Taking cast iron material of cylinder head as the research object, a series of thermo-mechanical fatigue experiments under different temperature ranges were conducted through bulk sampling. The results show that the fatigue test of cast iron materials exhibits three stages: cyclic softening, cyclic stability and rapid failure. Additionally, the fatigue life of materials under inverse phase loading is significantly shorter than that under positive phase loading. Six typical supervised learning models, including artificial neural networks (ANN) and random forest (RF), were used to predict the fatigue life of the experimental data. However, the results indicate that these models failed to learn the fatigue life distribution trend of the materials. For this problem, the prediction of the thermal mechanical fatigue life of cast iron materials for cylinder heads was achieved by using the self-supervised algorithm based on the generative adversarial network (GAN), and it showed a good prediction effect under the condition of small samples. This research has strong guiding significance and reference value for cylinder head design and fatigue analysis.

Sandwich structures are widely used in aerospace, national defense and other fields due to their lightweight and energy-absorbing properties, and it is of great significance to improve their anti-explosion performance under internal explosion loads.Three structures were designed, including ring sandwich tube (R), polyurethane foam sandwich tube (F), and ring-polyurethane foam hybrid sandwich tube (RF), with the non-filled sandwich tube (A) as the control group. Through internal explosion load tests and finite element simulations, the deformation modes and energy absorption capacities of the four structures under different explosive amounts were compared and analyzed, and the influence of foam filling methods on the mechanical properties of sandwich tubes was explored.The results showed that, compared with the control group, the non-dimensional deflection of structures F, R and RF was reduced to varying degrees under TNT equivalents of 24 g, 36 g and 48 g.At a TNT equivalent of 48 g, the specific energy absorption of RF structure was 5% higher than that of R structure, exhibiting the best anti-explosion performance. In addition, when the TNT equivalent was greater than 37.39 g, the foam-filled ring structure (FR) showed the strongest deformation resistance; when it was less than this value, the foam-filled structure in the gap between the ring and the tube wall (RF) had the optimal anti-explosion performance.

Under the background of automotive lightweighting, the use of resistance spot welding to achieve effective connection of aluminum to steel structures is an unremitting pursuit. However, in actual welding production, fluctuation of working conditions occur frequently, seriously affecting the quality of weld points. Firstly, the resistance spot welding process was adopted to connect aluminum alloy and low-carbon steel plates. The influences of different inclination angles, plate gaps,and fluctuations in cooling water flow conditions on the resistance spot welding of aluminum-steel were investigated. Then,the quality of the weld points was evaluated by comparing the diameter and thickness of the nugget, the thickness of the intermetallic compound, the coach peel performance, as well as the fracture mode. The research results show that an increase in the inclination angle and the gap between the plates within a certain range, as well as a decrease in the cooling water flow within a certain range, will both reduce the quality of the weld points. Therefore, they should be avoided as much as possible in actual production. The results of this study provide a theoretical basis and practical guidance for optimizing the resistance spot welding process of aluminum to steel.

In order to improve the comprehensive mechanical properties of 960 MPa high strength steel weld metal, the optimum content of Ti element in 960 MPa high strength steel weld metal was revealed. Firstly, four kinds of weld metals with different Ti contents (0.01%-0.08%) were designed and welded. The effects of Ti content on the microstructure and mechanical properties of welds were systematically studied by scanning electron microscopy, energy dispersive spectroscopy, tensile and impact tests. The effect of Ti content on the initiation energy and propagation energy was evaluated by fracture observation and fracture morphology. The results show that when the Ti content is less than 0.06%, the microstructure of the weld metal changes from granular bainite to granular bainite + acicular ferrite. With the increase of Ti content, the content of acicular ferrite increases significantly. When the Ti content reaches 0.06%, the tensile strength reaches 939 MPa, the elongation reaches 23.5%, the elongation increases by 27% compared with Ti0.01, and the impact absorption energy at -40 ℃ reaches 104 J;when the Ti content increases to 0.08%, the formation of coarse lath bainite and the precipitation of TiN lead to a sharp decrease in plasticity and toughness, the elongation decreases to 18.2%, and the impact energy at -40 ℃ is only 25 J. Ti promotes the nucleation of acicular ferrite and improves the comprehensive mechanical properties by forming TiO₂ inclusions.However, excessive Ti will induce the precipitation of brittle phase and the formation of coarse lath bainite, which significantly deteriorates the plasticity and toughness.

To address the issue of characterizing static and dynamic mechanical behaviors of the surface-modified layer (SML) in 18CrNiMo7-6 alloy steel, a layered inversion method for the Johnson-Cook (J-C) constitutive model of SML was proposed. The SML was subjected to layered processing, and dynamic compression tests were conducted on cylindrical specimens with different SML thicknesses. Through progressive parameter inversion, the strain rate sensitivity coefficient C at each depth of the SML was determined. Combined with quasi-static thin plate tensile tests at different temperatures for each depth of the SML, the corresponding yield strength A, strain hardening coefficient B, strain hardening index n, and thermal softening exponent m were determined. Test results show that the SML of 18CrNiMo7-6 alloy steel exhibits significant strain hardening, strain rate strengthening, and temperature softening effects. Additionally, a correlation model between J-C constitutive parameters and dimensionless depth h/h_b (distance to SML surface/SML effective depth) was established,providing support for subsequent composite strengthening simulations.

