In recent years, various deep learning-based health management models for mechanical equipment have made significant progress. However, existing models tend to be smaller in scale and are typically designed to handle data from specific frequencies, speeds, or modes, focusing on particular components such as gears and bearings to perform tasks like monitoring, diagnosis, and prediction. These models struggle to adapt to new scenarios and lack the capability for continuous evolution. With the increasing precision and complexity of high-end equipment, there is a growing demand for highly general, scalable, and evolvable "one-stop" health management services. Inspired by the trend of generalization in large language models like ChatGPT, which excel in handling diverse data, tasks, and scenarios, a large model for general prognostics and health management of machinery is proposed. First, multimodal data is resampled in the angular domain and segmented to token sequence. Then, the data is input into a Transformer-based information integration foundational model to extract health and degradation information into specific tokens. Finally, these specific tokens are used to perform downstream tasks such as monitoring, diagnosis, and prediction. The proposed large model's baseline performance, multitask synergy, and scalability were verified using fault and long-term degradation datasets. The results show that the proposed large model can simultaneously perform condition monitoring, fault diagnosis, and remaining useful life prediction for multiple objects like bearings and gears. Additionally, the diagnostic and predictive multitasks can effectively collaborate, mutually enhancing performance, and achieving better results compared to single-task models. In few-shot learning and continual learning scenarios, the large model can be rapidly deployed and continuously evolved. Therefore, the proposed large model features high generality, scalability, and sustainability, and is expected to provide universal "one-stop" health management services for mechanical equipment.

Cutting force is highly sensitive and capable of rapid response to changes in cutting state, which is considered as the most valuable physical quantity for machining state monitoring and adaptive machining. Since there is no need to introduce additional sensing components, an online prediction cutting force solution based on inherent servo monitoring signals in CNC systems has the potential to achieve long-term, low-cost, and accurate monitoring of cutting force. However, the relationship between servo monitoring signals and cutting force is very complex. Therefore, a cutting force online prediction method based on recurrent neural networks is proposed. Firstly, the problem of feed-axis cutting force prediction based on machine tool servo signals is defined as a nonlinear dynamic system modeling problem with adaptive time delay. Then, two types of recurrent neural networks, long short-term memory neural network (LSTM NN) and gated recurrent unit neural network (GRU NN), are introduced to directly learn the dynamic prediction model from end-to-end observation data. A set of variable speed hole milling experiments are carried out to construct a cutting excitation dataset under time-varying working conditions for comparative verifications. For the X-axis with more complex dynamic characteristics, LSTM NN has better prediction performance, with a relative root mean square error of 17.62%. For the Y-axis with relatively more simple dynamic characteristics, GRU NN has better prediction performance, with a relative root mean square error of 11.74%.

The current methods for detecting weld defects essentially belong to the paradigm of ‘industry dataset + AI model’ based on a single image, lacking integration of knowledge in the field of non-destructive testing. For a large number of defects with low contrast and insignificant targets, it is easy to cause missed and false detections. Aiming at this problem, a new paradigm of ‘industry dataset + AI model + domain knowledge’ is proposed for weld defect target detection technology that can integrate dynamic evaluation knowledge in the field of non-destructive testing. Firstly, based on the knowledge of the ‘dynamic’ process of manually detecting defects, a multi graph decomposition method based on logarithmic transformation is proposed to transform the ‘static’ analysis of a single image into the ‘dynamic’ analysis of multiple images; Secondly, by designing a channel attention mechanism module, shallow fusion of multi-image features was achieved; Finally, based on YOLOX network and combined with bidirectional feature pyramid network (BiFPN), deep fusion of multi graph features and defect target detection were achieved. Using data from a certain enterprise’s pipeline circumferential weld seam for verification, the results show that the proposed method achieves a defect detection mAP of 96.72%, which is 6.68% higher than YOLOX. Especially, it significantly improves the detection ability for incomplete fusion and incomplete penetration, enhancing the application ability of AI technology in non-destructive testing.

As a critical component, bearings are difficult to excavate fault features due to the weak or coupled characteristics of multi-state fault features, which brings great challenges to the health monitoring of mechanical equipment. Therefore, a fault diagnosis method based on the sparse resolution of feature atoms is proposed to realize sparse feature resolution and diagnosis of multi-state faults. First, a feature atom filter construction method is proposed. The wavelet basis atoms are extracted based on the maximum kurtosis criterion of the reconstructed sub-band of the tunable Q-factor wavelet transform. The basis atoms are given periodic a priori features to match the multi-state fault components in the signal. Secondly, a multi-channel convolutional sparse multi-state fault feature resolution model is constructed. The sparse coefficient components are resolved based on convolutional sparse coding with multiple feature atoms and alternating direction multiplier method optimization. Reconstruct each fault feature component to realize the sparse resolution of multi-state fault components. Meanwhile, a sparsity parameterization method based on the combination of sparse signal kurtosis and energy is proposed. Finally, the results of the envelope spectrum analysis of the reconstructed components are used to determine the feature components in the signal for multi-state fault diagnosis.. The proposed method is experimentally verified through simulations, experiments and industrial pump signals, and has the advantage of better sparse resolution compared to the convolutional dictionary learning method.

