The electromagnetic induction leveling method has the characteristics of high efficiency and easy operation. It has a good application prospect in the thin plate leveling process. Based on the fixed inline coil induction leveling process used by the shipyard, this research uses COMSOL Multiphysics to establish a three-dimensional electromagnetic-thermal-mechanical coupling induction leveling finite element model. The model inputs the temperature-dependent physical properties as the material properties of the AH36 steel plate, and takes the residual stress and welding deformation of the butt weldment as the initial state. The method of sequential coupling is used to calculate the changes of electromagnetic field, temperature field, and structure field during the leveling process. The two-way coupling relationship between the temperature field and the electromagnetic field is verified and the deformation of the welded part after leveling is obtained. Through the self-built induction leveling experiment platform, the accuracy and effectiveness of the finite element model are verified.
The combustion of porous media is characterized by high efficiency and good stability. A simple cubic packed structure consisting of an alumina particle packed bed and double-layer silicon carbide foam ceramics was proposed to study the filtration combustion characteristics of the structure. By changing the premixed gas equivalent ratio and inlet velocity, the flammability limit of flame, flame propagation law, CO emission law, and combustion efficiency under different working conditions were studied. It is found that the stabilization and propagation of the flame depend on the regional temperature, the equivalent ratio, and the velocity. In the bed with a particle diameter of 40 mm, the flame is easy to spread and the combustion efficiency is high, while in the bed with a particle diameter of 20 mm, the flame is more stable.
Zero-liquid discharge is an efficient pathway for high concentration brine and wastewater treatment. Contactless solar evaporation is a new configuration proposed in recent years towards this target, which has the advantages of solar energy utilization, simple structure, passive operation, and anti-fouling. Considering that contactless solar evaporation lacks an effective predictive model to guide the optimization in real scenarios, a steady-state thermal resistance network model is developed for the first time and further analyses are conducted. According to the results, two main heat sources of the water, radiative heat transfer and air gap heat transfer, contribute 54.2% and 45.8% to the total heat flow and both have a significant impact on the evaporation performance. The larger air gap thickness has a negative effect on both of the two heat transfer processes. The evaporation rate with an air gap thickness of 10 mm is only 70% of that with an air gap thickness of 4 mm. Additionally, decreasing vapor diffusion resistance is an efficient way to increase the evaporation rate. The evaporation rate triples when the vapor diffusion coefficient increases from 5×10-6 m2/s to 2.5×10-5 m2/s.
The compression deformation of the measuring membrane of the differential pressure capacitance sensor is studied. The classical von Kármán thin plate theory is applied to the elastic circular thin plate subjected to pretension, and the approximate analytical solution is given by adopting the homotopy analysis method. The results are compared with the simulation results of the finite element software ANSYS, which shows that they have a high degree of agreement. The magnitude of pretension has a great influence on the deformation of the membrane under compression, thus affecting the capacitance output characteristics of the sensor. The effect of pretension on the nonlinear characteristic of the sensor is verified by the sensor performance test. The results suggest that the linearity of the sensor can be effectively improved by selecting the appropriate pretension, and the sensitivity of the output can be improved by appropriately reducing the membrane thickness. The analysis results have an important reference value for the design of membrane of differential pressure capacitance sensors.
Fuel atomization plays an important role in premixed combustion of aero-engine. In order to improve the atomization characteristics of an aviation fuel nozzle and optimize its structural parameters, the volume of fluid (VOF) interface capture algorithm and orthogonal experimental design were used to study the influence of internal flow and structural parameters (expansion angle, length of straight section, rise angle of swirl groove, and number of swirl groove) on the atomization characteristics. The results show that the local vortex on the swirl groove affects the fuel flow in the nozzle, and the local pressure loss can be eliminated by changing the structure of the swirl groove inlet. The number of swirl grooves has the most significant effect on Sauter mean diameter (SMD), the expansion angle is the biggest factor affecting the atomization cone angle, there is an optimal swirl groove elevation angle to minimize the oil film thickness, and the length of straight section has relatively little effect on the atomization characteristics. When the expansion angle is 60°, the length of straight section is 0.25 mm, the rising angle of swirl groove is 45°, the number of swirl grooves is 2, and the optimization effect is the best. After optimization, the oil film thickness decreases by 43.68%, the atomization cone angle increases by 3.70%, and the SMD decreases by 14.79%.