The challenge in predicting the remaining useful life (RUL) of multi-mode stochastic degradation equipment lies in establishing a class of stochastic degradation models capable of characterizing multiple distinct degradation modes and deriving the remaining useful life distribution of the equipment under such multi-mode stochastic degradation models.First, a generalized stochastic degradation model based on the nonlinear Wiener process was developed, achieving a unified characterization of multi-mode stochastic degradation processes. Second, a maximum likelihood estimation (MLE) method for model parameters was proposed, utilizing historical degradation data from similar equipment. Third, an analytical approximate solution for the probability density function (PDF) of the remaining useful life distribution of multi-mode stochastic degradation equipment was derived under the first hitting time (FHT) framework. Finally, a sequential Bayesian framework for model parameter updating was constructed, enabling online prediction of the remaining useful life of in-service equipment.Numerical simulation analyses and an application case study on bearing remaining useful life prediction demonstrate that the proposed method can effectively model the multi-mode stochastic degradation processes of stochastic degradation equipment and accurately predict the remaining useful life, thereby providing predictive information to support subsequent maintenance decision-making for the system.

Bearings, as critical rotating components in precision instruments, directly affect the safety and stability of the system. Therefore, accurate prediction of their remaining useful life (RUL) is crucial. Existing RUL prediction methods for bearings can be classified into two types: physical model-based and data-driven approaches. Physical models offer high interpretability and require fewer samples but suffer from low prediction accuracy and cannot be used for online prediction.Data-driven methods, on the other hand, provide higher accuracy and support online prediction but require large amounts of data and have poor generalization ability under varying operating conditions or between different equipment. To address these limitations, a Wiener-ANN hybrid model is proposed for bearing RUL prediction, combining the advantages of both physical models and data-driven approaches. The model optimizes the Wiener process using time-frequency domain features as multi-source input data for the first-stage prediction. Subsequently, a three-layer artificial neural network (ANN) is trained using the first-stage prediction results to optimize the model. The optimized Wiener model is then combined with the ANN to predict the RUL of the test dataset. Comparisons with traditional Wiener models and ANN methods show that the proposed approach significantly outperforms these methods in prediction accuracy and application performance, demonstrating strong potential for engineering applications.

In response to the problems of reduced surface quality and severe twist drill wear in HR-2 hydrogen resistant steel deep small holes drilling, integrated thermal coupling finite element simulation with experimental investigations of deep small holes drilling to analyze the variations in tool wear, drilling temperature, and the quality of the machined surface during the process of machining deep small holes. The improvement effect of introducing ultrasonic vibration on poor surface quality and severe tool drilling wear was analyzed by comparing ultrasonic vibration assisted drilling (UVAD) and conventional drilling (CD). The results show that as the drilling depth increases, the heat accumulation of the tool's transverse and cutting edges significantly increases, gradually leading to problems such as coating peeling, edge passivation and chipping.Concurrently, the accumulation of cutting heat on the surface of the machined hole causes temperature rise, resulting in material coating, debris adhesion, oblique scratching and other problems on the machined surface, resulting in a deterioration of surface quality and an elevation in surface roughness. Compared to CD, the UVAD effectively reduces drilling temperature,helps to reduce tool wear and maintain cutting edge integrity, while suppressing the increase in surface roughness during machining, ultimately improving surface quality.

Different parts of high-speed train bogies are usually designed with aluminum alloy materials of varying strengths, and welding is adopted to connect these different parts. When high-speed trains operate under complex road conditions, the bogies will be subjected to tensile overload, which will produce a coupled superposition effect with the strength difference of welded joints. Therefore, tensile overload tests were carried out on the welded structural components of bogies to study the fatigue crack growth behavior and intrinsic mechanism of aluminum alloy welded joints with different strengths under the action of tensile overload. The compliance method was used to measure the crack growth rate under tensile overload;the digital image correlation (DIC) technology was applied to analyze the change in the size of the plastic zone at the crack tip before and after the application of tensile overload; the scanning electron microscope (SEM) was employed to observe the fracture morphology characteristics of different aluminum alloys in the region affected by tensile overload. The crack growth behavior and intrinsic mechanism under tensile overload were explained based on the change in the size of the plastic zone at the crack tip and the corresponding fracture morphology characteristics. The results show that a single tensile overload can reduce the fatigue crack growth rate and extend the fatigue life. Further analysis indicates that during the tensile overload process, the plastic zone at the crack tip expands and the crack tip is blunted, which together lead to the reduction of the fatigue crack growth rate. The lower the material strength, the more severe the deformation at the crack tip and the more obvious the hysteresis effect under the same tensile overload. The test results of welded joints under tensile overload are consistent with those of the base metal, suggesting that the strength of the hysteresis effect depends only on the inherent strength of the material itself.

To address the insufficient stability of high-altitude line inspection robots under wind loads, this study proposes optimization strategies involving a novel elastic pressing mechanism and an improved wheel groove, which can effectively enhance their walking stability. A power transmission and distribution line inspection robot with dual-mode switching (flight and walking) capabilities was developed. Firstly, a dynamic model of the robot under wind loads was established, and the relationship between the swing decay time and clamping force, contact area, and friction coefficient was derived. Secondly,dynamic simulations were conducted to verify the performance advantages of the two optimization strategies in suppressing swings. Finally, outdoor wind swing tests were performed to validate the effect of structural improvements. The results show that the elastic pressing mechanism can effectively increase the contact area between the pressing wheel and the line, and the improved wheel groove can enhance the friction coefficient of the walking wheel; both significantly shorten the robot's swing decay time and improve its inspection stability in wind load disturbance environments. The effective technical support and engineering practice basis for the stable operation of high-altitude line inspection robots in complex environments were provided.