Aiming at the current measurement requirements of high temperature H-beam section size, a high temperature H-beam section size measurement system composed of multi-camera and linear laser sensors is designed and built. The system consists of four laser triangle model subsystems. The subsystems measure the size of the steel in the corresponding direction and splicing method is adopted to realize the measurement of the section size of the steel. Zhang’s calibration method and plane fitting method are used to calibrate the subsystem respectively, and the calibration accuracy is evaluated by the gauge block. The experimental results show that the accuracy can reach ±0.05 mm. Aiming at the problem of unevenness and disconnection of light stripe caused by oxide scale and other impurities on the surface of high temperature H-beam, a light stripe center extraction algorithm based on local regression analysis and quadratic fitting correction and a visual measurement method of H-beam section size based on analog caliper measurement are proposed. The experimental results show that the accuracy of high temperature H-beam measurement can reach ±0.5 mm, and the average processing time of each image is 0.24 s, which provides size data support for the closed-loop control in the production process of hot rolled H-beam.

In recent years, automated detection and identification of defects in carbon fiber reinforced polymer (CFRP) composites has emerged as a hot topic in the field of nondestructive testing. However, insufficient defect data of CFRP components might result in overfitting and low defect recognition accuracy. Therefore, an eddy current testing approach for CFRP defects using improved migration learning is proposed. Firstly, the methods of eddy current C-scan imaging and complex plane signal feature extraction are used to obtain CFRP defect samples and implement data enhancement, which solves the problem of insufficient samples. The MobileNet V2 network with K-means clustering is then used to pick out source domain images with similar features in the hot rolled strip surface defect data set for pre-training, to complete the extraction of similar features in the target domain and reduce the negative migration. Finally, the convolutional attention module is integrated into the feature extraction network to reduce the influence of background feature information in the feature map. The network weights trained on the source domain are transferred to the improved Faster R-CNN object detection model through model transfer, to establish a CFRP defect detection model. Through comparison tests, the method efficiently overcomes the problem of less defect data for CFRP components while maintaining high accuracy and robustness. The constructed CFRP defect detection model achieves high-precision recognition of three types of defects, namely, crack, delamination, and wrinkle. The mean average precision reaches 94.62%, which is 29.31% and 2.79% higher than that of the traditional training method and the original network migration learning detection accuracy, respectively. The recognition accuracy of wrinkle defects in particular is significantly improved, which achieves a better result and meets the requirements for CFRP defect detection.

To address the challenges encountered in measuring very small liquid flow rates(≤1mL/h), a novel method for the online measurement of minuscule liquid flow rates is proposed. The method involves the analysis of visual information to determine the rate of change in the morphological dimensions of droplets at the pipe outlet under conditions of extremely low flow, where the liquid is in a dripping state. This rate of change is then used to investigate the relationship between these measurements and the velocity of the liquid within the pipe. To address the measurement errors resulting from minute droplet oscillations and non-axial symmetry at extremely low flow rates, a hexagonal prism cavity has been developed. Combined with three groups of visual acquisition units and a synchronous trigger controller, the multi-angle synchronous acquisition of dynamic volume visual information data of suspended droplets can be realised. The verification of multi-parameter symmetry is proposed, along with an optimised droplet volume measurement algorithm based on multi-angle acquisition, to further enhance the precision of system measurements. The experimental outcomes demonstrate that the droplets produced by the system exhibit good axial symmetry even at very low flow rates. The multi-view droplet volume measurement optimization algorithm improves accuracy by 2.39% over single-view methods and reduces repeatability by 0.357%. Both measurement precision and repeatability are sustained at high levels across a flow rate range of 0.8 to 60 mL /h. Through extensive experimental verification, this method for measuring very low liquid flow rates is proved to be efficient, convenient, and highly accurate, offering significant potential for application and providing a referential approach for the measurement of ultra-low flow rate rates.

In response to the problem of a reduction in magnetic induction intensity when a traditional permanent magnet electromagnetic acoustic transducer (EMAT) is used in high-temperature detection, the EMAT probes with water-cooled devices are bulky and unable to detect in narrow areas, and magnets easily adsorbing ferromagnetic particles, resulting in a decrease in conversion efficiency, A coil-only EMAT technique, its detection circuit and modeling method are proposed. Taking the coil-only spiral coil EMAT as an example, the coil-only EMAT detection circuit was constructed, and a field-circuit coupled finite element model analysis was conducted on the high-temperature detection process. The influence of temperature on circuit characteristics, excitation efficiency, ultrasonic propagation characteristics, and reception efficiency of the coil-only EMAT was studied. The results show that the factors that affect the amplitude of high-temperature detection echoes are ranked in order of contribution ratio：medium attenuation, excitation efficiency, reception efficiency, diffusion attenuation, and unit-force-excited ultrasonic displacement amplitude. The developed coil only EMAT detection system can achieve continuous detection of 450 ℃ high-temperature aluminum alloy samples, and the signal-to-noise ratio of the secondary bottom wave is not less than 16.86 dB.

