Abstract:The part tolerance design of RV reducer is a major difficulty in its research and development process. A method based on fuzzy analytic hierarchy process is proposed for tolerance design of RV reducer. The sensitivity weight coefficient of part parameter error to hysteresis degree is constructed by sensitivity analysis, and the weight coefficient of part processing difficulty is constructed by triangular fuzzy-analysis hierarchy process. Based on the geometric mean method, the weight expression of the part design parameter is established to calculate the hysteresis of the RV reducer, so as to realize the tolerance assignment of the part design parameters. The theory and experimental results show that the method is feasible and has guiding significance for RV reducer tolerance design.

Abstract:Smoothed particle hydrodynamics (SPH) method is a fully Lagrangian meshless method, which is available to simulate the problems with instantaneous very large deformation, such as wave cracking, high-speed water flow, high-speed impact and collision. The basic principle,kernel function,discretization of governing equations and boundary treatment of SPH method are introduced, a numerical flume model is constructed and its validity is verified. 2D dam-break problem under two cases is simulated respectively, i.e. obstacle with and without holes, and the computational results are compared and analyzed. It is demonstrated that the SPH method can nicely capture the variation of the free surface flow, the fluid fragment and coalescence, and to some extent, the energy dissipation effect is better when the obstacle has holes.

Abstract:To investigate the characteristics of adiabatic oxidation reaction and predict critical temperature of coal spontaneous combustion, we carry out the adiabatic oxidation experiments of five coal samples and use the index of activation energy to reflect the characteristics of microcosmic reaction of spontaneous combustion in different stages. In addition, the critical point (T_c) is determined by using the F test of linear regression analysis. The results show that in the early stage of low temperature oxidation of coal, the values of activation energy range greatly, which indicates that reactions of the functional groups is very unstable at this time; as the temperature increases, the values of all samples are in a range of 55 to 70 kJ/mol in late period of the experiment, which indicates that the reaction has become relatively stable; T_c has good correlation with macro-heating rate, which indicates the model is scientific. In addition, T_c has linear relationship with t₀ (the time needed for spontaneous combustion temperature increasing to 160℃ in the experiment). Thus T_c could be predicted by t₀. This research could provide reference for the prevention fire and coal storage in mine.

Abstract:The width of production drifts has a definitely significant effect on the economic benefits of mines adopting sub-level caving mining operations. In this study, an optimization method has been presented to determine the width of production drifts in sub-level mining, based on the stability analysis of pillar between sub-level drifts using the stochastic medium theory for ore draw, Wilson theory and FLAC3D routine. The case study of an iron mine in Xinjiang, China, shows that the theoretically optimal width for the drifts is 7 m, and this figure is optimized to 6.6 m after a detailed technological and economical investigation of seven various drift widths has been made by using the highest integral method. The optimization results indicate that the effect of ore drawing is good, and the profit for a single drift is increased by 0.6 million Yuan accordingly. This methodology present involves an integrated consideration of safety, practices for driving and supporting drifts and economic benefits in sub-level caving mining, and can be of significance to guide production operations for similar mines.

Abstract:The method of measuring the electric field of a tapered fiber-slab coupler(TFSC) is studied. The influence of the parameters of TFSC on the propagation performance is discussed in detail in order to design a TFSC sensor with better parameters. Firstly, the simulation platform is simulated in RsoftBPM, and the influence of the coupling parameters on measurement accuracy, measurement range and size of the equipment is analyzed qualitatively according to the coupled-mode theory. Then, the design principle for the sensor of improving measurement accuracy or increasing measurement range is proposed and a set of design examples is given. Finally, the distortion of the original electric field is analyzed, and the coupler structure is improved by simulation.

Abstract:With the development of power electronics technology, the proportion of nonlinear load in the power grid is increasing. It is easy for nonlinear load in the power system to produce harmonics which result in harmonic pollution, therefore, it is necessary to make an analysis for its characteristics. In this paper, a method to obtain the nonlinear load characteristic by obtaining the real-time equivalent impedance of the nonlinear load based on the high order differential equation and the signal fitting is proposed. With using improved matrix beam method to fit the port voltage and current signal and putting voltage and current signal into the high-order differential equation which is to constrain port voltage and current, the equivalent reactance parameters of the load can be obtained through mathematical transformation. The characteristics of the nonlinear load are obtained according to the change characteristics of the equivalent parameters of the load. Simulation results show that the method is feasible and the equivalent impedance parameters of the load can be obtained in real time so that the nonlinear load characteristics can be obtained.

