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Symmetry in Mechanical Engineering

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Nguyễn Gia Hào

Academic year: 2023

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An analysis of the dynamic behavior of systems with fractional damping for mechanical engineering applications. The matching model of the dual mass flywheel and the power transmission by integration of the sensitivity analysis method was presented in the paper [3].

Summary

Acoustic analysis is also profitable for power transformer analysis and fault finding in on-load tap-changers [29,30]. Monitoring and maintenance of a gantry based on a wireless vibration level measurement and analysis system.Eksploat.

A Novel Surface Inset Permanent Magnet Synchronous Motor for Electric Vehicles

  • Introduction
  • The Proposed SIPMSM 1. Structure Design
  • Optimization Model
  • Experimental Validation
  • Conclusions

The ratio of the peak velocity to the base velocity is the rate of expansion of the flux weakening [23]. However, the output torque of the novel SIPMSM is clearly higher than the traditional SIPMSM.

Figure 1. Schematic diagram of typical SIPMSM and tile shape magnetic poles. (a) Schematic diagram of traditional SIPMSM; (b) Schematic diagram of tile shape magnetic poles.
Figure 1. Schematic diagram of typical SIPMSM and tile shape magnetic poles. (a) Schematic diagram of traditional SIPMSM; (b) Schematic diagram of tile shape magnetic poles.

Modelling of Material Removal in Abrasive Belt Grinding Process: A Regression Approach

Theoretical Basis 1. Abrasive Belt Grinding

Interaction effects of the predictors through linear regression can be obtained by using the stepwise regression. Each connection between neurons is articulated in terms of a weight value, and these connections are controlled based on training the network.

Figure 1. Principle of the belt grinding process.
Figure 1. Principle of the belt grinding process.

Experimental Setup 1. Methodology

Averaging over all decision trees results in a reduction in variance thereby increasing prediction accuracy. The depth of cut is calculated as the distance from the deepest point in the soil path to the bare surface of the workpiece as shown in Figure 7.

Figure 6. Compliant abrasive belt grinding experimental setup [12].
Figure 6. Compliant abrasive belt grinding experimental setup [12].

Regression Modelling for Abrasive Belt Grinding Process 1. Multiple Linear Regression Based Modelling

The architecture of the ANN that estimated the material removal in abrasive belt grinding is shown in Figure 12. The development of the relationship between the belt grinding parameters and material removal RF model was carried out using MATLAB.

Figure 8. Schematic illustration of the multilinear regression model for prediction of the material removal.
Figure 8. Schematic illustration of the multilinear regression model for prediction of the material removal.

A Hybrid Mechanism for Helicopters

  • Problem Formulation and Methods
  • Conceptual Framework and Design for Experiment This drone application proposal [4] is shown as Figure 2
  • Discussion
  • Patents and Recognitions

Once we start the turbine motor (12), this motor operationally rotates the first output shaft (121) and the first bevel gear (122) to drive the first bevel gear (123). On the other hand, if the turbine engine accidentally lacks fuel/engine failure, the electronic motor (13) immediately works to drive the second output shaft (131), the second drive shaft (132) and the second V-shaped gear (133) to rotate the first V-shaped gear (116).

Figure 1. Parallel hybrid electric vehicle mechanism [10].
Figure 1. Parallel hybrid electric vehicle mechanism [10].

An Analysis of the Dynamical Behaviour of Systems with Fractional Damping for Mechanical

Engineering Applications

Theoretical Background: A 1 DOF System with Fractional Damping

One of the distinguishing features of a fractional attenuation system is the nature of its poles. Time response of a fractionally damped system for different values ​​of the derivative order. For example, the 1 DOF system studied presents this behavior when the damping parameter c=2 and the order of the derivative α= 0.9 (Figure 6).

According to this reasoning, the value of critical damping can be estimated for several orders of magnitude of the derivative α.

Figure 1. Distribution of poles for different values of α. The solutions that comply with (5) are highlighted in red.
Figure 1. Distribution of poles for different values of α. The solutions that comply with (5) are highlighted in red.

Application: Bearing Support

It can be observed that, as found for the 1 DOF system, the change of the order of the derivative affects the stiffness of the supports and, thus, the vibration frequencies. Then, the time response of the axis to a disturbance from the base is calculated following the procedure in [35] by means of the aM-C-KNewmark method. In this case, by tuning the stiffness and damping parameters and the order of the derivative, different behaviors can be reproduced.

The evolution of the shaft over time can be seen in the four videos provided as supplementary material to this article.

Figure 11. Evolution of the frequency of the first two modes with the order of the derivative α.
Figure 11. Evolution of the frequency of the first two modes with the order of the derivative α.

