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RSS2023 Vol. 42, No. 1
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2023, 42(1): 1-23.
doi: 10.13433/j.cnki.1003-8728.20200489
PDF 3390KB
Abstract:
Rolling bearing are a key component of rotating machinery, and remaining useful life prediction of them will be of great significance to production, maintenance and personal safety. Due to the complex and changeable working environment of the rolling bearing, there are fewer reference samples in the same working condition but more in different working conditions. Moreover, the samples have the characteristics of unbalanced, incomplete, no label and noise interference, which increases the difficulty of RUL prediction. With the advent of the era of big data and the development of artificial intelligence, rolling bearing RUL prediction methods have become more abundant. Therefore, based on the framework of prognosis and health management, the failure modes and fault data characteristics of the rolling bearing are stated, methods concerning fault feature extraction, dimension reduction and fusion, as well as the obtained performance degradation indicators are respectively classified and contrastive analysis are performed. Combining with the data driven algorithms, the prediction approach, model selection and evaluation criteria of rolling bearing RUL are sorted and compared. Finally, the future development trend of rolling bearing RUL prediction is prospected.
Rolling bearing are a key component of rotating machinery, and remaining useful life prediction of them will be of great significance to production, maintenance and personal safety. Due to the complex and changeable working environment of the rolling bearing, there are fewer reference samples in the same working condition but more in different working conditions. Moreover, the samples have the characteristics of unbalanced, incomplete, no label and noise interference, which increases the difficulty of RUL prediction. With the advent of the era of big data and the development of artificial intelligence, rolling bearing RUL prediction methods have become more abundant. Therefore, based on the framework of prognosis and health management, the failure modes and fault data characteristics of the rolling bearing are stated, methods concerning fault feature extraction, dimension reduction and fusion, as well as the obtained performance degradation indicators are respectively classified and contrastive analysis are performed. Combining with the data driven algorithms, the prediction approach, model selection and evaluation criteria of rolling bearing RUL are sorted and compared. Finally, the future development trend of rolling bearing RUL prediction is prospected.
2023, 42(1): 24-30.
doi: 10.13433/j.cnki.1003-8728.20220020
Abstract:
Aiming at the problem of accurate classification of compound faults of planetary gearboxes, a fault diagnosis method combining improved adaptive noise complete set empirical mode decomposition (ICEEMDAN) and support vector machine (SVM) is proposed in this study. First, the different fault signals of the planetary gearbox are decomposed by ICEEMDAN to obtain the intrinsic mode function (IMF) of each order. Second, the correlation between the IMF component of each order and the original signal is used to remove the false IMF component. Finally, the multi-scale fuzzy entropy average value of the preferred IMF component is used as the feature vector and input into the multi-class SVM to accomplish fault classification. The classification accuracy is as high as 100%. The experimental results prove the feasibility of this method.
Aiming at the problem of accurate classification of compound faults of planetary gearboxes, a fault diagnosis method combining improved adaptive noise complete set empirical mode decomposition (ICEEMDAN) and support vector machine (SVM) is proposed in this study. First, the different fault signals of the planetary gearbox are decomposed by ICEEMDAN to obtain the intrinsic mode function (IMF) of each order. Second, the correlation between the IMF component of each order and the original signal is used to remove the false IMF component. Finally, the multi-scale fuzzy entropy average value of the preferred IMF component is used as the feature vector and input into the multi-class SVM to accomplish fault classification. The classification accuracy is as high as 100%. The experimental results prove the feasibility of this method.
2023, 42(1): 31-37.
doi: 10.13433/j.cnki.1003-8728.20200562
Abstract:
In order to solve the problem of early fault detection of rolling bearings, a performance degradation assessment model of rolling bearings combining variable mode decomposition (VMD) symbol entropy and support vector data description (SVDD) was proposed in study. Firstly, the vibration signal is decomposed by VMD and the symbol entropy of each component is extracted. Then, the Z value of double samples is used to evaluate the symbol entropy of each component, and the feature with the largest Z value of double samples is selected as the feature vector. After feature extraction, SVDD model is finally used to evaluate performance degradation, and life cycle data is used to verify the model. The experimental results show that this model can better show the performance degradation law of rolling bearings compared with permutation entropy (PE) feature extraction method and fuzzy c-means clustering (FCM) method.