Impinging jet is widely implemented at the leading edge of aircraft wings for anti-/de-icing purposes. To further improve the anti-icing performance, this paper utilized numerical simulation to explore the impingement heat transfer characteristics of different fin arrays on flat plate and concave surface sequentially. The fin array in the flat-plate model consisted of 8, 12 straight fins or 12 curved fins. The concave surface model consisted of 8 short or long fins. The results show that the addition of fin arrays on the flat plate and airfoil surface can significantly improve the jet impact heat transfer performance at different Reynolds numbers. Compared with non-fins, the comprehensive heat transfer effect on the airfoil surface is increased by 4%—10%, especially for the stagnation region. Further flow field analysis reveals that adding fin array not only increases the area of heat transfer, but also strengthens the turbulent kinetic energy of impingement jet flow, leading to an enhancement of heat transfer performance.
Aimed at the important position of the steam generator liquid level control system in maintaining the safe and efficient operation of the power plant in the PWR nuclear power plant, and the fact that there exist strong nonlinear characteristics in the controlled object of the steam generator liquid level under different load sections and changing conditions, this paper proposes a fuzzy control algorithm with the adaptive variable universe function. Based on the general fuzzy control algorithm, the Lyapunov function is constructed through the nonlinear system model, and the optimal adaptive expansion factor is solved based on the ideal control law, and Lyapunov theorem is used to prove the stability of the control system. The simulation results show that the fuzzy control with adaptive variable universe function can better effectively control the liquid level of the steam generator under different working conditions and variable working conditions than the traditional proportional integral (PI) control and fuzzy PI control. The problem of controller overrun is solved, and the system has a better robustness.
To realize efficient scheduling of automatic guided vehicles (AGV) in the aircraft final assembly workshop, a two-stage method of AGV task allocation and path planning is proposed which effectively solves the problem of multi-trip distribution scheduling of AGV in the workshop. In the task allocation stage, an AGV task allocation model based on the trip is established to improve task allocation efficiency. In the path planning stage, the time window algorithm is used to initialize, update, and arrange the time window of the resources occupied by the AGV. Considering that the latest delivery time constraints may be violated due to obstacle avoidance and waiting, three adjustment strategies are designed to realize the conflict-free path planning of AGV, including the package exchanging strategy, the priority exchanging strategy, and the reserved conflict duration relaxation strategy. In numerical experiments, the average solving time of the two-stage method applied to problems with the scale of 50, 100, and 150 is 15.86, 41.12, and 162.29 s, which indicates that the two-stage method effectively alleviates the complexity of the multi-trip AGV scheduling problem. The two-stage method can realize the scheduling of the AGV in aircraft assembly workshop within a reasonable time and adapt to the rapid increase in the annual production of aircraft.
The objective of this study is to establish generalized correlations for R32 flow boiling heat transfer and frictional pressure drop in channels with wide ranges of geometric and flow parameters. In this paper, two consolidated databases for heat transfer and frictional pressure drop were amassed from open literature, which involved R32 as working fluid. The heat transfer database consisted of 1 489 data points from 8 sources, with hydraulic diameters of 1—6.3 mm, while the pressure drop database included 496 data points from 8 sources, which covered hydraulic diameters of 0.643—6 mm. A new heat transfer coefficient correlation and a frictional pressure drop correlation were developed based on the prediction technique of dimensionless parameter analysis considering the governing force effect. Moreover, the existing correlations were also introduced to perform assessment. The validation results show that the existing correlations have poor results of mean absolute errors (MAE) and significantly high maximum absolute errors (MAX), but the new heat transfer coefficient correlation provides a superior prediction accuracy with a MAE of 14.59% and 90.85% of data within ±30% error bands. In addition, the new pressure drop correlation exhibits the best performance, which yields a MAE of 17.86%. The two new correlations have a broad application range and satisfactory prediction accuracy, which are applicable to analyze the heat transfer and pressure drop performance of heat exchangers with refrigerant R32.
