Author Center
Editor Work
Peer Review
Editorial Entry
Email Alert
RSS2022 Vol. 41, No. 3
Display Method:
2022, 41(3): 329-336.
doi: 10.13433/j.cnki.1003-8728.20200346
PDF 3378KB
Abstract:
When a local fault occurs in the bearing, the weak impact characteristic that can represent the early fault of the rolling bearing is often submerged by strong background noise in the process of sensor acquisition, and it is easily affected by the signal transmission path, thus making it difficult to diagnose the bearing fault. To solve the above problems, an adaptive combined rolling bearing denoising method based on improved variational mode decomposition (VMD) and multi-point optimal minimum entropy deconvolution (MOMEDA) is proposed in this paper. Firstly, in order to solve the problem of VMD which relies heavily on artificial prior knowledge, particle swarm optimization (PSO) is adopted to optimize VMD, and kurtosis is taken as the optimization index to select the optimal IMF component, and then MOMEDA is further adopted to eliminate the influence of the transmission path on the signal. Finally, the rolling bearing fault is diagnosed combined with 1.5D energy spectrum. Compared with MED-VMD and conventional envelope spectrum methods, the advantages of the proposed method are proved in the field of bearing fault feature extraction.
When a local fault occurs in the bearing, the weak impact characteristic that can represent the early fault of the rolling bearing is often submerged by strong background noise in the process of sensor acquisition, and it is easily affected by the signal transmission path, thus making it difficult to diagnose the bearing fault. To solve the above problems, an adaptive combined rolling bearing denoising method based on improved variational mode decomposition (VMD) and multi-point optimal minimum entropy deconvolution (MOMEDA) is proposed in this paper. Firstly, in order to solve the problem of VMD which relies heavily on artificial prior knowledge, particle swarm optimization (PSO) is adopted to optimize VMD, and kurtosis is taken as the optimization index to select the optimal IMF component, and then MOMEDA is further adopted to eliminate the influence of the transmission path on the signal. Finally, the rolling bearing fault is diagnosed combined with 1.5D energy spectrum. Compared with MED-VMD and conventional envelope spectrum methods, the advantages of the proposed method are proved in the field of bearing fault feature extraction.
2022, 41(3): 337-341.
doi: 10.13433/j.cnki.1003-8728.20200368
Abstract:
The sulfuric acid paper is sensitive to humidity, the deformation mechanism is studied, the intelligent structure is designed, and it is proposed to apply to the design of the soft machine. Firstly, the microstructure and mechanical properties of sulfuric acid paper were characterized and analyzed, which indicated that the paper plane is anisotropic and can realize motion modes such as curling and spiraling, and the deformation mechanism is given; an intelligent structure of self-folding cube was designed and guided with the finite element analysis and verified with the experimental results. Secondly, a soft actuator based on smart paper is proposed and applied to the design of an underwater adaptive soft gripper. It does not require an external string input, and can achieve motion control depending on the humidity environment, and can lift objects that are 45 times heavier than itself. Finally, the strip worm-bot can achieve continuous motion in a stable environment, and the speed can reach 0.06 BL/s. It will be a good prospect for the smart material to use in soft machines.
The sulfuric acid paper is sensitive to humidity, the deformation mechanism is studied, the intelligent structure is designed, and it is proposed to apply to the design of the soft machine. Firstly, the microstructure and mechanical properties of sulfuric acid paper were characterized and analyzed, which indicated that the paper plane is anisotropic and can realize motion modes such as curling and spiraling, and the deformation mechanism is given; an intelligent structure of self-folding cube was designed and guided with the finite element analysis and verified with the experimental results. Secondly, a soft actuator based on smart paper is proposed and applied to the design of an underwater adaptive soft gripper. It does not require an external string input, and can achieve motion control depending on the humidity environment, and can lift objects that are 45 times heavier than itself. Finally, the strip worm-bot can achieve continuous motion in a stable environment, and the speed can reach 0.06 BL/s. It will be a good prospect for the smart material to use in soft machines.
2022, 41(3): 342-348.
doi: 10.13433/j.cnki.1003-8728.20200373
Abstract:
Aiming at the problem that it is easy to obtain a large amount of labeled fault type data in a laboratory environment, but it is difficult or impossible to obtain a large amount of labeled data under actual working conditions, a deep anti-migration diagnosis method (MAAN) for mechanical equipment failure is proposed. This method transfers the fault diagnosis knowledge accumulated in the laboratory environment to the actual engineering equipment, through the fusion of time domain and frequency domain data to obtain more comprehensive fault information; in the feature extraction layer, the residual network is used to deeply extract fault features. The adversarial layer uses maximizing domain classification loss to align the marginal distribution and conditional probability distribution between the source domain and target domain, and minimizing the category prediction loss to implement unsupervised migration learning for fault classification of mechanical equipment. Experimental results show that this method and its network models have high classification accuracy in unlabeled target data sets. Under certain conditions, this method can effectively solve the problem of lack of labels in data sets, that is, realize intelligent diagnosis of mechanical fault diagnosis.