In order to solve the problem of early fault detection of rolling bearings, a performance degradation assessment model of rolling bearings combining variable mode decomposition (VMD) symbol entropy and support vector data description (SVDD) was proposed in study. Firstly, the vibration signal is decomposed by VMD and the symbol entropy of each component is extracted. Then, the Z value of double samples is used to evaluate the symbol entropy of each component, and the feature with the largest Z value of double samples is selected as the feature vector. After feature extraction, SVDD model is finally used to evaluate performance degradation, and life cycle data is used to verify the model. The experimental results show that this model can better show the performance degradation law of rolling bearings compared with permutation entropy (PE) feature extraction method and fuzzy c-means clustering (FCM) method.
2023, 42(1): 38-45.
doi: 10.13433/j.cnki.1003-8728.20200601
Abstract:
Aiming at the problems of dynamic characteristics and vacuum module force balance in the process of climbing robot crossing obstacles, a climbing robot dynamics characteristic analysis method in the process of obstacle crossing motion is established based on the Lie group, Lie algebra and screw theory. The space velocity Jacobian matrix is deduced in the form of index product space thereby reducing the singularity generated due to the differential derivation, a clear physical meaning low computational complexity dynamic equation is established based on Lagrange equation, Lie group Lie algebra and screw theory. The mechanical model of the vacuum module is established, and the optimal adsorption force of the vacuum module is obtained during the obstacle crossing process. The driving torque of the robot joint is solved by coppeliasim simulation, which verified the correctness and dynamics of Lie group Lie algebra and screw theory modeling. The effectiveness of the scientific model is verified by the adsorption experiment to verify the optimal solution of the adsorption force.
Aiming at the problems of dynamic characteristics and vacuum module force balance in the process of climbing robot crossing obstacles, a climbing robot dynamics characteristic analysis method in the process of obstacle crossing motion is established based on the Lie group, Lie algebra and screw theory. The space velocity Jacobian matrix is deduced in the form of index product space thereby reducing the singularity generated due to the differential derivation, a clear physical meaning low computational complexity dynamic equation is established based on Lagrange equation, Lie group Lie algebra and screw theory. The mechanical model of the vacuum module is established, and the optimal adsorption force of the vacuum module is obtained during the obstacle crossing process. The driving torque of the robot joint is solved by coppeliasim simulation, which verified the correctness and dynamics of Lie group Lie algebra and screw theory modeling. The effectiveness of the scientific model is verified by the adsorption experiment to verify the optimal solution of the adsorption force.
2023, 42(1): 46-52.
doi: 10.13433/j.cnki.1003-8728.20200571
Abstract:
In order to solve the problems such as difficulty in moving and poor stability of the dredging robot, a kind of amphibious turtle inspired robot was designed by referring to the body structure and crawling movement of turtles. Based on the introduction of the structure of the robot, the D-H method was used to analyze the kinematics of the robot, and the transformation matrix and kinematics equation of the leg were established and solved. Two kinds of crawling gaits were planned. According to the robot structure, the travel space of the electric push cylinder was planned, and the foot trajectory and crawling gait were optimized. The motion simulation was carried out in ADAMS, and the curves of displacement and velocity of the airframe were analyzed. The results show that the optimized gait can greatly improve the crawling speed and stability of the robot.
In order to solve the problems such as difficulty in moving and poor stability of the dredging robot, a kind of amphibious turtle inspired robot was designed by referring to the body structure and crawling movement of turtles. Based on the introduction of the structure of the robot, the D-H method was used to analyze the kinematics of the robot, and the transformation matrix and kinematics equation of the leg were established and solved. Two kinds of crawling gaits were planned. According to the robot structure, the travel space of the electric push cylinder was planned, and the foot trajectory and crawling gait were optimized. The motion simulation was carried out in ADAMS, and the curves of displacement and velocity of the airframe were analyzed. The results show that the optimized gait can greatly improve the crawling speed and stability of the robot.
2023, 42(1): 53-58.
doi: 10.13433/j.cnki.1003-8728.20200578
Abstract:
The spectrum amplitude modulation (SAM) method, which was proposed recently, can be used to do the feature extraction of different fault signals by adjusting the exponential of amplitude adaptively, and it has a quite good practical perspective. However, the exponential of amplitude of this method still needs to be judged manually, which leads to the result that it can not be used to extract the fault features automatically. Moreover, when the fault features are interfered by complex disturbances, it is difficult to select the optimal exponential of amplitude manually. Therefore, a robust amplitude exponential adaptive spectral amplitude modulation method is proposed in this paper. Firstly, the signal is converted to angular domain by angle domain resampling, and then the shock characteristics generated by the faulty planet bearing are enhanced by the multipoint optimal minimum entropy deconvolution adjusted (MOMEDA). Finally, the exponential of cepstrum amplitude in SAM is adaptively selected with ICS2 (indicator of second order cyclostationary). The cepstrum signal is calculated by the optimal exponential of amplitude, in this way, the problem that the SAM method cannot automatically extract fault features is solved. The fault feature extraction of inner race of planetary bearing is verified. Experimental results show that the proposed method can adaptively extract fault features of inner race of planetary bearing under complex interference.
