基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Eco-friendly tape casting of borosilicate glass/Al2O3 sheets for LTCC applications

This work reports the innovative development of a borosilicate glass/Al₂O₃ tape for LTCC applications using an eco-friendly aqueous tape casting slurry. Polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) were the respective dispersants, while carboxymethyl cellulose (CMC) and styrene acrylic emulsion (SA) were the respective binders. The results showed that PVP was more suitable than PAA as the dispersant for the aqueous casting slurry, and that 1.5 wt% PVP would achieve well dispersion of CABS glass/Al₂O₃ powder in the aqueous slurry. Moreover, a small amount of 2.0 wt% CMC binder could yield smooth CABS glass/Al₂O₃ tapes crack free. A high-quality CABS glass/Al₂O₃ tape with a smooth surface was made from an aqueous slurry containing 1.5 wt% PVP dispersant, 2.0 wt% CMC binder, and 2.0 wt% PEG-400 plasticizer. The density, tensile strength, and surface roughness of the green tape were 2.05 g/cm³, 0.87 MPa, and 148 nm, respectively. The resulting CABS glass/Al₂O₃ composites sintered at 875 °C exhibited a bulk density of 3.14 g/cm³, a dielectric constant of 8.09, a dielectric loss of 1.0 × 10^?3, a flexural strength of 213 MPa, a thermal expansion coefficient of 5.30 ppm/^°C, and a thermal conductivity of 3.2 W m^?1 K^?1, thus demonstrating its broad prospects in LTCC applications.     

基于机器视觉的轮胎表面缺陷检测系统的研究与应用

在传统的轮胎表面缺陷依靠人工检测,存在劳动强度高、受人的主观影响大以及效率低下的问题。针对这一现象,研究了一种基于机器视觉的轮胎表面缺陷3D检测系统。该系统依靠机器视觉系统获取检测轮胎的表面图像,然后创建3D模型、判定缺陷类型,最终实现实时自动预警,为轮胎生产商提供一种自动化检测方案。系统集成了先进的技术、软件和工具,配套的信息管控系统可以对轮胎型号和生产数据进行采集、存储、分析,以便在生产过程中实现更高效、更可靠的质量控制,具有较高的实际应用推广价值。     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

Anisotropic thermal expansion and ionic conductivity of a crystal-oriented,Mg2+-conducting NASICON-type solid electrolyte

Multivalent ion-conducting ceramics are required for the manufacture of high-safety, high-capacity rechargeable batteries. However, the low ionic conductivity of solid electrolytes and discrepancies in the thermal expansion between the battery components limit their widespread application. Furthermore, anisotropic thermal expansion in crystals during battery manufacturing and the charge-discharge cycles causes the formation of microcracks, which degrade the battery performance. The physical properties of ceramic materials with anisotropic crystal structures can be modified by varying the crystallographic orientation of their grains. In this study, a co-precipitation approach was used to synthesize an Mg²⁺-conducting (Mg_0.1Hf_0.9)_4/3.8Nb(PO₄)₃ solid electrolyte, and the grain orientation in the bulk sample was controlled using strong magnetic fields during the slip casting process. The results showed that inducing an orientation along the c-axis enhanced the apparent ionic conductivity of the bulk sample. It was also observed that (Mg_0.1Hf_0.9)_4/3.8Nb(PO₄)₃ crystal has a negative volumetric thermal expansion despite a positive linear thermal expansion along its c-axis. By adjusting the c-axis orientation of the grains, (Mg_0.1Hf_0.9)_4/3.8Nb(PO₄)₃ electrolytes with negative or positive linear thermal expansion coefficient have been produced. The findings of this study suggest that solid-electrolytes with negative, positive, or zero linear thermal expansion can be produced to create more compatible and higher-performance solid-state devices.     

Earliness–tardiness minimization on scheduling a batch processing machine with non-identical job sizes

This paper considers the scheduling problem of minimizing earliness–tardiness (E/T) on a single batch processing machine with a common due date. The problem is extended to the environment of non-identical job sizes. First, a mathematical model is formulated, which is tested effectively under IBM ILOG CPLEX using the constraint programming solver. Then several optimal properties are given to schedule batches effectively, and by introducing the concept of ARB (Attribute Ratio of Batch), it is proven that the ARB of each batch should be made as small as possible in order to minimize the objective, designed as the heuristic information for assigning jobs into batches. Based on these properties, a heuristic algorithm MARB (Minimum Attribute Ratio of Batch) for batch forming is proposed, and a hybrid genetic algorithm is developed for the problem under study by combining GA (genetic algorithm) with MARB. Experimental results demonstrate that the proposed algorithm outperforms other algorithms in the literature, both for small and large problem instances.     

Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.     

Hierarchical electromagnetic absorption in micro-waveguide stuffed with magnetic media for resin-based composites of graphene nanosheets and manganese oxides

Waveguide configurations of hierarchical system are proposed as new microstructures for composites in absorbing enhancement. Supercritical fluid (SCF) one-pot exfoliation of layered graphite and manganese oxide mixing materials is developed to obtain a hierarchical system, containing graphene nanosheets (GNS) and exfoliated manganese oxides (EMO) in different sizes. Composites with GNS–EMO embedded in epoxy resin matrix are produced for a design of dielectric and magnetic loss integrated absorber. Volume fraction of GNS–EMO in composites is given for an optimal quantity of resin epoxy in fixation and formation. The effect of mixing ratios between electric and magnetic components is provided for the design of dielectric and magnetic loss integrated absorbers. Frequency shifting phenomena are revealed in the component adjusting course. Excluding the offsetting sizes, reflection loss of composites is enhanced as thickness increases. Synergistic effect of electric and magnetic coordinated materials demonstrates the superiority of micro-waveguide structures in GNS–EMO composite absorber.     

烧结机卸料装置耐磨性改善

烧结机导料箱、单辊破碎机和卸料漏斗承载着烧结热矿的导料、破碎与输送,是烧结生产的重要组成部分。高温、重载的工况环境决定着机尾卸料装置必须具有抗磨损、耐高温的特性。针对邯钢1^#435m^2烧结机机尾关键部件耐磨工作面寿命短,更换不方便等问题,分析磨损机理与失效原因,提出改进抗磨工作面结构,升级耐磨材料,优化焊接工艺等措施。通过技术方案的实施,使烧结机导料箱、单辊破碎机和卸料漏斗等卸料装置维持了较高的抗磨损性能,达到了预期的改造效果。     

Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.