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RSS2024 Vol. 43, No. 1
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2024, 43(1): 1-8.
doi: 10.13433/j.cnki.1003-8728.20220191
PDF 5774KB
Abstract:
A stochastic model updating method is proposed by combining the Cokriging surrogate model technique with the single objective function. The method transforms the uncertainty model updating problem into a simple updating problem of the statistical characteristics of the parameters to be updated, which can effectively alleviate the high computational cost problem caused by the stepwise and multi-objective updating while ensuring the updating accuracy. Firstly, assuming that the parameters to be updated and the corresponding responses obey Gaussian distribution, the Latin hypercube sampling is used to obtain the training set samples, and the Cokriging model satisfying the accuracy requirement is constructed to replace the complex finite element model in the iterative calculation. Then, the weighted residual objective function between the statistical characteristics of the finite element model calculated responses and the statistical characteristics of the test responses is established, and the coyote optimization algorithm is introduced to minimize the single objective function to obtain the statistical characteristics of the parameters to be updated. Finally, the feasibility of the proposed method is verified by the two-dimensional and the three-dimensional truss structures.
A stochastic model updating method is proposed by combining the Cokriging surrogate model technique with the single objective function. The method transforms the uncertainty model updating problem into a simple updating problem of the statistical characteristics of the parameters to be updated, which can effectively alleviate the high computational cost problem caused by the stepwise and multi-objective updating while ensuring the updating accuracy. Firstly, assuming that the parameters to be updated and the corresponding responses obey Gaussian distribution, the Latin hypercube sampling is used to obtain the training set samples, and the Cokriging model satisfying the accuracy requirement is constructed to replace the complex finite element model in the iterative calculation. Then, the weighted residual objective function between the statistical characteristics of the finite element model calculated responses and the statistical characteristics of the test responses is established, and the coyote optimization algorithm is introduced to minimize the single objective function to obtain the statistical characteristics of the parameters to be updated. Finally, the feasibility of the proposed method is verified by the two-dimensional and the three-dimensional truss structures.
2024, 43(1): 9-15.
doi: 10.13433/j.cnki.1003-8728.20220203
Abstract:
The robotic scanning system has been widely used in the quality inspection field of automobiles, especially the studies of viewpoint sampling and path planning based on the genetic optimization algorithm in the model-based environment. However, the path planning results based on the nominal models are difficult to apply to the actual inspection environment. To address this problem, a viewpoint adaptive sampling method is proposed based on an improved Monte Carlo tree search, and industrial robot motion trajectories are planned online. Finally, the case of the car door inner panel was used to illustrate the effectiveness of the method.
The robotic scanning system has been widely used in the quality inspection field of automobiles, especially the studies of viewpoint sampling and path planning based on the genetic optimization algorithm in the model-based environment. However, the path planning results based on the nominal models are difficult to apply to the actual inspection environment. To address this problem, a viewpoint adaptive sampling method is proposed based on an improved Monte Carlo tree search, and industrial robot motion trajectories are planned online. Finally, the case of the car door inner panel was used to illustrate the effectiveness of the method.
2024, 43(1): 16-22.
doi: 10.13433/j.cnki.1003-8728.20220197
Abstract:
Shock response and energy analysis of quasi-zero stiffness (QZS) vibration isolation platform is carried out. To focus on the shock performance and energy loss characteristics, the six-degree freedom nonlinear dynamic equations of the QZS system under impact excitation are deduced firstly. The shock response of system is numerically analyzed and compared with that of the corresponding linear isolation system. Subsequently, the influences of damping and structural parameters on the buffering performance are analyzed by using the energy loss velocity as the evaluation index of the buffering performance. The results indicate that the response amplitude of system is higher than that of the corresponding linear system, but the response of the QZS system declines faster than that of the corresponding linear system, and the number of periods required for attenuation is less than that of the linear system. Therefore, the damping can improve the buffering performance, and the stiffness ratio and inclination angle have few impacts on the buffering performance of the QZS vibration isolation platform.
Shock response and energy analysis of quasi-zero stiffness (QZS) vibration isolation platform is carried out. To focus on the shock performance and energy loss characteristics, the six-degree freedom nonlinear dynamic equations of the QZS system under impact excitation are deduced firstly. The shock response of system is numerically analyzed and compared with that of the corresponding linear isolation system. Subsequently, the influences of damping and structural parameters on the buffering performance are analyzed by using the energy loss velocity as the evaluation index of the buffering performance. The results indicate that the response amplitude of system is higher than that of the corresponding linear system, but the response of the QZS system declines faster than that of the corresponding linear system, and the number of periods required for attenuation is less than that of the linear system. Therefore, the damping can improve the buffering performance, and the stiffness ratio and inclination angle have few impacts on the buffering performance of the QZS vibration isolation platform.
2024, 43(1): 23-30.
doi: 10.13433/j.cnki.1003-8728.20220226
Abstract:
In health monitoring of industrial robots, a joint vibration solution method based on current information and modal analysis was proposed to solve the problem of increasing testing cost caused by the need to use vibration sensors to detect each joint one by one. Firstly, the joint current information is introduced to establish the vibration model of industrial robot based on joint current. Then, the modal analysis is carried out by the finite element method to obtain the first 6 vibration modes of the robot, so as to optimize the layout of measuring points for subsequent modal tests. Then, in the force hammer excitation experiment, based on the optimized measuring points, the modal parameters such as mass and stiffness of the industrial robot system are measured. After that, the driving torque and modal parameters were put into the model to solve the Runge-Kutta numerical solution, and the vibration response of each joint of the robot was obtained. Finally, the proposed algorithm is validated by the measured vibration data of single and linkage joints running at a specified joint angle.
