Simulation Comparison Experiments Research Articles

Design and Simulation of a Novel Planetary Gear Mixer for Dry Particle Materials

Background: Mixer with excellent performance is the essential premise for high-quality mixture production to ensure uniformity. In the fields of food, pharmacy, powder metallurgy and machinery industry, materials mixing is an indispensable process. At present, the mixing efficiency and performance of the traditional mixer are very low, which has its own limitations, and it is difficult to ensure the quality of the mixture, which seriously affects the safety and reliability of the mixture products such as synthetic drugs, chemical reagents, cement, synthetic fiber, etc. Objective: In order to improve the mixing performance by improving the mixing uniformity, volume utilization, reducing the mixing time and mixing blind area, a novel planetary gear mixer for dry particle materials is designed. Its blades can rotate and the angle of attack can be changed at any time, which realizes the multi-degree of freedom movement of the blades. Methods: Firstly, the shortcomings of three kinds of traditional mixers are compared and analyzed, a novel planetary gear mixer for dry particle is proposed and its structural characteristics are described. Then, the transmission system and blade parameters of the mixer are designed and calculated, and the blade parameters of the mixers are optimized based on ADAMS and EDEM. Finally, the comparative simulation experiment between planetary gear mixers and SHR-10A mixers is carried out. The experiment is used to inquiry on the mixing performance of the new planetary gear mixer. Results: The complementary cycloid was the ideal mixing trajectory of the blade. The most distinctive feature of this motion is that the attack angle of the blade can change in all directions. When the blade parameter p = 11, the Lacey index rises the fastest and the mixing degree is the largest, which indicates that the optimal mathematical model of the blade is ‘y2= 22x’. The comparison with SHR-10A mixer showed that spatial distribution of multi-degree of freedom blades in the new planetary gear mixer has strong dispersion effects on particles and better mixing performance. Conclusion: The planetary gear mixer for dry particle materials is a new type of mixer, which is composed of two sets of blades whose attack angle can be changed at any time. Convection and shear mixing dominate its mixing space, which is conducive to its rapid and full mixing, improving the mixing performance. The dry particle planetary gear mixer for dry particle materials has great developmental value and wide engineering application prospect. In this article, various patents have been discussed.

Disturbance-Encoding-Based Neural Hammerstein–Wiener Model for Industrial Process Predictive Control

The control reliability of model predictive control is largely determined by the accuracy of the process model. The Hammerstein–Wiener (HW) model is an important nonlinear process modeling technique that has obtained great success in some process industries. Disturbances result in model mismatch and steady-state deviation, but little effort has been devoted to the coupling effects and inertial information in measured disturbances. In addition, few studies try to construct a disturbance observer (DO) to alleviate unmeasured disturbances. The present work proposes prompt disturbance rejection. First, a spatial–temporal long short-term memory-based measurable disturbance encoder is devised to analyze time-series information from measured disturbances and their coupling effects. The encoder can further clarify the status of inertial interference components and the disturbance intensity. Second, a DO is designed to estimate and attenuate unmeasured disturbances. Third, to create the new HW network, which is improved by integrating the disturbance encoder and observer differential, neural networks are used as nonlinear parts. Finally, a model predictive controller based on this improved model is constructed for real-time industrial process control. Simulation comparison experiments have demonstrated the superiority of the proposed methods. Real industry application in the country’s largest lead-zinc froth flotation plant in China validated the proposed model’s effectiveness in controlling chemical reagents.

Distribution of Data Dissemination Model using DTN Routing Protocols

In this research paper compare the protocol’s performance together with the experimental results of optimal routing using real-life scenarios of vehicles and pedestrians roaming in a city. In this research paper, conduct several simulation comparison experiments(in the NS2 Software) to show the impact of changing buffer capacity, packet lifetime, packet generation rate, and number of nodes on the performance metrics. This research paper is concluded by providing guidelines to develop an efficient DTN routing protocol. To the best of researcher(Parameswari et al.,) knowledge, this work is the first to provide a detailed performance comparison among the diverse collection of DTN routing protocols.

Study on optimal urban land classification method based on remote sensing images

Traditional urban land classification methods are relatively complicated in information collection, resulting in large time consumption and low classification accuracy. Therefore, an optimal urban land classification method based on remote sensing images is proposed in this paper. In this paper, four influencing factors of urban land classification are clarified based on the actual situation, on which the information about urban land in urban areas is extracted through the NDBI index method, and the ETM remote sensing image information of urban land is obtained. The genetic algorithm based on K-means mutation operator is adopted to classify the ETM remote sensing image information of urban land and finally the optimal classification results of urban land are obtained. In order to test the superiority of the method, a simulation comparison experiment was carried out. The simulation results show that the proposed method can provide overall accuracy of 93.75% and classification accuracy of 96.18% in urban land information collection, has the overall Kappa coefficient of 0.8967 and cost 10 s averagely, indicating that this method is superior in time consumption during urban information collection, collection accuracy and land classification accuracy, so it has high application value.

