Glass is a non-conducting, hard and brittle material. It has a wide range of applications in optics, biomedicine and microelectromechanical systems. Electrochemical Discharge Machining (ECDM) is an effective microfabrication technique for insulating hard and brittle materials. It enables effective microstructural processing of glass. In ECDM, the discharge phenomenon is generated by the breakdown of the gas film, the quality of which, as the main medium in the process, is an important factor in forming good surface microstructures. This study focuses on the characteristics of the gas film and its influence on the discharge energy distribution. The study uses a full factorial test method with three factors and three levels of power supply, duty cycle and frequency as the influencing factors and gas film thickness as the response for the experimental study to obtain the best combination of process parameters for the best gas film quality. In addition, experiments were carried out on two types of glass, quartz glass and K9 optical glass, for the processing of micro-holes. The results show that the optimum combination of process parameters results in a thinner gas film and the best conditions for obtaining micro-holes with a smaller diameter overcut, a larger depth-to-diameter ratio and a smaller roundness error.
In order to investigate the effect of ultrasonic frequency on laser clad coatings, five sets of control experiments were conducted to investigate the macroscopic morphology, microstructure and wear resistance of TiCN-enhanced nickel-based coatings by applying ultrasonic frequencies of 0 kHz, 26 kHz, 30 kHz, 34 kHz and 38 kHz. The results showed that: the application of ultrasound did not generate new phases in the coatings and promoted the generation of TiCN-enhanced phases to some extent; the number of bubbles in the coatings decreased with increasing ultrasound frequency, the grains were finer and tighter, and the agglomeration phenomenon in the coatings was reduced; the microhardness of the coatings increased with increasing ultrasound frequency, and the microhardness of the coatings was highest and varied smoothly when the ultrasound frequency was 38 kHz; compared with the coatings without the application of ultrasound, the microhardness of the coatings with the application of 38 kHz was higher. Compared with the coating without ultrasound, the coating wear at 38 kHz was reduced by about 30%, and the main wear was changed from adhesive wear to slight plowing.
In order to achieve better finishing and strengthening effect on laser cladding layer of axle steel, ultrasonic rolling method was used to treat laser cladding layer of EA4T axle steel and its main machining parameters optimization was analyzed. The results show that the surface roughness of laser cladding increases with the increase of the reduction amount. With the increase of static pressure, the surface hardness of cladding layer firstly increases and then decreases. When the rolling rate is increased, the surface roughness of the sample decreases first and then increases. With the increase of rolling times, the surface hardness of the cladding layer increases first and then decreases. The optimal parameters were determined as follows: under the conditions of rolling down 0.10 mm, rolling rate 2100 mm/min, static pressure between 0.45~0.65 MPa and rolling three times, the ultrasonic rolling method could achieve excellent surface finishing effect. There are obvious plastic deformation layers on the surface of laser cladding layer after ultrasonic rolling. The plastic deformation degree of laser cladding layer decreases with increasing depth, while the grain size increases. According to the research results of this paper, it can provide a theoretical reference for the optimization of ultrasonic rolling process of laser cladding hot working axle steel, and provide theoretical guidance for the practical application process. In addition, it can also promote the improvement of die manufacturing technology and repair ability.
The profile of the end section of the flute is an important factor in tool design, machining and performance analysis. In this paper, a new method, polar pixel layout method (PPM), is proposed to obtain the profile of the flute end section of an end mill by combining the spiral motion of the grinding wheel with polar coordinate transformation and mathematical morphology. PPM extracts the section profile directly through the polar coordinate binary image of the point cloud combined with the erosion and dilation algorithm of mathematical morphology. It does not need to solve the contact line equation, nor do Boolean operations. PPM can stably obtain the high-precision profile of the flute of the end mill. Finally, PPM calculation results are compared with the analytical method. These comparison errors are within the allowable range, thus verifying the correctness and effectiveness of PPM.
Stellite6 alloy is a high temperature alloy with cobalt, chromium and tungsten as the main element. It has good red hardness but poor thermal conductivity. During cutting, the contact area between the tool and the chip is easy to produce higher temperature. The cutting simulation model of Stellite6 alloy is established, and the experimental methods and conditions are determined. The influence of feed per tooth, cutting speed and cutting width on cutting temperature is studied by orthogonal test and simulation. The range analysis method and variance analysis method are used to obtain the primary and secondary order of the influence of milling parameters on cutting temperature. The optimal cutting parameters with the minimum cutting temperature as the goal are obtained, and the empirical calculation formula of cutting temperature is established.