In health monitoring of industrial robots, a joint vibration solution method based on current information and modal analysis was proposed to solve the problem of increasing testing cost caused by the need to use vibration sensors to detect each joint one by one. Firstly, the joint current information is introduced to establish the vibration model of industrial robot based on joint current. Then, the modal analysis is carried out by the finite element method to obtain the first 6 vibration modes of the robot, so as to optimize the layout of measuring points for subsequent modal tests. Then, in the force hammer excitation experiment, based on the optimized measuring points, the modal parameters such as mass and stiffness of the industrial robot system are measured. After that, the driving torque and modal parameters were put into the model to solve the Runge-Kutta numerical solution, and the vibration response of each joint of the robot was obtained. Finally, the proposed algorithm is validated by the measured vibration data of single and linkage joints running at a specified joint angle.
2024, 43(1): 31-38.
doi: 10.13433/j.cnki.1003-8728.20220208
Abstract:
In recent years, fault diagnosis methods based on neural networks have shown great advantages in the accuracy and efficiency of diagnosis. However, the exponentially increasing number of model parameters limits the application of neural networks in engineering practice. Aiming at this problem, this paper proposes an improved MobileNet network based on one-dimensional convolutional neural network for fault diagnosis of rolling bearings. The improved network can be directly applied to one-dimensional vibration signals, effectively reducing the requirements of system hardware resources and realizing lightweight deployment of the network; The proposed method is validated using the Western Reserve University bearing dataset and the QPZZ-Ⅱ fault simulation test bench dataset. The accuracy of the model proposed in this paper is more than 99.8%, and the number of parameters is 1/2 of the standard convolutional neural network. The method proposed provides a new way for realizing intelligent diagnosis in light-resource embedded systems.
In recent years, fault diagnosis methods based on neural networks have shown great advantages in the accuracy and efficiency of diagnosis. However, the exponentially increasing number of model parameters limits the application of neural networks in engineering practice. Aiming at this problem, this paper proposes an improved MobileNet network based on one-dimensional convolutional neural network for fault diagnosis of rolling bearings. The improved network can be directly applied to one-dimensional vibration signals, effectively reducing the requirements of system hardware resources and realizing lightweight deployment of the network; The proposed method is validated using the Western Reserve University bearing dataset and the QPZZ-Ⅱ fault simulation test bench dataset. The accuracy of the model proposed in this paper is more than 99.8%, and the number of parameters is 1/2 of the standard convolutional neural network. The method proposed provides a new way for realizing intelligent diagnosis in light-resource embedded systems.
2024, 43(1): 39-44.
doi: 10.13433/j.cnki.1003-8728.20220215
Abstract:
The damage of a derrick steel structure affects its bearing safety. In order to identify the damage location quickly and accurately, a method for identifying the damage of a derrick steel structure based on the BP neural network optimized with wavelet packet and genetic algorithm is proposed. Firstly, the excellent performance of the wavelet packet that processes non-stationary vibration signals is used to extract the original vibration signal features, and the information that characterizes the damage is obtained. Then, the data set is established through characteristic parameters to train and test the derrick steel structural damage identification method. Combined with the characteristics of the genetic algorithm, the identification method reduces the shortcomings of the traditional BP neural network. The identification method can determine the damage location without comparing the data characteristics before damage. The experimental results show that the accuracy of the derrick steel structural damage identification method is more than 90%, being higher than that of the traditional BP neural network.
The damage of a derrick steel structure affects its bearing safety. In order to identify the damage location quickly and accurately, a method for identifying the damage of a derrick steel structure based on the BP neural network optimized with wavelet packet and genetic algorithm is proposed. Firstly, the excellent performance of the wavelet packet that processes non-stationary vibration signals is used to extract the original vibration signal features, and the information that characterizes the damage is obtained. Then, the data set is established through characteristic parameters to train and test the derrick steel structural damage identification method. Combined with the characteristics of the genetic algorithm, the identification method reduces the shortcomings of the traditional BP neural network. The identification method can determine the damage location without comparing the data characteristics before damage. The experimental results show that the accuracy of the derrick steel structural damage identification method is more than 90%, being higher than that of the traditional BP neural network.
2024, 43(1): 45-53.
doi: 10.13433/j.cnki.1003-8728.20230324
Abstract:
In order to study the potential improvement of intake port water injection (w PWI) technology on the thermal efficiency of gasoline engines, a research single cylinder gasoline engine was used to compare and study the effects of w PWI on the engine combustion performance under different spray ratios, load conditions, and compression ratios (CRs) through experimental means. The results show that the w PWI technology can effectively reduce the knock tendency of the engine. With the increasing of water injection ratio, the CA50 is gradually advanced, the ignition delay period and combustion duration are increased, and the heat transfer loss is gradually increased. Comparing with the result of no port water injection (w/o PWI), although the introduction of water injection leads to the increase in unburned loss, it is conducive to the substantial reduction of exhaust energy loss. The final economic performances of engine show that the thermal efficiency increases firstly and then decreases with the increasing of proportion of water injection, and the fuel consumption rate is opposite to that of the thermal efficiency. At this time, the best gross indicating thermal efficiency (GITE) is 43.1%, which is 2.5% percentage points higher than that of w/o PWI; The best gross indicated specific fuel consumption (GISFC) is 197.9 g/(kW·h), which is 11.8 g/(kW·h) lower than that of w/o PWI. The application of water injection technology at high load will achieve more significant improvement in thermal efficiency and fuel consumption. At the same time, the introduction of the water injection technology makes it possible to apply the high compression ratio (CR) on the engine.