The spectrum amplitude modulation (SAM) method, which was proposed recently, can be used to do the feature extraction of different fault signals by adjusting the exponential of amplitude adaptively, and it has a quite good practical perspective. However, the exponential of amplitude of this method still needs to be judged manually, which leads to the result that it can not be used to extract the fault features automatically. Moreover, when the fault features are interfered by complex disturbances, it is difficult to select the optimal exponential of amplitude manually. Therefore, a robust amplitude exponential adaptive spectral amplitude modulation method is proposed in this paper. Firstly, the signal is converted to angular domain by angle domain resampling, and then the shock characteristics generated by the faulty planet bearing are enhanced by the multipoint optimal minimum entropy deconvolution adjusted (MOMEDA). Finally, the exponential of cepstrum amplitude in SAM is adaptively selected with ICS2 (indicator of second order cyclostationary). The cepstrum signal is calculated by the optimal exponential of amplitude, in this way, the problem that the SAM method cannot automatically extract fault features is solved. The fault feature extraction of inner race of planetary bearing is verified. Experimental results show that the proposed method can adaptively extract fault features of inner race of planetary bearing under complex interference.
2023, 42(1): 59-66.
doi: 10.13433/j.cnki.1003-8728.20200573
Abstract:
The complex gas-liquid two-phase flow occurs in the torque limited hydrodynamic coupling, in order to grasp the internal flow field distribution and torque characteristics of the torque limited hydrodynamic coupling, the internal flow field of the coupling was simulated by solving VOF(Volume of fluid) and Mixture two-phase flow model, and its torque characteristics was monitored. The gas-liquid two-phase distribution inside the coupling obtained by the VOF model, the internal pressure and velocity distribution obtained by the Mixture model can better reflect the change of the internal flow field of the coupling. The simulation results show that the VOF model can better simulate the torque drop of the coupling caused by the transition of the flow regime; the Mixture model cannot simulate this effect, but the torque under high or low speed ratios still have certain reference significance.
The complex gas-liquid two-phase flow occurs in the torque limited hydrodynamic coupling, in order to grasp the internal flow field distribution and torque characteristics of the torque limited hydrodynamic coupling, the internal flow field of the coupling was simulated by solving VOF(Volume of fluid) and Mixture two-phase flow model, and its torque characteristics was monitored. The gas-liquid two-phase distribution inside the coupling obtained by the VOF model, the internal pressure and velocity distribution obtained by the Mixture model can better reflect the change of the internal flow field of the coupling. The simulation results show that the VOF model can better simulate the torque drop of the coupling caused by the transition of the flow regime; the Mixture model cannot simulate this effect, but the torque under high or low speed ratios still have certain reference significance.
2023, 42(1): 67-74.
doi: 10.13433/j.cnki.1003-8728.20230073
Abstract:
During the installation and operation of transmission equipment, there always are bearing clearance problems, which is also one of the main reasons for bearing failure. Therefore, the research on the bearing clearance has important theoretical significance and engineering value. In order to determine the influence of bearing clearance on bearing vibration, the theoretical model of 2-DOF rolling bearing was established based on the dynamic characteristics of bearing vibration. For the tested bearing, the dynamic characteristics of the rolling bearing is analyzed based on the Hertz-elastic contact theory. It is known that the number of balance points of the inner ring of the bearing depends on the clearance of the bearing. When there is a gap (e < 4.5 μm) in the bearing, there is the stable equilibrium point, and near the center of the balance point, there is periodic vibration in the inner ring of the bearing. When there is a gap(e≥4.5 μm), as the gap and the rotational speed of the bearing increase continuously, the system will generate chaotic vibration, and the area where chaotic vibration occurs is also increasing. At the same time, the experimental results of the Ø127 rolling bearing shows that under the same damping parameters, bearing size and rotational speed, the results of the singular attractors obtained from the experimental data are close to those obtained by solving the equation of motion. This qualitative result not only confirms the existence of bearing chaotic behavior, but also verifies the reliability of the theoretical model.