Aiming at the problem that it is easy to obtain a large amount of labeled fault type data in a laboratory environment, but it is difficult or impossible to obtain a large amount of labeled data under actual working conditions, a deep anti-migration diagnosis method (MAAN) for mechanical equipment failure is proposed. This method transfers the fault diagnosis knowledge accumulated in the laboratory environment to the actual engineering equipment, through the fusion of time domain and frequency domain data to obtain more comprehensive fault information; in the feature extraction layer, the residual network is used to deeply extract fault features. The adversarial layer uses maximizing domain classification loss to align the marginal distribution and conditional probability distribution between the source domain and target domain, and minimizing the category prediction loss to implement unsupervised migration learning for fault classification of mechanical equipment. Experimental results show that this method and its network models have high classification accuracy in unlabeled target data sets. Under certain conditions, this method can effectively solve the problem of lack of labels in data sets, that is, realize intelligent diagnosis of mechanical fault diagnosis.
2022, 41(3): 349-356.
doi: 10.13433/j.cnki.1003-8728.20200358
Abstract:
Aiming at the characteristics of industrial water pumps in actual operating environment, such as large amount of working condition data, long running time and multiple feature types, a combined fault diagnosis classification algorithm based on the weighted Gaussian weighted K nearest neighbor and the support vector machine (GWKNN-SVM) is proposed. First, feature extraction and cleaning of given industrial data which is collected from three pumps of a chemical plant from 5 months are performed, and then the Gaussian weighted K nearest neighbor algorithm (GWKNN) is used to classify the data quickly and coarsely. Moreover, the support vector machine algorithm (SVM) is used to classify the boundary data which is chosen by GWKNN for fine classification to improve the classification accuracy and identification efficiency of pump faults. Finally, a simulation example is used to compare the fault classification effects using the GWKNN-SVM algorithm and other classification algorithms under the same conditions. Experimental results show that the combined classification method proposed can improve the fault classification accuracy of the water pump effectively, and then achieves the object of the pump health monitoring in the industrial environment.
Aiming at the characteristics of industrial water pumps in actual operating environment, such as large amount of working condition data, long running time and multiple feature types, a combined fault diagnosis classification algorithm based on the weighted Gaussian weighted K nearest neighbor and the support vector machine (GWKNN-SVM) is proposed. First, feature extraction and cleaning of given industrial data which is collected from three pumps of a chemical plant from 5 months are performed, and then the Gaussian weighted K nearest neighbor algorithm (GWKNN) is used to classify the data quickly and coarsely. Moreover, the support vector machine algorithm (SVM) is used to classify the boundary data which is chosen by GWKNN for fine classification to improve the classification accuracy and identification efficiency of pump faults. Finally, a simulation example is used to compare the fault classification effects using the GWKNN-SVM algorithm and other classification algorithms under the same conditions. Experimental results show that the combined classification method proposed can improve the fault classification accuracy of the water pump effectively, and then achieves the object of the pump health monitoring in the industrial environment.
2022, 41(3): 357-362.
doi: 10.13433/j.cnki.1003-8728.20200363
Abstract:
In view of the design of ultrasonic plastic welding horns due to different processing objects, combined with the specific engineering case, integrated with the method of parametric modeling based on longitudinal wave transmission theory, finite element modal and harmonic response analysis, impedance analysis and experimental analysis, the efficiency and accuracy of the design, modeling and structure optimization of the conical composite horns are realized. The results show that the structural design and optimization of the composite horn can be realized more quickly with the parameters. The results also show that the finite element analysis and impedance analysis is in a good agreement with the vibration mode and frequency characteristics of the composite ultrasonic horn, and the experimental test meets the design requirements. It can provide a universal design and analysis method for the single-head ultrasonic plastic welding composite horn.
In view of the design of ultrasonic plastic welding horns due to different processing objects, combined with the specific engineering case, integrated with the method of parametric modeling based on longitudinal wave transmission theory, finite element modal and harmonic response analysis, impedance analysis and experimental analysis, the efficiency and accuracy of the design, modeling and structure optimization of the conical composite horns are realized. The results show that the structural design and optimization of the composite horn can be realized more quickly with the parameters. The results also show that the finite element analysis and impedance analysis is in a good agreement with the vibration mode and frequency characteristics of the composite ultrasonic horn, and the experimental test meets the design requirements. It can provide a universal design and analysis method for the single-head ultrasonic plastic welding composite horn.
2022, 41(3): 363-370.
doi: 10.13433/j.cnki.1003-8728.20200369
Abstract:
In order to improve the ride comfort and handling stability of the car and realize the recovery of vibration energy, the electro-magnetic linear hybrid actuator (EMLHA) was designed. Based on the analysis of EMLHA suspension energy feedback, semi-active and active three working modes, the real-time switching control strategy of compound suspension mode and the variable voltage source system which can realize bidirectional energy flow were designed. The energy consumption characteristics and dynamic characteristics of the compound suspension with the variable voltage source system were simulated and analyzed. The energy consumption and dynamic characteristics of the rack in the compound suspension system with the variable voltage source is simulated and analyzed. The results show that, under the B-level road, comparing with passive suspension, the compound suspension has a 22.41% reduction in the sprung mass acceleration root mean square value, a 19.83% reduction in suspension dynamic deflection root mean square value, and a tire dynamic load root mean square value reduced by 29.74% and energy consumed by 30.7%. The compound suspension can effectively improve the dynamic performance of the suspension and realize the vibration energy recovery.