Grouping Method of Semiconductor Bonding Equipment Based on Clustering by Fast Search and Find of Density Peaks for Dynamic Matching According to Processing Tasks

Given that the equipment for the semiconductor packaging line adopts the fixed grouping production method, thus failing to dynamically match the processing task demand capacity, in the present study, we proposed a semiconductor bonding equipment-grouping method based on processing task matching. This method sets the device group closed position constraint and the matching constraint between the device type and the processing type and uses the graph theory method to establish the device grouping model. The dynamic grouping of equipment under the capacity demand of different processing tasks was achieved by changing the relationship matrix between devices. The drawback of this grouping method is rather large grouping deviation, which we tried to solve with the clustering by fast search and find of density peaks (CFSFDP) that was added to cluster the sets of attribute information of the devices so as to obtain the maximum number of grouping groups obtained to reduce the grouping deviation. Simulation comparison experiments were carried out under different circumstances considering the size of the formation, the distribution of demand capacity, and the coefficient of difference in demand capacity. Compared with the standard device grouping method, the grouping method based on semiconductor bonding equipment and CFSFDP algorithm for dynamic matching according to processing tasks had better performance in solving the dynamic grouping problem.

Parameters Optimization and Application of SVM Based on PCA-Particle Swarm Algorithm

The parameter optimization of Support Vector Machine (SVM) has been a hot research direction. To improve the optimization rate and classification performance of SVM, the Principal Component Analysis (PCA) - Particle Swarm Optimization (PSO) algorithm was used to optimize the penalty parameters and kernel parameters of SVM. PSO which is to find the optimal solution through continuous iteration combined with PCA that eliminates linear redundancy between data, effectively enhance the generalization ability of the model, reduce the optimization time of parameters, and improve the recognition accuracy. The simulation comparison experiments on 6 UCI datasets illustrate that the excellent performance of the PCA-PSO-SVM model. The results show that the proposed algorithm has higher recognition accuracy and better recognition rate than simple PSO algorithm in the parameter optimization of SVM. It is an effective parameter optimization method.

Denoising and Baseline Drift Removal Method of MEMS Hydrophone Signal Based on VMD and Wavelet Threshold Processing

Aiming at the problem that the signals received by MEMS vector hydrophones are mixed with a large amount of external environmental noise, and inevitably produce baseline drift and other distortion phenomenons which made it difficult for the further signal detection and recognition, a joint denoising method (VMD-NWT) based on variational mode decomposition (VMD) and nonlinear wavelet threshold (NWT) processing is proposed. The main frequency of the noisy signal is first obtained by Fourier transform. Then the noisy signal is decomposed by VMD to obtain the IMF components. The center frequency and correlation coefficient of each IMF component further determine that the IMF components belong to noise IMF components, noisy IMF components or pure IMF components. Then the pure IMF components are reserved, the noise IMF components are removed, and the noisy IMF components are denoised by NWT processing method with new threshold function as a whole. Finally, the denoised IMF components and the pure IMF components are reconstructed to obtain the denoised signal to realize the extraction of useful signals and baseline drift removal. Compared with complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT), ensemble empirical mode decomposition combined with wavelet threshold processing method (EEMD-WT), and single wavelet threshold processing method with compromised function between hard and soft threshold (ZWT), the VMD-NWT in this paper has the advantages of less calculation and simple implementation. The simulation comparison experiments verify that the VMD-NWT is superior to CEEMDAN-WT, EEMD-WT, and ZWT. Then VMD-NWT is applied to process the measured data obtained from the Fenji experiment conducted by the North University of China. Simulation and lake trial results show that VMD-NWT has better denoising effect and can realize baseline drift removal. So the proposed VMD-NWT has certain practical research value.

Small Moving Target Detection Model Based on Improved Mixed Disturbance Gauss Model

In order to obtain ideal moving target detection results, a kind of moving target detection algorithm of improved mixture Gaussian model is proposed in this paper on the basis of analyzing the deficiency of traditional Mixture Gaussian model. Firstly, in this algorithm, the update rate is increased to better adapt to the change of environment and the idea of pixel connected region is introduced to remove the noise, then the invariance property of chroma is adopted to avoid arising of “shadow” phenomenon; finally, simulation comparison experiment is used to test its performance. The experiment results show that this algorithm can generate reliable background image and accurately and completely detect the moving target to obtain more superior detection results of comparison algorithm, which can meet the practical application requirement of target tracking.