During the installation and operation of transmission equipment, there always are bearing clearance problems, which is also one of the main reasons for bearing failure. Therefore, the research on the bearing clearance has important theoretical significance and engineering value. In order to determine the influence of bearing clearance on bearing vibration, the theoretical model of 2-DOF rolling bearing was established based on the dynamic characteristics of bearing vibration. For the tested bearing, the dynamic characteristics of the rolling bearing is analyzed based on the Hertz-elastic contact theory. It is known that the number of balance points of the inner ring of the bearing depends on the clearance of the bearing. When there is a gap (e < 4.5 μm) in the bearing, there is the stable equilibrium point, and near the center of the balance point, there is periodic vibration in the inner ring of the bearing. When there is a gap(e≥4.5 μm), as the gap and the rotational speed of the bearing increase continuously, the system will generate chaotic vibration, and the area where chaotic vibration occurs is also increasing. At the same time, the experimental results of the Ø127 rolling bearing shows that under the same damping parameters, bearing size and rotational speed, the results of the singular attractors obtained from the experimental data are close to those obtained by solving the equation of motion. This qualitative result not only confirms the existence of bearing chaotic behavior, but also verifies the reliability of the theoretical model.
2023, 42(1): 75-82.
doi: 10.13433/j.cnki.1003-8728.20200611
Abstract:
The axial and radial mixed ventilation structure is adopted in order to improve the ventilation and cooling performance and reduce the operating temperature rise of the motor. Taking a 400 kW medium-sized high voltage motor as an research object, the influence law of temperature rise of the integral motor under steady state condition is studied through magnetic-fluid-solid coupling simulation. The cooling effect of the ventilation structure is quantitatively evaluated by proposing temperature rise uniformity coefficient. The results show that the temperature rise distribution of mixed ventilation structure is more uniform, and the uniformity coefficient of temperature rise is 85.78% and 6.23% higher than that of axial ventilation structure in the inner and outer winding of motor, respectively. The influence of the height and number of radial air ducts on motor temperature rise is further studied. Cooling effect is the best when the height is 6 mm and the number of radial duct is 13.
The axial and radial mixed ventilation structure is adopted in order to improve the ventilation and cooling performance and reduce the operating temperature rise of the motor. Taking a 400 kW medium-sized high voltage motor as an research object, the influence law of temperature rise of the integral motor under steady state condition is studied through magnetic-fluid-solid coupling simulation. The cooling effect of the ventilation structure is quantitatively evaluated by proposing temperature rise uniformity coefficient. The results show that the temperature rise distribution of mixed ventilation structure is more uniform, and the uniformity coefficient of temperature rise is 85.78% and 6.23% higher than that of axial ventilation structure in the inner and outer winding of motor, respectively. The influence of the height and number of radial air ducts on motor temperature rise is further studied. Cooling effect is the best when the height is 6 mm and the number of radial duct is 13.
2023, 42(1): 83-91.
doi: 10.13433/j.cnki.1003-8728.20200607
Abstract:
In order to achieve ankle rehabilitation exercise, a 2UPS/RR ankle rehabilitation robot was designed and developed. The degree of freedom of the parallel mechanism was calculated using the spiral theory, the inverse equation of the mechanism was obtained by closed vector method, and the point set search method was used to calculate its workspace. The spatial positions and layout of the mechanism rods were adjusted and their influence on the workspace and area was researched. The results show that the working space of the optimized mechanism can meet the motion range required for ankle rehabilitation. Finally, the MATLAB and ADAMS software were used to verify the correctness of the inverse solution through examples, and the trajectory of the mechanism to determine the point in the space was obtained by simulation.
In order to achieve ankle rehabilitation exercise, a 2UPS/RR ankle rehabilitation robot was designed and developed. The degree of freedom of the parallel mechanism was calculated using the spiral theory, the inverse equation of the mechanism was obtained by closed vector method, and the point set search method was used to calculate its workspace. The spatial positions and layout of the mechanism rods were adjusted and their influence on the workspace and area was researched. The results show that the working space of the optimized mechanism can meet the motion range required for ankle rehabilitation. Finally, the MATLAB and ADAMS software were used to verify the correctness of the inverse solution through examples, and the trajectory of the mechanism to determine the point in the space was obtained by simulation.
2023, 42(1): 92-98.
doi: 10.13433/j.cnki.1003-8728.20220182
Abstract:
In order to solve the problem of lateral stability control when actuator and sensor faults occur in four-wheel independent driving electric vehicles with parameter uncertainty, an H∞ robust fault-tolerant control method is proposed. A two degree of freedom vehicle dynamic model with parameter uncertainty considering actuator and sensor faults is established by introducing vehicle continuous fault with fault matrix function. The linear matrix inequality method is used to design the lateral stability H∞ robust fault-tolerant controller of vehicle to ensure the asymptotic stability and anti-interference ability of the vehicle dynamics system, and realize that the H∞ robust performance of the control system meets the given interference attenuation target. A joint simulation experiment platform of CarSim and MATLAB/Simulink is built to verify the effectiveness of the controller. Simulation results show that the designed H∞ robust fault-tolerant controller can effectively improve the lateral stability and safety of vehicles, and has good fault-tolerant control ability for vehicle faults.