In view of the fuzzy classification boundaries of massive and diverse cloud manufacturing (CMfg) service resources, this paper analyzes the relationship between cloud services and manufacturing resources, and establishes a CMfg hybrid service aggregation model based on the service resources aggregation type. In addition, this paper establishes a clustering validity evaluation function based on k-means clustering algorithm. Aiming at the disadvantage that k-means clustering algorithm is sensitive to the initial clustering center, the shuffled frog leaping algorithm (SFLA) is introduced to determine the initial clustering center. The inverse solution is used to expand the search range of the initial frog population, and the optimization of the worst frog population is improved by combining the mean value of the optimal solution. Based on the improved leapfrog algorithm and k-means iteration, an improved k-means clustering algorithm based on leapfrog algorithm is proposed. Finally, the validity of the algorithm is verified by the Iris test data set and a self-constructed data set (Self-cd), and the feasibility of the algorithm is illustrated by the application of lathe resource on the CMfg platform.
In order to solve the problems of complex circuit design and low precision wiring design in the process of electromechanical product design and manufacturing under the background of mass customization, a three-dimensional intelligent wiring method based on SolidWorks was proposed. A* algorithm was improved to automatically plan the optimal wiring path, and a wiring space definition method based on channel network was proposed, which restricted the generation of wiring path and guaranteed the correctness of wiring path. Finally, the corresponding wiring system was constructed through secondary development, and the feasibility of this method was verified. The results show that this method can effectively improve the efficiency and accuracy of product circuit design.
With the development of industrial technology, the teleoperating system is widely used in various fields. In teleoperation, The completion effect of the task is affected by the motion performance of the slave arm. Therefore, it is hoped that the performance of the slave arm can be optimized while the slave arm follows the trajectory of the human arm. However, the existing performance optimization methods will change the motion state of the robotic arm, resulting in the movement of the human and robotic arm is not similar. Therefore, a teleoperation performance optimization method based on an equivalent arm is proposed. Firstly, a kinematic mapping method was established based on the equivalent arm model to map the motion information of the human arm to the robot arm completely. Then, a performance optimization method is proposed to optimize the motion performance of the robotic arm by adjusting the equivalent arm. Finally, the performance optimization experiment is carried out. The experimental results show that the performance optimization method can improve the performance of the robotic arm while guaranteeing the kinematic similarity of the two arms.
To improve the optimization quality of cloud manufacturing service composition, an optimization method for multi-objective cloud manufacturing service composition based on improved NSGA-II algorithm was proposed. Firstly, improved the concept of dominant strength was quickly determined the ordering of individuals in non-dominated set. Then, different local search strategies were applied to the NSGA-II algorithm to accelerate the convergence by strengthening the search for excellent individuals in the early stage of the algorithm. In the later stage, sparse individuals were searched by using method combining neighborhood search and simulated annealing algorithm to increase population diversity. Finally,the effectiveness of the optimization model and the feasibility of the algorithm are verified by an actual enterprise case．
To gain a comprehensive understanding of the current state and competitive landscape of intelligent manufacturing technology research and development in China, an in-depth analysis was conducted from the perspective of patent information. By using China National Intellectual Property Administration Intellectual Property Publishing House as a data source, the overall trend of technological development, regional competition, key areas of technological competition, and main competitors were analyzed. This paper revealed the focus and trends of intelligent manufacturing patent technology research and development in China, as well as the patent layout and technological advantages of major competitors. This provides a reference for promoting the development of intelligent manufacturing technology in China.
In order to obtain the reasonable structure and support mode of the grinding wheel rod with a large length-diameter ratio and ensure that the grinding wheel rod meets the stiffness requirements, the static deformation and constraint mode of the grinding wheel rod were analyzed via Finite element method by establishing a three-dimensional parametric model of the grinding wheel rod for large depth-diameter ratio hole, and the second-order response surface model of each design variable and optimization goal of the grinding wheel rod were constructed via optimal space-filling design method. The NSGA-II algorithm was used to optimize the grinding wheel rod with multiple objectives. After lightweight optimization design and simulation comparison, a rationalized structure of grinding wheel rod and support with large length-diameter ratio was obtained, and the lightweight rate reaches to 10.3%. The analysis results show that the quality, stiffness and mode of the grinding wheel rod all meet the engineering requirements.
In order to improve the synchronous control performance of electro-hydraulic proportional position in machine tools, the electro-hydraulic proportional position control platform of hydraulic cylinder was built, the OPC-based “industrial computer +PLC” control mode was proposed, and the active disturbance rejection controller was designed for experimental research. The test results show that compared with the single PLC control mode and PID control algorithm, the system response speed is faster, the tracking accuracy is higher and the position synchronization effect is better by using “industrial computer +PLC” and active disturbance rejection control algorithm.