As a low-energy, sustainable green manufacturing technology, wire arc additive manufacturing (WAAM) technology is very suitable for low-cost and high-efficiency manufacturing of large and complex components. However, the manufacturing requirements of complex structures and high-performance components pose great challenges to the WAAM equipment system. At present, the forming accuracy, quality and stability of the WAAM equipment system limit its further development and application. The technical principles of WAAM are expounded. The development status of WAAM equipment system is summarized from the aspects of mechanism freedom, forming precision and quality, forming efficiency and heat input control. Combined with the application examples of WAAM technology in the industrial manufacturing, its broad application prospects are discussed. Finally, the future development direction of this field is prospected. By summarizing the equipment systems and applications, the aim is to promote further industrial applications of WAAM.

Brazed structures are widely used in petrochemical, nuclear power, aerospace and other process equipment fields. However, under the harsh environment such as high temperature and high pressure, the difference in mechanical properties between brazing filler metal and base material can easily lead to cracks in the joints, which can cause structural damage. In order to find a high-temperature life extension method for aero-engine recuperator, a finite element method based on continuous damage mechanics was used to systematically analyze the effects of uniaxial and multiaxial creep properties of BNi-2 fillers containing various copper content on the creep life of brazed joints. The results show that the uniaxial creep life of copper-containing nickel-based fillers is well predicted based on the modified Liu-Murakami intrinsic model. The ductility decreases slightly with the addition of 3% Cu elements, and the creep life of filler metals with more than 6% Cu elements decreases, but the creep fracture strain increases. Under the same load level, when the minimum creep rate mismatch between filler metals and base material is reduced by 5% and 10% respectively, the creep fracture time of the recuperator will be increased by 3.2 times and 11.8 times respectively. Based on the filler metal’s modification design with multi-axial creep performance, the joint creep life increases with the decrease of filler metal’s multi-axial creep performance parameter α. When considering the minimum creep rate and the multi-axial creep performance parameter α, the brazing material change should be devised with the purpose of lowering both. The proposed method of significantly extending the service life of aircraft engine regenerators by adjusting the creep mismatch between the braze filler metal and the base metal may provide an innovative scheme for the service life design of high temperature brazed structures.

In order to solve the problem that buckling distortion induced by welding of thin plates structures was difficult to be perfectly corrected after welding, induction heating during welding process was proposed to control it and the effect of processing parameters was investigated. Conventional welding (CW) and induction heating during welding process were performed on butt welded joints with thin plates. The temperature histories in the additional induction heating region were measured by K-type thermocouple, while the deformation profile was obtained by a coordinate measuring machine after cooling down. The butt welded joints showed saddle shape, but the distortion under induction heating during welding process was less than that of CW. Then, a solid elements model of butt welded joint was established, which was used to conduct thermal elastic plastic (TEP) FE analysis considering material nonlinearity and geometric nonlinearity. The computed temperature histories and welding distortions were in good agreement with the measured results of CW and induction heating during welding process, so that the accuracy of TEP FE analysis was validated. Finally, the influence of the size and number for additional induction heating region on control effect of buckling distortion induced by welding was studied with the validated TEP FE analysis. The results showed that better control effect can be obtained by increasing the size and number of additional induction heating region. The optimized process parameters of induction heating during welding process can reduced out-of-plane displacement by more than 90%. The thermal stretching action formed by induction heating during welding process significantly decreased residual compressive stress in base material region and improved the stability of welded structures, so as to control or even eliminate buckling distortion induced by welding.

Based on the thermal-elastic-plastic finite element method (TEP-FEM) and inherent strain theory, the laser welding deformation of curved sandwich structure was calculated with ABAQUS general finite element simulation platform. Firstly, for the curved laser welding T-joint, the welding deformation was simulated based on the TEP-FEM considering material nonlinearity, geometric nonlinearity and contact nonlinearity, and compared with the test results to verify the prediction accuracy of the heat source and material model was higher than 95%. Then, influence of different constraint conditions on welding deformation was investigated, and the calculation results of TEP-FEM and inherent strain method were compared to guarantee the reliability of the prediction results of welding deformation by inherent strain method. Finally, based on the inherent strain method, influence of welding sequence on the welding deformation of the curved sandwich structure was investigated. Results showed that by using the welding sequence of middle welds before side welds, the distance change of panels of the curved sandwich structure could be effectively controlled within 0.6 mm, which can satisfy the welding requirement of large structures. By considering the effect of different constraint effect in the TEP-FEM, the prediction accuracy of welding deformation can be improved through inherent strain theory for large structures.

