Inverse kinematics and error analysis of cooperative welding robot with multiple manipulators

Precise welding of the T-joints between aircraft hyperbolic panels and stringers is required. Therefore, a method of solving inverse kinematics equations for a cooperative welding robot with multiple manipulators based on neural networks was investigated. To build an effective Denavit-Hartenberg(DH)model for this robot, sample data was obtained considering the movement ranges of the robot joints.Based on back propagation(BP) and radial basis function(RBF) neural networks, 18 joint sub-spaces were mapped to the workspaces of three manipulators. The high-dimensional and nonlinear inverse kinematics problem was transformed into a multi-input and multi-output prediction model. The results revealed that the prediction model of solving the cooperative welding robot kinematics equations was quite accurate. Moreover, compared with the BP-based model, the calculation process of the RBF-based prediction model was slower, but yielded more accurate predictions.

Research on multiple elimination methods in inverse data space based on randomized singular value decomposition

Based on surfaced-related multiple elimination （SRME） , this research has derived the methods on multiples elimination in the inverse data space. Inverse data processing means moving seismic data from forward data space （FDS） to inverse data space （ IDS） . The surface-related multiples and primaries can then be sepa-rated in the IDS, since surface-related multiples wi l l form a focus region in the IDS. Muting the multiples ener-gy can achieve the purpose of multiples elimination and avoid the damage to primaries energy during the process of adaptive subtraction. Randomized singular value decomposition （ RSYD） is used to enhance calculation speed and improve the accuracy in the conversion of FDS to IDS. The synthetic shot record of the salt dome model shows that the relationship between primaries and multiples is simple and clear, and RSVD can easily eliminate multiples and save primaries energy. Compared with conventional multiples elimination methods and ordinary methods of multiples elimination in the inverse data space, this technique has an advantage of high cal-culation speed and reliable outcomes.

Modified constructions of binary sequences using multiplicative inverse

Two new families of finite binary sequences are constructed using multiplicative inverse. The sequences are shown to have strong pseudorandom properties by using some estimates of certain exponential sums over finite fields. The constructions can be implemented fast since multiplicative inverse over finite fields can be computed in polynomial time.

Inverse scattering method and soliton solution family for the Einstein-Maxwell theory with multiple Abelian gauge fields

A Hauser-Ernst-type extended hyperbolic complex linear system given in our previous paper [Gao Y J 2004 Chin. Phys. 13 602] is slightly modified and used to develop a new inverse scattering method for the stationary axisymmetric Einstein-Maxwell theory with multiple Abelian gauge fields. The reduction procedures in this inverse scattering method are found to be fairly simple, which makes the inverse scattering method be fine and effective in practical application. As an example, a concrete family of soliton solutions for the considered theory is obtained.

Space Complexity of Algorithm for Modular Multiplicative Inverse

In certain computational systems the amount of space required to execute an algorithm is even more restrictive than the corresponding time necessary for solution of a problem. In this paper an algorithm for modular multiplicative inverse is introduced and its computational space complexity is analyzed. A tight upper bound for bit storage required for execution of the algorithm is provided. It is demonstrated that for range of numbers used in public-key encryption systems, the size of bit storage does not exceed a 2K-bit threshold in the worst-case. This feature of the Enhanced-Euclid algorithm allows designing special-purpose hardware for its implementation as a subroutine in communication-secure wireless devices.

Enhanced Euclid Algorithm for Modular Multiplicative Inverse and Its Application in Cryptographic Protocols

Numerous cryptographic algorithms (ElGamal, Rabin, RSA, NTRU etc) require multiple computations of modulo multiplicative inverses. This paper describes and validates a new algorithm, called the Enhanced Euclid Algorithm, for modular multiplicative inverse (MMI). Analysis of the proposed algorithm shows that it is more efficient than the Extended Euclid algorithm (XEA). In addition, if a MMI does not exist, then it is not necessary to use the Backtracking procedure in the proposed algorithm;this case requires fewer operations on every step (divisions, multiplications, additions, assignments and push operations on stack), than the XEA. Overall, XEA uses more multiplications, additions, assignments and twice as many variables than the proposed algorithm.

Heat, Resolvent and Wave Kernels with Multiple Inverse Square Potential on the Euclidian Space Rⁿ

In this paper, the heat, resolvent and wave kernels associated to the Schr?dinger operator with multi-inverse square potential on the Euclidian space Rn are given in explicit forms.