In order to obtain the friction characteristics of ground the structured fish scale surface. The topological structured fish scale surface is firstly designed, and then the hydrodynamic lubrication model of the surface is established, and the fluid simulation software is used for analysis. The oil film bearing capacity and friction coefficient of the ground unit fish scale dimples with different roughness are studied and compared, and the pressure and friction coefficient of the structured fish scale surface change with the oil film thickness are analyzed as a whole. The results show that the lower the ground roughness is, the better the lubrication effect of the structured fish scale surface unit is in the given range of structured surface parameters. Overall, the lubrication effect of the structured fish scale surface has a significant cumulative effect. The structured fish scale surface with proper parameters can improve the oil film bearing capacity and reduce the friction coefficient, thus improving the lubrication effect of friction pairs.
The thermal deformation of the motorized spindle is one of the main factors affecting machining accuracy, and the thermal deformation is mainly caused by the temperature rise of the motorized spindle. The cooling system is the key factor affecting the temperature rise of the motorized spindle. In order to optimize the key technical parameters of the cooling system, taking a certain type of high-speed motorized spindle as an example, a thermal characteristic modeling is established by considering the heat transfer coefficient of different rotating surfaces of the spindle. The simulation accuracy of temperature field and thermal error is improved. The correctness of the simulation model is verified by the temperature rise and thermal error experiments at different spindle speeds. Based on the established simulation model of the thermal characteristics of the motorized spindle, the cooling system parameters were optimized by using the orthogonal test. After optimizing the cooling parameters, the simulation experiment results show that the maximum temperature of the motorized spindle is reduced by 2.0 ℃, and the thermal deformation is reduced by 25.76 μm, which provides a theoretical reference for optimizing the cooling system of the motorized spindle.
The purpose of this paper is to construct a predictive model for the very-high cycle fatigue limit of carburized Cr-Ni alloy steel. Very-high cycle fatigue tests were carried out on carburized Cr-Ni alloy steel under two stress ratios, and the results showed that the S-N characteristics of carburized Cr-Ni alloy steel showed a continuous downward trend. By observing the crack morphology on the fracture surface through scanning electron microscopy, it was found that surface failure was the main failure mode of the fatigue specimen when the fatigue life was less than 5×105 cycles, and internal inclusion-FGA-fisheye-induced failure became the main failure mode of carburized Cr-Ni alloy steel when the life was higher than 1×106 cycles. The FGA size was evaluated using the crack propagation threshold, and finally, combined with the El-Haddad model, a fatigue limit prediction model based on the threshold stress intensity factor of long cracks was constructed. Compared with the fatigue limit predicted by other models, the threshold stress model constructed had the smallest prediction error, and the predicted results were more conservative.
Milling cutters are widely used in the processing of components in various fields such as aviation, shipping, and healthcare. However, tool wear directly affects the machining quality and processing efficiency of the workpiece. A wear error compensation method with adaptive shooting angle was proposed. The problem that it is difficult to accurately measure the amount of tool wear during end mill machining has been solved. The influence of the shooting angle on different shape wear areas is analyzed. Then, the mapping model between the tool wear amount and the shooting angle combining with tool structure parameters were built. The methods can realize the automatic compensation of the detection error for tool wear caused by different shooting angles. The experimental results from different shooting angles show that the wear detection accuracy is greater than 95%, which verifies the feasibility of the self-compensation method for the wear detection error. The research methods and ideas in this paper provide references for the high-precision and intelligent tool wear detection.
Cold extrusion reinforcement for crack-filling sleeve is an effective strengthening technique in Anti-fatigue and longevity technology. It is widely used in the reinforcement of aircraft critical parts’ connecting holes. In actual engineering application scenarios, the end face of the reinforced hole are mostly non-mating surface. The protruding material at the reinforced hole’s outlet can be removed by polishing or milling, which is not difficult. However, The core part’s intersecting hole at the rotating beam cylindrical axis of an aircraft’s all-moving winglet is difficult to implement hole extrusion strengthening, the rotary beam’s material is titanium-alloy, its outer circle need high precision and it has corrosion-resistant spray coating. Threrfore, how to remove the material raised around the orifice on a circular shaft and guarantee the high precision cylindrical dimensions after the hole’s strengthening, how to ensure that hole extrusion reinforcement with not to damage the spray layer after the hole’s strengthening, all that are technical difficulties in engineering practice, which caused the hole extrusion technology can not be applied in such scenarios This paper focuses on the above issues, An experiment which is from the perspective of engineering application was designed and had been verified. A feasible technical solution is finally obtained, which is successfully solving the hole extrusion technology’s application difficulties of Titanium alloy rotary beam cylindrical intersecting hole.
