采煤机截割部行星减速器可靠性分析

为研究多因素影响下采煤机截割部行星减速器的可靠性,以MG400/951-WD采煤机为研究对象,根据截齿受力分析和煤样机械性质测定结果,计算出螺旋滚筒受到的载荷曲线。将载荷施加给截割部模型进行仿真,得到行星架与行星轴的应力信息;通过构建应力-可靠度的高斯型隶属度函数,获取行星架与行星轴的可靠度信息。基于正交试验分析煤的普氏系数、采煤机牵引速度及滚筒截割深度对行星减速器可靠度的影响规律及显著性程度,得出结论:采煤机牵引速度对行星减速器可靠性的影响最大,其次是煤的普氏系数,截割深度对行星减速器可靠性的影响最小;随着煤的普氏系数增大,行星减速器可靠度降低的幅度增大,且可靠度降低趋势愈加明显;随着牵引速度和截割深度的增加,行星减速器可靠度降低的幅度趋于平缓。     

电动机加液力变矩器驱动下的采煤机性能分析

目前采煤机主要采用电动机加变频器的驱动方式牵引,难以满足低速截割复杂煤层时需要更大输出转矩的要求。针对该问题,分析了采用电动机加液力变矩器驱动方式时采煤机的性能,对电动机与液力变矩器的合理匹配进行了理论分析并建立了相应的计算模型。以MG750/1860-WD型采煤机为例进行匹配分析,得出结论:电动机加液力变矩器的驱动方式在一定速度范围内可以实现采煤机牵引的无极变速及采煤机在不同工况下的截割牵引;与变频牵引相比,在相同截割牵引速度下,采用液力变矩器截割牵引可增大输出转矩,且液力变矩器的输出转矩随着牵引速度的降低而增大,最大输出转矩远超过变频牵引的最大输出转矩;在低速截割牵引条件下,液力变矩器截割牵引可以提高行走轮的输出转矩,增大采煤机的牵引能力,对于截割薄煤层和阻力较大的煤层具有重要意义。     

矸石层形态对掘锚机截割特性影响仿真分析

巷道实际掘进过程中掘进工作面除全煤层外还有各种矸石层,矸石层的存在会影响掘锚机掘进效率。然而目前大多以全煤层工作面为研究背景对滚筒截割特性进行分析,或考虑的矸石层形态较为单一。针对上述问题,以MB670-1型掘锚机为研究对象,利用Pro/E软件绘制掘锚机三维模型,将模型导入RecurDyn软件并添加相应的运动副,之后再导入EDEM软件,建立EDEM-RecurDyn耦合仿真模型。从滚筒截割性能、滚筒位移和滚筒振动3个方面仿真分析了水平矸石层、斜矸石层、半矸石层3种矸石层形态对掘锚机截割特性的影响,结果表明：(1)与全煤层相比,在矸石层条件下滚筒截割阻力、载荷波动系数、截割比能耗均有所增加,尤其在斜矸石层条件下增加最明显,截割阻力均值增大了35.61%,X轴（沿掘锚机掘进方向）、Y轴（垂直于巷道底板方向）、Z轴（与滚筒轴平行方向）载荷波动系数分别增大了26.79%,25.39%,61.28%,截割比能耗增大了37.21%。(2)矸石层的存在使滚筒位移有所减小,相比于全煤层,在水平矸石层、斜矸石层、半矸石层条件下滚筒位移分别缩短了53,89,14 mm。(3)滚筒在截割含矸石层工作面时产生...     

煤岩特性对掘进机截割头载荷的影响分析

针对煤岩条件对掘进机截割头载荷的影响问题,提出采用有限元仿真方法对截割头截割过程进行动态仿真分析。以煤岩普氏系数为煤岩特性参数,经仿真得到不同煤岩条件下的截割头动态载荷,通过分析得到了截割头三向力随煤岩普氏系数的变化规律,即截割头载荷随煤岩普氏系数的增加而增大,且当煤岩的普氏系数增大到一定程度时,截割头的牵引阻力将成为截割头的最大载荷,而侧向力一直处于较低的水平。     