Conclusions

On the occurrence of fractional operators in non-linear stress-strain relationship of metals.Int. Finite element formulations for transient dynamic analysis in structural systems with viscoelastic treatments containing fractional derivative models. Int. Statistical correlation of fractional oscillator response by complex spectral moments and state variable expansion.Community.

Finite element analysis of the seismic response of damped structural systems including fractional derivative models.J.

Complete Geometric Analysis Using the Study SE(3) Parameters for a Novel, Minimally Invasive Robot

Mathematical Framework

The coordinates of the Q point are based on the dual quaternion and are also called study parameters in the scientific literature. As can be seen from Equation (4), there are four ways to write the study parameters, and at least one way is guaranteed to give a non-singular representation of the Euclidean displacement (ie, the study parameters are free of parametric singularities). For example, as long as the parameters of the study do not represent a rotation by the value of π, the first relation from equation (4) [2] can be used.

A more direct method of obtaining the constraint equations of a mechanism is to write directly the study parameters for each element of the kinematic chain (joints and links) and then use quaternion multiplication to obtain the constraints (this is analogous to multiplying the homogeneous matrices).

Pro-Hep-LCT Parallel Robotic System

The two guiding modules of the Pro-Hep-LCT robotic system are identical and work "in mirror". The mobile platform (or the end effector) of the robot is guided by the two planar mechanisms through a pair of universal joints. The singularities for the robotic system are determined using the ranking of the input and output Jacobians for the three presented mechanisms.

Figure 4a shows the boundary of the operative space in which the end effector of the Pro-Hep-LCT robotic system has no orientation (ie, the medical tool points vertically downward) and Figure 4b shows a cross section of the space.

Figure 1. The CAD model for the Pro-Hep-LCT robotic system.
Figure 1. The CAD model for the Pro-Hep-LCT robotic system.

Numerical Results and Discussion

Finally, Table 5 shows the numerical values ​​of the active joint parameters for each ultrasound probe pose (calculated by inverse kinematics using equations and (18)). Linear interpolation also showed that the displacement of the insertion point is not significant for the medical procedure. The numerical values ​​of the active connection parameters calculated via inverse kinematics (for successive points on predefined tool paths) were linearly interpolated and used as input to a kinematic simulation in the Siemens NX environment that showed a maximum relative deviation (from the insertion point) of 1.45 mm.

The preliminary numerical results show that the robot control based on the study parameters is feasible due to the insignificant deviation of the insertion point (from the imposed point).

Figure 6 illustrates the discretization of the two paths of the ultrasound probe tip starting from a point O’ (where the tool is in a vertical pose and inserted at a 100 mm depth) and ending at the points A and B respectively (with 30 ◦ angle values about
Figure 6 illustrates the discretization of the two paths of the ultrasound probe tip starting from a point O’ (where the tool is in a vertical pose and inserted at a 100 mm depth) and ending at the points A and B respectively (with 30 ◦ angle values about

Research of the Operator’s Advisory System Based on Fuzzy Logic for Pelletizing Equipment

  • Materials and Methods
  • System Model
  • Evaluation of the Prilling Process
  • Combined Advisory System Model
  • Discussion
  • Conclusions

One of the most important parameters in the milling process is the pellet size. Based on the operators' experience, a rule base for the fuzzy logic controller was created. Importantly, the final decision on contamination of the production line is made by the operator.

The graph of the system status estimation together with the measurement results is presented in Figure 14.

Figure 1. The algorithm of the estimation of equipment contamination.
Figure 1. The algorithm of the estimation of equipment contamination.

The Use of Structural Symmetries of a U12 Engine in the Vibration Analysis of a Transmission

Results

The representation of the vibrational modes for the branched system is suggestive of the presentation of the results (Figures 8 and 9). Thus, in Section 3 we showed that eigenvalues ​​for a single engine were below the eigenvalues ​​of the entire mechanical system. Thus it was shown that the vibrations of the symmetrical parts can also be found between the natural frequencies of the entire system.

A method for the study of the vibration of mechanical rod systems with symmetries. Acta Tech.

Table 4. Eigenvalues for the two models.
Table 4. Eigenvalues for the two models.

Research on a Real-Time Monitoring Method for the Wear State of a Tool Based on a Convolutional

Bidirectional LSTM Model

CABLSTM Model

The neural network framework for real-time monitoring of tool wear condition based on CABLSTM is shown in Figure 2. In this paper, maximum pooling was used to obtain the maximum value of the nearby feature points. In this paper, the attention mechanism was used to assign weights to each time step output vector of the BiLSTM layer by assigning different initialization probability weights.

A partial extension of the BiLSTM network model with an attention mechanism along the time axis is shown in Figure 5.

Figure 2. Neural network framework for real-time monitoring of tool wear state based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) network with an attention mechanism (CABLSTM).
Figure 2. Neural network framework for real-time monitoring of tool wear state based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) network with an attention mechanism (CABLSTM).