Abstract:As an important and fast construction method for drilling holes, rotary drilling rig is superior to other drilling machines. The drilling parameters based on the online monitoring system which we can get from the drilling process provide not only significant information for construction operation, but also original data for identification of the bearing strata. Due to the complex original site environment, the drilling parameters such as drilling rate, rotation rate, rotary force and torque of the power head would be changed with time and space during the drilling process. According to the parameters database and theoretical analysis, the curves of drilling parameters varying with drilling depth are establishecl, from which we can find that the single-factor curves cannot identity the bearing strata accurately. In addition, a multi-factor collaborative control method for identification is proposed, and a load-strength model of the rock masses is built to determine the bearing strata, which is based on comprehensive index and all the drilling parameters are included. And then the model is applied to analyze the strength and bearing capacity of the formation considering the rotary drilling. By comparing the analysis results with the results from strength testing values in the geological survey, we can find that the strata property identified by the proposed method is in accordance with the real characteristics. Therefore, the above identification method based on drilling parameters is rational and reliable to determine the strata properties and identify the bearing strata, and it could be used for formation identification considering drilling process under different geological environment.

Abstract:Significant creep deformation occurs on steel with the coaction of high temperature and loading, and the creep has a large effect on the deformation and load bearing capacity of steel beams in fire. In order to consider the effect of creep on the fire resistance performance of restrained steel beams, the high temperature creep model is employed to establish analysis theory on restrained steel beams by considering creep strain in the cross section of steel beam. And a computer program is performed by using MATLAB software. Restrained axial force and deflection of restrained beam under fire are analyzed by the computer program, and good agreement is found between calculation results and test data. The effect of creep on the fire resistance performance of simply supported beams and restrained steel beams is further investigated by employing the validated program. The results show that the proposed approach can accurately consider the effect of creep on the fire resistance performance of steel beams, and creep has a small effect on the fire resistant performance of simply supported beams, but has a large effect on that of restrained beams.

Abstract:Accurate calculation of shear strength of reinforced concrete (RC) circular columns plays a key role in the ductile seismic design, which can effectively prevent the occurrence of brittle shear and flexure-shear failure. Based on the existing quasi-static test results of RC circular columns, the seismic failure modes and the method for determining the shear strength capacity of RC circular columns are analyzed. On the basis of theoretical analysis, a shear strength model of RC circular column considering the effects of inelastic deformation (displacement ductility) is proposed and compared with the existing model. The results show that the shear strength capacity of RC circular columns decreases with the increase of deformation in the plastic hinge region under seismic loading. The shear strength capacity of flexural-shear failure columns depends on the lateral load corresponding to the shear failure point of the plastic hinge region rather than peak lateral load of the skeleton curve. The proposed model is able to effectively reflect the effects of deformation on the shear strength capacity of RC circular columns. And the results are in good agreement with the experimental data and can be used to predict the shear strength capacity of RC circular columns with different failure modes under seismic excitations.

Abstract:Surface electromyography(sEMG) is one of the main information sources of human motion detection and has been widely used in the field of well-being of robots. We present a feature extraction method based on wavelet transform power for identifying the movement of human legs. The average power of the active segment in wavelet subspace is used to make up the feature vector according to the frequency domain distribution of the sEMG signal. In order to verify the effectiveness of the proposed method, we design and implement a small portable multi-channel sEMG signal acquisition system, and construct a classifier with support vector machine (SVM) to identify the leg movements. The results of the study show that the method can distinguish four kinds of common actions of the leg, the recognition rate of the same individual can reach more than 95%, and the recognition rate of different individuals can reach 85%, which can be applied to daily rehabilitation training of patients with lower limb movement disorders.

Abstract:Brain control is a new man-machine control method using electroencephalogram (EEG) and electromyography (EMG) to control the device. In order to facilitate its multi-device integrated control system construction, a design of a new compatible multi-device control signal interface is presented. Meanwhile, its working principle of three-tier structure, work processes in different modes and hardware design of the functional modules are described in detail. By ways of display feedback and confirmation alert, the interface also includes a security function, which can effectively improve the safety control system.

Abstract:Traditional methods for action recognition include several isolated processes and depend on well-designed features, which makes them has the shotcomings of large time cost and difficult to optimize the parameters from the whole. In this paper, we use depth sequences to study deep learning-based action recognition and construct a 3D-based deep convolution neural network to automatically learn spatio-temporal features from raw depth sequences. A Softmax classifier is used on the learned features to take action recognition. Experimental results demonstrate that our method can learn feature representation automatically from depth sequences. The proposed method performs comparable results to the state-of-the-art methods on the MSR-Action3D dataset and achieves good performance in comparison to baseline methods on the UTKinect-Action3D dataset. And the proposed method is simpler in feature extracting and action recognition consist of a closed loop system which can learn features automatically. We further investigate the generalization of the trained model by transferring the learned features from one dataset (MSR-Action3D) to another dataset (UTKinect-Action3D) without retraining and obtain very promising classification accuracy.