Video Seamless Splicing Method Based on SURF Algorithm and Harris Corner Points Detection

In order to improve video image registration accuracy during splicing, a video image registration algorithm based on corner point detection and feature point integration is proposed in the article. Firstly, Harris algorithm is adopted to detect image corner points and fetch surf feature points of the image as well as integrate the corner points and feature points and eliminate the repeated points to generate feature vector; secondly, neural network is used to learn the image vector and establish image registration model, and the particle swarm algorithm is used to optimize the parameters of neural network; finally, the specific image is adopted for simulation comparison experiment. The result shows: compared with other image registration algorithms, the algorithm proposed in the article can improve image registration accuracy and efficiency and has relatively strong robustness.

An Adaptive Fruit Fly Optimization Algorithm Based on Velocity Variable

In view of the problems of easily relapsing into local extremum and low convergence accuracy of fruit fly optimization algorithm (FOA), this paper proposes a adaptive fruit fly optimization algorithm based on velocity variable (VFOA). The idea of this algorithm is based on the flight characteristics of fruit fly, using particle swarm optimization (PSO) concept of particle velocity, based on fruit fly optimization algorithm, improved the convergence speed of fruit fly optimization algorithm by adding the particle velocity variable parameter. Finally, simulation comparison experiment tests are conducted on 13 benchmark functions, test results show that adaptive fruit fly optimization algorithm based on velocity variable VFOA compared to swarm intelligence algorithms of FOA, PSO, CS, and so on, the convergence speed and accuracy are improved obviously.

The Performance Analysis of a Compound Modulation Signal

Step-Frequency signal is widely used in radar systems. However it suffers from the technique challenges that are the imaging moving-targets. In this paper, a new compound modulation signal is analyzed. It combines phased code modulation during the pulse and Step-Frequency modulation between the pulses time, and it is called as phase-coded StepFrequency signal. Numeric simulation comparison experiments show that PCSF signal can get the same imaging result with less pulse number, which can be used to solve the conflict problem, such as the number of pulse and transmit average power. So this compound modulation signal can be widely used in the application of engineering project. Finally, the processing method of PCSF is simple analyzed, and numerical simulation proves its effectiveness and accuracy.

Two steps generalized maximum entropy estimation procedure for fitting linear regression when both covariates are subject to error

This paper presents a procedure utilizing the generalized maximum entropy (GME) estimation method in two steps to quantify the uncertainty of the simple linear structural measurement error model parameters exactly. The first step estimates the unknowns from the horizontal line, and then the estimates were used in a second step to estimate the unknowns from the vertical line. The proposed estimation procedure has the ability to minimize the number of unknown parameters in formulating the GME system within each step, and hence reduce variability of the estimates. Analytical and illustrative Monte Carlo simulation comparison experiments with the maximum likelihood estimators and a one-step GME estimation procedure were presented. Simulation experiments demonstrated that the two steps estimation procedure produced parameter estimates that are more accurate and more efficient than the classical estimation methods. An application of the proposed method is illustrated using a data set gathered from the Centre for Integrated Government Services in Delma Island – UAE to predict the association between perceived quality and the customer satisfaction.

Optimal Energy Routing Protocol Algorithm in Wireless Network

As some nodes in the wireless network are supplied by the battery, energy is critical to data transmission, to optimize the energy consumption of the wireless network and prolong the network lifetime, the optimal energy routing protocol algorithm is proposed. The algorithm of this text uses threshold energy and average residuary energy to balance the energy consumption, uses network coding to reduce the energy consumption, unify them to optimize the network energy effectively. Finally the comparative simulation experiment between this algorithm and COPE, DSR algorithm is conducted in the variance of energy consumption in unit time, energy consumption in unit bit and residuary energy, the result shows the energy optimization routing protocol algorithm this text puts forward can reduce the transmission energy consumption and balance the network energy allocation

Comparing Plume-Tracing Algorithms in Obstructed Multi-Source Environments

In this paper, we compare the common plume-tracing algorithms: chemotaxis and anemotaxis in obstructed multi-source environment using multi-robot system. A multi-robot cooperation strategy with virtual physics force, which includes structure formation force, goal force, obstacle avoidance force, repulsion force and rotary force, is proposed. First, plume model with two sources in three obstacles environment is constructed by computation fluid dynamics simulations. Second, parallel searches by two groups robots with chemotaxis and anemotaxis are used to locate two sources in obstructed environment. Simulation comparison experiment with two plume-tracing algorithms discussed the influence of the varied wind direction/ speed frequency and methane release frequency and different initial positions of two groups to the search performance. Finally, the comparative result is illustrated.