Double-pulsed variable polarity TIG welding brings about deep penetration welding of medium-thick aluminum alloy structures by stimulating a keyhole in the weld pool. The dynamic behavior and morphological characteristics of the keyhole have a significant impact on the weld formation. In order to explore the effects of the keyhole on the weld penetration, the dynamic evolution law of the keyhole in various pulse cycles is obtained and analyzed by using high-speed image acquisition technology. A transient numerical model of the welding process is established based on computational fluid dynamics. The dynamic characteristics of the temperature field and flow field of the weld pool and the relationship between keyhole and the weld pool are analyzed by using this model. The research results show that the weld pool exhibits various dynamic behaviors with the pulsating current. The keyhole is formed at the low-frequency pulse peak stage, and causes the welding heat source moving downward and excites a high-speed heat transfer channel in the weld pool, which can improve the heat transfer efficiency of the arc towards weld pool bottom and promote the increase of the weld pool depth. Moreover, there is a mutual promotion relation between the depth of keyhole and weld pool, which further improves the penetration.

The traditional forming limit theory model is not applicable to aluminum alloy sheets with low elongation. In order to accurately predict the forming limit of aluminum alloy sheets, a modified GTN model is established based on the Gurson-Tvergaard-Needlemen (GTN) microscopic damage model, taking into account the effects of sheet anisotropy and pore shear mechanism on damage evolution. A method for predicting the forming limit curve of aluminum alloy sheets from the perspective of microscopic damage is proposed. Taking 6061-T6 aluminum alloy sheet as the research object, the damage parameters of the GTN model are determined using a finite element reverse calibration method combining central composite design, response surface model, and multi-objective genetic algorithm. And write a VUMAT user-defined material subroutine to modify the GTN model, use finite element analysis software ABAQUS to numerically simulate NAKAZIMA punch bulging experiments, and obtain the aluminum alloy forming limit curve. The results indicate that the modified GTN model considering anisotropy and shear behavior has better accuracy and applicability for predicting the forming limit of aluminum alloys, and improves the problem of inaccurate prediction of the original GTN model at the inflection point of the forming limit curve.

Copper-steel composite structures are widely used due to their advantages in both cost and performance. However, there are differences in material physical properties and difficulties in welding. Traditional welding methods using a uniform heat source often lead to significant elemental segregation in the joints and severe softening in the copper side heat-affected zone. A full-domain power modulation laser oscillating welding system is employed to design a non-uniform heat source to meet the different heat requirements of the two materials. Three different power modes were investigated to study their effects on the elements diffusion, microstructure, and properties of Cu/304SS dissimilar joints. The findings revealed that when the power ratio between the copper and steel sides was set at 6:4, the joint exhibited the maximum degree of liquid phase separation, with the solid solution of copper and steel uniformly dispersed in the weld. The joint exhibited the lowest degree of elemental segregation and the least softening. Additionally, it demonstrated a maximum tensile strength of 211 MPa, which was 93 % of the copper base material (226 MPa). It provides a novel approach for the flexible control of energy distribution during the welding process of dissimilar joints between copper and steel.

The traditional hot stamping technique for high-strength aluminum alloys initially forms the geometric structure and obtains the microstructure properties after heat treatment, which has a number of drawbacks, including heat treatment deformation, poor precision, a long process, and low efficiency. A quick, accurate, and effective hot stamping forming process without additional heat treatment is developed：pre-aged hardening forming. Taking 7075 aluminum alloy as the research object, the influence of process parameters on the thermal deformation behavior and formability of pre-aged aluminum alloy sheet is investigated by experiments of uniaxial thermal tensile test and Erichsen test. By using EBSD and TEM to analyze the evolution of microstructure during the process, the evolution law of mechanical properties and strengthening mechanism in the forming process PHF are revealed. The peak flow stress of pre-aged aluminum alloy sheet increases with the increase in treatment temperature and duration, according to the true stress-strain curve, and it shows obvious work hardening phenomena. Pre-aged aluminum alloy sheet has a greater Erichsen test value than O-state aluminum alloy under identical test conditions and is easier to shape, and diminishes as pre-aged temperature and time rise. The larger the deformation, the better the mechanical properties of the formed components will be enhanced. In PHF stamping, the superposition of phase transformation and deformation strengthening allows the produced component to acquire the necessary mechanical characteristics without additional heat treatment.

