Intelligent Fault Identification for Rolling Bearings Fusing Average Refined Composite Multiscale Dispersion Entropy-Assisted Feature Extraction and SVM with Multi-Strategy Enhanced Swarm Optimization

Rolling bearings act as key parts in many items of mechanical equipment and any abnormality will affect the normal operation of the entire apparatus. To diagnose the faults of rolling bearings effectively, a novel fault identification method is proposed by merging variational mode decomposition (VMD), average refined composite multiscale dispersion entropy (ARCMDE) and support vector machine (SVM) optimized by multistrategy enhanced swarm optimization in this paper. Firstly, the vibration signals are decomposed into different series of intrinsic mode functions (IMFs) based on VMD with the center frequency observation method. Subsequently, the proposed ARCMDE, fusing the superiorities of DE and average refined composite multiscale procedure, is employed to enhance the ability of the multiscale fault-feature extraction from the IMFs. Afterwards, grey wolf optimization (GWO), enhanced by multistrategy including levy flight, cosine factor and polynomial mutation strategies (LCPGWO), is proposed to optimize the penalty factor C and kernel parameter g of SVM. Then, the optimized SVM model is trained to identify the fault type of samples based on features extracted by ARCMDE. Finally, the application experiment and contrastive analysis verify the effectiveness of the proposed VMD-ARCMDE-LCPGWO-SVM method.     

Enhancement of the electrocatalytic oxidation of dyeing wastewater (reactive brilliant blue KN-R) over the Ce-modified Ti-PbO2 electrode with surface hydrophobicity

Journal of Solid State Electrochemistry - Rational hydrophobic anode has been considered as a promising approach for water pollution remediation. However, the construction method of the hydrophobic...     

Minimum-time optimal control of robotic manipulators based on Hamel’s integrators

Meccanica - In this paper, we develop a framework of time optimization path planning for robotic manipulators surrounded by static obstacles. Our approach is based on the recursive dynamics method...     

富Mn鸢尾生物炭的制备及在类Fenton体系中的应用

通过在N₂气氛围下热裂解富集Mn的鸢尾可得到Mn/生物炭(BC)材料, 并按植物叶(Leaf)和根部(Root)分别将其分别命名为BC-L0, BC-L1, BC-L2, BC-R0, BC-R1和BC-R2. 采用扫描电子显微镜(SEM)、 能谱分析(EDS)仪、 X射线衍射(XRD)仪、 X射线光电子能谱(XPS)、 傅里叶变换红外光谱(FTIR)、 原子吸收光谱(AAS)和比表面积分析(BET)仪等对Mn/生物炭材料的Mn含量、 化学组成与形貌进行了表征, 发现鸢尾叶部为Mn主要富集部位, 最大富集量为13.0 mg/g, 且Mn以Mn₂O₃薄片存在于生物炭表面. 利用Mn/生物炭与H₂O₂构建了类Fenton体系, 在中性条件下BC-L2-H₂O₂体系对有机污染物罗丹明B(RhB, 3×10 ^-5 mol/L)的降解率达到50%(180 min), 表明该体系具备氧化去除RhB的能力, 并推测了该体系对RhB的催化氧化机理. 结果表明, 先将Mn超富集植物转化为Mn/生物炭材料, 再通过添加H₂O₂能构建具有氧化能力的类Fenton体系, 可用于对有机污染物的降解, 实现“以废治废”的绿色循环思路, 为Mn富集的植物后续处理提供一种新的转化及应用方式.     

Gradient systems and mechanical systems

All types of gradient systems and their properties are discussed. Two problems connected with gradient sys-tems and mechanical systems are studied. One is the direct problem of transforming a mechanical system into a gradi-ent system, and the other is the inverse problem, which is transforming a gradient system into a mechanical system.     

Discrete optimal control for Birkhoffian systems

In this paper, we investigate a discrete variational optimal control for mechanical systems that admit a Birkhoffian representation. Instead of discretizing the original equations of motion, our research is based on a direct discretization of the Pfaff–Birkhoff–d’Alembert principle. The resulting discrete forced Birkhoffian equations then serve as constraints for the minimization of the objective functional. In this way, the optimal control problem is transformed into a finite-dimensional optimization problem, which can be solved by standard methods. This approach yields discrete dynamics, which is more faithful to the continuous equations of motion and consequently yields more accurate solutions to the optimal control problem which is to be approximated. We illustrate the method numerically by optimizing the control for the damped oscillator.     

Variational integrators for fractional Birkhoffian systems

In this paper, we generalize the Pfaff–Birkhoff principle to the case of containing fractional derivatives and obtain the so-called fractional Pfaff–Birkhoff–d’Alembert principle. The fractional Birkhoff equations in the sense of Riemann–Liouville fractional derivative are derived. Under the framework of variational integrators, we develop the discrete fractional Birkhoff equations by approximating the Riemann–Liouville fractional derivative with the shifted Grünwald–Letnikov fractional derivative. The resulting algebraic equations can be served as an algorithm to numerically solve the fractional Birkhoff equations. A numerical example is demonstrated to show the validity and applicability of the presented methodology.     

Preparation and third-order nonlinear optical properties of self-organized complex oxide Ce:BaTiO3 quantum dots

Pulsed laser ablation epitaxial Strancky-Krastanow growth of self-organized complex oxide Ce:BaTiO3 quantum dots on MgO(100) substrates is demonstrated.Atomic force microscopy and X-ray diffraction are used to observe the structure and the growth process of the self-organized complex oxide quantum dots.The average dimension,height,and the density of self-organized complex oxide Ce:BaTiO3 quantum dots are given.The nonlinear refractive indexes of the wetting layer and the self-organized ordered quantum dots are determined by the single beam Z-scan method.The mechanisms of the nonlinear effect enhancement for these low-dimensional structure are discussed.