GROUND REACTON FORCE OF TABLE TENNIS PLAYERS WHEN USING FOREHAND ATTACK AND LOOP DRIVE TECHNIQUE

The subjects were 10 excellent ping-pong players in China. The table tennis techniques of the forehand attack and forehand loop drive were tested, using the measurement methods of the KISTLER force-plate system. The results showed that the biggest GRF of the attack technique in vertical direction was higher than the loop drive technique, and the biggest GRF of the attack technique in left-right direction and the fore-aft direction were mostly lower than the loop drive technique

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

Multivariate Operator-Self-Similar Random Fields

Multivariate random fields whose distributions are invariant under operator-scalings in both time-domain and state space are studied. Such random fields are called operator-self-similar random fields and their scaling operators are characterized. Two classes of operator-self-similar stable random fields $X=\{X(t), t \in \R^d\}$ with values in $\R^m$ are constructed by utilizing homogeneous functions and stochastic integral representations.Comment: 27 page

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

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

Rapid, non-invasive characterization of the dispersity of emulsions via microwaves

A rapid and non-invasive method to determine the dispersity of emulsions is developed based on the interrelationship between the droplet size distribution and the dielectric properties of emulsions. A range of water-in-oil emulsions with different water contents and droplet size distributions were analysed using a microwave cavity perturbation technique together with dynamic light scattering. The results demonstrate that the dielectric properties, as measured by non-invasive microwave cavity analysis, can be used to characterise the dispersity of emulsions, and is also capable of characterizing heavy oil emulsions. This technique has great potential for industrial applications to examine the sedimentation, creaming and hence the stability of emulsions