Magnetic treatment has attracted widespread attention due to its advantages such as low consumption, high efficiency and no pollution. However, the mechanism and interaction between the magnetic properties and internal stress during magnetic treatment are not yet clear, and the correlation between magnetic treatment parameters and stress relaxation remains to further study. Therefore, The influence of magnetic treatment parameters on the dynamic evolution and mechanism of residual stress in silicon steel are revealed through experimental platforms. The gain effect of external tension on stress control effect is explored. The difference in stress control effect and mechanism of magnetic treatment between ferromagnetic and non-ferromagnetic materials under magnetic treatment are analyzed. The results show that the control effect of the residual stress of silicon steel fluctuates sinusoidally with time. The residual stress relief can be effectively driven when the magnetic induction does not reach saturation, but raise when the magnetic induction exceeds saturation. The external tension affected the magnetization state of the material, and a large external tension promoted the dynamic reconstruction of the old and new domain walls, resulting in a gain effect on the stress control effect of magnetic treatment. Magnetic treatment can control the residual stress of non-ferromagnetic materials, but its dominant mechanism is different from ferromagnetic materials. When the superposition of magnetostriction and local stress is greater than the dislocation resistance considering for magnetoplastic effect, the residual stress relaxation can be started. The results provides theoretical basis and technical support for magnetic treatment to control residual stress in ferromagnetic and non-ferromagnetic materials.

Based on the concept of layer-by-layer inversion, a method for determining the quasi-static constitutive parameters of the surface-modified layer of 18CrNiMo7-6 alloy steel after carburising heat treatment is presented. After carburizing, the surface microstructure of the matrix specimen changes and forms a surface-modified layer. The carburised specimen is subjected to chemical corrosion stripping to obtain a round rod specimen with different thicknesses of the surface-modified layer. The stress-strain relationships of matrix and surface-modified layer specimens with different thicknesses were obtained through a servo fatigue testing machine at 25 ℃ and a strain rate of 0.000 5 s^-1. The Johnson-Cook (J-C) constitutive model was applied to describe the quasi-static mechanical properties of 18CrNiMo7-6 alloy steel while at the same time ignoring the influence of strain rate and temperature. The J-C model parameters of the surface-modified layer are determined based on the test data and genetic optimisation algorithm. Results show that after carburizing, the elastic modulus of the specimen does not show any evident difference, but there is a significant increase in the yield strength and tensile strength of the specimen. The surface-modified layer was characterized. The microstructure information of the surface-modified layer was elicited, which showed the physical nature that led to the evident differences in the mechanical properties of the surface-modified layer specimens with different thicknesses. The LS-DYNA finite element software was used to simulate the quasi-static tensile test process of the specimen. The reliability of the obtained parameters was verified. All these results provide an essential reference for numerical simulations in practical engineering applications.

In order to study the interaction between multiple defects on the rail surface, the surface defect(depth h≈450 μm，intersection angle θ≈60° and the diameter of circular surface d≈0.6 mm) were prepared on the rail sample based on the defect preparation apparatus. Rolling contact fatigue damage and microstructure evolution of rail samples with surface defect clusters in different spacing and alignment were studied using the twin-disc wheel/rail rolling-sliding wear testing machine and the ABAQUS finite element simulation software. The results show that compared with the single defect, once the spacing between two defects aligned transversely and longitudinally was less than 3.5 mm(6d) and 1 mm(1.5d) respectively, the two defects would affect each other during the wheel/rail rolling contact process, and the defects would need a longer time to be removed. The material damage area, the area that influenced by contact stress and the remaining crack depth could be increased to 2.5, 4.5 and 1.5 times of the single defect respectively. Meanwhile, once the spacing between transverse and longitudinal defects was greater than 4 mm(6.5d) and 1.5 mm(2.5d) respectively, there was basically no interaction between the two defects. In addition, damage degree of the material around the two defects within the critical distance increased with the increase in the spacing. Research results have a certain reference significance for the field rail maintenance.

Based on a single pantograph, the carbon contact strip of pantograph is optimized into five different models and their flow fields are analyzed. The results show that optimizing the windward and leeward sides of the carbon contact strip into a circular surface can optimize the flow field structure of the panhead area, and the deceleration effect of the airflow through the skateboard is greatly reduced, which reduces the aerodynamic drag of the carbon contact strip area. Only increasing the arc of the leeward side of the carbon contact strip can also optimize the aerodynamic drag of the carbon contact strip area. The aerodynamic drag optimization rate of all four optimized pantograph models reaches more than 12%, and the drag of model Ⅳ reduces 13.84%, and the drag reduction rate of the carbon contact strip reaches 91.82%. Aerodynamic drag reduction design of new high-speed trains can receive references and data support.

Metro vehicles are prone to curve squeal noise in small radius curves. The decreasing friction mechanism between wheel and rail is considered to be one of the possible reasons for curve squeal noise. However, under long-term service conditions, the creep conditions between wheel and rail with different temperatures and humidity are different, and the wheel-rail contact state is significantly affected by environmental factors. The mechanism of the influence of the environment on curve squeal noise needs to be further explored. To explore the influence of the environment on the curve whistle, a theoretical model of subway curve whistle noise considering temperature and humidity changes is established. Based on the analysis of the curve passing behavior of the train, the dominant mode that may cause the curve squealing noise of the wheel is found by using the measured noise data, and the relationship between the axial vibration mode of the wheel that produces the curve squealing and the squealing noise is pointed out. Through the investigation of the annual temperature and humidity changes in Shanghai, the influence of temperature and humidity changes on the lateral vibration of wheels and the curve squeal noise is analyzed, and the causes of the curve squeal noise are discussed. The results show that the descending friction condition between wheel and rail is necessary for transverse self-excited vibration of the wheel. When the lateral vibration velocity of the wheel is close to the creep velocity, the periodic lateral force mutation occurs. The asymmetry of the system's periodic input power causes the system's energy dissipation. The excitation of the axial mode of the wheel is the possible reason for the curve whistling. Compared with high temperature and humidity in summer, low temperature and dry winter are more prone to curve squeal noise, and the squealing noise is sharper. To avoid environmental pollution caused by squealing noise, it is recommended to pay more attention to the maintenance of wheel-rail in winter. The work of this study has a certain reference value for understanding the causes of rail vehicle whining and further suppressing the whining noise.