Pallet recognition is one of the critical technologies of cargo handling for unmanned industrial vehicles. A pallet recognition method based on adaptive color fast point feature histogram (ACFPFH) is proposed to solve the problems of current recognition methods such as low efficiency, time-consuming, poor robustness and random parameter selection. The Kinect V2 sensor is used to collect the point cloud data which represents the whole scene including pallet. Next, outliers are removed and the optimal neighborhood radius of each point is obtained based on the minimum criterion of neighborhood feature entropy function. Then, the key points are extracted from scene point clouds. The ACFPFH consisting of color feature and adaptive geometric feature is applied for similarity matching between the template and scene point clouds. Finally, wrong feature correspondences are rejected and the pallet in the scene point cloud is recognized. A comparison of the fast point feature histogram with the fixed neighbor radius of 0.012 m shows that the pallet recognition precision and efficiency of the method based on ACFPFH is improved by 83.74% and 35.55% respectively, which verifies the superiority of the proposed method.
For the maintenance outsourcing requirements of complex systems in service-oriented manufacturing, a multi-level optimization policy of opportunistic maintenance and inventory control (OMICP) is proposed by considering the challenges of redundant machine interference, high shutdown penalty, and spare parts inventory limit of k-out-of-n: G system. At the machine layer, the degeneration model of each machine is built. Then, preventive maintenance cycles of each machine are outputted in sequence by minimizing the maintenance cost rate. At the system level, these maintenance time points are taken as opportunities. In addition, a dynamic combination opportunistic maintenance policy is established by comprehensively considering inventory level, shutdown quantity, and redundancy interference. At the joint level, based on the opportunistic maintenance decision feedback, the inventory control policy is updated in real time by modeling and analyzing the profit balance of spare parts ordering. Through this multi-level interactive decision-making under outsourcing maintenance, the coupling relationship between complex system maintenance and inventory control is integrated to optimize the total cost of maintenance outsourcing services. The case study has shown that OMICP has the feasibility of complex decision-making and the effectiveness of cost optimization.
In this paper, the influence of the multiple injection strategy on premixed charge compression ignition (PCCI) combustion of a heavy-duty diesel engine in low load speed extension is studied experimentally and numerically, and the general optimization direction of low-load spray combustion of a heavy-duty diesel engine is obtained. The injection timing should match the shape of the combustion chamber, so that the oil, gas, and chamber are combined to make full use of the advantage of the shape of the combustion chamber. As the speed increases, the multi-injection strategy can overcome the defects such as the decrease of injection rate and the decrease of oil-gas mixing degree caused by the extension of injection duration. For single injection at a low speed, through optimizing the injection strategy, the NOx emission is reduced by 38%, the soot emission is decreased by one order of magnitude, and the indicated thermal efficiency is increased by 8.66%. For single injection at a medium speed, the indicated thermal efficiency remains unchanged, the NOx emission is reduced by 59.3%, and the soot emission is reduced by 70%. For single injection at a high speed, the thermal efficiency and the NOx emission are increased slightly while the soot emission is decreased significantly. In addition, it is found that with the increase of speed, the influence of the multiple injection strategy on indicated thermal efficiency and emissions is gradually increased, and the optimization effect of the multiple injection strategy is more obvious than that of low speed.
With the wide application of the service-oriented manufacturing mode, the scale of leasing manufacturing enterprises continues to expand, which leads to the global multi-regional development of maintenance outsourcing services. To address the multi-location maintenance scheduling problem of multi-center leasehold networks in the provision of “products+services”, this paper proposes a multi-center collaboration maintenance scheduling (MCMS) strategy with the dynamic interaction between the system level and the network level. At the system level, it considers the impact of the maintenance downtime, cumulative failure, and system combination selection on maintenance decisions, then optimizes the maintenance grouping of machines in the same manufacturing system. Based on the proposed optimization model, the group maintenance set and the corresponding maintenance start time can be obtained by minimizing the total maintenance cost. At the network level, it further considers the impact of service routing optimization, team dispatch selection, and maintenance response speed on scheduling decision, and then outputs the optimal service route for each team by minimizing the total scheduling cost. It also verifies the feasibility and cost-effectiveness of the MCMS strategy in the field of multi-location maintenance scheduling problems by analyzing the case study.