In order to solve the problem of lateral stability control when actuator and sensor faults occur in four-wheel independent driving electric vehicles with parameter uncertainty, an H∞ robust fault-tolerant control method is proposed. A two degree of freedom vehicle dynamic model with parameter uncertainty considering actuator and sensor faults is established by introducing vehicle continuous fault with fault matrix function. The linear matrix inequality method is used to design the lateral stability H∞ robust fault-tolerant controller of vehicle to ensure the asymptotic stability and anti-interference ability of the vehicle dynamics system, and realize that the H∞ robust performance of the control system meets the given interference attenuation target. A joint simulation experiment platform of CarSim and MATLAB/Simulink is built to verify the effectiveness of the controller. Simulation results show that the designed H∞ robust fault-tolerant controller can effectively improve the lateral stability and safety of vehicles, and has good fault-tolerant control ability for vehicle faults.
2023, 42(1): 99-105.
doi: 10.13433/j.cnki.1003-8728.20200587
Abstract:
In order to increase the energy absorption of the anti-impact hydraulic support and improve its safety, a lattice energy-absorbing device was designed. The specific energy absorption and unit mass support force of three typical lattice cells were studied with the finite element simulation. The pyramid structure was determined to be the best topology of the lattice cells. The three-factor and five-level orthogonal experiment was used to analyze the influence of their body height, body inclination width and body diameter on energy absorption and support force and to determine the best body structural parameters. The simulation analysis shows that the total energy absorption of the pyramid lattice energy absorbing device with the best structural parameters is 1 470 kJ and that its support force is 4 699.76 kN. The support force changes relatively smoothly. It proves that the lattice energy-absorbing device with the pyramid structure has superior energy absorption and can improve the safety of the anti-impact hydraulic support.
In order to increase the energy absorption of the anti-impact hydraulic support and improve its safety, a lattice energy-absorbing device was designed. The specific energy absorption and unit mass support force of three typical lattice cells were studied with the finite element simulation. The pyramid structure was determined to be the best topology of the lattice cells. The three-factor and five-level orthogonal experiment was used to analyze the influence of their body height, body inclination width and body diameter on energy absorption and support force and to determine the best body structural parameters. The simulation analysis shows that the total energy absorption of the pyramid lattice energy absorbing device with the best structural parameters is 1 470 kJ and that its support force is 4 699.76 kN. The support force changes relatively smoothly. It proves that the lattice energy-absorbing device with the pyramid structure has superior energy absorption and can improve the safety of the anti-impact hydraulic support.
2023, 42(1): 106-112.
doi: 10.13433/j.cnki.1003-8728.20200616
Abstract:
In order to obtain a higher contact angle and improve its hydrophobicity, the micro texture on the surface of dimple array of titanium alloy was machined by using the mask electrolysis technology. Firstly, a model for micro pit array mask electrochemical machining is established and multi physical field coupling simulation is carried out; Secondly, the effect of the mask electrochemical machining parameters on the micro pit array is analyzed, and the solid-liquid contact area ratio of the micro pit array is obtained by means of the wetting theory model; Finally, with the area ratio as the dependent variable, the electrolyte mass fraction, electrolytic voltage and mask size as the independent variables, the orthogonal experiment simulation and range analysis were carried out to obtain the best combination of process parameters. Comparing with the predicted values, the errors of the measured values of cell diameter, spacing, depth, solid-liquid contact area ratio and surface contact angle are less than 8%, which indicates that the micro pit array with a contact angle of about 140° is successfully fabricated without modification of low surface energy materials.
In order to obtain a higher contact angle and improve its hydrophobicity, the micro texture on the surface of dimple array of titanium alloy was machined by using the mask electrolysis technology. Firstly, a model for micro pit array mask electrochemical machining is established and multi physical field coupling simulation is carried out; Secondly, the effect of the mask electrochemical machining parameters on the micro pit array is analyzed, and the solid-liquid contact area ratio of the micro pit array is obtained by means of the wetting theory model; Finally, with the area ratio as the dependent variable, the electrolyte mass fraction, electrolytic voltage and mask size as the independent variables, the orthogonal experiment simulation and range analysis were carried out to obtain the best combination of process parameters. Comparing with the predicted values, the errors of the measured values of cell diameter, spacing, depth, solid-liquid contact area ratio and surface contact angle are less than 8%, which indicates that the micro pit array with a contact angle of about 140° is successfully fabricated without modification of low surface energy materials.