滚筒式采煤机调高机构机液联合仿真研究

为精确验证滚筒式采煤机调高机构工作可靠性与稳定性,利用ADAMS/Hydraulics插件建立了调高机构液压系统模型,并将其与机械系统模型进行耦合,实现了调高机构的机液联合仿真。根据实际工况,用Matlab模拟了最恶劣工况下滚筒所受的瞬时负载,在ADAMS中以Akima拟合的spline函数的形式将其施加给滚筒。结合实际项目,对滚筒调高至工作面顶部并进行截割这一过程进行仿真,对仿真所得的滚筒所受台力和合力矩曲线、液压缸受力曲线、液压缸长度和速度曲线、无杆腔压力及流量曲线进行分析,结果表明此调高机构具有一定的稳定性和可靠性,此方法能够为今后采煤机调高机构的设计与优化提供借鉴。     

采煤机截齿与牵引速度和滚筒转速之间关系

对采煤机单个截齿进行受力分析,用软件Matlab进行编程,模拟井下的一种复杂的工作状况,利用程序文本,生成滚筒瞬时负载曲线,再模拟不同滚筒转速和牵引速度下截齿的受力情况,并将其施加给采煤机滚筒刚柔耦合系统,分析了各情况下截齿的应力情况.研究表明:该采煤机的牵引速度应控制在2～3 m/min之间.考虑到采煤机截割效率、煤块煤率和齿耗,滚筒转速应选择较小的91.1 r/min.     

基于工况触发的采煤机滚筒截割高度模板生成方法

针对采煤机在工作过程中易受不同工况条件的影响导致滚筒调高精度低的问题,提出了一种基于工况触发的采煤机滚筒截割高度模板生成方法。对采煤机历史传感器数据进行预处理和特征提取,选择影响滚筒高度调节的截割电动机电流、截割电动机温度、俯仰角、横滚角、牵引速度5维特征数据,构建用于生成滚筒截割高度模板的补偿回声状态网络（C-ESN）模型;建立工况触发机制,将采煤机传感器实时数据输入C-ESN模型,以测试误差为判断准则,识别当前采煤机的工况为正常区域、三角煤区域或异常工况;最后,C-ESN模型生成相应的滚筒截割高度模板。当三角煤区域和正常区域测试误差都大于阈值时,采用迁移学习方法对测试误差小的截割高度模板参数进行修正,以保证异常工况下截割高度模板的精度。基于现场采煤机实际数据的实验结果表明：左右滚筒截割高度模板与实际截割高度相比,在正常区域的最大误差分别为11.47,9.96 cm,在三角煤区域最大误差分别为12.91,7.94 cm,能够满足工程实际要求;与传统回声状态网络和径向基函数网络模型相比,C-ESN模型的精度在正常区域分别提升了54%和57%,在三角煤区域分别提升了10%和69%。     

采煤机滚筒工作性能优化研究

在实际生产中,截割破碎过程是多作用耦合的结果,离散元法(DEM)与多体动力学(MBD)双向耦合技术可实现煤机设备与煤壁的信息交互,符合实际生产情况,具有较大的优越性。为提高采煤机滚筒的工作性能,基于DEM-MBD双向耦合机理,结合力学性能试验和模拟试验得到实际工况参数,采用仿真软件EDEM和RecurDyn建立了采煤机滚筒截割煤壁的双向耦合模型,对仿真过程中滚筒所受的转矩和截割力进行分析,证明耦合效果和截割效果较好。设计了单因素试验和正交试验,分析了滚筒运行参数对工作性能的影响规律,并利用SPSS软件得到滚筒转速、截割深度、牵引速度对截割比能耗、装煤率、载荷波动系数的影响程度,通过现场试验验证了模型的可行性。构建了以滚筒转速、截割深度、牵引速度为决策变量,以截割比能耗、装煤率和载荷波动系数为目标的多目标优化模型,利用改进多目标灰狼(MOGWO)算法和优劣解距离法(TOPSIS)对模型进行求解,得出当滚筒转速为31.12 r/min、截割深度为639.4 mm、牵引速度为5.58 m/min时,采煤机滚筒的工作性能最优,此时截割比能耗为0.467 7 kW·h/m³...     

