三维动静组合加载下花岗岩能量耗散试验研究

利用改造的三维霍普金森试验系统(split Hopkinson pressure bar, SHPB),选取4个轴压水平(25, 50, 75和100 MPa)和4个围压水平(0, 5, 10和15 MPa),对应开展4种应变率(约70, 90, 110和130 s^-1)下花岗岩三维动静组合加载试验研究,分析静载轴压、静载围压和应变率对花岗岩受冲击过程中能量耗散的影响规律,并讨论其破坏模式。试验结果表明:轴压增大时,花岗岩破坏时单位体积吸收能逐渐降低;围压或应变率增大时,单位体积吸收能逐渐升高。岩石储能极限在能量耗散过程中发挥关键作用,且不同情况下具体表现不同:储能极限与初始储能的差值影响岩石受冲击时的吸能值;当岩石在静载下进入损伤阶段初期时,储能极限与初始储能的比值决定岩石受冲击时的释能值;当岩石在静载下进入损伤阶段后期甚至发生屈服时,储能极限值正比于岩石释能值。此外,岩石破坏模式与单位体积耗散能关系密切:应变率相似静载组合变化时,破碎程度与单位体积吸收能变化呈负相关;静载组合确定应变率梯度变化时,破碎程度与单位体积吸收能变化呈正相关。

Application of information measure and support vector machine in image edge detection

A novel method for image edge detection is presented based on information measurement and Support Vector Machine,which is called ISEDM(Information measure and support vector machine edge detection method).At first,a vector is constructed to fully describe a edge point information measure,which includes neighborhood homogeneity information measure,orientation information measure, and gradient strengths.(Secondly,) SVM is applied to train and classify the set of feature vectors,so that the edge of the image is detected.The experimental results show that ISEDM can not only effectively reduce the noises of the image,but also can precisely detect the edge-position,and keep the image edges' details well.