In order to improve the ride comfort and handling stability of the car and realize the recovery of vibration energy, the electro-magnetic linear hybrid actuator (EMLHA) was designed. Based on the analysis of EMLHA suspension energy feedback, semi-active and active three working modes, the real-time switching control strategy of compound suspension mode and the variable voltage source system which can realize bidirectional energy flow were designed. The energy consumption characteristics and dynamic characteristics of the compound suspension with the variable voltage source system were simulated and analyzed. The energy consumption and dynamic characteristics of the rack in the compound suspension system with the variable voltage source is simulated and analyzed. The results show that, under the B-level road, comparing with passive suspension, the compound suspension has a 22.41% reduction in the sprung mass acceleration root mean square value, a 19.83% reduction in suspension dynamic deflection root mean square value, and a tire dynamic load root mean square value reduced by 29.74% and energy consumed by 30.7%. The compound suspension can effectively improve the dynamic performance of the suspension and realize the vibration energy recovery.
2022, 41(3): 371-378.
doi: 10.13433/j.cnki.1003-8728.20200347
Abstract:
The leaf spring bench fatigue load spectrum has always been derived from the empirical estimates. It does not reflect the true stress state of the leaf spring. A new method for editing the leaf spring bench fatigue load spectrum is proposed. Starting from the actual working conditions of the vehicle, road load spectrum acquisition, multi-body dynamics modeling, and load spectrum editing techniques were comprehensively applied. The bench load spectrum was edited based on the original random load spectrum of test field. The simulation analysis and experimental verification were used to compare the effects of the original random load spectrum and bench load spectrum on the component. The results show that the leaf spring failure modes under the two spectrum are the same, and the bench spectrum is more conservative than the original spectrum. It proves that the fatigue analysis of leaf spring can be transformed from the expensive test field verification to simple and efficient indoor bench verification by using the load editing technology.
The leaf spring bench fatigue load spectrum has always been derived from the empirical estimates. It does not reflect the true stress state of the leaf spring. A new method for editing the leaf spring bench fatigue load spectrum is proposed. Starting from the actual working conditions of the vehicle, road load spectrum acquisition, multi-body dynamics modeling, and load spectrum editing techniques were comprehensively applied. The bench load spectrum was edited based on the original random load spectrum of test field. The simulation analysis and experimental verification were used to compare the effects of the original random load spectrum and bench load spectrum on the component. The results show that the leaf spring failure modes under the two spectrum are the same, and the bench spectrum is more conservative than the original spectrum. It proves that the fatigue analysis of leaf spring can be transformed from the expensive test field verification to simple and efficient indoor bench verification by using the load editing technology.
2022, 41(3): 379-385.
doi: 10.13433/j.cnki.1003-8728.20200367
Abstract:
Aiming at the problems of poor self-adaptive and low control accuracy of multi mobile robot control system when communication range is restricted and external interference exists, a prescribed performance fuzzy sliding-mode formation control algorithm based on the hyperbolic tangent constraint function is proposed to realize high-precision and stable formation of multiple robots in arbitrary formation. Then, the control system was verified by the simulation experiment in MATLAB. The results show that under the action of the designed prescribed performance fuzzy-sliding controller can not only realize the formation of multiple robots in arbitrary formation, but also ensure the transient and steady performance of the formation. And compared with the existing control method, it is proved that the proposed control method has high control accuracy and stability.
Aiming at the problems of poor self-adaptive and low control accuracy of multi mobile robot control system when communication range is restricted and external interference exists, a prescribed performance fuzzy sliding-mode formation control algorithm based on the hyperbolic tangent constraint function is proposed to realize high-precision and stable formation of multiple robots in arbitrary formation. Then, the control system was verified by the simulation experiment in MATLAB. The results show that under the action of the designed prescribed performance fuzzy-sliding controller can not only realize the formation of multiple robots in arbitrary formation, but also ensure the transient and steady performance of the formation. And compared with the existing control method, it is proved that the proposed control method has high control accuracy and stability.
2022, 41(3): 386-393.
doi: 10.13433/j.cnki.1003-8728.20200569
Abstract:
Considering the state acquisition for control law of the control system when facing applications, based on the UKF state observation system, the multi-objective integrated control of handling stability and anti-roll of active front steering and active anti-roll bar is carried out to comprehensively improve the vehicle lateral stability and roll stability. A 9-DOF vehicle dynamics model is established, and a state observer is constructed with the unscented Kalman filter method. The sliding mode variable structure control algorithm is adopted, and the handling stability controller is designed for the active front steering system, and the anti-roll controller is developed for the active anti-roll bar system to realize the on-demand control of body roll. Considering the coupling influence of the tire vertical load and lateral force, the PID control algorithm is used to dynamically adjust the torque distribution coefficient of the front and rear active anti-roll bars to achieve integrated control of vehicle anti-roll and handling stability. Finally, the fishhook test is simulated for the multi-objective integrated control system. The results show that the present integrated controller can effectively improve the vehicle stability while achieving the on-demand control of body roll.
