Research on transverse parametric vibration and fault diagnosis of multi-rope hoisting catenaries

According to application characteristics of the multi-rope friction hoisting catenaries, a linear transverse parametric vibration model of axially moving string was setup with fixed length and inhomogeneous boundary conditions. The Galerkin method was applied to discretize the dynamic governing equations. Using the Newmark method, the coupling coefficient second-order ODEs were solved. The parametric resonance vibrations of catenaries generated by tension variation along with forced boundary excitations were diagnosed with analytical and experimental validations. The transverse vibration amplitudes and frequencies of catenaries measured and analyzed by non-contact video gauge method were consistent with simulation outputs. The simulation outputs were based on practically measured parameters such as boundary displacement excitations and tension variations. The research results indicated that tension imbalance distributions of the catenaries could change their natural frequencies and result in transverse resonance under boundary harmonic displacement excitations. Therefore specific measures should be provided to maintain tension balance in multi-rope hoisting applications

Pattern recognition of rigid hoisting guides based on vibration characteristics

A test rig is built to simulate the typical fault patterns of rigid hoisting guides and to collect vibration and inclination signals. In this work, we use these signals to perform data mining for fault-pattern recognition. Parameters are initially defined by analyzing collected signals. Then, the importance of each parameter is calculated using the boosting-tree method. Some valuable parameters are retained. To establish a data-mining algorithm that works remarkably for the fault recognition of rigid hoisting guides, six different algorithms including the boosting tree, K-nearest neighbor, MARSpline, neural network, random forest, and support vector machine are compared. Results show that the best performance is that of the boosting-tree algorithm, whose mechanism is then presented in detail

Vibration modal shapes and strain measurement of the main shaft assembly of a friction hoist

In order to evaluate the reliability of the main shaft unit of a friction hoisting system, strain measurement is a significant method. In this paper, a test rig of a friction hoisting system was built, which could applied periodically changing load on its main shaft unit; The mechanical analysis under the test load was conducted and the boundary limits were obtained; A three dimensional model of the main shaft unit was built in Pro-E and its finite element analysis was performed in ANSYS; With the analytical result, measuring points for strain rosettes were initially selected; Vibration modal shapes of the main shaft unit were analyzed, based on which Modal Assurance Criterion (MAC) was utilized in the Particle Swarm Optimization (PSO) algorithm to make the final decision of the number and positions of the measuring points; A wireless measurement system was developed to acquire strain signals from the optimized measuring positions; The test result verified the efficiency of the methods employed in this paper and revealed how strain of the main shaft unit changes during running process

Density functional theory for freezing transition of vortex-line liquid with periodic layer pinning

By the density functional theory for crystallization, it is shown that for vortex lines in an underlying layered structure a smectic phase with period m=2 can be stabilized by strong layer pinning. The freezing of vortex liquid is then two-step, a second-order liquid-smectic transition and a first-order smectic-lattice transition. DFT also indicates that a direct, first-order liquid-lattice transition preempts the smectic order with m>2 irrespectively of the pinning strength. Possible H-T phase diagrams are mapped out. Implications of the DFT results to the interlayer Josephson vortex system in high-Tc cuprates are given.Comment: 4 pages, 5 figures, references adde

Self-Assembly of Isostatic Self-Dual Colloidal Crystals

Self-dual structures whose dual counterparts are themselves possess unique hidden symmetry, beyond the description of classical spatial symmetry groups. Here we propose a strategy based on { a nematic monolayer of} attractive half-cylindrical colloids to self-assemble these exotic structures. { This system can be seen as a 2D system of semi-disks.} By using Monte Carlo simulations, we discover two isostatic self-dual crystals, i.e., an unreported crystal with pmg {space-group} symmetry and the twisted Kagome crystal. For the pmg crystal approaching the critical point, we find the double degeneracy of the {full} phononic spectrum at the self-dual point, and the merging of two tilted Weyl nodes into one \emph{critically-tilted} Dirac node. The latter is `accidentally' located on the high-symmetry line. The formation of this unconventional Dirac node is due to the emergence of the critical flat bands at the self-dual point, which are linear combinations of \emph{finite-frequency} floppy modes. These modes can be understood as mechanically-coupled self-dual rhomb chains vibrating in some unique uncoupled ways. Our work paves the way for designing and fabricating self-dual materials with exotic mechanical or phononic properties.Comment: 6 pages, 3 figure

Pattern recognition of rigid hoisting guides based on vibration characteristics

A test rig is built to simulate the typical fault patterns of rigid hoisting guides and to collect vibration and inclination signals. In this work, we use these signals to perform data mining for fault-pattern recognition. Parameters are initially defined by analyzing collected signals. Then, the importance of each parameter is calculated using the boosting-tree method. Some valuable parameters are retained. To establish a data-mining algorithm that works remarkably for the fault recognition of rigid hoisting guides, six different algorithms including the boosting tree, K-nearest neighbor, MARSpline, neural network, random forest, and support vector machine are compared. Results show that the best performance is that of the boosting-tree algorithm, whose mechanism is then presented in detail

Encapsulation of hydrophobic phthalocyanine with poly(N-isopropylacrylamide)/lipid composite microspheres for thermo-responsive release and photodynamic therapy

Phthalocyanine (Pc) is a type of promising sensitizer molecules for photodynamic therapy (PDT), but its hydrophobicity substantially prevents its applications. In this study, we efficiently encapsulate Pc into poly(N-isopropylacrylamide) (pNIPAM) microgel particles, without or with lipid decoration (i.e., Pc@pNIPAM or Pc@pNIPAM/lipid), to improve its water solubility and prevent aggregation in aqueous medium. The incorporation of lipid molecules significantly enhances the Pc loading efficiency of pNIPAM. These Pc@pNIPAM and Pc@pNIPAM/lipid composite microspheres show thermo-triggered release of Pc and/or lipid due to the phase transition of pNIPAM. Furthermore, in the in vitro experiments, these composite particles work as drug carriers for the hydrophobic Pc to be internalized into HeLa cells. After internalization, the particles show efficient fluorescent imaging and PDT effect. Our work demonstrates promising candidates in promoting the use of hydrophobic drugs including photosensitizers in tumor therapies