Aiming at the problem that the driving stability and maneuverability of intelligent vehicles are difficult to be guaranteed simultaneously under extreme working conditions, a dynamic stability domain-based linear parametric varying(LPV/H_∞) lateral-longitudinal stability cooperative control method is proposed. Firstly, a closed dynamic stability domain based on the β-β' phase plane is constructed by combining the bilinear method and the lateral swing angular velocity method, and the dynamic margin is designed to improve the boundary stability control performance under the ultimate working condition; secondly, a lateral-longitudinal cooperative control strategy based on the dynamic stability domain is constructed, and on this basis, the LPV/H_∞ lateral-longitudinal stability cooperative controller is designed to solve the conflict drawback between vehicle stability and maneuverability; finally, a high-speed low Finally, the effectiveness of the lateral-longitudinal stability control method is verified by selecting the high-speed and low attachment double-shift line condition. The experimental results show that the proposed lateral-longitudinal stability cooperative controller has a good control effect under extreme working conditions, enabling the controlled vehicle to quickly regain stability while avoiding transient instability. This approach enhances vehicle stability and actual maneuvering performance. Moreover, the proposed control method exhibits strong robustness to system parameter disturbances, providing theoretical support for active vehicle safety control.

In order to quantitatively analyze the influence of raindrop particle size distribution on aerodynamic performance of high-speed train, a high-speed train outflow field model is established based on Euler method, and the effectiveness of its calculation method is verified. Rainfall models with uniform particle size and non-uniform particle size are established based on Lagrange method. The wind and rain coupling numerical simulation of high-speed trains under different rainfall models, different rainfall intensities and different vehicle speeds is carried out by using the phase coupling calculation method. The results show that the raindrop trajectory of the uniform particle size rainfall model is approximately parallel, while the non-uniform particle size rainfall model is complex and staggered; In both models, the raindrop mass per unit time increases with the increase of rainfall intensity and vehicle speed. When the vehicle speed is constant, the concentration of raindrop on the train surface increases with the increase of rainfall intensity. The concentration distribution of raindrop on the train surface of uniform particle size rainfall model is more concentrated and regular, while the non-uniform particle size rainfall model is more scattered and disorderly; When the vehicle speed is constant, with the increase of rainfall intensity, the positive pressure range at the nose tip of the train increases gradually, and the aerodynamic drag force and longitudinal rain load of the train increase; Under the same vehicle speed and rainfall intensity, compared with the calculation results of uniform particle size rainfall model, the positive pressure range at the nose tip of the head train under the non-uniform particle size rainfall model decreases, which leads to the reduction of aerodynamic drag force of the head train under the non-uniform particle size rainfall model, but the longitudinal rain load of the head train under the non-uniform particle size rainfall model increases. To sum up, the longitudinal total drag force of the head train under the non-uniform particle size rainfall model is lower than that under the uniform particle size rainfall model.

Due to the interference of wheel-rail excitation and complex vibration transmission path, the weak fault features of axle box bearings are easily drowned by strong background noise and are difficult to be extracted effectively. Therefore, the vibration response characteristics of axle-box under wheel-rail excitation and the fault diagnosis method are studied based on a high-speed train’s single-axle roller vibration rig. Firstly, the vertical vibration response data of axle-box under the condition of bearing health state, tread damage, and bearing with outer race fault are collected by carrying out the high-frequency excitation experiment with the speed level in the range of 50-300 km/h, and the characteristics of the time-domain waveform, Fourier spectrum, and envelope spectrum are compared and analyzed. The results show that with the increase of the speed, the background noise of the system is gradually enhanced, and the fault characteristics of the axle-box bearing are gradually submerged. However, the tread damage will provoke periodic transient impacts, which have obvious sparsity in the frequency-domain and are characterized as harmonic clusters spaced by frequency rotation, which further aggravate the difficulty of bearing fault feature extraction. Then, on this basis, a method combining cepstrum prewhitening(CPW) and fast median kurtogram(FMK) is proposed to identify the optimal resonance parameters of axle-box bearing fault signals. The effect of random impact and periodic impact induced by tread damage can be avoided simultaneously. Finally, the effectiveness of the proposed method is verified by experimental signals.