Considering the state acquisition for control law of the control system when facing applications, based on the UKF state observation system, the multi-objective integrated control of handling stability and anti-roll of active front steering and active anti-roll bar is carried out to comprehensively improve the vehicle lateral stability and roll stability. A 9-DOF vehicle dynamics model is established, and a state observer is constructed with the unscented Kalman filter method. The sliding mode variable structure control algorithm is adopted, and the handling stability controller is designed for the active front steering system, and the anti-roll controller is developed for the active anti-roll bar system to realize the on-demand control of body roll. Considering the coupling influence of the tire vertical load and lateral force, the PID control algorithm is used to dynamically adjust the torque distribution coefficient of the front and rear active anti-roll bars to achieve integrated control of vehicle anti-roll and handling stability. Finally, the fishhook test is simulated for the multi-objective integrated control system. The results show that the present integrated controller can effectively improve the vehicle stability while achieving the on-demand control of body roll.
2022, 41(3): 394-401.
doi: 10.13433/j.cnki.1003-8728.20200374
Abstract:
In the case of mine hoist reducer fault signal low-high frequency symbiosis, it is difficult to extract the compound fault features of mine hoist reducer and the identification degree of fault type is low. In this paper, a new compound fault diagnosis method of frequency division and fusion for reducer is proposed. Firstly, in order to obtain the low frequency meshing and high-frequency resonance components, the vibration signal is decomposed by combined mode function (CMF). Then, the low-frequency component is decomposed again by improved local mean decomposition (CELMD), and combined with multi-scale permutation entropy method (MPE), the PF components are selected for reconstruction and envelope analysis. In addition, to obtain different fault frequency components, the high-frequency component is preprocessed with the maximum correlation kurtosis deconvolution (MCKD) inverse filter bank. Next, the optimal resonance frequency determined by Average Infogram method is used to envelope analysis. Finally, the fusion diagnosis of envelope analysis results is carried out. The experimental study shows that the frequency division fusion method can effectively extract the signal features information, and is sensitive to the fault features. Moreover, it can accurately identify the compound fault type of mine hoist reducer, and avoid the missed diagnosis and misdiagnosis caused by incomplete selection of frequency band information.
In the case of mine hoist reducer fault signal low-high frequency symbiosis, it is difficult to extract the compound fault features of mine hoist reducer and the identification degree of fault type is low. In this paper, a new compound fault diagnosis method of frequency division and fusion for reducer is proposed. Firstly, in order to obtain the low frequency meshing and high-frequency resonance components, the vibration signal is decomposed by combined mode function (CMF). Then, the low-frequency component is decomposed again by improved local mean decomposition (CELMD), and combined with multi-scale permutation entropy method (MPE), the PF components are selected for reconstruction and envelope analysis. In addition, to obtain different fault frequency components, the high-frequency component is preprocessed with the maximum correlation kurtosis deconvolution (MCKD) inverse filter bank. Next, the optimal resonance frequency determined by Average Infogram method is used to envelope analysis. Finally, the fusion diagnosis of envelope analysis results is carried out. The experimental study shows that the frequency division fusion method can effectively extract the signal features information, and is sensitive to the fault features. Moreover, it can accurately identify the compound fault type of mine hoist reducer, and avoid the missed diagnosis and misdiagnosis caused by incomplete selection of frequency band information.
2022, 41(3): 402-408.
doi: 10.13433/j.cnki.1003-8728.20200216
Abstract:
A visual servo method based on image trajectory planning and sequential control was proposed for uncalibrated eye-in-hand robot system. First, the trajectory planning method in image space and task space was presented. Second, the Kalman filter was adopted to estimate the relative pose of the target to camera, and combined with camera measurement, the adaptive estimation of Jacobian matrix was realized. A visual servo controller with image feedback was designed to realize the visual tracking of target. At the end of this paper, this method and relative algorithm were verified by MATLAB simulations and experimental researches, and compared with classical PBVS (position-based visual servoing) and IBVS (image-based visual servoing) methods. The results verify the effectiveness of the method.
A visual servo method based on image trajectory planning and sequential control was proposed for uncalibrated eye-in-hand robot system. First, the trajectory planning method in image space and task space was presented. Second, the Kalman filter was adopted to estimate the relative pose of the target to camera, and combined with camera measurement, the adaptive estimation of Jacobian matrix was realized. A visual servo controller with image feedback was designed to realize the visual tracking of target. At the end of this paper, this method and relative algorithm were verified by MATLAB simulations and experimental researches, and compared with classical PBVS (position-based visual servoing) and IBVS (image-based visual servoing) methods. The results verify the effectiveness of the method.