In order to study the theoretical relationship between the material removal rate and the laser cutting process parameters under the model of Fiber laser nitrogen melting cutting, a mathematical model which is based on dimensional analysis method is established, Then, a single-factor laser cutting experiment was carried out on SUS304 stainless steel with a thickness of 3 mm by a fiber laser cutting machine with a power of 3 000 W, and the variation law of cutting comprehensive parameters in the model was determined. According to the analysis of the experimental results and the model, it is shown that the effect of the removal coefficient on the molten slag height is mainly determined by the critical value of the focus position. When the focus position is greater than this critical value, they are positively correlated, otherwise they are negatively correlated; Whether the material can be penetrated depends on the comprehensive parameters of laser cutting. There are different critical values of laser comprehensive parameters at different focus position. For 3 mm stainless steel, the minimum critical value appears at the focus position of 1 mm, with the size of 42.76.
The problem of thin-walled aluminum alloy box parts due to thin side walls and milling deformation caused by the reduction of accuracy. A special fixture was designed and finite element analysis was performed, and the clamping deformation was reduced from 0.015 7 mm to 0.005 98 mm, a reduction of 61.9%; parameter samples were created and objective functions were generated by Design-Expert software, and an artificial bee colony algorithm was used to optimize the objective functions, and a set of milling parameters with the minimum milling force was obtained and the predicted values were output. ABAQUS software was used to simulate the output parameters, and the optimized results reduced the milling force of the thin-walled aluminum alloy box by 35.3%; finally, the actual machining experiments were conducted, and the dimensions of the parts were measured to be within the tolerance range. The study shows that the method is important for the thin-walled box parts to improve the machining dimensional accuracy.
Aiming at the problem of the insufficient precision and frequent oversights or misidentifications in casting detection, a YOLOv5 casting automatic detection algorithm based on multi-scale feature is proposed. This algorithm uses a binocular camera to capture images of castings and builds a dataset of casting images. To extract more comprehensive features of the castings, a multi-scale feature fusion module is employed, and adding an extra detection layer to identify castings of different scales. To capture more detailed features, a Convolutional Block Attention Module (CBAM) is embedded in the Feature Pyramid Network to enhance the ability to extract key features of casting images. At the same time, the Swish activation function in the convolutional layer is replaced with Hardswish to reduce the amount of model parameters. Experimental results demonstrate that this algorithm achieves a mean average precision (mAP) of 96.5%, representing a 2.6% improvement compared to the original YOLOv5 algorithm, effectively meeting the precision and real-time requirements for casting automatic detection.
To address the issues of low efficiency and accuracy in detecting numerous complex micro defects on the surface of parts, an improved detection network called BCGS-YOLOv7 tiny is proposed, based on the YOLOv7-tiny architecture. In the feature extraction stage, the CBAM (Convolutional Block Attention Module) attention mechanism is incorporated, and the SPD-Conv downsampling layer is used instead of stride convolution and max-pooling layers to enhance the feature extraction capability for small objects. In the feature fusion stage, the Path Aggregation Feature Pyramid Network (PAFPN) is replaced by the BPANet network structure, and the gnCSP module and SPD-Conv downsampling layer are introduced to improve the feature fusion ability for small objects.Experimental results on the reconstructed GC10-DET dataset demonstrate that the BCGS-YOLOv7 tiny detection network achieves a mean Average Precision (mAP) of 91.6%, which is a 6.0% improvement over the original YOLOv7-tiny network. Moreover, the detection accuracy for various types of micro defects on part surfaces is significantly enhanced.
A new measurement method of straight slot tap radial comprehensive multi-parameter based on vision principle was proposed aiming at the problems of single measurement parameter and manual operation in the current tap measurement method. The radial profile map of the tap in polar coordinates was obtained by preprocessing. The end and core diameters were obtained by fitting a circle to the pixel with the maximum and minimum polar diameter back to the geometric center of the end edge. By fitting the characteristic curve, two pairs of line equations were obtained, and the angle formula was used to obtain the front angle and back angle values. The width of the edge back was obtained by calculating the distance between the first and last pixels of the edge back. The pole diameter difference of the first and last pixel of the edge back was taken as the shovel back amount. The experimental results show that the relative errors of the above geometric parameters are within 0.58%, and the average time is 7 s, which can meet the engineering requirements of high-precision, high-efficiency and multi-parameter automatic measurement.