The long-wavelength of 250-600 mm has been observed on a straight line of steel spring floating slab track in a metro of china. The operation speed is approximately 60 km/h and the corrugation-passing frequency is 28-67 Hz. A test was performed with an impact hammer to identify the actual vibration response of the floating slab track. A rigid-flexible metro vehicle and floating slab track dynamic model is established, in which the car body is considered as a rigid body, the rail is simulated by Timoshenko beam, the slab and lining are simulated by three-dimensional solid elements, and the shear force dowels are simulated by beam elements. This dynamic model is used to study the correlation between the vibration response of track, the creep characteristic of wheel-rail, the wheel-rail force and the corrugation. The three-dimensional finite element model of unsprung and floating slab track is established, which is used to analyze the formation mechanism of corrugation combined with the vehicle-track dynamic model. Numerical results show that the long-wavelength corrugation at the weld joint belongs to P2 resonance corrugation, and its formation mechanism is the vibration of the unsprung mass and the rail as whole relative to the floating slab. The lateral and torsional vibration of the rail relative to the floating slab, the fluctuation of wheel-rail normal force and the wheel-rail lateral creepage are also important factors for the formation and evolution of corrugation.

An energy coordination control strategy with layered constraints is proposed for the problem of poor dynamic characteristics of mild hybrid electric vehicles under transient conditions. The dynamic model of the power system is established, the coupling constraints of the power system are obtained by simulating the vehicle acceleration process, the key factor restricting the dynamic characteristics of the vehicle is obtained through the simulation analysis of the turbocharging system. Then, an energy coordination control strategy with Layered constraints is proposed. The bottom layer constrains the generator torque by the theoretical maximum load torque of the engine at the smoke limit oil, and the top layer constrains the motor power by the power supply capacity of the system. The effectiveness of the proposed strategy is verified by simulation. The results show that compared with the traditional strategy, the proposed strategy can effectively coordinate the loading process of the engine-generator set, greatly shorten the response time of the engine-generator set from idle speed to rated power, significantly improve the acceleration performance of the vehicle, and provide a new technical approach for optimizing the dynamic characteristics of series mild hybrid electric vehicles.

According to the change of Gibbs free energy as the fatigue crack initiation criterion, the fatigue crack initiation life prediction model of defective axle steel is established. The deformation mechanism of crack initiation of EA4T axle steel was explored by fatigue test, and the finite element crystal model of external defect axle was constructed based on the theoretical framework of crystal plasticity. The energy efficiency factor f of the crystal model was obtained by fatigue test and finite element simulation. From the microscopic point of view, the stress field and structural deformation near the axle defects are analyzed to explore the influence of external defects on the crack initiation life of the axle. The plastic strain energy density and life prediction of two kinds of defective axle models, ring scratch and diamond, are carried out. The results show that the high stress concentration range of annular scratch defect is wider, the damage range of material structure is larger, and fatigue failureis more likely to occur. The crack initiation life of annular scratch defects is lower than that of diamond defects, and the defect area is larger, which has a more severe effect on the crack initiation life.

The many advantages of composite materials are crucial for the development of high-performance hydraulic machinery. In the paper, the schlieren image of the collapse process of a single cavitation near the composite boundaries of three thicknesses is observed and analyzed by combining high-speed schlieren observation technology and image processing technology. The evolution process of the shock wave of single cavitation collapse and the surrounding flow field structure is also discussed. Furthermore, the paper utilizes a hydrophone pressure signal measurement system to monitor the pressure fluctuation process in the bubble flow field and extracts spectral characteristics. The study shows that the thickness of the composite material boundary significantly affects the evolution process of the bubble collapse, the pressure of the shock wave, and its frequency-time characteristics. When γ = 1.0, the study found that there are significant differences in the bubble collapse process and pressure at the boundaries of the three types of composite materials. The main stages include expansion, contraction, and rebound when the bubble collapses. During bubble expanding, the cross-sectional diameter ratio d^* of the bubbles varies differently as a function of the dimensionless distance γ from the different thickness boundaries. During the contraction phase, the bubble divided-collapses at the δ = 0.5 mm boundary and generates high-speed jets at the δ = 1.0 mm and 2.0 mm boundaries. During the rebound phase, the bubble collapses to produce a double-ring shockwave near the δ = 0.5 mm boundary, while only a single-ring shockwave occurs near the δ = 1.0 mm and 2.0 mm boundaries. At the δ = 0.5 mm boundary, three pressure peaks can be detected during collapse, whereas only two pressure peaks are observed at the δ = 1.0 mm and 2.0 mm boundaries. As γ increases, the intensity of the frequency components in the pressure signal gradually increases, and the influence on the bubble collapse decreases with decreasing boundary thickness.

