一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。     

基于SVD和SSA-VMD降噪的轴承故障特征提取

针对强噪声背景下轴承故障特征提取困难的问题，提出一种基于奇异值分解和参数优化变分模态分解联合降噪的轴承故障特征提取方法(SSVMD)：首先，对原始信号进行奇异值分解(Singular Value Decomposition，SVD)处理，运用奇异值差分谱法选取有效奇异值并将原始信号重构得到初步降噪信号；其次，为防止故障信息丢失，将残余信号进行麻雀算法(Sparrow Search Algorithm，SSA)优化的变分模态分解(Variational Mode Decomposition，VMD）算法处理，得到最佳的模态个数K和惩罚参数α，选取峭度值最大、包络熵最小的IMF分量与初步降噪信号叠加得到最终降噪信号，并对信号进行包络分析；最后，通过仿真和试验数据分析得出，该方法能在信噪比很低的情况下降低噪声含量并提取轴承故障特征，为设备的状态监测和故障诊断提供理论依据。     

立井过砂岩富含水层工作面预注浆分析

郑煤集团杨河煤业43采区樊寨副立井施工中需要穿过预计涌水量187 m³/h、厚57 m的砂岩含水层。针对第1回次采用普通水泥工作面预注浆、吸浆量少、升压快、效果差、达不到预期目的等不利情况，在后3回次采用大压力，白银水泥、超细水泥等新材料、单孔上下端正反同时注浆新工艺，采用压注清水、水玻璃，利用水玻璃的黏性，反复冲洗钻孔把细小裂隙中锈蚀颗粒带出，打开注浆通道，同时针对竖向裂隙多、横向裂隙不联系，加密钻孔布置，缩小注浆段高，取得了较好的注浆效果。     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

塔河奥陶系隐蔽溶洞体地震精细识别

实际钻探结果表明，塔河奥陶系发育T₇⁴强轴屏蔽型溶洞体和强“串珠”屏蔽型溶洞体，部分溶洞体产能较高，初步显示了较大的开发潜力。由于该类储集体埋深大（超过5300m）、地震资料主频较低（约28Hz），地震分辨率为30m（约1/4波长）；同时小型溶洞体尺度小，地震响应较弱，地震异常特征不明显，预测强“串珠”储集体的方法明显不适用，亟需加强预测方法研究。为此，在钻、测井资料解释基础上，针对T₇⁴强轴屏蔽型溶洞体，首次采用主成分分析技术克服强子波匹配不足或匹配过度等稳定性问题，有效剥离T₇⁴强干扰，增强隐蔽缝洞体地震响应特征；针对强“串珠”屏蔽型溶洞体，采用低频模型优化的地质统计学反演去除强“串珠”子波旁瓣干扰，以增强隐藏在强子波旁瓣中的缝洞体的辨识度，精细预测隐蔽溶洞体。结果表明，对溶洞体的纵向辨识能力明显提高，可刻画8m厚的溶洞体，反演结果与钻测井符合率达83%，可靠性较高。     

Study of planar structure applying reciprocity technique combined with MGEC and analysis of discontinuity

The 3D structure electromagnetic computation presents several difficulties related to the volume mesh. In fact, the entire volume space must be taken into account even the smallest details. In this article, we propose a formulation based on the reciprocity theorem combined with the generalized equivalent circuit method to model a planar 3D structure with both coaxial and planar excitation. The major advantage of this formulation is the fact to reduce the computational volume into 2D ones in the discontinuity plane. In addition, we focused on the calculation of the discontinuity between the excitation source and the planar structure to determine the exact behavior of the electric coaxial excitation model. The obtained current density, electric field distributions, and the input impedance are presented and discussed in the following sections. An approximately good agreement of input impedance with those obtained by the simulator and measurement is shown.     

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.