In order to study the potential improvement of intake port water injection (w PWI) technology on the thermal efficiency of gasoline engines, a research single cylinder gasoline engine was used to compare and study the effects of w PWI on the engine combustion performance under different spray ratios, load conditions, and compression ratios (CRs) through experimental means. The results show that the w PWI technology can effectively reduce the knock tendency of the engine. With the increasing of water injection ratio, the CA50 is gradually advanced, the ignition delay period and combustion duration are increased, and the heat transfer loss is gradually increased. Comparing with the result of no port water injection (w/o PWI), although the introduction of water injection leads to the increase in unburned loss, it is conducive to the substantial reduction of exhaust energy loss. The final economic performances of engine show that the thermal efficiency increases firstly and then decreases with the increasing of proportion of water injection, and the fuel consumption rate is opposite to that of the thermal efficiency. At this time, the best gross indicating thermal efficiency (GITE) is 43.1%, which is 2.5% percentage points higher than that of w/o PWI; The best gross indicated specific fuel consumption (GISFC) is 197.9 g/(kW·h), which is 11.8 g/(kW·h) lower than that of w/o PWI. The application of water injection technology at high load will achieve more significant improvement in thermal efficiency and fuel consumption. At the same time, the introduction of the water injection technology makes it possible to apply the high compression ratio (CR) on the engine.
2024, 43(1): 54-63.
doi: 10.13433/j.cnki.1003-8728.20220198
Abstract:
Because it is difficult to take into account the machining flexibility and machining efficiency at the same time in improving the S-type acceleration and deceleration for the traditional NURBS curve interpolation, a speed planning algorithm that combines multiple S-type accelerations and decelerations is proposed. Two S-type acceleration and deceleration models which have been separately improved for machining flexibility and efficiency are selected. A novel and improved S-type acceleration and deceleration model with both flexibility and efficiency considered is designed. According to the simplified four acceleration and deceleration forms, the speed planning algorithm flexibly combines the three models, and the speed smoothing method that merges curve segments is adopted to reduce the velocity fluctuation between the curve segments. The simulation results show that the speed planning algorithm can improve the machining efficiency and satisfy the continuity of jerk, finally achieving both machining flexibility and machining efficiency.
Because it is difficult to take into account the machining flexibility and machining efficiency at the same time in improving the S-type acceleration and deceleration for the traditional NURBS curve interpolation, a speed planning algorithm that combines multiple S-type accelerations and decelerations is proposed. Two S-type acceleration and deceleration models which have been separately improved for machining flexibility and efficiency are selected. A novel and improved S-type acceleration and deceleration model with both flexibility and efficiency considered is designed. According to the simplified four acceleration and deceleration forms, the speed planning algorithm flexibly combines the three models, and the speed smoothing method that merges curve segments is adopted to reduce the velocity fluctuation between the curve segments. The simulation results show that the speed planning algorithm can improve the machining efficiency and satisfy the continuity of jerk, finally achieving both machining flexibility and machining efficiency.
2024, 43(1): 64-72.
doi: 10.13433/j.cnki.1003-8728.20220207
Abstract:
In order to obtain the reasonable process parameters in the vertical continuous casting of large diameter Ø260×Ø80 C70600 cupronickel alloy hollow ingot, the effects of the processing parameters on the temperature field and stress field were quantitatively analyzed by using numerical simulation. The results show that the sump depth increases by 10 mm when the casting temperature increases by 20 ℃, and the sump depth increases by 20 mm when the drawing speed increases by 10 mm/min. The sump depth decreases with the increasing of cooling strength of the graphite core tube. Based on the orthogonal test and variance analysis: FA > F0.01(3, 3), FB > FD > F0.1(3, 3), FC < F0.1(3, 3), therefore, the sump depth is extremely sensitive to the drawing speed, the sump depth is not sensitive to the drawing speed primary cold strength. According to the simulation results, the reasonable processing parameters are as follows: primary cooling strength of 24 m3/h, drawing speed of 80 mm/min, casting temperature of 1 280 ℃, and air cooling for core tube, on this basis, the C70600 cupronickel alloy hollow ingots were successfully produced.
In order to obtain the reasonable process parameters in the vertical continuous casting of large diameter Ø260×Ø80 C70600 cupronickel alloy hollow ingot, the effects of the processing parameters on the temperature field and stress field were quantitatively analyzed by using numerical simulation. The results show that the sump depth increases by 10 mm when the casting temperature increases by 20 ℃, and the sump depth increases by 20 mm when the drawing speed increases by 10 mm/min. The sump depth decreases with the increasing of cooling strength of the graphite core tube. Based on the orthogonal test and variance analysis: FA > F0.01(3, 3), FB > FD > F0.1(3, 3), FC < F0.1(3, 3), therefore, the sump depth is extremely sensitive to the drawing speed, the sump depth is not sensitive to the drawing speed primary cold strength. According to the simulation results, the reasonable processing parameters are as follows: primary cooling strength of 24 m3/h, drawing speed of 80 mm/min, casting temperature of 1 280 ℃, and air cooling for core tube, on this basis, the C70600 cupronickel alloy hollow ingots were successfully produced.