纵轴式掘进机截割头载荷影响因素的仿真分析

针对现有掘进机截割头载荷特性研究方法采用单一影响因素不能全面反映截割头载荷及其波动变化规律的问题,通过分析截割头瞬时载荷,确定了纵轴式掘进机在水平截割工况下截割头载荷的主要影响因素有截割岩石特性、截割头掏槽深度、截割头吃刀深度、截割头转速和截割臂摆速。针对某纵轴式掘进机水平截割工况,采用Matlab对影响截割头载荷的多种因素进行仿真分析,得到了各向载荷及其波动随各因素的变化规律:截割头载荷随着岩壁普氏系数的增大而增加,其中横向阻力增加尤为明显,横向阻力波动程度高于其他方向载荷,且随着岩壁普氏系数的增大呈减小趋势;随着截割头掏槽深度的增加,截割头各向载荷近似呈线性增加,其中升力增加幅度最大,各向载荷波动则随着截割头掏槽深度的增大而减小;随着吃刀深度的增加,截割头载荷总体呈增大趋势,载荷波动程度则随之减小;在截割头转速一定的情况下,截割头载荷均随着截割臂摆速的增加而增大,在同一摆速下,截割头载荷随着截割头转速的减小而增大,横向阻力波动明显高于升力和推进阻力波动,横向阻力和推进阻力波动按截割头载荷规律变化,升力波动则与之相反。截割头载荷波动变化规律与截割头载荷变化规律不尽一致,有时甚至相互冲突。因此,掘进机作业过程中应合理选择截割头掏槽深度、吃刀深度等操作参数和截割头转速、截割臂摆速等运动参数,使各参数相互匹配,以减小掘进机振动,延长使用寿命。     

基于预测控制的采煤机滚筒自动调高系统

为了快速跟随工作面顶板的起伏变化,提高采煤机截割滚筒调高系统的响应速度,防止截割顶板而造成部件的损坏,利用预测控制的理论和方法,建立了基于预测控制的采煤机截割滚筒自动调高控制系统,该系统通过历史数据对煤岩界面进行预测,实时调节调高油缸的位移,使采煤机的截割滚筒跟随煤岩界面。利用MATLAB/simulink构建了该系统的仿真模型,仿真试验表明:该系统对截割滚筒高度具有超前预见性,较常规传统控制系统的调节时间缩短0.25s,超调量减小4.8%,反应灵敏、波动小、工作平稳。预测算法中采样点的增多,对滚筒高度的波动和超调量有减小作用,但是调节时间增大。     

Optimization of cutting conditions during cutting by using neural networks

Optimum selection of cutting conditions importantly contribute to the increase of productivity and the reduction of costs, therefore utmost attention is paid to this problem in this contribution. In this paper, a neural network-based approach to complex optimization of cutting parameters is proposed. It describes the multi-objective technique of optimization of cutting conditions by means of the neural networks taking into consideration the technological, economic and organizational limitations. To reach higher precision of the predicted results, a neural optimization algorithm is developed and presented to ensure simple, fast and efficient optimization of all important turning parameters. The approach is suitable for fast determination of optimum cutting parameters during machining, where there is not enough time for deep analysis. To demonstrate the procedure and performance of the neural network approach, an illustrative example is discussed in detail.     

Sequential optimization approach for nesting and cutting sequence in laser cutting

The economy of the laser cutting process depends on two productivity issues: (i) nesting, a classic problem of finding the most efficient layout for cutting parts with minimum material waste; (ii) cutting sequence, which targets the optimal sequence of edges of the parts to be cut for minimum cycle time. This paper presents a two stage sequential optimization procedure for nesting and cutting sequence for the objectives of maximizing material utilization and minimization of ideal (non-cut) travel distance of laser cut tool. However, the focus of this paper is the development of solution technique for optimal cutting sequence to any given layout. Simulated annealing algorithm (SAA) is considered to evolve the optimal cutting sequence. The proposed SAA is illustrated with the optimal material utilization layout obtained using sheet cutting suite software, a professional rectangular nesting software package. The robust test carried out with five typical problems shows that the SAA proposed for cutting sequence is capable of providing near optimal solutions. The performance comparison with two literature problems reveals that the proposed SAA is able to give improved result than GA and ACO algorithms.     

Automated cutting tool selection and cutting tool sequence optimisation for rotational parts

The aim of this work is to define computer-aided optimum operation and tool sequences that are to be used in Generative Process Planning System developed for rotational parts. The software developed for this purpose has a modular structure. Cutting tools are selected automatically using the machinability data, workpiece feature information, machine tool data, workholding method and the set-up number. An optimum tool sequence is characterised by a minimum number of tool changes and minimum tool travel time. Tool and operation sequence for minimum tool change are optimised with a developed optimisation method that is based on “Rank Order Clustering”.     