2022, 41(3): 409-413.
doi: 10.13433/j.cnki.1003-8728.20200365
Abstract:
The traditional tooth surface contact analysis technology has many disadvantages such as numerous adjustment parameters of the machine tool, unclear control objectives and no transmission error optimization. Aiming at the above problems, a global optimization algorithm based on genetic algorithm for the contact area of the spiral bevel gear tooth surface and transmission error curve is proposed, in which taking the instantaneous contact ellipse semi-major axis, the contact trace direction angle and the ordinate of the transmission error curve intersection point as the optimization targets, the normal curvature along the tooth height direction, the normal curvature along the tooth length direction and the short-range deflection as control parameters. The optimization result can reach the expected optimization goal, and the algorithm has good convergence. In addition, the optimized finite element model of the spiral bevel gear pair is established, and its meshing characteristics are analyzed. The results again verify the correctness of the optimization method, and the influence of the torque load on the tooth surface contact area and transmission error is analyzed.
The traditional tooth surface contact analysis technology has many disadvantages such as numerous adjustment parameters of the machine tool, unclear control objectives and no transmission error optimization. Aiming at the above problems, a global optimization algorithm based on genetic algorithm for the contact area of the spiral bevel gear tooth surface and transmission error curve is proposed, in which taking the instantaneous contact ellipse semi-major axis, the contact trace direction angle and the ordinate of the transmission error curve intersection point as the optimization targets, the normal curvature along the tooth height direction, the normal curvature along the tooth length direction and the short-range deflection as control parameters. The optimization result can reach the expected optimization goal, and the algorithm has good convergence. In addition, the optimized finite element model of the spiral bevel gear pair is established, and its meshing characteristics are analyzed. The results again verify the correctness of the optimization method, and the influence of the torque load on the tooth surface contact area and transmission error is analyzed.
2022, 41(3): 414-420.
doi: 10.13433/j.cnki.1003-8728.20200360
Abstract:
Since the feedforward and feedback control method foriterative learningcan accelerate convergence speed and reduce convergence error for systems that have repetitive motion properties, itis introduced intothe micro-nano manipulation imaging system to improve the tracking accuracy of a scanner. Firstly, an open-loop PD type iterative learning law is combined with a closed-loop feedback PD type learning law, and the convergence condition of the learning law is given. At the same time, in order to reduce the operating time of themicro-nano manipulation imaging system and improve its learning efficiency, the traditional fixed learning gain is changed into the exponential variable gain. Secondly, an iterative learning controller based on the micro-nano manipulation imaging system is built and simulated. Thesimulation results show that, compared with the open-loop iterative learning control and the closed-loop iterative learning control, the maximum convergence error is low and the robustness is strong.The method is easy to implement and effectively meets the requirements for trajectory tracking accuracy during scanning.
Since the feedforward and feedback control method foriterative learningcan accelerate convergence speed and reduce convergence error for systems that have repetitive motion properties, itis introduced intothe micro-nano manipulation imaging system to improve the tracking accuracy of a scanner. Firstly, an open-loop PD type iterative learning law is combined with a closed-loop feedback PD type learning law, and the convergence condition of the learning law is given. At the same time, in order to reduce the operating time of themicro-nano manipulation imaging system and improve its learning efficiency, the traditional fixed learning gain is changed into the exponential variable gain. Secondly, an iterative learning controller based on the micro-nano manipulation imaging system is built and simulated. Thesimulation results show that, compared with the open-loop iterative learning control and the closed-loop iterative learning control, the maximum convergence error is low and the robustness is strong.The method is easy to implement and effectively meets the requirements for trajectory tracking accuracy during scanning.
2022, 41(3): 421-432.
doi: 10.13433/j.cnki.1003-8728.20200618
Abstract:
Aiming at the problem that certain brand of single crystal silicon materials cannot achieve discharge in electrical discharge machining systems, this paper proposes a method to define the critical conductivity σ of single crystal silicon electrical discharge machining, and systematically reveals that the conductivity σ of single crystal silicon is the fundamental reason that affects the breakdown of the discharge channel and forms the spark discharge. Based on the theory of semiconductor physics, the process from the establishment of the inter-electrode electric field to the formation of the inter-electrode plasma discharge channel in electrical discharge machining system of the single crystal silicon is systematically analyzed. Introducing the cathode field electron emission theory, the physical model between the electrodes current density J of the single crystal silicon electrical discharge machining system and the single crystal silicon conductivity σ is established. The relationship between the critical current density J and the conductivity σ of single crystal silicon is simulated and analyzed. The model was verified by the actual machining process, the results show that the model can determine the critical conductivity of the electrical discharge machining of single crystal silicon, thus defining the machinability of single crystal silicon.
Aiming at the problem that certain brand of single crystal silicon materials cannot achieve discharge in electrical discharge machining systems, this paper proposes a method to define the critical conductivity σ of single crystal silicon electrical discharge machining, and systematically reveals that the conductivity σ of single crystal silicon is the fundamental reason that affects the breakdown of the discharge channel and forms the spark discharge. Based on the theory of semiconductor physics, the process from the establishment of the inter-electrode electric field to the formation of the inter-electrode plasma discharge channel in electrical discharge machining system of the single crystal silicon is systematically analyzed. Introducing the cathode field electron emission theory, the physical model between the electrodes current density J of the single crystal silicon electrical discharge machining system and the single crystal silicon conductivity σ is established. The relationship between the critical current density J and the conductivity σ of single crystal silicon is simulated and analyzed. The model was verified by the actual machining process, the results show that the model can determine the critical conductivity of the electrical discharge machining of single crystal silicon, thus defining the machinability of single crystal silicon.