2024, 43(1): 73-80.
doi: 10.13433/j.cnki.1003-8728.20220201
Abstract:
In order to improve the surface quality of polished surface parts, a roughness model should be established to select reasonable process parameters. Therefore, a modeling method based on support vector machine (SVM) is proposed in this paper. Through researching the robot polishing process and polishing process parameters, the tool rotation speed, polishing force, row spacing, robot feed speed, etc. are used as input variables, and roughness is used as output variables. Combined with particle swarm optimization (PSO) and SVM, a prediction model of curved surface parts polishing roughness was established, and compared with the regression analysis method. The experimental results show that the prediction error of the regression analysis method is relatively large, and the prediction model of polishing roughness of curved surface parts established based on SVM is highly consistent with the experimental results. The average relative error between the experimental measured value and the predicted value is 2.84%. The optimal combination of process parameters is obtained by optimization, and the model provides a basis for rational selection of polishing process parameters.
In order to improve the surface quality of polished surface parts, a roughness model should be established to select reasonable process parameters. Therefore, a modeling method based on support vector machine (SVM) is proposed in this paper. Through researching the robot polishing process and polishing process parameters, the tool rotation speed, polishing force, row spacing, robot feed speed, etc. are used as input variables, and roughness is used as output variables. Combined with particle swarm optimization (PSO) and SVM, a prediction model of curved surface parts polishing roughness was established, and compared with the regression analysis method. The experimental results show that the prediction error of the regression analysis method is relatively large, and the prediction model of polishing roughness of curved surface parts established based on SVM is highly consistent with the experimental results. The average relative error between the experimental measured value and the predicted value is 2.84%. The optimal combination of process parameters is obtained by optimization, and the model provides a basis for rational selection of polishing process parameters.
2024, 43(1): 81-89.
doi: 10.13433/j.cnki.1003-8728.20220210
Abstract:
With the rapid development of 3D printing technology in recent years, the material extrusion process to fabricate functionally graded materials has become a research hotspot. The transition between materials is the critical issue which affects the final molding quality. At present, only the transition distance between two independent materials has been studied by domestic and foreign scholars, and there were less research on the transition distance between materials with different components. The transition distance between different component materials was investigated by using a dual barrel printer, and through experiments to explore the influence of different feeds on the transition distance, the feed with the smallest transition distance was obtained under the premise of ensuring the print quality. Visual Studio 2019 was utilized as the development platform to propose a new feed strategy to shorten the transition distance, the materials information of the sliced points were judged in the path planning, for materials with increasing components, the feeds of two barrel printer were calculated based on the change values, and a new G-code was generated for printing. Finally, the new G-code was employed for printing experiments, which shorten the material transition distance and achieve the desired material transition curve.
With the rapid development of 3D printing technology in recent years, the material extrusion process to fabricate functionally graded materials has become a research hotspot. The transition between materials is the critical issue which affects the final molding quality. At present, only the transition distance between two independent materials has been studied by domestic and foreign scholars, and there were less research on the transition distance between materials with different components. The transition distance between different component materials was investigated by using a dual barrel printer, and through experiments to explore the influence of different feeds on the transition distance, the feed with the smallest transition distance was obtained under the premise of ensuring the print quality. Visual Studio 2019 was utilized as the development platform to propose a new feed strategy to shorten the transition distance, the materials information of the sliced points were judged in the path planning, for materials with increasing components, the feeds of two barrel printer were calculated based on the change values, and a new G-code was generated for printing. Finally, the new G-code was employed for printing experiments, which shorten the material transition distance and achieve the desired material transition curve.
2024, 43(1): 90-95.
doi: 10.13433/j.cnki.1003-8728.20220193
Abstract:
According to the constant amplitude fatigue test results of ST12 steel double-spot and three-spot tensile shear resistance spot welded specimens, the fatigue lives were predicted by using the notch stress method and equivalent structure stress method respectively. While using notch stress method, the three-dimensional solid finite element models for double-spot and three-spot tensile shear spot weld according to the actual specimen size and the recommendation of International institute of welding(IIW), the von Mises maximum stress change regime were obtained from the finite element results, the fatigue lives were predicted according to the S-N curve in the IIW recommended standard and while using the structural stress method, a hybrid model for beam and shell stress analysis, then the fatigue lives were predicted according to the main S-N curve. The results showed that the results predicted by using the notch stress method and the equivalent structural stress method are well correlated relatively to the actual lives of the specimen within low cycle regime, where the results by using the equivalent structural stress method are closer to the experimental results.
According to the constant amplitude fatigue test results of ST12 steel double-spot and three-spot tensile shear resistance spot welded specimens, the fatigue lives were predicted by using the notch stress method and equivalent structure stress method respectively. While using notch stress method, the three-dimensional solid finite element models for double-spot and three-spot tensile shear spot weld according to the actual specimen size and the recommendation of International institute of welding(IIW), the von Mises maximum stress change regime were obtained from the finite element results, the fatigue lives were predicted according to the S-N curve in the IIW recommended standard and while using the structural stress method, a hybrid model for beam and shell stress analysis, then the fatigue lives were predicted according to the main S-N curve. The results showed that the results predicted by using the notch stress method and the equivalent structural stress method are well correlated relatively to the actual lives of the specimen within low cycle regime, where the results by using the equivalent structural stress method are closer to the experimental results.