2023, 42(1): 113-118.
doi: 10.13433/j.cnki.1003-8728.20200598
Abstract:
To improve the surface machining quality and machining efficiency of TC4 titanium alloy in EDM (Electrical discharge machining), the copper cylindrical electrode was selected to carry out EDM small hole machining experiment of TC4 titanium alloy. The orthogonal experiment method was adopted. Taking the relative electrode wear rate, surface roughness and material removal volume of workpiece as optimization objectives, the influences of the peak current, discharge voltage and discharge pulse width on the optimization objectives were analyzed. RBF (Radial basis function) neural network was used to train with the experimental data, and the prediction model between the discharge parameters and the optimization objectives was established. Taking the prediction model as the fitness function, the multi-objective optimization simulation was carried out by combining the genetic algorithm with the Skyline selection algorithm, and the optimal technical index was obtained. Finally, the multi-objective optimization verification experiment was carried out. The results show that when the peak current is 14 A, the maintenance voltage is 39 V/42 V, and the discharge pulse width is 102 μs/108 μs, the optimal machining results can be obtained, and the error between the optimal value and the experimental value is small.
To improve the surface machining quality and machining efficiency of TC4 titanium alloy in EDM (Electrical discharge machining), the copper cylindrical electrode was selected to carry out EDM small hole machining experiment of TC4 titanium alloy. The orthogonal experiment method was adopted. Taking the relative electrode wear rate, surface roughness and material removal volume of workpiece as optimization objectives, the influences of the peak current, discharge voltage and discharge pulse width on the optimization objectives were analyzed. RBF (Radial basis function) neural network was used to train with the experimental data, and the prediction model between the discharge parameters and the optimization objectives was established. Taking the prediction model as the fitness function, the multi-objective optimization simulation was carried out by combining the genetic algorithm with the Skyline selection algorithm, and the optimal technical index was obtained. Finally, the multi-objective optimization verification experiment was carried out. The results show that when the peak current is 14 A, the maintenance voltage is 39 V/42 V, and the discharge pulse width is 102 μs/108 μs, the optimal machining results can be obtained, and the error between the optimal value and the experimental value is small.
2023, 42(1): 119-124.
doi: 10.13433/j.cnki.1003-8728.20200585
Abstract:
This paper proposes a multi-track and speed-forward-looking algorithm that uses path angles to optimize the path in a CNC system that has continuous micro-line segments. Firstly, it calculates the connection speed based on the constraint relationship between front and back paths. Secondly, it uses the path angle to map the connection speed and the maximum jerk vector function. Finally, it introduces the obtained acceleration and deceleration parameters into the S-shaped acceleration and deceleration model to obtain the asymmetric S-shaped acceleration and deceleration data. The particle swarm-taboo search hybrid algorithm is used to optimize the adjustment coefficient of the introduced path angle. The weight of the fitness function synthesis index is calculated with the entropy weight method, and the global optimal solution is obtained. The results show that compared with the traditional S-type acceleration and deceleration model, the algorithm proposed in this paper significantly improves the processing efficiency, has higher flexibility and greatly improves the processing accuracy.
This paper proposes a multi-track and speed-forward-looking algorithm that uses path angles to optimize the path in a CNC system that has continuous micro-line segments. Firstly, it calculates the connection speed based on the constraint relationship between front and back paths. Secondly, it uses the path angle to map the connection speed and the maximum jerk vector function. Finally, it introduces the obtained acceleration and deceleration parameters into the S-shaped acceleration and deceleration model to obtain the asymmetric S-shaped acceleration and deceleration data. The particle swarm-taboo search hybrid algorithm is used to optimize the adjustment coefficient of the introduced path angle. The weight of the fitness function synthesis index is calculated with the entropy weight method, and the global optimal solution is obtained. The results show that compared with the traditional S-type acceleration and deceleration model, the algorithm proposed in this paper significantly improves the processing efficiency, has higher flexibility and greatly improves the processing accuracy.