Research on Theodolite Auto-Focus Motor Control Technology Based on a Disturbance Observer

The design of DC servo control system for focus motor is an important part to realize the electronic theodolites auto-focusing. Focus motor is seriously influenced by various disturbances, such as friction and torque fluctuation, in frequently reversing process. It is difficult to accurately locate. To solve these problems, a DC motor control method was put forward which combined the integral separation PID and disturbance observer. Based on the three closed-loop DC servo system, the integral separation PID controller was taken in position loop, in order to eliminate static error and improve the control precision. The methods of motor trajectory planning were analyzed, the 4-5-6-7 interpolation trajectory planning was used to decline or prevent the start-stop impact and oscillation. The effectiveness of the control strategy was verified by comparative simulation experiment. The robustness anti-disturbance and location precision performance is improved significantly.

On Low-Velocity Compensation of Brushless DC Servo in the Absence of Friction Model

Friction compensation is usually realized based on a friction model; however, the induced undercompensation or overcompensation, which can lead to steady-error or limit-cycle phenomenon, respectively, is inevitable. A novel straightforward reference compensation scheme for the brushless dc servo system independent of the friction model is presented to reject the aftereffect caused by the friction instead of its original mechanics. Neither the accurate friction model nor any estimation of some specific characteristic parameters is needed in this design. Moreover, the inexact velocity estimation information is not as crucial as it is in the traditional compensation methods. A linear control law is proposed based on a reduced-order observer, which could be readily implemented in low-cost embedded fixed-point chips. Two guidelines for the selection of control parameters are presented in terms of delay sensitivity and limit-cycle avoidance. The approach can be applied to the cases with multiple disturbance torque sources except the friction one, where the friction-model-based strategy is difficult to take effect. Finally, comparative mathematical simulation and practical experiment results are used to validate the effectiveness of the proposed method. Substantial low-velocity performance improvements are achieved in the hardware experiments.

Retrieving vertical profile of aerosol extinction by multi-axis differential optical absorption spectroscopy

Using the oxygen dimer (O4 information measured by multi-axis differential optical absorption spectroscopy (MAX-DOAS)), an inversion method of vertical profile of aerosol extinction based on nonlinear optimal estimation algorithm is developed. At first we study how to calculate some parameters (weighting function, the covariance matrices of measurement and a priori) of the algorithm and design nonlinear iteration strategy suited to Chinese region where aerosol usually shows rapid variation and high load. Then this inversion method is verified by computer simulation combined with discussion about error source in three typical cases of low, high and elevated aerosol. After that a continuous observation is reported in the city of Hefei. The aerosol optical depth (AOD) derived from MAX-DOAS is compared with that of CE318 sun photometer and the correlation coefficient is 0.94. The total relative error of AOD is about 20%. In addition the aerosol extinction in the lowest altitude (0-0.3 km) is compared with that of visibility meter and the correlation coefficient is about 0.65. The total relative error of surface-near aerosol extinction is about 25%. Both of simulation verification and comparison experiment indicate that the inversion method can well rebuild the vertical profile of aerosol extinction in the troposphere.

Research of Query Optimization Based on Improved Quantum Particle Swarm Optimization Algorithm in Distributed Database

Database query optimization is a very complicated issue, also is the key influencing factor in database systems performance. Database query operation efficiency is one of the key factors that affect system response time. Therefore, how to improve the efficiency of database query system becomes particularly important. This paper, on the basis of the advantages of Quantum particle swarm optimization algorithm, proposes distributed database query optimization methods based on Quantum particle swarm optimization algorithm, and improves algorithm. Simulation comparison experiments show that Quantum particle swarm optimization algorithm can improve the efficiency of the distributed database query, and is an effective way to solve the optimization of distributed database query.

Trajectory Planning for Concrete Pump Truck Based on Intelligent Hill Climbing and Genetic Algorithm

This paper takes the five –link concrete pump boom as the research object, and transforms its trajectory planning issue into a multi-object optimization problem. Using intelligent hill climbing algorithm and genetic algorithm, and integrating them closely to ensure real-time online planning for the pump truck effectively, and make the planned motion trajectory for the boom is global optimized under particular constrained conditions. Simulation and performance comparison experiments show that this hybrid algorithm is practical and effective, which offers a new approach for the trajectory planning problem of concrete pump truck.

Effect of adhesive on molten pool structure and penetration in laser weld bonding of magnesium alloy

Laser weld bonding (LWB) is a new hybrid technique that combines adhesive bonding with laser seam welding together, and can achieve higher joint strength than adhesive bonding or laser welding individually. Some new physical phenomena have been observed in this welding method, and the phenomena are different from the normal laser welding process, such as a remarkable deeper penetration in LWB than that in laser welding direct (LWD). The adhesive-induced gas can influence the molten pool structure in front of the keyhole, so that less energy is required for laser keyhole through the upper sheet; thus, higher laser power density can interact with the lower sheet, leading to deeper penetration. Simulation comparison experiments are set to indirectly verify these conclusions above.