2022, 41(3): 433-438.
doi: 10.13433/j.cnki.1003-8728.20200348
Abstract:
In order to solve the interpolation of NURBS and its offset curve concisely and effectively, the new interpolation method, parameter tracking method is proposed. Firstly, the parameter-tracking method for curve interpolation is proposed and its principle and calculation process are explained. Secondly, the effectiveness of the interpolation method is proved by an example of NURBS curve interpolation. Thirdly, the interpolation method is applied to the tool compensation calculation of NURBS curve, including constant tool compensation and linear tool compensation. Finally, the interpolation method is combined with the linear tool compensation and coordinate compensation to improve the interpolation accuracy of the NURBS curve under different machining conditions. The parameter-tracking method applied to the NURBS curve interpolation calculation process is simple and easy to program. In the tool compensation calculation, the first-order derivative of the curve can be directly applied, and the calculation increment is small. The present coordinate elimination method for interpolation results can be used to eliminate the self-intersecting part of the NURBS curve.
In order to solve the interpolation of NURBS and its offset curve concisely and effectively, the new interpolation method, parameter tracking method is proposed. Firstly, the parameter-tracking method for curve interpolation is proposed and its principle and calculation process are explained. Secondly, the effectiveness of the interpolation method is proved by an example of NURBS curve interpolation. Thirdly, the interpolation method is applied to the tool compensation calculation of NURBS curve, including constant tool compensation and linear tool compensation. Finally, the interpolation method is combined with the linear tool compensation and coordinate compensation to improve the interpolation accuracy of the NURBS curve under different machining conditions. The parameter-tracking method applied to the NURBS curve interpolation calculation process is simple and easy to program. In the tool compensation calculation, the first-order derivative of the curve can be directly applied, and the calculation increment is small. The present coordinate elimination method for interpolation results can be used to eliminate the self-intersecting part of the NURBS curve.
2022, 41(3): 439-444.
doi: 10.13433/j.cnki.1003-8728.20200613
Abstract:
Firstly, the removal mechanism of the relative motion between the machine tool and the workpiece and the characterization of the stability of the removal function are described. Then, the stability of the removal function obtained by the workpiece movement in a plane at different speeds and rotating around a fixed point is studied. Finally the stability of the removal function is verified via numerical experiments. It is concluded that the speed in the X direction causes the removal function to be unstable; the increase in the movement speed in the Y direction causes the stability of the removal function to fluctuate.
Firstly, the removal mechanism of the relative motion between the machine tool and the workpiece and the characterization of the stability of the removal function are described. Then, the stability of the removal function obtained by the workpiece movement in a plane at different speeds and rotating around a fixed point is studied. Finally the stability of the removal function is verified via numerical experiments. It is concluded that the speed in the X direction causes the removal function to be unstable; the increase in the movement speed in the Y direction causes the stability of the removal function to fluctuate.
2022, 41(3): 445-450.
doi: 10.13433/j.cnki.1003-8728.20200361
Abstract:
In order to improve the measuring efficiency of spiral bevel gear tooth surface, it was studied to the measurement path of the coordinate measuring machine (CMM). By analyzing the composition of the measurement path, the measurement path planning problem is converted into a Traveling Salesman Problem (TSP), and the objective function is determined. The basic genetic algorithm is improved by considering the characteristics of tooth surface measurement path planning. The new solution generation and acceptance rules of simulated annealing algorithm are applied to genetic algorithm, which improves the diversity of population and avoids local convergence; A more simple and efficient coding method is adopted to improve the convergence speed of the algorithm. In this paper, the simulation experiment is carried out by taking the non-uniformly distributed measurement points on the tooth surface as an example. The results show that this algorithm is superior to the basic ant colony algorithm, simulated annealing algorithm and genetic algorithm in path optimization of surface measurement.
In order to improve the measuring efficiency of spiral bevel gear tooth surface, it was studied to the measurement path of the coordinate measuring machine (CMM). By analyzing the composition of the measurement path, the measurement path planning problem is converted into a Traveling Salesman Problem (TSP), and the objective function is determined. The basic genetic algorithm is improved by considering the characteristics of tooth surface measurement path planning. The new solution generation and acceptance rules of simulated annealing algorithm are applied to genetic algorithm, which improves the diversity of population and avoids local convergence; A more simple and efficient coding method is adopted to improve the convergence speed of the algorithm. In this paper, the simulation experiment is carried out by taking the non-uniformly distributed measurement points on the tooth surface as an example. The results show that this algorithm is superior to the basic ant colony algorithm, simulated annealing algorithm and genetic algorithm in path optimization of surface measurement.