At present, there is no method for predicting oil retention applicable to various working fluids. Oil retention characteristics in compressor suction lines are studied and a general method for predicting oil retention is established. The database of oil retention in suction lines is established according to experimental values in the public literature. After analyzing the influencing factors, a correlation of the volume ratio of oil retention in the database is fitted. According to the correlation and the state of working fluid at the inlet of suction line, the amount of oil retention can be predicted. In addition, oil retention of R32/PVE VG68 in suction lines is tested. A comparison of the experimental values and the prediction values indicate that for the flow of R32/PVE VG68 in suction lines, the calculation method can accurately show the variation trend of oil retention with various factors, and can accurately predict the amount of oil retention under different conditions.
Prior studies on cryogenic thermal contact resistance (TCR) measurement mainly focus on liquid nitrogen temperature region and above. There are limited solid TCR data in the lower temperature region. The present measurement is based on an RDK-408D2 two-stage G-M cryogenic refrigerator. By using the laminated method, the TCR data of brass samples in the temperature range of 10—30 K at different roughnesses and preloads are measured and the influence of different factors on TCR is discussed. The results show that the TCR of the brass contact surface in this temperature zone is between 6.89×10-4 and 1.86×10-2 m2·W/K. With a smaller roughness of the contact surface, higher temperature, and greater pre-tightening force, the TCR becomes smaller. This behavior is consistent with the conventional qualitative understanding. The above cryogenic experimental data can provide certain support for the calculation of TCR for related cryogenic application design.
Based on the nonlinear geometric relationship of the bulging angle and the bending angle, and the principle of virtual work and nonlinear constitutive relationship of Neo-Hookean incompressible hyperelastic material, a quasi-static mechanical model for pneumatic toothed soft actuator was established, considering the strain energy of the bottom, side walls, and front and rear walls. Considering the geometric nonlinearity and material nonlinearity, the proposed model could solve the configuration of the soft actuator at different driving pressures and terminal loads precisely and efficiently. The finite element simulation of the cantilevered-free soft actuator was conducted by Abaqus, and the corresponding experimental device was established. The simulation analysis and experimental investigation were performed at different driving pressures. A comparison of the results show that there is a positive linear correlation between the driving pressure and the bending angle of the soft actuator, and the prediction of the theoretical model agrees well with the simulation and experimental results. In addition, the distribution of the strain energy was analyzed. Based on the equal-curvature model, the configuration results of the soft actuator at terminal loads are basically consistent with those obtained by Abaqus. The proposed quasi-static mechanical modeling method provides a theoretical basis for the structural optimization design, performance improvement, and motion control of similar soft actuators.
Aimed at the poor accuracy in traditional deep drawing of aerospace aluminum alloy hemispherical shells, and by introducing metal spinning, a stamping-spinning hybrid process strategy for aluminum alloy hemispherical shells is proposed, which can achieve the forming processing of the formed component with a high thickness uniformity and high shape accuracy. The finite element simulation model of the hybrid process of the aluminum alloy hemispherical shell is developed, which realizes the simulation. In addition, the variation law of the wall thickness and shape fitting of the hemispherical shells formed by the hybrid process are analyzed. The simulation results show that the uniformity of wall thickness of the hemispherical shells formed by 50% stamping + 50% spinning is significantly improved. The shape accuracy of the component can be obviously improved by changing the stress state of the forming component by power spinning. Meanwhile, the hybrid process is verified by using an aluminum alloy hemispherical shell with a diameter of 1 m in processing test, which improves the thickness uniformity and the shape accuracy of the hemispherical shell.