Multiplicity of solutions to geophysical inversion reflected by rupture slip distribution of the 2015 Nepal earthquake

The equivalence of geophysical fields, the finiteness of measurements and the measurement errors make the result of geophysical inversion non-unique. For example, the measurements and inversion method used, the priori rupture model determined and the slip distribution smoothing factor selected will have significant influences on the earthquake rupture slip distribution. Using different data and methods, different authors have given different rupture slip distribution models of the 2015 Mw7.9 Nepal earth- quake, with the maximum slip ranging from 3.0 m to 6.8 m. In this paper, geometry parameters of the single rectangular fault model in elastic half-space were inferred constraining with the Global Posi- tioning System （GPS） and Interferometric Synthetic Aperture Radar （InSAR） coseismic deformations and bounding the slip with approximate average value; and then, the single rectangular fault was divided into multiple sub-faults, and the final slip smoothing factor, the final slip distribution and the maximum slip were determined with the misfit-roughness tradeoff curve, the cross-validation sum of squares （CVSS） and the third-party observation data or indexes being comprehensively taken into account. The results show that, the rupture of the Nepal earthquake extended by over 100 km east by south. The maximum slip of the earthquake was about 6.5-6.7 m, and most of the slip is confined at depths of 8 -20 kin, consistent with the depth distribution of aftershocks. The method for reducing the multiplicity of solutions to rupture slip distribution in this paper was ever used in inversion of rupture slip distri- bution for the 2008 Wenchuan and 2013 Lushan earthquakes, and the third-party measurement - surface dislocation has very large effect on reducing the multiplicity of solutions to inversion of the Wenchuan earthquake. Other priori information or indicators, such as fault strike, dip, earthquake magnitude, seismic activity, Coulomb stress, and seismic period, can be used for beneficial validation of and comparison with inversion results.

Detection performance and inversion processing of logging-while-drilling extra-deep azimuthal resistivity measurements

We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.

Internal Multiple Prediction Based on Imaging Profile Prediction and Kirchhoff Demigration

This paper introduces an internal multiple prediction method based on imaging profile prediction and Kirchhoff demigration.First,based on an inputted prestack time migration profile,the method predicts the prestack time migration profile that only includes internal multiples by inverse scattering series method.Second,the method uses velocity-weighted Kirchhoff demigration to create shot gathers that contains only internal multiples.Internal multiple prediction based on the prestack time migration profile effectively reduces the computational cost of multiple predictions,and the internal-multiple shot gathers created by Kirchhoff demigration remarkably reduces the complexity of the practical problem.Internal multiple elimination can be conducted through the combined adaptive multiple subtraction based on event tracing.Synthetic and field data tests show that the method effectively predicts internal multiples and possesses considerable potential in field data processing,particularly in areas where internal multiples develop seriously.

Prestack AVA joint inversion of PP and PS waves using the vectorized reflectivity method

Most current prestack AVA joint inversion methods are based on the exact Zoeppritz equation and its various approximations. However, these equations only reflect the relation between reflection coefficients, incidence angles, and elastic parameters on either side of the interface, which means that wave-propagation effects, such as spherical spreading, attenuation, transmission loss, multiples, and event mismatching of P-and S-waves, are not considered and cannot accurately describe the true propagation characteristics of seismic waves. Conventional AVA inversion methods require that these wave-propagation effects have been fully corrected or attenuated before inversion but these requirements can hardly be satisfied in practice. Using a one-dimensional(1 D) earth model, the reflectivity method can simulate the full wavefield response of seismic waves. Therefore, we propose a nonlinear multicomponent prestack AVA joint inversion method based on the vectorized reflectivity method, which uses a fast nondominated sorting genetic algorithm(NSGA II) to optimize the nonlinear multiobjective function to estimate multiple parameters, such as P-wave velocity, S-wave velocity, and density. This approach is robust because it can simultaneously cope with more than one objective function without introducing weight coefficients. Model tests prove the effectiveness of the proposed inversion method. Based on the inversion results, we find that the nonlinear prestack AVA joint inversion using the reflectivity method yields more accurate inversion results than the inversion by using the exact Zoeppritz equation when the wave-propagation effects of transmission loss and internal multiples are not completely corrected.

High resolution 3D nonlinear integrated inversion

The high resolution 3D nonlinear integrated inversion method is based on nonlinear theory. Under layer control, the log data from several wells （or all wells） in the study area and seismic trace data adjacent to the wells are input to a network with multiple inputs and outputs and are integratedly trained to obtain an adaptive weight function of the entire study area. Integrated nonlinear mapping relationships are built and updated by the lateral and vertical geologic variations of the reservoirs. Therefore, the inversion process and its inversion results can be constrained and controlled and a stable seismic inversion section with high resolution with velocity inversion, impedance inversion, and density inversion sections, can be gained. Good geologic effects have been obtained in model computation tests and real data processing, which verified that this method has high precision, good practicality, and can be used for quantitative reservoir analysis.

