【摘要】：電流左右區(qū)間積分差值法是一種常用的擺動(dòng)電弧傳感偏差提取算法。為了推出電流積分差與位置偏差的關(guān)系,需要建立準(zhǔn)確的電弧傳感數(shù)學(xué)模型,根據(jù)試驗(yàn)得到焊槍高度與送絲速度、焊接電流的線性關(guān)系式。針對(duì)在焊槍高度很低或很高時(shí)線性化處理有較大誤差或很難建立準(zhǔn)確的電弧傳感數(shù)學(xué)模型的問題,提出了一種基于BP神經(jīng)網(wǎng)絡(luò)的方法建立模型并優(yōu)化積分差值偏差提取算法。進(jìn)行了多組不同偏差值的焊接試驗(yàn),分別用2種方法分析處理電流信號(hào),將得到的偏差值與實(shí)際偏差對(duì)比,推出了線性回歸方程并建立、驗(yàn)證了神經(jīng)網(wǎng)絡(luò)模型。結(jié)果驗(yàn)證了BP神經(jīng)網(wǎng)絡(luò)方法的可靠性。
[Abstract]:The current and right interval integral difference method is a common swing arc sensing deviation extraction algorithm. In order to develop the relationship between the current integral difference and the position deviation, an accurate mathematical model of electric arc sensing is needed, and the linear relationship between the height of the welding gun and the wire feeding speed and the welding current is obtained according to the test. In order to solve the problem of large error or difficult to establish an accurate electric arc sensing mathematical model when the height of the welding gun is very low or very high, a method based on the BP neural network is proposed to set up the model and to optimize the integral difference deviation extraction algorithm. In this paper, a series of welding tests with different deviation values were carried out. The current signal was analyzed by two methods, and the obtained deviation value was compared with the actual deviation. The linear regression equation was introduced and the neural network model was established. The results verify the reliability of the BP neural network method.
【作者單位】： 天津工業(yè)大學(xué)天津市現(xiàn)代機(jī)電裝備技術(shù)重點(diǎn)試驗(yàn)室;解放軍汽車修理廠;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(U1333128) 天津市科技計(jì)劃資助項(xiàng)目(14ZCDZGX00802)
【分類號(hào)】：TG409

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本文編號(hào)：2508549