Micro cutting of steel

Micro-cutting offers good potentialities in order to manufacture small and medium lot sizes of micro-parts with arbitary geometry at an economically reasonable expense. Either by direct machining or as a means to fabricate moulds for micro injection moulding, the major advantages turn out to be large removal rates, good compliance with tolerance ranges, high surface quality and a wide choice of materials which can be processed. Particularly if highly wear resistant materials are to be processed, as it is the case in mould fabrication for powder injection moulding, micro cutting of steel is a very eligible option. Consequently, the possibility to manufacture wear resistant micro structures of high aspect ratios by mechanical cutting is demonstrated with regard to its specific requirements in terms of transferability of the laboratory process into an industrial manufacturing process. Accordingly the paper focuses on process parameters and repeatability of machining results and machining capabilities.The work presented here is part of a cooperation of various institutes at the University of Karlsruhe and the Research Center of Karlsruhe (FZK) and is financially funded by the Deutsche Forschungsgemeinschaft DFG (german society for research). The close cooparation with the Institute of Material Science and Engineering (iwkl) of the University of Karlsruhe (TH) has been particularly beneficial for this research. The experiments with modifications of the tool were carried out at Forschungszentrum Rossendorf.     

Die-cavity pocketing via cutting simulation

For die-cavity pocketing, the cavity volume is sliced into a number of cutting-layers by horizontal cutting-planes, and each layer is pocket-machined using the contour-parallel offset method in which the tool-paths are obtained by repeatedly offsetting the boundary-pocketing curve. The major challenges in die-cavity pocketing include: 1) finding a method for obtaining the boundary-pocketing curve, 2) generating evenly spaced contour-parallel offset toolpaths, 3) detecting and removing uncut-regions, and 4) estimating chip-loads for an adaptive feed control. No systematic solution for these problems has been offered in the literature, except the curve offsetting methods for computing contour-parallel offset curves. Presented in the article is a straightforward approach to die-cavity pocketing, in which all the four challenges are handled successfully by using the existing cutting-simulation methods.     

删除边的免疫策略

为了使用更少的免疫数量且更快地消灭病毒,提出了基于删除边的免疫策略。该策略根据边与重要节点之间的关系,对重要节点直接相连的边或任意两个重要节点与其共同邻居节点之间的边进行免疫。实验使用SIS病毒传播模型,分别在ER随机网络、BA无标度网络和几种实际网络中测试了该策略的免疫临界值以及对应网络的连通度,结果表明：删除边的免疫策略与目标免疫策略相比可以通过免疫较少的节点来消灭病毒,并且可以更好地保持网络的连通性。     

无嫉妒蛋糕分配中的谎言

对于给定的任意一个蛋糕分配算法,研究了玩家能从谎报中获取多大的利益。考虑两种类型的玩家：风险寻求玩家和风险厌恶玩家,并且把玩家的价值密度函数限制为分段常数。证明了风险寻求玩家和风险厌恶玩家均不能从谎报中获取更多利益。但如果只允许算法在蛋糕上切[n-1]刀,证明了玩家通过谎报能够拿到多出[Θ(n)]倍的利益。     

Algorithms for 3D guillotine cutting problems: Unbounded knapsack, cutting stock and strip packing

We present algorithms for the following three-dimensional (3D) guillotine cutting problems: unbounded knapsack, cutting stock and strip packing. We consider the case where the items have fixed orientation and the case where orthogonal rotations around all axes are allowed. For the unbounded 3D knapsack problem, we extend the recurrence formula proposed by [1] for the rectangular knapsack problem and present a dynamic programming algorithm that uses reduced raster points. We also consider a variant of the unbounded knapsack problem in which the cuts must be staged. For the 3D cutting stock problem and its variants in which the bins have different sizes (and the cuts must be staged), we present column generation-based algorithms. Modified versions of the algorithms for the 3D cutting stock problems with stages are then used to build algorithms for the 3D strip packing problem and its variants. The computational tests performed with the algorithms described in this paper indicate that they are useful to solve instances of moderate size.     

Mesh cutting during real-time physical simulation

The ability to cut through meshes in real-time is an essential ingredient in a number of practical interactive simulations. Surgical simulation, cloth design, clay sculpting and many other related VR applications require the ability to introduce arbitrary discontinuities through models to separate, reposition, and reshape various pieces of the model as needed for the target application. In addition, in order to provide the necessary realism for these applications, model deformations must be computed from an underlying physically-based model—most commonly a continuum-based finite element model.In this work, we present a method for representing and computing, at interactive rates, the deformations of a mesh whose topology is being dynamically modified with multiple virtual tools. The method relies on introducing controlled discontinuities in the basis functions used to represent the geometry of deformation, and on fast incremental methods for updating global model deformations. The method can also generate the forces needed for force rendering in a haptic environment. The method is shown to scale well with problem size (linearly in the number of nonzeros of the Cholesky factor) allowing realistic interaction with fairly large models.