The throttling process, as an important part of the heat pump system, plays a crucial role in the efficient and reliable operation of the whole system. This paper, taking the quasi two-stage compression high-temperature heat pump with green refrigerant HP-1 as the research subject, established the mathematical models of the circulatory system and electronic expansion valve by using MATLAB and considering the influence of the opening of electronic expansion valve and thermodynamic properties of the new green refrigerant. It simulated the matching characteristics of electronic expansion valve opening and flow rate under variable operating conditions, and fitted the HP-1 dimensionless flow coefficient correlation by power-law distribution using experimental data. The research results show that the electronic expansion valve with an elliptical conical body structure adapts to the throttling characteristics of the HP-1 high-temperature heat pump system under variable operating conditions. When the evaporating temperature varies from 50 ℃ to 90 ℃ and the condensing temperature varies from 60 ℃ to 120 ℃, the opening adjustment range of this type of valve body is from 49.8% to 69.8% for the main throttle valve, and from 41.5% to 56.0% for the injection throttle valve. The relative deviation of the fitted correlation results and the actual test data is between -7.8% and +7.5%, and the flow coefficient correlation can accurately predict the flow characteristics of the electronic expansion valve with a similar body structure. The selection of favorable electronic expansion valve matching refrigerant properties and the optimization of the electronic expansion valve control system are essential for the actual operating performance. This study provides a good research foundation for the selection of electronic expansion valves and the optimization of the control system for the HP-1 high temperature heat pump.
A novel variable thickness scroll expander composed of involutes of circle with different base circle radii is proposed. The generating method of profile is discussed, the general equation of profile is given, and a series of geometric models of the variable thickness scroll expander are established. According to the established geometric model, the influence of control coefficient on the volume change of the variable thickness scroll expander is analyzed. In addition, the geometric models of the traditional equal constant thickness and variable thickness scroll expander are constructed, and the advantages and disadvantages of the geometric models are compared. The results show that the novel variable thickness scroll expander model not only has the advantages of the traditional variable thickness model, but also greatly reduces the amount of calculation. To a certain extent, it enriches the types of variable thickness scroll expanders and provides reference for the development of high-performance scroll expanders.
Accurate boiler load forecasting of cogeneration units plays a direct role in production management and dispatching of power plants. A long-term load forecasting model of combined heat and power (CHP) based on attention mechanism and the deep convolution long-short-term memory network (CNN-LSTM-AM) is proposed, which takes the historical data of boiler outlet steam flow (load) and multi-dimensional load influence factors as input to make long-term load forecasting. First, the original data is screened by Pearson correlation coefficient judgment. Then the processed data is processed by convolution layer for feature extraction and further dimensionality reduction, fitted through long-term and short-term memory layer, and optimized the weight by adopting attention mechanism, so as to achieve accurate load forecasting. The proposed model is verified by the measured data of Tongxiang Power Plant in Zhejiang Province. The results show that the MAPE of the proposed method is less than 1%. It can realize the accurate prediction of boiler load, which has a certain reference significance for the application of intelligent algorithm in the field of combined heat and power.
An improved multi-swarm migrating birds optimization (IMMBO) algorithm is proposed for hybrid flow shop scheduling with sequence-dependent setup times (HFS-SDST), to minimize the total maximum completion time (i.e., makespan). Permutation-based encoding is adopted to substitute the individual. The modified Nawaz-Enscore-Ham (MNEH) algorithm is employed to generate initial population which are assigned to each sub-swarm according to the makespan. For each sub-swarm, the neighborhood individuals of the leader and followers are generated respectively by performing serial and parallel neighborhood strategies. If the follower is better than the leader according to their makespan, they are exchanged to ensure the information interaction of individuals within the sub-swarm. Moreover, the discrete whale optimization strategy is embedded in IMMBO to optimize the leaders of all sub-swarms to enhance the interaction among them. Furthermore, the local search is designed for the optimal individual to further improve the local search ability of the algorithm. Meanwhile, to avoid algorithm premature convergence, the control strategy for population diversification is designed to the leader of each sub-swarm. Finally, based on adjusting the algorithm parameters experimentally, simulation experiments are conducted on four variants of IMMBO to verify the function of each part by testing an adaptation dataset of Ta. Moreover, the IMMBO is compared with three existing algorithms by testing an adaptation dataset of Ta, and the experimental results demonstrate the effectiveness of the IMMBO algorithm to solve the hybrid flow shop scheduling problem.
