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   李   燦1  ,  王    龍1  ,   熊俊馳1  ,  林    峰2  ,  魏    豪3  ,  周殷弘2

( 1 .  中國(guó)空氣動(dòng)力研究與發(fā)展中心 ，綿陽(yáng) 621000 ;  2.  中國(guó)建筑第八工程局有限公司 ，上海 200120 ;

3 .  哈爾濱工程大學(xué) 航天與建筑工程學(xué)院 ，哈爾濱 150009)

摘   要 ：為研究大體積混凝土溫度及應(yīng)力監(jiān)測(cè)在傳感器數(shù)量有限情況下的最優(yōu)布設(shè)位置 ，通過(guò)有限元仿真  獲取測(cè)點(diǎn)位置的溫度和應(yīng)力值搭建數(shù)據(jù)庫(kù) ，利用神經(jīng)網(wǎng)絡(luò)的高擬合性及遺傳算法的尋優(yōu)特性 ，對(duì)大體積混凝土  溫度場(chǎng) 、應(yīng)力場(chǎng)進(jìn)行神經(jīng)網(wǎng)絡(luò)擬合及傳感器布設(shè)位置尋優(yōu)。結(jié)果表明：嵌套遺傳算法對(duì)監(jiān)測(cè)點(diǎn)位優(yōu)化后 ，各節(jié)  點(diǎn)預(yù)測(cè)值與實(shí)測(cè)值的均方根誤差從 5. 21 減小至 3 . 56 ,  確定系數(shù)從 0. 71 提升至 0. 91 ,  優(yōu)化效果顯著。通過(guò)優(yōu)化， 能夠在有限傳感器數(shù)量下實(shí)現(xiàn)大體積混凝土狀態(tài)監(jiān)測(cè)需求 ，具體較好的適用性。

關(guān)鍵詞：神經(jīng)網(wǎng)絡(luò) ；遺傳算法 ；大體積混凝土 ；溫度場(chǎng) ；應(yīng)力場(chǎng) ；監(jiān)測(cè)位置

中圖分類(lèi)號(hào)：TU755 . 4           文獻(xiàn)標(biāo)志碼：A     

文章編號(hào)： 1005- 8249   (2025)  03- 0134- 07 

DOI:10. 19860/j.cnki.issn1005 - 8249.2025 .03 .024

Li Can, Wang Long¹, Xiong Junchi¹, Lin Feng², Wei Hao³,Zhou Yinhong²

(1. China Aerodynamics Research and Development Center, Mianyang 621000, China; 2. China Construction Eighth Engineering Division Co., LTD., Shanghai 200120, China; 3. College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150009, China）

Abstract：In order to study the optimal location of temperature and stress monitoring of mass concrete under the circumstance of limited number of sensors, the temperature and stress values of measuring points were obtained by finite element simulation to build a database, and the high fit of neural network and the optimization characteristics of genetic algorithm were used to fit the temperature field and stress field of mass concrete and optimize the location of sensors. The results show that the RMSE between the predicted and measured values of each node decreases from 5.21 to 3.56, and the coefficient of determination increases from 0.71 to 0.91, and the optimization effect is remarkable. Through optimization, the condition monitoring requirements of mass concrete can be realized under the limited number of sensors, and the specific applicability is better.

Keywords: neural network; genetic algorithm; mass concrete; temperature field; stress field; monitoring position

作者簡(jiǎn)介：李    燦  (1995—) ,   男 ，碩士 ，工程師 ，研究方向 ：混凝土結(jié)構(gòu)。

通信作者： 熊俊馳  (1972—) ,   男 ，本科 ， 工程師 ，研究方 向 ：混凝土結(jié)構(gòu)。

       收稿日期：2023 - 05 - 06