2024, 43(1): 96-102.
doi: 10.13433/j.cnki.1003-8728.20230287
Abstract:
Thin-walled parts are widely used in aerospace applications, and their manufacturing accuracy directly determines the performance of the equipment in service. However, the effect of the heat treatment leads to the existence of residual stresses in thin-walled parts prior to machining. If not properly controlled, it is very easy to cause the part to exceed the tolerance. Therefore, for 7075 aluminum alloy sheet, the principle of residual stresses generated in the quenching and pre-stretching of the sheet is analyzed. Furthermore, the generation process of residual stresses in 7075 aluminum alloy blanks in the quenching process and pre-stretching is simulated by using the finite element method. It was found that the quenched residual stresses were reduced up to 91.2% when the blank was stretched by about 3% with a plastic strain of about 2.4%. According to the reduction of residual stresses, a simulation model for milling of thin-walled structural parts is established to simulate the milling deformation under the coupling effect of the multiple factors. The correctness of the simulation results is verified by using the milling experiments.
Thin-walled parts are widely used in aerospace applications, and their manufacturing accuracy directly determines the performance of the equipment in service. However, the effect of the heat treatment leads to the existence of residual stresses in thin-walled parts prior to machining. If not properly controlled, it is very easy to cause the part to exceed the tolerance. Therefore, for 7075 aluminum alloy sheet, the principle of residual stresses generated in the quenching and pre-stretching of the sheet is analyzed. Furthermore, the generation process of residual stresses in 7075 aluminum alloy blanks in the quenching process and pre-stretching is simulated by using the finite element method. It was found that the quenched residual stresses were reduced up to 91.2% when the blank was stretched by about 3% with a plastic strain of about 2.4%. According to the reduction of residual stresses, a simulation model for milling of thin-walled structural parts is established to simulate the milling deformation under the coupling effect of the multiple factors. The correctness of the simulation results is verified by using the milling experiments.
2024, 43(1): 103-109.
doi: 10.13433/j.cnki.1003-8728.20230389
Abstract:
To fulfill the lightweight requirements of helicopter transmission systems, transmission gears as a critical component of helicopters, possess the noticeable characteristic of thin walls, which presents challenges in terms of severe deformation and the assurance of dimensional precision during the machining process. This article focuses on the study of thin-walled gear spoke plate made from high-strength medium alloy carburized steel. Using the ABAQUS finite element analysis software, a simulation study on the cutting process was conducted. By establishing a three-dimensional dynamic cutting simulation model, the relationship between the cutting forces and the cutting parameters on the parts in the machining was analyzed. Static simulation methods were used to analyze the influence of the superposition of cutting force and clamping force on the processing deformation of thin-walled spoke. Then range analysis was used to examine the simulation results. Finally, the experimental validation of the simulation results was carried out. The results indicate that in the static analysis of gear thin-walled spoke plate machining deformation, the axial deformation of the gear spoke plate is most significant, and the radial deformation is most prominent at the hub. Range analysis reveals that the optimal cutting parameters are the cutting speed of 150 m/min, the feed rate of 0.06 mm/r, and the cutting depth of 1.8 mm, with the prediction error for the maximum deformation of below 10%.
To fulfill the lightweight requirements of helicopter transmission systems, transmission gears as a critical component of helicopters, possess the noticeable characteristic of thin walls, which presents challenges in terms of severe deformation and the assurance of dimensional precision during the machining process. This article focuses on the study of thin-walled gear spoke plate made from high-strength medium alloy carburized steel. Using the ABAQUS finite element analysis software, a simulation study on the cutting process was conducted. By establishing a three-dimensional dynamic cutting simulation model, the relationship between the cutting forces and the cutting parameters on the parts in the machining was analyzed. Static simulation methods were used to analyze the influence of the superposition of cutting force and clamping force on the processing deformation of thin-walled spoke. Then range analysis was used to examine the simulation results. Finally, the experimental validation of the simulation results was carried out. The results indicate that in the static analysis of gear thin-walled spoke plate machining deformation, the axial deformation of the gear spoke plate is most significant, and the radial deformation is most prominent at the hub. Range analysis reveals that the optimal cutting parameters are the cutting speed of 150 m/min, the feed rate of 0.06 mm/r, and the cutting depth of 1.8 mm, with the prediction error for the maximum deformation of below 10%.
2024, 43(1): 110-116.
doi: 10.13433/j.cnki.1003-8728.20220235
Abstract:
With the development of Internet of Things, self-powered acoustic sensors have attracted extensive attention. However, it is difficult to further improve piezoelectric sensors′ sensitivity and other vital indicators. Acoustic metamaterials can manipulate sound waves, while traditional materials cannot, thus providing a new method for designing new acoustic sensors. This paper designs a self-powered sensor of acoustic metamaterial and Helmholtz resonance structure. It also verifies that the defective acoustic metamaterial can focus acoustic energy. In addition, the Helmholtz resonator can further amplify the acoustic energy focused on the defective acoustic metamaterial. Its transmission ratio is more than 40 mV/Pa and meets the demand of a small self-powered sensor. The experimental results show that compared with the acoustic metamaterial sensor, the acoustic metamaterial sensor based on the Helmholtz resonator has higher sensitivity and signal-to-noise ratio.
