a horizontal pipeline is proposed. Research into the flow-induced vibration response for the wet gas flow was conducted under the conditions of pipe diameter 50 mm, pressure from 0.25 MPa to 0.35 MPa, Lockhart-Martinelli parameter from 0.02 to 0.6, and gas Froude Number from 0.5 to 2.7. The flow-induced vibration signals were measured by a transducer installed on outside wall of pipe, and then the normalized energy features from different frequency bands in the vibration signals were extracted through 4-scale wavelet package transform. A "binary tree" multi-class support vector machine(MCSVM) classifier, with the normalized feature vector as inputs, and Gaussian radial basis function as kernel function, was developed to identify the three typical flow regimes including stratified wavy flow, annular mist flow, and slug flow for wet gas flow. The results show that the method can identify effectively flow regimes and its identification accuracy is about 93.3%. Comparing with the other classifiers, the MCSVM classifier has higher accuracy, especially under the case of small samples. The noninvasive measurement approach has great application prospect in online flow regime identification.展开更多
文摘利用汛期三峡枢纽工程泄洪期间泄流荷载对左导墙产生的激励作用,对三峡左导墙结构进行了原型动力响应测试,分析了导墙泄洪振动动位移响应均方根的沿程分布特征;在此基础上,以泄流荷载为激励源,利用动力响应对导墙结构的工作模态参数进行了动态识别;最后,综合导墙结构泄洪振动动位移原型观测、模态参数动态识别结果对三峡左导墙汛期的泄洪振动安全性进行了综合评估.结果表明,三峡左导墙泄洪振动安全,按M e ister感觉曲线标准,其泄洪振动响应属于"强烈地感觉到"阶段,但产生低阶共振可能性不大.
基金Supported by the National Natural Science Foundation of China （60672003）
文摘A novel noninvasive approach, based on flow-induced vibration, to the online flow regime identification for wet gas flow in a horizontal pipeline is proposed. Research into the flow-induced vibration response for the wet gas flow was conducted under the conditions of pipe diameter 50 mm, pressure from 0.25 MPa to 0.35 MPa, Lockhart-Martinelli parameter from 0.02 to 0.6, and gas Froude Number from 0.5 to 2.7. The flow-induced vibration signals were measured by a transducer installed on outside wall of pipe, and then the normalized energy features from different frequency bands in the vibration signals were extracted through 4-scale wavelet package transform. A "binary tree" multi-class support vector machine(MCSVM) classifier, with the normalized feature vector as inputs, and Gaussian radial basis function as kernel function, was developed to identify the three typical flow regimes including stratified wavy flow, annular mist flow, and slug flow for wet gas flow. The results show that the method can identify effectively flow regimes and its identification accuracy is about 93.3%. Comparing with the other classifiers, the MCSVM classifier has higher accuracy, especially under the case of small samples. The noninvasive measurement approach has great application prospect in online flow regime identification.