In order to explore the characterization of the hardness of stainless steel after laser remelting by laser induced breakdown spectroscopy technology, using stainless steel after laser remelting as raw material, the effect of stainless steel with different hardness on the spectral and physical characteristics of laser-induced plasma was studied, the effect of different laser power and scanning speed on the hardness after laser remelting was analyzed, the change rule of different hardness and characteristic spectral lines as well as the change rule of different hardness and plasma electron temperature were analyzed. The experimental results show that the characteristic spectral lines of Fe, Si, Cr and Mn were selected to analyze the relationship between spectral line intensity and hardness as well as the relationship between the ratio of the intensity of spectral lines and hardness, the atomic spectral lines of the elements are negatively correlated with hardness, while the intensity ratio of ionic spectral lines and atomic spectral lines is positively correlated with hardness. Four ionic spectral lines of Fe element were selected to analyze the relationship between plasma electron temperature and hardness. The higher the hardness, the higher the plasma electron temperature, the linear correlation coefficient is 0.919. From this study, it can be shown that LIBS technology has the potential to characterize the hardness of stainless steel after laser remelting, which provides a new method for hardness characterization.
To address the sequential problem of planning the measurement of complex workpieces in in-machine measurement, this paper introduces TPS before the genetic algorithm plans the measurement sequence. A measurement constraint model and an envelope Boolean matrix are established for the test model, and then a genetic algorithm is used to plan the optimal measurement sequence. Compared to the direct use of genetic algorithms, the method proposed in this paper divides the measurement methods of each feature to be measured in advance, and thus achieves a more efficient and optimised measurement sequence on the workpiece as a whole. The method established in this study allows for better planning of in-machine inspection solutions and fast and accurate workpiece measurement tasks, further improving the quality and efficiency of industrial production.
Noise components exist in the actual signals obtained by data feature acquisition in the running process of CNC machine tools, and the actual running status of machine tools cannot be judged according to the signal features. In order to improve the ability of signal denoising extracting characteristic parameters, a spectral wavelet threshold denoising (SWTD) algorithm was constructed according to the spectral wavelet transform theory and practical application process, which could analyze one-dimensional digital signals. Then, the reliability of spectral wavelet threshold denoising was verified by the denoising method of simulation signal and machine tool spindle vibration signal. The research results show that the useful frequencies contained in the vibration signals of machine tool spindle are basically in the low frequency region within the range of 400 Hz. After the denoising is completed, the SWTD denoising signal forms a stable amplitude, which is close to the initial signal, and the high frequency band of more than 400 Hz in the envelope spectrum is eliminated, forming the main component consisting of the spindle rotation frequency and the hobbing frequency. Obvious characteristics of the spindle rotation frequency are observed, indicating that the proposed method has better performance than the wavelet threshold denoising results.
The current predictive control strategy based on switched extended state observer (SESO) is proposed for controllable excitation linear synchronous motor (CELSM) . According to the working principle of the controllable excitation linear synchronous motor, the mathematical model is established, the deadbeat prediction current controller (DPCC) is designed. The extended state observer is used to observe and compensate the total disturbance. In this paper, the linear state extended observer (LESO) and the nonlinear state extended observer (NLESO) are designed, the advantages of the linear and nonlinear control strategies are combined with SESO by designing suitable switching rules. The observation accuracy and robustness are improved while the convergence rate of LESO is preserved. Finally, SIMULINK is used to simulate and compare the SESO-DPCC control strategy with LESO-DPCC control strategy. The results show that the SESO-DPCC control strategy can make the output current and torque of the controllable excitation linear synchronous motor more stable and have better parameter robustness.
Using a small number of thermal key points to build an accurate model of thermal errors has been one of the difficulties in modeling thermal errors in CNC machine tool spindle systems.Taking a gantry milling machine as the research object, this paper analyzed the temperature field, thermal stress, thermal mode and thermal deformation of the machine tool spindle system by finite element simulation method, and three thermal key points were selected on the spindle system according to the simulation results. Then, the temperature change of the thermal key points and the thermal deformation of the spindle system along x, y and z directions were measured experimentally. Finally, the thermal errors of the spindle system were established by multiple linear regression model. The results show that the fitting accuracy of the thermal error models in all three directions exceeds 95%, which proves the effectiveness of the thermal key point selection method in this paper.