Experimental Study on Cracking Groove of Automotive Connecting Rod using Wire-free WEDM Machine Tool
2023, 42(1): 125-131.
doi: 10.13433/j.cnki.1003-8728.20200582
Abstract:
For studying Wire-free WEDM machine tool processing the inner surface cracking groove in the double sides of the connecting rod quality and efficiency, the new Wire-free WEDM machine tool is used as the experimental equipment, which carries out the single-station processing and double-station processing experiment, among the double-station processing experiment is divided into the different types and the same type of connecting rod cracking groove double-station processing experiment. The single-station processing experiments have proved that the experimental sample groove depth H decreases firstly and then increases by the wire moving frequency increasing in the single-station processing, and the groove width W is increased by the pulse period; the same type of double-station processing proves that the groove depth H is significantly affected by the power supply voltage. The width W of the cracking groove of the left station experimental sample changes from 30 to 40 μs, and the groove width W of the right station experimental sample increases with the increasing of voltage. All experimental groups can meet the preparation requirements of connecting rod cracking groove by 20 s, and it have good an application prospective.
For studying Wire-free WEDM machine tool processing the inner surface cracking groove in the double sides of the connecting rod quality and efficiency, the new Wire-free WEDM machine tool is used as the experimental equipment, which carries out the single-station processing and double-station processing experiment, among the double-station processing experiment is divided into the different types and the same type of connecting rod cracking groove double-station processing experiment. The single-station processing experiments have proved that the experimental sample groove depth H decreases firstly and then increases by the wire moving frequency increasing in the single-station processing, and the groove width W is increased by the pulse period; the same type of double-station processing proves that the groove depth H is significantly affected by the power supply voltage. The width W of the cracking groove of the left station experimental sample changes from 30 to 40 μs, and the groove width W of the right station experimental sample increases with the increasing of voltage. All experimental groups can meet the preparation requirements of connecting rod cracking groove by 20 s, and it have good an application prospective.
2023, 42(1): 132-138.
doi: 10.13433/j.cnki.1003-8728.20200590
Abstract:
Aiming at the problem of steel plate defect recognition, combined with the principle of ultrasonic pulse reflection, a steel plate defect recognition method based on Volterra series and Support Vector Machine (SVM) is proposed. Firstly, Volterra series model is used to construct the characteristic model of steel plate defects. Then, the feature parameters in the original signal, namely Volterra series kernel, are extracted by using the Fractional Order Particle Swarm Optimization (FO-PSO). Finally, the extracted feature vectors are input into the SVM model for training and testing to complete the classification and recognition of steel plate defects. Experiments were designed to obtain multiple sets of data samples for model validation. The experimental results show that the recognition model based on Volterra series and SVM can better complete the classification and recognition of steel plate defects, and the recognition accuracy is 93.3%.
Aiming at the problem of steel plate defect recognition, combined with the principle of ultrasonic pulse reflection, a steel plate defect recognition method based on Volterra series and Support Vector Machine (SVM) is proposed. Firstly, Volterra series model is used to construct the characteristic model of steel plate defects. Then, the feature parameters in the original signal, namely Volterra series kernel, are extracted by using the Fractional Order Particle Swarm Optimization (FO-PSO). Finally, the extracted feature vectors are input into the SVM model for training and testing to complete the classification and recognition of steel plate defects. Experiments were designed to obtain multiple sets of data samples for model validation. The experimental results show that the recognition model based on Volterra series and SVM can better complete the classification and recognition of steel plate defects, and the recognition accuracy is 93.3%.
2023, 42(1): 139-148.
doi: 10.13433/j.cnki.1003-8728.20200576
Abstract:
Because the efficiency for estimating the state of health (SOH) of a retired lithium battery is low, a fast and efficient estimation method is proposed. Firstly, the third-order RC equivalent circuit model is used to describe the characteristics and obtain the state equation in order to ensure the accuracy of the battery model. At the same time, the state of charge (SOC) and ohmic internal resistance (R0) are introduced as the parameters of the state equation. Secondly, the region concept was used to calculate the specific region capacity and region voltage so as to reduce the data and time needed for battery parameter estimation. The battery parameters SOC and R0 were estimated with the extended Kalman filtering (EKF) algorithm, and then the SOH of the battery was estimated. Finally, a battery test device (Arbin-BT2000) was used to conduct charging and discharging experiments on the 18650 battery to verify the feasibility of the method proposed in the paper. The experimental results show that the parameters required for SOH estimation are significantly reduced, that the time required for battery data measurement is significantly shortened and that the estimation error with the method is less than 4%, indicating that the method can quickly and effectively estimate the SOH of the lithium battery.