With the development of Internet of Things, self-powered acoustic sensors have attracted extensive attention. However, it is difficult to further improve piezoelectric sensors′ sensitivity and other vital indicators. Acoustic metamaterials can manipulate sound waves, while traditional materials cannot, thus providing a new method for designing new acoustic sensors. This paper designs a self-powered sensor of acoustic metamaterial and Helmholtz resonance structure. It also verifies that the defective acoustic metamaterial can focus acoustic energy. In addition, the Helmholtz resonator can further amplify the acoustic energy focused on the defective acoustic metamaterial. Its transmission ratio is more than 40 mV/Pa and meets the demand of a small self-powered sensor. The experimental results show that compared with the acoustic metamaterial sensor, the acoustic metamaterial sensor based on the Helmholtz resonator has higher sensitivity and signal-to-noise ratio.
2024, 43(1): 117-124.
doi: 10.13433/j.cnki.1003-8728.20220144
Abstract:
In order to study the stress intensity factors (SIFs) for hollow axle of EMU, the influencing factors of the axle SIFs were firstly analyzed. The finite element model for axle with crack was established, and the superposition method was used to evaluate SIFs under different loads. Then, the SIFs were calculated by using the stress extrapolation method (SEM) and displacement extrapolation method (DEM), and the calculation results were compared with that by using the shape factor formula method. Finally, a fifth-order polynomial was used to fit the shape factor function according to the general analytical formula of SIFs and calculation results via DEM. The applicability of the shape factor function and the analytical formula was verified by setting the different crack depths and loads. The results indicated the present method had certain reference value for calculating SIFs of axle under the same load mode.
In order to study the stress intensity factors (SIFs) for hollow axle of EMU, the influencing factors of the axle SIFs were firstly analyzed. The finite element model for axle with crack was established, and the superposition method was used to evaluate SIFs under different loads. Then, the SIFs were calculated by using the stress extrapolation method (SEM) and displacement extrapolation method (DEM), and the calculation results were compared with that by using the shape factor formula method. Finally, a fifth-order polynomial was used to fit the shape factor function according to the general analytical formula of SIFs and calculation results via DEM. The applicability of the shape factor function and the analytical formula was verified by setting the different crack depths and loads. The results indicated the present method had certain reference value for calculating SIFs of axle under the same load mode.
2024, 43(1): 125-129.
doi: 10.13433/j.cnki.1003-8728.20220232
Abstract:
Aiming at the safety problem and lightweight design requirements of train-set emergency battery box, the optimization analysis was carried out by integrating multiple optimization objectives. The thickness of the main components was taken as the design variables, the total mass of the emergency battery box and the minimum stress under harsh conditions were taken as the optimization objectives, and the first-order natural frequency was taken as the constraint function. The sample data were obtained by Box-Behnken design method. A low-order polynomial response surface model was established based on the sample data, and multi-objective optimization was carried out using the third-generation non-dominated sorting genetic algorithm (NSGA-Ⅲ). The results show that compared with the single response surface method or genetic algorithm, the combination of response surface method and genetic algorithm adopted in this paper makes the optimized parameters more reasonable, lightweight and safety are guaranteed.
Aiming at the safety problem and lightweight design requirements of train-set emergency battery box, the optimization analysis was carried out by integrating multiple optimization objectives. The thickness of the main components was taken as the design variables, the total mass of the emergency battery box and the minimum stress under harsh conditions were taken as the optimization objectives, and the first-order natural frequency was taken as the constraint function. The sample data were obtained by Box-Behnken design method. A low-order polynomial response surface model was established based on the sample data, and multi-objective optimization was carried out using the third-generation non-dominated sorting genetic algorithm (NSGA-Ⅲ). The results show that compared with the single response surface method or genetic algorithm, the combination of response surface method and genetic algorithm adopted in this paper makes the optimized parameters more reasonable, lightweight and safety are guaranteed.
2024, 43(1): 130-140.
doi: 10.13433/j.cnki.1003-8728.20220218
Abstract:
Path tracking plays an indispensable role in the autonomous driving of a vehicle. In order to ensure the real-time performance of the path tracking controller and improve its stability and adaptability, we improved a lateral path tracking controller based on the linear quadratic regulator (LQR). Firstly, we transform the vehicle′s dynamics model into a lateral error dynamics model. Based on this model, a feedforward plus feedback discrete LQR controller is designed. Then, the fuzzy control method is used to adjust the weighted coefficient of the LQR in real time according to the vehicle′s state. In addition, an update mechanism based on the cosine similarity is designed to reduce the calculation volume of the controller. Finally, the improved lateral path tracking controller was tested on the double change lane path through the Simulink-Carsim platform. The test results show that the controller dramatically improves the tracking accuracy, steering stability, and calculation efficiency.
Path tracking plays an indispensable role in the autonomous driving of a vehicle. In order to ensure the real-time performance of the path tracking controller and improve its stability and adaptability, we improved a lateral path tracking controller based on the linear quadratic regulator (LQR). Firstly, we transform the vehicle′s dynamics model into a lateral error dynamics model. Based on this model, a feedforward plus feedback discrete LQR controller is designed. Then, the fuzzy control method is used to adjust the weighted coefficient of the LQR in real time according to the vehicle′s state. In addition, an update mechanism based on the cosine similarity is designed to reduce the calculation volume of the controller. Finally, the improved lateral path tracking controller was tested on the double change lane path through the Simulink-Carsim platform. The test results show that the controller dramatically improves the tracking accuracy, steering stability, and calculation efficiency.