Under extremely small space, the pressure control performance of the hydraulic system can be improved by using a two-stage relief valve with a balanced piston pilot valve. In order to address the absence of a transfer function model for an integrated two-stage relief valve in the aerospace industry, the fundamental equation of a two-stage relief valve with a balanced piston pilot valve is established. The balancing piston separates a chamber in front of the pilot poppet, which is coupled with the pilot poppet to form a mass-spring vibration system with high resonant frequency. Additionally, an annular clearance is formed between the balancing piston and the pilot valve body, which is equivalent to an energy storage element, and its break frequency will decrease with the decrease of the clearance. When the break-frequency of the energy storage element is much lower than the natural frequency of the pilot valve mass-spring vibration system, the stability of the pilot valve will be guaranteed, thus improving the stability of the whole valve. The design requirement for the balanced piston is determined by the correlation between the annular clearance value and the stability of the relief valve. Finally, the correctness of the theoretical analysis is verified by experiments.

Friction torque model is an essential prerequisite for the rotor dynamic analysis and performance evaluation of hydraulic transformer. However, an accurate friction torque model within the full speed range is currently lacking. Based on the Stribeck friction model, the friction states of each friction pair are analyzed. The friction coefficient for boundary lubrication, mixed lubrication, and fluid lubrication are solved successively. According to the continuous condition of the friction coefficient, the calculation method of the transition points between lubrication states is given, and the general friction coefficient model for each friction pair is established. Based on the general friction coefficient model, the friction parameters of the slipper pair and the flow distribution pair are determined, the friction coefficients are solved, and the calculation method of the friction torque is given. The stirring torque of the free rotor is calculated, and the friction torque model of the free rotor in the full speed range is established. A platform on friction torque of the free rotor is built, and the test is carried out to verify the correctness of the theoretical model. The friction torque model provides a good basis for the dynamic analysis and accurate control of the hydraulic transformer.

In order to enhance the efficiency of multi-site assembly operation for non-standard automated production line integrators, the characteristics of assembly process control are analysed, and this process is abstracted as a distributed multi-site assembly project scheduling problem. A state-information-model-enabled rolling scheduling mechanism is proposed to deal with the uncertainties in practice, and a multi-objective constraints programming model with variable constraints is established. To verify the effectiveness of the rolling scheduling mechanism, common features are extracted from the projects of background enterprises. After that, the instance generator and simulator have been developed to conduct quasi-realistic simulation experiments. Experimental results demonstrate the effectiveness of rolling scheduling in coping with progressive deterministic disturbances and improving assembly efficiency. Finally, an extended simulation instance is designed from the perspective of the supply chain, the results show that the integrator should focus on its own business scope and pay attention to the material supply capacity of suppliers, avoiding centralized launch of projects.

High speed on/off valve(HSV) is the core control component of digital hydraulic system(DHS). Dynamic characteristic is not only an important index to evaluate the performance of HSV, but also the key to ensure the control accuracy of DHS. However, due to the compact structure and small size of the HSV, traditional displacement detection method is hardly to directly measure its dynamic performance, which makes the accurate evaluation for the dynamic performance of the HSV a huge challenge in the field of digital hydraulics. The detection method for the dynamic performance of HSV based on vibration characteristic is proposed, the valve vibration model during the dynamic opening and closing process is established, the vibration law of the valve body is revealed, and the relationship between valve body vibration and switching status of HSV is studied, and the real-time measurement for the dynamic performance of the HSV is finally realized. In order to reflect the superiority of the vibration-based detection method for the dynamic characteristic of HSV, the HSV driven by three-voltage and four-voltage methods is tested, and the laser displacement sensor method is used to verify the results. The experimental results show that the measurement approach can accurately obtain the dynamic opening and closing time of the HSV without changing the internal structure of the HSV and without destroying its original dynamic characteristic. Compared with the existing testing methods, the vibration test method has the advantages of strong reliability, real time performance and economic benefits.

Starting from the foundation, paper studies the internal flow field of special high viscosity pump by using computational fluid dynamics method. Based on the flow field data, the influence of the dynamic viscosity of the conveying medium on the pump performance parameters is emphatically studied. In order to improve the accuracy of the simulation, the turbulent RNG κ-ε is modified according to the characteristics of the internal flow field of the gear pump Model, combined with cavitation model, the flow field analysis equations are established. According to the calculated data of pressure field and velocity field in the pump, the influence of medium viscosity on performance parameters is analyzed. The increase of the medium viscosity leads to the decrease of the inlet pressure and the increase of the outlet pressure of the special pump. The laminar flow characteristics of the flow are obvious. The outlet flow pulsation of the pump is stable, and the pulsation amplitude increases with the increase of the medium viscosity. When the medium viscosity and the number of teeth of the special gear pump are considered at the same time, it can be seen that when the medium viscosity is in the medium viscosity section, the performance of the special pump is better when the number of teeth is 14. According to the simulation results, a 14 tooth high viscosity pump is designed and manufactured, and three different viscosity media are used to test. The results are in good agreement with the numerical results. The results of the paper will lay a theoretical foundation for the optimal design of high-end viscosity pump gears.