Because the efficiency for estimating the state of health (SOH) of a retired lithium battery is low, a fast and efficient estimation method is proposed. Firstly, the third-order RC equivalent circuit model is used to describe the characteristics and obtain the state equation in order to ensure the accuracy of the battery model. At the same time, the state of charge (SOC) and ohmic internal resistance (R0) are introduced as the parameters of the state equation. Secondly, the region concept was used to calculate the specific region capacity and region voltage so as to reduce the data and time needed for battery parameter estimation. The battery parameters SOC and R0 were estimated with the extended Kalman filtering (EKF) algorithm, and then the SOH of the battery was estimated. Finally, a battery test device (Arbin-BT2000) was used to conduct charging and discharging experiments on the 18650 battery to verify the feasibility of the method proposed in the paper. The experimental results show that the parameters required for SOH estimation are significantly reduced, that the time required for battery data measurement is significantly shortened and that the estimation error with the method is less than 4%, indicating that the method can quickly and effectively estimate the SOH of the lithium battery.
2023, 42(1): 149-158.
doi: 10.13433/j.cnki.1003-8728.20200575
Abstract:
Rolling bearings are widely used in rotating machinery, and the working conditions of the bearings seriously affect the normal operation of mechanical equipment. In order to improve the accuracy of bearing fault diagnosis, a new fault diagnosis method of rolling bearing combining time-frequency analysis with deep learning is proposed in this paper. Firstly, ten different time-frequency analysis methods are analyzed and compared. Then, the fault diagnosis model for rolling bearings using deep learning is established, and the transfer learning is applied to overcome the problem led by small number of training samples. By contrast, the accuracy of constant Q transform (CQT) can reach 100%. Finally, the effectiveness and reliability of the proposed method are verified via the experimental data. The recognition accuracies under different working loads and noise environment are evaluated respectively, and are compared to the results obtained by other methods in references. The results show that the proposed method has better robustness and higher recognition accuracy under different working environment conditions.
Rolling bearings are widely used in rotating machinery, and the working conditions of the bearings seriously affect the normal operation of mechanical equipment. In order to improve the accuracy of bearing fault diagnosis, a new fault diagnosis method of rolling bearing combining time-frequency analysis with deep learning is proposed in this paper. Firstly, ten different time-frequency analysis methods are analyzed and compared. Then, the fault diagnosis model for rolling bearings using deep learning is established, and the transfer learning is applied to overcome the problem led by small number of training samples. By contrast, the accuracy of constant Q transform (CQT) can reach 100%. Finally, the effectiveness and reliability of the proposed method are verified via the experimental data. The recognition accuracies under different working loads and noise environment are evaluated respectively, and are compared to the results obtained by other methods in references. The results show that the proposed method has better robustness and higher recognition accuracy under different working environment conditions.
2023, 42(1): 159-164.
doi: 10.13433/j.cnki.1003-8728.20200610
Abstract:
Taking an arc-side negative Poisson's ratio structure as the research object, the static compression was completed, the deformation and load data of the analysis test and simulation were compared. The peak error of the test and simulation bearing capacity was small, the overall deformation form was basically the same, and the model is reliable. Based on this structure, a filling core was established and filled in the front-end structure of a small electric vehicle for frontal collision application research. The difference between the two filling methods of the negative Poisson's ratio structure at the front end and the rear end of the longitudinal beam was analyzed by comparing the parameters of B-pillar acceleration, energy absorption, front-end collapse, and cab intrusion, and the traditional structure in the post-filling mode, the advantages and disadvantages of the impact resistance effect were compared. The results show that the rear filling method of the longitudinal beams has a superior impact resistance application effect than the front filling method. After the rear end of the arc-edge negative Poisson's ratio structure is filled, it can obtain lower acceleration peaks and less room invasion volume than the traditional structure.
Taking an arc-side negative Poisson's ratio structure as the research object, the static compression was completed, the deformation and load data of the analysis test and simulation were compared. The peak error of the test and simulation bearing capacity was small, the overall deformation form was basically the same, and the model is reliable. Based on this structure, a filling core was established and filled in the front-end structure of a small electric vehicle for frontal collision application research. The difference between the two filling methods of the negative Poisson's ratio structure at the front end and the rear end of the longitudinal beam was analyzed by comparing the parameters of B-pillar acceleration, energy absorption, front-end collapse, and cab intrusion, and the traditional structure in the post-filling mode, the advantages and disadvantages of the impact resistance effect were compared. The results show that the rear filling method of the longitudinal beams has a superior impact resistance application effect than the front filling method. After the rear end of the arc-edge negative Poisson's ratio structure is filled, it can obtain lower acceleration peaks and less room invasion volume than the traditional structure.
