大坝与安全
大壩與安全
대패여안전
Dam & Safety
2015年
4期
6-11
,共6页
神经网络%重力坝%损伤识别%模型试验
神經網絡%重力壩%損傷識彆%模型試驗
신경망락%중력패%손상식별%모형시험
neural networks%gravity dam%damage identification%model test
大坝在长期使用过程中或遭遇地震时可能出现损伤、产生裂缝,使用常规的方法诊断大坝内部裂缝损伤十分困难.为克服这一困难,提出了适用于大型水利工程结构损伤识别的两步诊断方法.以武都水库非溢流坝段为例,基于振动参数识别技术,利用径向基函数神经网络对重力坝损伤识别展开研究,先从理论研讨和数值模拟验证该方法的有效性,再结合振动台模型试验中所得的结构动力特性进行检验,对比所得的损伤识别效果.结果表明:该方法对重力坝进行损伤位置识别、损伤程度预测是可行的,有待于在实际工程应用中进行检验.
大壩在長期使用過程中或遭遇地震時可能齣現損傷、產生裂縫,使用常規的方法診斷大壩內部裂縫損傷十分睏難.為剋服這一睏難,提齣瞭適用于大型水利工程結構損傷識彆的兩步診斷方法.以武都水庫非溢流壩段為例,基于振動參數識彆技術,利用徑嚮基函數神經網絡對重力壩損傷識彆展開研究,先從理論研討和數值模擬驗證該方法的有效性,再結閤振動檯模型試驗中所得的結構動力特性進行檢驗,對比所得的損傷識彆效果.結果錶明:該方法對重力壩進行損傷位置識彆、損傷程度預測是可行的,有待于在實際工程應用中進行檢驗.
대패재장기사용과정중혹조우지진시가능출현손상、산생렬봉,사용상규적방법진단대패내부렬봉손상십분곤난.위극복저일곤난,제출료괄용우대형수리공정결구손상식별적량보진단방법.이무도수고비일류패단위례,기우진동삼수식별기술,이용경향기함수신경망락대중력패손상식별전개연구,선종이론연토화수치모의험증해방법적유효성,재결합진동태모형시험중소득적결구동력특성진행검험,대비소득적손상식별효과.결과표명:해방법대중력패진행손상위치식별、손상정도예측시가행적,유대우재실제공정응용중진행검험.
Damage and cracks may occur with dam during long operation period or when earthquake happens. It is difficult to diagnose internal damage by conventional methods, which would leave security hazards. A two-step damage detection method for large-scale hydraulic structures was introduced to solve this problem. Taking non-overflow section of Wudu reservoir as an example, combined with vibra-tion parameter identification technique, research on damage identification of gravity dam based on RBF neural networks is carried out. Firstly, this paper verifies the validity of this method by theoretical re-search and numerical simulation. Then, the result of damage identification is checked by comparing with the dynamic characteristics obtained from the shaking table model test. The results indicate that the method is feasible to identify the position of damage and predict the extent of damage of gravity dam, but further study is still needed to solve practical problems.