2024, 43(1): 141-149.
doi: 10.13433/j.cnki.1003-8728.20220186
Abstract:
Speed adaptive dynamic preview distance is an effective way to improve the lateral tracking control effect of intelligent vehicle, and as for the problem of using current vehicle speed for the preview distance, a dynamic preview distance tracking control algorithm combining planned path and planned speed information is proposed to improve the accuracy of path tracking at low speed. Based on the pure pursue algorithm, the lateral tracking control laws of moving forward and reversing are derived. According to the real-time planned path and speed information, a dynamic adjustment method of preview distance was designed, and the relationship between the preview distance and the steering angle with speed adaptability was thereby obtained. Finally, the effectiveness and accuracy of the proposed algorithm were verified in CarSim-MATLAB/Simulink co-simulation environment, and a real vehicle test was performed, indicating that the proposed algorithm has lower computational consumption and higher tracking accuracy than the LQR algorithm based on dynamics model.
Speed adaptive dynamic preview distance is an effective way to improve the lateral tracking control effect of intelligent vehicle, and as for the problem of using current vehicle speed for the preview distance, a dynamic preview distance tracking control algorithm combining planned path and planned speed information is proposed to improve the accuracy of path tracking at low speed. Based on the pure pursue algorithm, the lateral tracking control laws of moving forward and reversing are derived. According to the real-time planned path and speed information, a dynamic adjustment method of preview distance was designed, and the relationship between the preview distance and the steering angle with speed adaptability was thereby obtained. Finally, the effectiveness and accuracy of the proposed algorithm were verified in CarSim-MATLAB/Simulink co-simulation environment, and a real vehicle test was performed, indicating that the proposed algorithm has lower computational consumption and higher tracking accuracy than the LQR algorithm based on dynamics model.
2024, 43(1): 150-158.
doi: 10.13433/j.cnki.1003-8728.20220190
Abstract:
The real-time and accurate estimation of vehicle states is the premise of vehicle intelligence development. However, the existing researches usually ignore the time-varying characteristics of tire cornering stiffness, and introducing linear tire model into vehicle model seriously affects the estimation accuracy of vehicle states under extreme conditions. An algorithm for estimating intelligent electric vehicle longitudinal speed, yaw rate and sideslip angle of vehicle mass center with tire cornering stiffness updated online is proposed. Based on the fuzzy adaptive extended Kalman filter (FAEKF), the vehicle state estimation model is established. The fuzzy controller is used to adjust the Kalman gain matrix including the covariance of observation noise in EKF algorithm in real time to achieve the adaptive effect of the algorithm. Using the forgetting-factor recursive least square method (FFRLS), the estimation model of tire cornering stiffness is established. A new FAEKF+FFRLS algorithm is proposed by combining the two algorithms in an embedded way, which can better realize the joint estimation and mutual correction of states and parameters. The algorithm is verified by co-simulation Trucksim and MATLAB/Simulink. The results show that compared with the standard EKF algorithm, the proposed state estimation algorithm has higher accuracy, better stability and robustness.
The real-time and accurate estimation of vehicle states is the premise of vehicle intelligence development. However, the existing researches usually ignore the time-varying characteristics of tire cornering stiffness, and introducing linear tire model into vehicle model seriously affects the estimation accuracy of vehicle states under extreme conditions. An algorithm for estimating intelligent electric vehicle longitudinal speed, yaw rate and sideslip angle of vehicle mass center with tire cornering stiffness updated online is proposed. Based on the fuzzy adaptive extended Kalman filter (FAEKF), the vehicle state estimation model is established. The fuzzy controller is used to adjust the Kalman gain matrix including the covariance of observation noise in EKF algorithm in real time to achieve the adaptive effect of the algorithm. Using the forgetting-factor recursive least square method (FFRLS), the estimation model of tire cornering stiffness is established. A new FAEKF+FFRLS algorithm is proposed by combining the two algorithms in an embedded way, which can better realize the joint estimation and mutual correction of states and parameters. The algorithm is verified by co-simulation Trucksim and MATLAB/Simulink. The results show that compared with the standard EKF algorithm, the proposed state estimation algorithm has higher accuracy, better stability and robustness.
State Estimation and Control for Path Following of Intelligent Connected Vehicle with Network Attack
2024, 43(1): 159-165.
doi: 10.13433/j.cnki.1003-8728.20220205
Abstract:
Intelligent connected vehicle has the characteristics of CPS, vulnerable to the adverse impact of network attack in operation, then resulting in abnormal communication data interaction, and reducing driving safety. The path following dynamics model of intelligent connected vehicle and 2-DOF vehicle handling dynamics model are established. The information architecture for path following control system of vehicles is analyzed. Considering that there is a network attack in the system response, the state space equation of continuous system was discretized. A recursive state estimator based on linear quadratic estimation is designed. The influence of network attack on path following of intelligent connected vehicle, and the effect and robustness of state estimator on control for path following of vehicle under network attack are simulated. The results show that network attack will make the path following effect of intelligent connected vehicle worse. The state estimator can effectively improve the negative influence of network attack on vehicle tracking control. The state estimator shows good robustness with the difference of network attack degree λ and initial value of covariance P. This study can ensure the reliable interaction of data and information for intelligent connected vehicle under network attack, which is beneficial to improve the tracking performance of intelligent connected vehicle.