A high resolution inversion method for fluid factor with dynamic dryrock V_(P)/V_(S) ratio squared

As an important indicator parameter of fluid identification,fluid factor has always been a concern for scholars.However,when predicting Russell fluid factor or effective pore-fluid bulk modulus,it is necessary to introduce a new rock skeleton parameter which is the dry-rock VP/VS ratio squared(DVRS).In the process of fluid factor calculation or inversion,the existing methods take this parameter as a static constant,which has been estimated in advance,and then apply it to the fluid factor calculation and inversion.The fluid identification analysis based on a portion of the Marmousi 2 model and numerical forward modeling test show that,taking the DVRS as a static constant will limit the identification ability of fluid factor and reduce the inversion accuracy.To solve the above problems,we proposed a new method to regard the DVRS as a dynamic variable varying with depth and lithology for the first time,then apply it to fluid factor calculation and inversion.Firstly,the exact Zoeppritz equations are rewritten into a new form containing the fluid factor and DVRS of upper and lower layers.Next,the new equations are applied to the four parameters simultaneous inversion based on the generalized nonlinear inversion(GNI)method.The testing results on a portion of the Marmousi 2 model and field data show that dynamic DVRS can significantly improve the fluid factor identification ability,effectively suppress illusion.Both synthetic and filed data tests also demonstrate that the GNI method based on Bayesian deterministic inversion(BDI)theory can successfully solve the above four parameter simultaneous inversion problem,and taking the dynamic DVRS as a target inversion parameter can effectively improve the inversion accuracy of fluid factor.All these results completely verified the feasibility and effectiveness of the proposed method.

Breakthrough and significance of technology on internal multiple recognition and suppression: A case study of Ordovician Dengying Formation in Central Sichuan Basin, SW China

Aimed at the serious mismatch between the synthetic seismogram and the real data of the Sinian Dengying Formation and the Lower Cambrian Qiongzhusi Formation in the GS1 well area, Sichuan Basin, four aspects of internal multiples identification and suppression were studied. Firstly, a forward modeling method of internal multiple based on reflectivity method was developed. Through eight means such as post-stack and pre-stack forward modeling of internal multiple, and combined with VSP data, it was demonstrated that well-seismic mismatching in this area is mainly caused by the internal multiples. Secondly, the simulation results of internal multiple forward modeling using the stripping method combined with the internal multiple periodicity analysis showed that four groups of overburden layers with velocity inversion were the main sources of the internal multiples. Thirdly, by identifying internal multiples accurately and using suppression technology based on pattern recognition, an effective and replicable suppression scheme suitable for these formations was established, overcoming the difficulty of the small speed difference between internal multiple and primary reflection wave which makes the current methods ineffective. Fourthly, an evaluation index of internal multiple intensity was proposed, and the internal multiple intensity distribution diagram of the fourth member of Dengying Formation(Deng-4 Member) in Gaoshiti-Moxi area was compiled. This scheme greatly improved the well-seismic match, and the strata sedimentary features are clearer on the new seismic profiles with higher lateral resolution, with which smaller faults and geological anomalies can be identified and a series of the bead reflections in the Dengying Formation are first discovered. The coincidence rate of reservoir prediction based on seismic waveform classification was increased from 60% to 90%, and that of hydrocarbon detection based on dual phase medium theory was increased from 70% to 100%.

基于MLR–ANN算法的地应力场反演与裂缝预测

中国页岩气储层埋藏深,受构造运动影响,地应力分布规律复杂,传统方法很难准确反演区域地应力大小和方向。提出多元线性回归和人工神经网络的耦合算法,对川南长宁—建武区块的页岩气储层及周边地应力场进行反演,并采用综合破裂系数法,对储层裂缝进行预测,划分裂缝发育区域。研究表明,基于多元回归和神经网络的耦合算法能准确反演区域的地应力场分布规律。研究区的地应力以挤压应力为主,方向在NE115°左右。受构造运动产生的断层周边应力较为集中,易发育剪切裂缝,裂缝以发育和较发育程度为主。研究区在邻近龙马溪组底部的五峰组上段和构造大断层部位裂缝发育程度较高。研究成果对该区块完善页岩气开采的井网布置、压裂优化设计和套管损坏防治等有一定的参考价值。

一种高效轻量的双参数椭圆曲线数字签名批量验证方案

为解决大规模交易任务的签名验证给区块链节点带来繁琐的开销和经典的椭圆曲线数字签名算法(ECDSA)中耗时的模逆运算,提出一种高效轻量的双参数椭圆曲线数字签名(TP-ECDSA)批量验证方案。一方面,TP-ECDSA在签名和验证阶段均无模逆运算,在该算法中引入批量验证能将标量乘的计算次数从2t减少到[2,t+1]。另一方面,KGLP算法能加速标量乘运算,引入该算法能显著地提升签名验证的效率。实验表明,与ECDSA相比,不论是独立验证还是批量验证,TP-ECDSA的运行速度均提高了50%以上,签名验证效率显著提升。