Real-Time Monitoring Method of the Tool Wear State

During model training, the entire model was trained with Categorical_crossentropy loss. The resulting cross-entropy error was averaged as a function of model loss. Adam's method dynamically adjusts the learning rate of each parameter using the first-order moment estimator and the second-order gradient moment estimator.

The main advantage of the Adam method was that after compensation correction, the learning rate of each iteration had a specific range, which makes the parameter change relatively stable.

Experimental 1. Experimental Design

The real-time monitoring experimental device for the tool wear condition is shown in Figure 7. The tool wear condition was divided into initial wear, normal wear and rapid wear. In this paper, the tool wear condition was defined according to the actual wear curve of each cutter.

The loss function and the accuracy of the verification set and test set are shown in Table 5.

Figure 7. Real-time monitoring experimental device of the tool wear state.
Figure 7. Real-time monitoring experimental device of the tool wear state.

A Study of the Effect of Medium Viscosity on Breakage Parameters for Wet Grinding

Methodology 1. Materials

We will refer to as Sjwin the case of the specific refractive index when the fluid is only water, and Sjd. in the rest of the cases in which the properties of the water have been modified by dissolving the above-mentioned reagent. In order to perform an analysis of the data obtained in the laboratory tests, the effect of various variables was taken into account when defining the groups. The model coefficients representing each system and the suspension fluid viscosity range for which it is valid are shown in Table 5 below.

Results suggest that the viscosity of the suspension fluid affects the specific rupture velocity and that this effect is different depending on some other conditions, such as the sphere diameter.

Table 2. Trace elements in the quartz sample by ICP-OES (ppb).
Table 2. Trace elements in the quartz sample by ICP-OES (ppb).

An Improved Butterfly Optimization Algorithm for Engineering Design Problems Using the

Cross-Entropy Method

  • Methods
  • Hybrid BOA-CE Method
  • Experiment and Results
  • Using the BOA-CE Algorithm for Classical Engineering Design Problems
  • Conclusions

Table 5 shows that the BOA-CE method performs better than the other approaches in the majority of the test cases. The figure shows that the BOA-CE algorithm has the fastest convergence for the majority of the multimodal test functions. From Table 6, we can find that the BOA-CE algorithm outperforms others in most of the composite test functions.

In future research, a discrete version of the BOA-CE algorithm will be constructed to solve combinatorial optimization problems.

Figure 1. The flow chart of the BOA-CE algorithm.
Figure 1. The flow chart of the BOA-CE algorithm.

A New Second-Order Tristable Stochastic Resonance Method for Fault Diagnosis

STSR System

The time domain and amplitude spectrum of the noiseless signal are shown in Figure 5a. The time-domain waveform and amplitude spectrum of the STSR output signal are shown in Figure 5b when D=0.3, and the frequency 0.01 Hz cannot be seen. When the damping ratio increased to 0.885, the time-domain waveform and amplitude spectrum of the output signal are as shown in Fig. 6b.

In addition, the pre-processed signal is used as the input signal of the STSR to obtain the output signal.

Simulation Analysis

The Hilbert transform is used to demodulate the filtered signal, in which the received signal is denoted as S1.S2=S1−mean(S1),S=2×max(abs(SS2 2)). It is the input signal of the STSR system. Setting the population size, number of replications and range of parameters including a,b,V,R,c,k,andR. 3) Calculate the objective function value of each location according to equation (11). Rescale the amplitude and frequency of the signal to plot the waveform and amplitude spectrum in the time domain.

Experimental Verification and Analysis

Study of frequency shifts and rescaling of stochastic resonance and its application to fault diagnosis. An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis.Mech. Improving the bearing fault diagnosis efficiency by the adaptive stochastic resonance in a novel nonlinear system. Megan.

An underdamped stochastic resonance method with steady state adjustment for initial fault diagnosis of rolling bearings. Mech.

Research of the Equipment Self-Calibration Methods for Different Shape Fertilizers Particles Distribution

Measurement Method

Results of the received distribution can be adjusted according to the distribution average coefficient [28] or compared with various other measurements [29,30]. The diameter of the grains, which is close to the ideal circle, does not require any correction. Only the shadow of the grains near the ideal circle was evaluated (an example of an image captured by the camera is provided in Figure 1).

The regression model functions are used for the correction of the cumulative grain distribution curve shape.

Hình ảnh

Figure 4. Effect of interaction factors on peak value of cogging torque Y 1 : (a) 3D and (b) 2D contours.
Figure 5. Effect of interaction factors on peak value of cogging torque Y 2 : (a) 3D and (b) 2D contours.
Figure 10. Efficiency map and characteristic curve of the novel SIPMSM.
Table 1. Research efforts so far in modelling of belt grinding process.
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