Aimed at the problem that the accuracy of tool remaining life prediction was reduced due to the abnormal monitoring data in machining process, a data anomaly detection method based on self-paced learning was proposed. First, a multi-layer perceptron model was established to correlate the tool processing monitoring data with the tool remaining life. Next, in the process of updating model weight, the model weight parameters were fixed first, and the loss threshold of abnormal samples was obtained by predicting loss fitting Gaussian distribution. Then, the loss function based on the self-paced learning method was constructed to update model parameters iteratively. At the end of the model training, abnormal samples were divided according to the loss threshold. Finally, the actual processing monitoring data of turbine rotor groove were used to verify the proposed method, and compare with the local anomaly factor algorithm, the density-based clustering algorithm, the K-means algorithm, the isolated forest algorithm, and the one-class support vector machines.
With the continuous improvement of pump-driven liquid cooling requirements for electronic devices, the cooling requirements for multiple dispersed units are inevitable, resulting in higher requirements of equal cooling capacity for parallel microchannel evaporators. Because of the existence of negative slope region in the characteristic curve of two phase flow in microchannel sink, the flow excursion will occur. The flow distribution in the parallel microchannel evaporator is simulated with ammonia as the working medium, and the effects of inlet subcooling degree, heat flux and length of connecting pipe on flow characteristic curve in a microchannel evaporator are studied. Besides, the influence of flow excursion on the overall temperature distribution of evaporator, and the influence of heat flux, inlet subcooling degree, and length of connecting pipe on the flow distribution of two parallel evaporators are investigated. The results show that the flow excursion between evaporators does not necessarily deteriorate the heat transfer capacity of the system, and the arrangement of heating flux, inlet and outlet connecting pipes has a great influence on the stability of the parallel evaporator system.
In order to improve the accuracy of remaining useful life (RUL) prediction of insulated gate bipolar transistor(IGBT) modules across working conditions to enhance their reliability, an RUL prediction method based on the ProbSparse self-attention mechanism and transfer learning was proposed based on the transient thermal resistance features of IGBT modules under different working conditions. An accelerated aging test bench of the IGBT module was designed ang built to perform power cycling experiments in different temperature ranges, and state data of full life-time under different working conditions were collected. Transient thermal resistance change data during the IGBT module degradation were calculated, and the transient thermal features that can accurately reflect the aging state of the IGBT module were extracted and selected. These features were used to predict the RUL of IGBT modules across different working conditions based on the proposed method. The experimental result shows that the accuracy of the proposed RUL prediction method of IGBT modules across working conditions outperforms other compared methods. Particularly, the RUL prediction accuracy during the early degradation stage has been significantly improved.
A multi-shift tooling coordinated operation control strategy based on the backstepping method is investigated, a desired motion state planning scheme based on the improved artificial potential field method and the pure trajectory tracking method is proposed, and the actual situation is determined according to the adaptive Monte Carlo positioning method. For the estimated value of the motion state, a queue controller in combination the anti-stepping method and the virtual pilot following method is designed. A simulation model based on the robot operation system (ROS) environment is constructed, and the simulation is verified. The results show that the proposed formation error calculation method can improve the accuracy of error estimation. The formation control strategy can make the formation error converge within 6.2 s, and the designed formation controller can meet the operation requirements of multi-shift tooling.
The classification of the defects in welding applications based on the metallographic structure images plays an important part in industrial welding quality inspections. In order to improve the classification performance of defects in the weld metallographic structure images with a small sample dataset available (the amount of samples being less than 30), a Poisson fusion method is used for data augmentation of the defect images and the ResNet18_PRO network is proposed. Both of the methods notably improve the defects classification performance. During data augmentation, the defect area is extracted from original defect samples via digital image processing, and the defect area is fused with normal samples by the Poisson fusion method to generate new defect samples, thus increasing the number of defect samples. The model in this paper is improved based on the ResNet18 network. The downsampling structure is improved to reduce the information loss in the original downsampling structure, and an improved space pyramid pooling structure is added at the end of the network to integrate multi-scale feature information. The classification performance before and after data augmentation is compared by different classification models, which verifies the significant effect of the data augmentation on the classification performance. Meanwhile, the ablation experiment of the ResNet18_PRO is conducted to verify the effectiveness of the improved network structure and the training strategy. It is found that the average classification accuracy of ResNet18_PRO reaches 98.83% and the average F1-score reaches 98.76%, which greatly improves the classification accuracy of metallographic structure defects. Finally, the network is trained and tested with another industrial defect dataset and obtains good classification results. These results show that the proposed network has a good robustness and practical application value.