2022, 41(3): 451-456.
doi: 10.13433/j.cnki.1003-8728.20200568
Abstract:
Aiming at the problem that the diagnostic effect of Autogram is easily affected by the decomposition level of maximum overlap discrete wavelet packet transform (MOWDPT), an improved adaptive Autogram method is proposed for of rolling bearing fault diagnosis. In this method, the minimum value of the mean envelope entropy (MEE) was firstly used to search the optimal decomposition level of MOWDPT, and then the central frequency and bandwidth of the optimal resonance band was selected by the maximum value of the kurtosis of the unbiased autocorreelation (AC) of the squared envelope of the decomposed signal, finally the fault feature information was extracted by demodulating. The research results show that the adaptive determination of decomposition level improves the fault diagnosis effect of the improved Autogram, and this method can quickly and accurately identify the fault feature of rolling bearing.
Aiming at the problem that the diagnostic effect of Autogram is easily affected by the decomposition level of maximum overlap discrete wavelet packet transform (MOWDPT), an improved adaptive Autogram method is proposed for of rolling bearing fault diagnosis. In this method, the minimum value of the mean envelope entropy (MEE) was firstly used to search the optimal decomposition level of MOWDPT, and then the central frequency and bandwidth of the optimal resonance band was selected by the maximum value of the kurtosis of the unbiased autocorreelation (AC) of the squared envelope of the decomposed signal, finally the fault feature information was extracted by demodulating. The research results show that the adaptive determination of decomposition level improves the fault diagnosis effect of the improved Autogram, and this method can quickly and accurately identify the fault feature of rolling bearing.
2022, 41(3): 457-465.
doi: 10.13433/j.cnki.1003-8728.20200349
Abstract:
In order to establish an accurate dynamic simulation model of Magneto-rheological suspension system, parameter identification and model modification are carried out by collecting experimental data. The results show that the dynamic simulation model of MR suspension system established by parameter identification and model modification can simulate the vibration responses of the actual model under different excitation signals. Then, the influence of structural parameters of MR damper on the damping performance of MR suspension is analyzed based on the modified model. The simulation results show that the damping clearance and piston diameter have great influence on the damping performance of MR suspension under any type of excitation, and the piston diameter has the greatest influence on the acceleration and dynamic load of suspension under sinusoidal excitation, which are 1.287 5 and 1.072 7 respectively; under the excitation of road spectrum, the influence factor of piston diameter on the dynamic load of suspension is the largest, with a value of 0.810 4; while the influence factor of damping clearance on the acceleration of vehicle body is the largest, with a value of 0.635 5.
In order to establish an accurate dynamic simulation model of Magneto-rheological suspension system, parameter identification and model modification are carried out by collecting experimental data. The results show that the dynamic simulation model of MR suspension system established by parameter identification and model modification can simulate the vibration responses of the actual model under different excitation signals. Then, the influence of structural parameters of MR damper on the damping performance of MR suspension is analyzed based on the modified model. The simulation results show that the damping clearance and piston diameter have great influence on the damping performance of MR suspension under any type of excitation, and the piston diameter has the greatest influence on the acceleration and dynamic load of suspension under sinusoidal excitation, which are 1.287 5 and 1.072 7 respectively; under the excitation of road spectrum, the influence factor of piston diameter on the dynamic load of suspension is the largest, with a value of 0.810 4; while the influence factor of damping clearance on the acceleration of vehicle body is the largest, with a value of 0.635 5.
2022, 41(3): 466-472.
doi: 10.13433/j.cnki.1003-8728.20200366
Abstract:
In order to improve the dynamic performance of the high-speed maglev train, an efficient multi-objective optimization design method is proposed to optimize the suspension parameters, system control parameters and track beam parameters of the maglev train.A distributed cooperative simulation model for the maglev system including the dynamic model, the finite element model is constructed to obtain the output response that approximates the actual operating conditions of the high-speed maglev train, and five key design parameters are selected as optimization design variables; 20 sets of samples are uniformly drawn by using the optimal Latin hypercube experimental design method, and 7 dynamic performance values corresponding to each sample point are obtained based on the distributed collaborative simulation model. For 20 sets of small samples, 5 input and 7 output high nonlinear problems, the prediction accuracy of different surrogate modelsis analyzed, and a surrogate model between optimizedis established
In order to improve the dynamic performance of the high-speed maglev train, an efficient multi-objective optimization design method is proposed to optimize the suspension parameters, system control parameters and track beam parameters of the maglev train.A distributed cooperative simulation model for the maglev system including the dynamic model, the finite element model is constructed to obtain the output response that approximates the actual operating conditions of the high-speed maglev train, and five key design parameters are selected as optimization design variables; 20 sets of samples are uniformly drawn by using the optimal Latin hypercube experimental design method, and 7 dynamic performance values corresponding to each sample point are obtained based on the distributed collaborative simulation model. For 20 sets of small samples, 5 input and 7 output high nonlinear problems, the prediction accuracy of different surrogate modelsis analyzed, and a surrogate model between optimizedis established
2022, 41(3): 473-480.
doi: 10.13433/j.cnki.1003-8728.20200370
Abstract:
At present, the structure of MR damper is mostly optimized based on the body performance, but the influence of structural parameters of damper on vehicle ride comfort and handling stability is not considered. Therefore, a collaborative optimization method of MR damper for vehicle vibration suppression is proposed. A kind of magneto-rheological damper with conical inclined angle damping channel is designed, and the mathematical model of its damping force is derived. The structural parameters of magnetic circuit are analyzed by finite element method. The seven degree of freedom model of the whole vehicle is built, and the collaborative optimization simulation platform is built by ISIGHT software. The optimization objectives are suspension dynamic deflection, tire dynamic load and root mean square value of body vertical acceleration. The structure of MR damper is optimized by genetic algorithm. The results show that: the suspension dynamic deflection, tire dynamic load and body vertical acceleration have been improved, and the optimized damper can better improve the vehicle ride comfort and handling stability.
