基于遺傳算法的神經網(wǎng)絡對大體積混凝土監(jiān)測優(yōu)化研究
打開文本圖片集
中圖分類號：TU755.4 文獻標志碼：A 文章編號：1005-8249（2025）03-0134-07
DOI：10.19860/j.cnki.issn1005-8249.2025.03.024
Abstract：Inorder tostudytheoptimallocationof temperatureandstressmonitoringofmassconcreteunderthecircumstanceof limited numberof sensors，thetemperatureand stressvaluesof measuring pointswereobtainedbyfiniteelement simulationto buildadatabase，andthehighfitofneuralnetworkandtheoptimizationcharacteristicsof geneticalgoritmwereusedtofitthe temperature fieldand stressfieldofmassconcrete andoptimizethelocationof sensors.Theresultsshowthat theRMSEbetween thepredictedandmeasuredvaluesofeachnodedecreasesfrom5.21to3.56，andthecoeficientofdeterminationincreasesfrom 0.71to0.91，andtheoptimizationefectisremarkable.Throughoptimization，thecondition monitoringrequirementsof mass concrete can be realized under the limited number of sensors，and the specific applicability is better.
Key words：neural network；genetic algorithm；mass concrete；temperature field；stressfield；monitoring position
0 引言
隨著我國經濟高速發(fā)展，大型基礎設施數(shù)量日益增長，大體積混凝土成為不可或缺的組成部分[1]大體積混凝土存在水化熱高、散熱困難、裂縫控制難度高等問題，且澆筑倉塊不同位置的溫升規(guī)律存在一定差異[2]，通過合理有效的狀態(tài)監(jiān)測，可及時發(fā)現(xiàn)并解決混凝土溫升異常及裂縫問題。（剩余8244字）