Thermal energy field is the main way to improve the formability and dimensional precision of components in sheet forming. In order to solve the temperature fluctuation of traditional heat sources, a well-controlled laser heat source was introduced into sheet metal shear spinning to improve the spinnability and forming accuracy by matching local deformation with local heating reasonably. Laser-assisted shear spinning facility was built based on the existing spinning machine, and a model of laser irradiation point drift of ellipsoidal components under the rigid connection of laser heat source was established to analyse the optimal region of laser thermal field loading. The theoretical analysis shows that, during laser-assisted spinning, the rigid connection can be deemed as precise heating under the condition of mandrel with small variation of section circle radius. Subsequently, laser-assisted shear spinning tests on the thin-walled aluminum alloy ellipsoidal components were conducted. The results show that, compared with cold spinning, the laser assisted method extends the spinnability of difficult-to-deformation material in shear spinning and significantly improves the precision and thickness of the spun thin-walled components, which verifies the feasibility of the developed test setup and process design method.
A single roll maintenance model is established to realize the dynamic decision of single roll maintenance cycle by considering the influence of roll wear, unit faults, and roll gap quality control on accident loss, piece quality loss, and maintenance cost. Considering special scenarios such as different grinding cycles of each roll, the same unloading cycle and allowing small adjustment of dismounting schedule, a dynamic opportunity maintenance strategy of work roll is proposed and a decision model is constructed to optimize the work roll opportunity maintenance scheme of the finishing rolls. The case study shows that compared with the traditional time window strategy, the dynamic opportunity maintenance strategy has more advantages in reducing the maintenance cost of work roll.
In order to improve the energy harvesting efficiency of the wind energy capture structure, this paper proposes a novel wavy conical bladeless wind energy capture structure, and establishes a mathematical model for energy conversion of the wavy conical wind energy capture structure. The Reynolds-averaged N-S equations in combination with the SST k-ω turbulence model is used to numerically simulate the vortex-induced vibration response of the energy capture structure, and analyze the effects of mass ratio and damping ratio on the vortex-induced vibration response and wind energy conversion efficiency of the wavy conical wind energy capture structure. The results show that the wavy conical energy capture structure with a mass ratio of m*=2 and a damping ratio of ζ=0.05 can obtain a wider lock-in interval and higher energy conversion efficiency. It is also found that the mass damping ratio m*ζ directly affects the energy conversion efficiency, a suitable combination of m*ζ can improve the energy conversion efficiency, with an average energy conversion efficiency of nearly 31% higher at m*ζ=0.10 than at m*ζ=0.05. The research results can provide theoretical support for the improvement of the energy conversion efficiency of bladeless wind turbines.
In order to investigate the driving characteristics of multi-axis special vehicle under the limit condition of missing tires, a five-axis special vehicle dynamics simulation test model including vehicle parameters, power transmission and braking system, axle and suspension system, steering system, and tire system was established based on the vehicle dynamics software TruckSim. Focusing on the analysis of the effect of tire deficiency and based on the tire six component test, the simulation test model of tire parameter was modified and the 0—80—0 km/h linear acceleration brake comfort simulation test and double line operating stability simulation test were conducted to study the smooth features and stability characteristics under the condition of tire deficiency at different positions. Based on the deviation of the centroid of the vehicle, the maximum number of missing tires at different driving speeds was analyzed, and the tire layout methods as well as the degree of influence of each axle tire on the vehicle at different driving speeds were proposed. The results show that the multi-axle special vehicle has the limit condition of driving under the condition of tire deficiency, and the tire deficiency at different positions has little effect on the driving speed of the vehicle. The influence of each axle tire on the driving of this type of vehicle is ranked in order of importance, which are the first axle, the fifth axle, the third axle, the second axle, and the fourth axle. When the vehicle travels at 50 km/h, 30 km/h, and 20 km/h, the maximum numbers of missing tires are 1, 2, and 3, respectively. This paper can provide theoretical support for the assessment of driving safety of multi-axle special vehicles.
