Neural network based prediction of frictional coefficient in metal forming deep drawing 基于神經(jīng)網(wǎng)絡(luò)的板料拉深成形摩擦系數(shù)預(yù)測
The results showed that surface of different materials have obvious influence on the frictional coefficient while direction has no significant effect on it 結(jié)果表明:摩擦方向?qū)δΣ料禂?shù)的影響不大,實(shí)際生產(chǎn)中主要需考慮摩擦基材面對摩擦系數(shù)的影響。
One of the inequalities is that the initial disturbance amplitude is more than a critical value , and the other is that the frictional coefficient is more than another critical value 初始擾動(dòng)振幅大于某一臨界值; ( 2 )摩擦系數(shù)大于某一臨界值,前者對后者有很強(qiáng)的約束。
The established contact model has provided good explanation for the phenomena of the reduction of frictional coefficient induced by longitudinal ultrasonic vibration and has great academic significance in proposing friction reduction technology based on elliptical ultrasonic vibration 對該模型的分析很好地解釋了縱向超聲振動(dòng)所引起的摩擦系數(shù)降低的現(xiàn)象,為提出利用橢圓軌跡超聲振動(dòng)來實(shí)現(xiàn)減摩奠定了理論基礎(chǔ)。
By means of statistical inference as well as hypothesis test method , it is determined that the variables of compressive stress and shearing stress are of extreme - value distribution and that the variables of frictional coefficient and cohesion coefficient are of logarithmic normal distribution 應(yīng)用統(tǒng)計(jì)推理和假設(shè)檢驗(yàn)方法分析得知,壓應(yīng)力與切應(yīng)力隨機(jī)變量呈極值型分布,摩擦系數(shù)與粘結(jié)力系數(shù)隨機(jī)變量呈對數(shù)正態(tài)分布。