At present, the structure of MR damper is mostly optimized based on the body performance, but the influence of structural parameters of damper on vehicle ride comfort and handling stability is not considered. Therefore, a collaborative optimization method of MR damper for vehicle vibration suppression is proposed. A kind of magneto-rheological damper with conical inclined angle damping channel is designed, and the mathematical model of its damping force is derived. The structural parameters of magnetic circuit are analyzed by finite element method. The seven degree of freedom model of the whole vehicle is built, and the collaborative optimization simulation platform is built by ISIGHT software. The optimization objectives are suspension dynamic deflection, tire dynamic load and root mean square value of body vertical acceleration. The structure of MR damper is optimized by genetic algorithm. The results show that: the suspension dynamic deflection, tire dynamic load and body vertical acceleration have been improved, and the optimized damper can better improve the vehicle ride comfort and handling stability.
2022, 41(3): 481-486.
doi: 10.13433/j.cnki.1003-8728.20200372
Abstract:
In order to reduce the influence of temperature rise on the performance of the giant magnetostrictive actuator (GMA), a water-cooled system structure of the giant magnetostrictive actuator with inner tube and outer cavity was proposed and designed in this paper. The heat transfer model of GMA with water-cooled system was established based on the thermal resistance law, and the factors influencing the temperature of the giant magnetostrictive material rod were analyzed, and the steady state temperature field of the giant magnetostrictive actuator is simulated and analyzed. The results show that although the temperature of the giant magnetostrictive actuator will increase with the increase of current intensity, the use of forced water cooling system can effectively control the temperature rise, and the temperature rise decreases with the increase of the cooling water inlet flow rate. When the inlet velocity of cooling water is 3 m/s, the thermal deformation of the giant magnetostrictive material rod is no more than 0.09 μm.
In order to reduce the influence of temperature rise on the performance of the giant magnetostrictive actuator (GMA), a water-cooled system structure of the giant magnetostrictive actuator with inner tube and outer cavity was proposed and designed in this paper. The heat transfer model of GMA with water-cooled system was established based on the thermal resistance law, and the factors influencing the temperature of the giant magnetostrictive material rod were analyzed, and the steady state temperature field of the giant magnetostrictive actuator is simulated and analyzed. The results show that although the temperature of the giant magnetostrictive actuator will increase with the increase of current intensity, the use of forced water cooling system can effectively control the temperature rise, and the temperature rise decreases with the increase of the cooling water inlet flow rate. When the inlet velocity of cooling water is 3 m/s, the thermal deformation of the giant magnetostrictive material rod is no more than 0.09 μm.
2022, 41(3): 487-492.
doi: 10.13433/j.cnki.1003-8728.20200352
Abstract:
In order to obtain the best aerodynamic performance of the coaxial rotors, the test and numerical simulation of the coaxial rotors UAV with different rotor spacing ratios were carried out in this paper. Firstly, the aerodynamic performance parameters of the coaxial rotors are analyzed theoretically. Secondly, the coaxial rotors model is established and applied for numerical simulation, and the thrust and power are obtained by self-designed experiments. Moreover, the thrust and power obtained from the test are converted into power loading and hovering efficiency with aerodynamic analysis. Finally, combined with the test and simulation results, it is shown that the power loading increased by 1.5%, and the overall efficiency increased by about 5.64% at the spacing ratio i = 0.385 compared with i = 0.75 for the operation mode of 2 200 r/min. It is concluded that the aerodynamic performance at i = 0.385 is better, which can be used as the best aerodynamic layout of the coaxial rotors UAV.
In order to obtain the best aerodynamic performance of the coaxial rotors, the test and numerical simulation of the coaxial rotors UAV with different rotor spacing ratios were carried out in this paper. Firstly, the aerodynamic performance parameters of the coaxial rotors are analyzed theoretically. Secondly, the coaxial rotors model is established and applied for numerical simulation, and the thrust and power are obtained by self-designed experiments. Moreover, the thrust and power obtained from the test are converted into power loading and hovering efficiency with aerodynamic analysis. Finally, combined with the test and simulation results, it is shown that the power loading increased by 1.5%, and the overall efficiency increased by about 5.64% at the spacing ratio i = 0.385 compared with i = 0.75 for the operation mode of 2 200 r/min. It is concluded that the aerodynamic performance at i = 0.385 is better, which can be used as the best aerodynamic layout of the coaxial rotors UAV.
