本文選題：爆破振動(dòng)　切入點(diǎn)：民房結(jié)構(gòu)損傷　出處：《爆炸與沖擊》2017年06期

【摘要】：為快速、準(zhǔn)確地評(píng)價(jià)爆破振動(dòng)誘發(fā)民房結(jié)構(gòu)損傷效應(yīng),借鑒隨機(jī)森林理論并結(jié)合工程實(shí)際,建立露采爆破振動(dòng)誘發(fā)民房結(jié)構(gòu)損傷識(shí)別的隨機(jī)森林模型;綜合考慮爆破參數(shù)、爆破振動(dòng)特征參量及房屋結(jié)構(gòu)動(dòng)力特性等因素,選取質(zhì)點(diǎn)峰值振動(dòng)速度、主頻率、主頻率持續(xù)時(shí)間、段藥量、爆心距、施工質(zhì)量參數(shù)、場(chǎng)地條件參數(shù)、屋蓋形式參數(shù)、磚墻面積率、民房高度、灰縫強(qiáng)度和圈梁構(gòu)造柱參數(shù)等12個(gè)影響因素作為模型輸入,將磚混結(jié)構(gòu)建筑物的損害等級(jí)作為模型輸出;基于多分類(lèi)器集成的思想,以108組爆破振動(dòng)實(shí)測(cè)數(shù)據(jù)作為學(xué)習(xí)樣本進(jìn)行訓(xùn)練,建模過(guò)程中由多個(gè)決策樹(shù)集成隨機(jī)森林、用投票的方式實(shí)現(xiàn)對(duì)民房結(jié)構(gòu)損傷有效識(shí)別;用12組現(xiàn)場(chǎng)數(shù)據(jù)驗(yàn)證模型的有效性;在對(duì)樣本分類(lèi)的同時(shí),計(jì)算預(yù)測(cè)變量的重要性值,發(fā)現(xiàn)質(zhì)點(diǎn)峰值振動(dòng)速度為最重要的評(píng)價(jià)指標(biāo),其后依次為爆心距,主頻率持續(xù)時(shí)間,主頻率,圈梁構(gòu)造柱參數(shù),灰縫強(qiáng)度,屋蓋形式參數(shù),民房高度,段藥量,施工質(zhì)量參數(shù),磚墻面積率和場(chǎng)地條件參數(shù)。研究結(jié)果表明:隨機(jī)森林模型預(yù)測(cè)結(jié)果學(xué)習(xí)樣本準(zhǔn)確度是87.97%,而測(cè)試集準(zhǔn)確度是91.67%,與實(shí)際情況吻合較好,預(yù)測(cè)精度較高。
[Abstract]:In order to evaluate the damage effect of civil house structure induced by blasting vibration quickly and accurately, using the theory of random forest and combining with engineering practice, a stochastic forest model for structural damage identification of civil house induced by blasting vibration in open pit is established, and the blasting parameters are considered synthetically. The vibration characteristic parameters of blasting and the dynamic characteristics of building structure are selected. The peak vibration velocity of particle, the main frequency, the duration of main frequency, the quantity of explosive, the distance of blasting center, the construction quality parameter, the parameters of site condition, the form parameter of roof are selected. Twelve factors, such as area ratio of brick wall, height of house, strength of ash joint and parameters of ring beam structure column, are taken as model input, and the damage grade of brick and concrete structure building is taken as model output, which is based on the idea of multi-classifier integration. 108 groups of measured data of blasting vibration were used as learning samples to train, in the process of modeling, the random forest was integrated by multiple decision trees, and the damage of civil house structure was effectively identified by voting, and 12 groups of field data were used to verify the validity of the model. At the same time of classifying the samples, the importance of predicting variables is calculated, and it is found that the peak vibration velocity of particle is the most important evaluation index, followed by the burst distance, the duration of the main frequency, the main frequency, the parameters of the structure and column of the ring beam, the strength of the gray joint. Roof formal parameters, building height, section charge, construction quality parameters, The results show that the accuracy of learning sample is 87.97, while the accuracy of test set is 91.67, which is in good agreement with the actual situation, and the prediction accuracy is higher.
【作者單位】： 黃淮學(xué)院建筑工程學(xué)院;中南大學(xué)土木工程學(xué)院;湖南科技大學(xué)能源與安全工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(11072072)
【分類(lèi)號(hào)】：O38;TU317

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