In the process of steel rolling, due to wear and other reasons, the working performance of the roll under long and complex working conditions has a gradual decline. Considering the characteristics of complex working conditions and strong random interference of the roll working environment, this paper proposed a kernel-based Wiener process (KWP) degradation model to characterize the strong randomness of the roll degradation trend by using the Wiener process, and to capture the nonlinear degradation path of the roll by using the kerna function. This paper derives the analytical expression of parameter estimation in the Bayesian framework, and constructs the health index of the roll working rotation, then predicts the remaining useful life (RUL) of the roll. In combination with the field data of 1580 hot rolling production line of an iron and steel company, the goodness of fit of the model built is 0.989, and the residual life prediction error is less than 4.7%. Compared with the common machine learning algorithm, it has achieved better results, which is helpful to improve the operating efficiency and safety of equipment and achieve maintenance as needed.
Considering the problems that quantitative analysis and optimization of the geometrical model of scroll compressor created from involute of circle with variable radii are incomplete, the changing trend of the working chamber volume from the beginning of the suction process to the end of the discharge process is given. The volume calculation differences of Green’s theorem method, the graphical method, and the normal isometric method are compared, the reasons for calculation errors are analyzed, and the correctness of the geometrical model is verified. The calculation formula of teeth area utilization rate is deduced, and the sensitivity models of suction volume and teeth area utilization rate are constructed. It is concluded that the influence of the base circle radius variation coefficient and the occurrence angle of the inner profile are particularly significant. A multi-objective optimization analysis model considering nonlinear constraints and taking the suction volume and teeth area utilization rate as the optimization goals is established. The results show that the multi-objective genetic algorithm NSGA-II has a better comprehensive performance than the multi-objective particle swarm algorithm MOPSO and the suction volume of the scroll compressor created from the involute of circle with variable radii for an automobile air conditioner has been increased by 6.5% and the teeth area utilization rate has been reduced by 4.27%. This paper can provide further theoretical reference for the optimal design and quantitative research of the scroll compressor constructed from involute of circle with variable radii.
Functional design is an extremely important part in the design and development of complex systems. It is necessary to establish a forward development method to ensure the correctness and completeness of functional design. Therefore, taking the flight control system of civil aircraft as an example, a forward development method for functional design is proposed. First, system modeling language is used to establish the functional requirements relationship model from aircraft level to system level and then to item level. Then, the functional requirements are combined with the safety requirements in SAE ARP4754A aircraft development guide to construct the functional knowledge set of the flight control system. Finally, the functional model of the flight control system is established based on functional unit block diagram and functional integration block diagram. This method can be used as a reference for the functional design of complex systems.
Under operating conditions, bearings have a substantial service life with short failure time periods, which leads to unbalanced dataset and greatly affects the accuracy of deep learning model fault diagnosis. To address this problem, a fault diagnosis method of rolling bearing unbalanced dataset based on two-step transfer learning is proposed in this paper. First, a small amount of data in the source and target domains is used to generate the transition dataset by conditional gradient penalized generative adversarial network (CWGAN-GP). Then, the constructed convolutional neural network model is migrated twice between the source domain dataset, the transition dataset, and the target domain dataset. Finally, a small amount of data from the target domain is used to fine-tune the transferred model to obtain the final fault diagnosis model. The experimental results show that the method has a good diagnostic recognition effect on rolling bearing spalling class faults with unbalanced dataset under different working conditions.
Proper preventive maintenance can improve equipment reliability and prolong equipment life to a certain extent. Aimed at the problems that the decision granularity of the current preventive maintenance strategy is too large and the maintenance effect of preventive maintenance on different types of failures is rarely considered, the imperfect sequential preventive maintenance strategy of the meta-action unit is studied. Taking the meta-action unit as the research carrier, the failures are divided into damage failure and essential fatigue failure according to the difference of preventive maintenance effect. Based on the generalized geometric process, a sequential preventive maintenance optimization model is established. The research shows that the overall maintenance cost rate will be underestimated without considering the differences in preventive maintenance effectiveness. At the same time, various types of maintenance costs, the proportion factor of damage-type failures and intrinsic fatigue-type failures, and the preventive maintenance effect parameter have a significant influence on the formulation of maintenance strategy. This research has a certain guiding role in formulating the sequential preventive maintenance strategy of meta-action unit and reducing its maintenance cost.