深江铁路洪奇沥公铁两用大桥主桥方案构思与总体设计

深江铁路洪奇沥公铁两用大桥主桥采用(3×100+808+3×100)m超短边跨钢-混组合混合梁斜拉桥,一跨跨越通航水域。该桥公铁分层布置,上层布置8车道城市快速路,下层布置4线铁路。主梁采用倒梯形双主桁截面,桥面布置紧凑、受力明确、经济性好。中跨主梁采用板桁-箱桁组合结构钢梁,桥面结构参与主桁受力,具有高效综合性能。边跨主梁采用矩形钢管混凝土叠合板-桁组合梁,融结构受力和锚固压重于一体,叠合板采用32 cm厚预制板+40 cm厚现浇层。钢-混结合段采用“钢格室+承压板”构造,钢-混结合面位于桥塔向中跨侧4.6 m。桥塔采用H形混凝土塔,基础采用35根直径4.0 m的大直径钻孔灌注桩。斜拉索采用标准抗拉强度2000 MPa的平行钢丝成品索,最大规格为PES(C)7-547。索梁锚固采用副桁弦杆节点兜底钢锚箱结构,传力可靠、抗疲劳性能好。索塔锚固创新地采用自平衡交叉混合锚固技术,以适应大规格斜拉索锚固。钢桁梁采用“纵向分段、横向分区”制造、运输、现场吊装的施工方案。

基于无人机遥感的多特征组矿区草本植物地上生物量反演

植被地上生物量可作为评价矿山生态修复地生态功能的重要指标,为实现对修复地地上植被生物量快速、准确的预测,以安徽省铜陵市铜官山矿区草本植物地上生物量为研究对象,将无人机高分辨率多光谱影像作为数据源,提取了单波段光谱反射率、植被指数两种光谱特征以及各波段纹理特征变量,并利用高精度DEM(digital elevation model)生成地形特征,再先后使用灰色关联法和熵权法对光谱特征和纹理特征分别进行筛选,进而将筛选出的特征变量和地形特征变量分为光谱特征组和多特征组。采用反向传播神经网络(back propagation neural network,BPNN)、卷积神经网络(convolutional neural network,CNN)以及Elman神经网络3种机器学习算法分别构建基于光谱特征组和多特征组的生物量预测模型,比选精度较高的矿区草本植物地上生物量反演模型。结果表明,在光谱特征基础上引入纹理特征和地形特征后3种反演模型精度都有相应程度提高,其中,基于多特征组构建的BPNN模型表现出最优性能,其决定系数(R2)为0.841,均方根误差为11.813 g·m-2,并同时对3种模型进行交叉验证,进一步证明了基于多特征组的BPNN模型更加稳定,反演精度最优。然后,采用最优反演模型对研究区域内植被生物量进行分级评估,结果显示区内生物量集中于20~40 g·m-2,研究区域内植被生物量整体偏低。研究结果可为矿区草本植物生物量反演研究提供理论支持。

应用保幅逆散射成像条件的全波场偏移方法

地震波传播机制与成像机理逐渐成熟化、系统化,对于多次散射波的处理不再局限于噪声去除,而是将其用于高精度地震成像。不同于基于单次散射的常规成像方法,全波场偏移是一种基于多次散射假设与反演理论的数据驱动成像方法。基于逆散射成像理论,对现有全波场偏移的成像条件进行改进,发展了一种保幅逆散射成像条件,实现了高精度地震成像。该成像条件是通过对已有的直达波估计与下行格林函数互相关成像条件添加拉普拉斯滤波和照明项,衰减后向散射并补偿深部能量。相较于原有成像条件,改进后的保幅逆散射成像条件对于复杂构造具有更高的成像精度和更强的适应性。数值测试验证了方法的有效性和适用性。

地震资料层间多次波压制方法研究进展

层间多次波压制是目前困扰油气地震勘探的难题之一。为推动层间多次波压制方法的发展,对层间多次波预测及自适应相减方法的研究进展进行了调研,总结了共聚焦点技术、地表数据分离法、逆散射级数法、虚同相轴法、Marchenko自聚焦方法等备受关注的层间多次波预测方法以及自适应相减法的发展进程,分析了上述方法的优缺点。共聚焦点技术中层相关算法相比边界算法具有更强的适应性,但以牺牲计算成本为代价;逆散射级数法虽然具有较高的多次波预测精度,但是巨大的计算量限制了其推广应用;地表数据分离法和虚同相轴法虽然具有较高的计算效率,但是数据分离过于依赖人工操作;Marchenko自聚焦方法目前在实际应用中尚不成熟。自适应相减方法在一次波和多次波非正交情况下的局限性导致了层间多次波压制方法的诞生。在保证层间多次波压制效果的前提下提高计算效率以及实用性,是当前层间多次波压制方法的重要发展方向。结合目前研究热点,层间多次波压制方法与波形反演、深度学习等方法技术的结合可能是未来的发展趋势。