【摘要】：為研究場(chǎng)道脫空檢測(cè)方法,進(jìn)行室內(nèi)模型試驗(yàn),獲得沖擊荷載作用下道面板加速度響應(yīng)時(shí)程曲線,利用Matlab小波變換工具箱提取加速度曲線特征值,分析脫空對(duì)振動(dòng)信號(hào)的影響規(guī)律.通過(guò)優(yōu)化荷載級(jí)數(shù)、篩選輸入向量,建立了場(chǎng)道脫空的BP(back propagation)神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)方法.為檢驗(yàn)理論研究結(jié)果的正確性,利用重錘式彎沉儀在機(jī)場(chǎng)進(jìn)行跑道脫空測(cè)試,通過(guò)場(chǎng)道取芯脫空觀察評(píng)價(jià)BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)結(jié)論的可靠性.結(jié)果表明,荷載級(jí)數(shù)、輸入向量、訓(xùn)練次數(shù)、訓(xùn)練強(qiáng)度和算法對(duì)BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)準(zhǔn)確性影響較大;脫空影響下場(chǎng)道加速度信號(hào)可作為BP神經(jīng)網(wǎng)絡(luò)脫空預(yù)測(cè)的輸入向量,取芯后場(chǎng)道脫空狀況同BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)結(jié)果一致.
[Abstract]:In order to study the detection method of field channel void, the time-history curve of acceleration response of track panel under impact load was obtained by indoor model test. The eigenvalue of acceleration curve was extracted by Matlab wavelet transform toolbox. The influence of void on vibration signal is analyzed. By optimizing load series and selecting input vectors, a prediction method of field channel void based on BP (back propagation) neural network is established. In order to verify the correctness of the theoretical research results, the reliability of the prediction results of BP neural network was evaluated by using the heavy-weight deflectometer to test the runway clearance at the airport. The results show that load series, input vector, training times, training intensity and algorithm have great influence on the prediction accuracy of BP neural network. The acceleration signal of field track can be used as input vector of BP neural network to predict void under the influence of void. The condition of field track void in core is consistent with the prediction result of BP neural network.
【作者單位】： 凍土工程國(guó)家重點(diǎn)實(shí)驗(yàn)室;中國(guó)民航大學(xué)機(jī)場(chǎng)學(xué)院;
【基金】：國(guó)家自然基金資助項(xiàng)目(51178456) 凍土工程國(guó)家重點(diǎn)實(shí)驗(yàn)室開放基金資助項(xiàng)目(SKLFSE201409) 中央高校基本業(yè)務(wù)費(fèi)資助項(xiàng)目(3122016D019)~~
【分類號(hào)】：V351;TP183

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本文編號(hào)：2418595