Intelligent connected vehicle has the characteristics of CPS, vulnerable to the adverse impact of network attack in operation, then resulting in abnormal communication data interaction, and reducing driving safety. The path following dynamics model of intelligent connected vehicle and 2-DOF vehicle handling dynamics model are established. The information architecture for path following control system of vehicles is analyzed. Considering that there is a network attack in the system response, the state space equation of continuous system was discretized. A recursive state estimator based on linear quadratic estimation is designed. The influence of network attack on path following of intelligent connected vehicle, and the effect and robustness of state estimator on control for path following of vehicle under network attack are simulated. The results show that network attack will make the path following effect of intelligent connected vehicle worse. The state estimator can effectively improve the negative influence of network attack on vehicle tracking control. The state estimator shows good robustness with the difference of network attack degree λ and initial value of covariance P. This study can ensure the reliable interaction of data and information for intelligent connected vehicle under network attack, which is beneficial to improve the tracking performance of intelligent connected vehicle.
2024, 43(1): 166-172.
doi: 10.13433/j.cnki.1003-8728.20220192
Abstract:
Composite damage failure form is various, the damage failure forms including laminated plate damage, colloid crack extension and interface debonding. To investigate damage of laminates, colloid crack propagation, interface delamination inherent relations among the three kinds of damage failure, the hybrid bending (MMB) fracture finite element model is firstly established by using ABAQUS/Explicit software, by comparing the simulation and experimental results, which proves the accuracy of MMB model. Then, the internal relationship among the three failure modes was studied by combining the Hashin failure criterion, extended finite Element method (XFEM) and cohesive force model (CZM). The results show that the damage of laminates can not only affect the time of interface viscous separation failure, but also affect the crack propagation path in colloid, which provides a certain reference for numerical analysis of the damage problem of composites.
Composite damage failure form is various, the damage failure forms including laminated plate damage, colloid crack extension and interface debonding. To investigate damage of laminates, colloid crack propagation, interface delamination inherent relations among the three kinds of damage failure, the hybrid bending (MMB) fracture finite element model is firstly established by using ABAQUS/Explicit software, by comparing the simulation and experimental results, which proves the accuracy of MMB model. Then, the internal relationship among the three failure modes was studied by combining the Hashin failure criterion, extended finite Element method (XFEM) and cohesive force model (CZM). The results show that the damage of laminates can not only affect the time of interface viscous separation failure, but also affect the crack propagation path in colloid, which provides a certain reference for numerical analysis of the damage problem of composites.
2024, 43(1): 173-179.
doi: 10.13433/j.cnki.1003-8728.20220194
Abstract:
Negative poisson's ratio (NPR) cellular material has been widely used in aerospace and military equipment and other fields owing to its outstanding multidirectional energy absorption and adjustable volume. Based on the re-entrant theory, the cell structure with a novel orthogonal isotropic spatial negative poisson's ratio cellular material (REC cell for short) is designed and reinforced. The uniaxial tensile mechanical behavior of REC cells and seven reinforced cells in z direction is studied by using the finite element simulation. The effects of the geometric parameters on the non-dimensional elastic modulus and poisson's ratio of cells are analyzed. The simulation results are verified by using the tensile tests of a group of 3D printed cell specimens. The results can provide a basis for designing the specific mechanical performance parameters in the engineering application of new spatial negative poisson porous structure.
Negative poisson's ratio (NPR) cellular material has been widely used in aerospace and military equipment and other fields owing to its outstanding multidirectional energy absorption and adjustable volume. Based on the re-entrant theory, the cell structure with a novel orthogonal isotropic spatial negative poisson's ratio cellular material (REC cell for short) is designed and reinforced. The uniaxial tensile mechanical behavior of REC cells and seven reinforced cells in z direction is studied by using the finite element simulation. The effects of the geometric parameters on the non-dimensional elastic modulus and poisson's ratio of cells are analyzed. The simulation results are verified by using the tensile tests of a group of 3D printed cell specimens. The results can provide a basis for designing the specific mechanical performance parameters in the engineering application of new spatial negative poisson porous structure.
2024, 43(1): 180-186.
doi: 10.13433/j.cnki.1003-8728.20220220
Abstract:
To analyze the noise characteristics of restriction orifice in aircraft air conditioning duct system and carry out the noise reduction optimization design of restriction orifice plate, the computational fluid dynamics method is used to calculate the steady flow field of a straight duct with the restrictor orifice at first and explore the flow state of the airflow through the orifice. Then, according to the large eddy simulation method and the Ffowcs Williams and Hawkings(FW-H) equation, the transient flow field and acoustic calculation of the duct are carried out, and the flow-induced noise characteristics of restriction orifice at the aircraft cockpit monitoring point are analyzed. Finally, the effects of restriction orifices with different aperture on the cockpit monitoring points are compared and studied, and a better low-noise structure design form of the orifice plate is proposed. The research results show that increasing the flow aperture can improve the noise reduction effect, but the pressure drop performance is reduced, and the noise reduction of the restriction orifice needs to be considered comprehensively with its pressure drop performance.
To analyze the noise characteristics of restriction orifice in aircraft air conditioning duct system and carry out the noise reduction optimization design of restriction orifice plate, the computational fluid dynamics method is used to calculate the steady flow field of a straight duct with the restrictor orifice at first and explore the flow state of the airflow through the orifice. Then, according to the large eddy simulation method and the Ffowcs Williams and Hawkings(FW-H) equation, the transient flow field and acoustic calculation of the duct are carried out, and the flow-induced noise characteristics of restriction orifice at the aircraft cockpit monitoring point are analyzed. Finally, the effects of restriction orifices with different aperture on the cockpit monitoring points are compared and studied, and a better low-noise structure design form of the orifice plate is proposed. The research results show that increasing the flow aperture can improve the noise reduction effect, but the pressure drop performance is reduced, and the noise reduction of the restriction orifice needs to be considered comprehensively with its pressure drop performance.
