As a typical self-excited vibration phenomenon in metal cutting processes, chatter leads to deteriorated machining surface quality, manifested by texture fluctuations, increased dimensional errors, and compromised surface integrity. Effective detection and suppression of chatter is crucial for ensuring machining efficiency and enhancing component performance. Current research has established a multi-dimensional technical framework encompassing physics-model-based offline prediction methods, multi-sensor signal-dependent experimental detection schemes, and intelligent algorithm-integrated online monitoring frameworks. However, existing review literature lacks in-depth dissection of this domain. Addressing this gap, this study conducts a systematic technical review and analysis focusing on chatter detection and suppression technologies.For chatter detection, an analytical-experimental dual methodological framework is established, emphasizing the dissection of applicability scenarios and performance boundaries of various techniques. In terms of chatter suppression, a triple control strategy classification system integrating active-passive-parameter adjustment is constructed, comparing implementation costs and vibration attenuation effects of different solutions. Based on multi-dimensional technical comparisons and cross-disciplinary method integration, existing challenges and potential solutions in this field are explored, providing comprehensive theoretical support and technical references for subsequent research.

Reaction bonded silicon carbide (RB-SiC) is widely used for manufacturing core components in nuclear energy and optics due to its excellent thermal stability, radiation resistance and chemical inertness. However, RB-SiC is highly hard and brittle, making it difficult to ensure processing quality and efficiency with traditional methods. Ultrasonic diamond wire saw cutting technology, as an efficient machining method for hard brittle materials, has been successfully applied in the processing of single crystal Si, single crystal SiC, and other hard brittle materials. However, the cutting test and process research of this technology in RB-SiC materials need to be carried out. To this end, the ultrasonic sawing test of RB-SiC was carried out for the first time. The ultrasonic wire saw cutting RB-SiC platform was built. The surface quality of parallel and vertical ultrasonic vibration directions was compared and analyzed. The effects of ultrasonic amplitude, line speed and feed speed parameters on surface roughness and surface micro-morphology were studied. Results demonstrate ultrasonic sawing has significant advantages in improving surface quality. Increasing the amplitude from 3 μm to 7 μm reduces surface roughness value by 17.4% and decreases the number of surface scratches and pits. Compared to the vertical feed direction, ultrasonic vibration sawing in the parallel feed direction is more effective in improving the surface quality of RB-SiC materials. This study can provide guidance for the research of ultrasonic sawing process of RB-SiC materials.

Blind bolted rivets with large flange are widely used as standard fasteners for single-side connection in the aerospace industry, and their minimum tensile load is one of the clearly specified mechanical properties. However, the current method for calculating the tensile strength of blind bolted rivets with large flanges is not yet fully developed. In order to improve the forward design process of blind bolted rivets with large flanges and predict their tensile strength, the failure modes during the tensile process were investigated. First, mechanical analysis reveals three failure modes due to stress concentration:the breakage of the forming sleeve, breakage of the head, and indentation of the nut sleeve. Then, a finite element simulation was used to propose a prediction method for the tensile strength of blind rivet nuts with large flanges, which helps obtain the failure modes and predict the tensile strength. Finally, a hydraulic testing system was used to conduct tensile tests on a specific model of blind bolted rivets with a large flange, the specific failure modes and force-displacement curves are obtained. The accuracy of the proposed prediction method is verified by the test result. This study provides a reference for improving the connection strength of blind bolted rivets with large flanges and enables the prediction of tensile strength in the forward design process.

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.

Addressing the rotational vibration issues encountered during the operation of seawater pumps, and integrating measured vibration characteristics, a quasi-zero stiffness ring meta-structure isolator was designed for vibration control based on the principles of quasi-zero stiffness isolation and the bandgap features of meta-structure. First of all, taking a typical seawater pump as the research object and based on an integrated quasi-zero stiffness structure, a structural design scheme of the ring meta-structure isolator was proposed. Then, models of quasi-zero stiffness unit cell, one-dimensional quasi-zero stiffness meta-structure and quasi-zero structure ring meta-structure isolator were established using finite element method and theoretical method, respectively. Their static and dynamic mechanical characteristics were calculated and analyzed, and their isolation effect on the output vibration of seawater pumps was evaluated. The calculation and test results show that the quasi-zero stiffness ring meta-structure isolator provides multiple bandgaps at low frequencies, and exhibits significant vibration suppression effects on typical frequencies of seawater pumps.

To compensate for the intermittency of renewable energy generation, coal-fired power units are required to operate under low-load conditions over a long time, which causes the last stage blades of steam turbine low-pressure cylinders under small flow conditions persistently, leading to increased dynamic stresses and fatigue damage in the blades. To evaluate the safety of these last-stage blades, the fluid-structure interaction analysis of the last two-stage flow path and last stage rotating blades were conducted for a 660 MW air-cooled steam turbine under typical operating conditions. The results demonstrate that as the load decreases, both the maximum equivalent stress and deformation of the last stage rotating blades gradually diminish first, then slightly increasing. The maximum equivalent stress of the last stage rotating blades remains consistently below the material’s yield strength, indicating that the blades are in the stage of elastic deformation and no plastic deformation has occurred. Using the Goodman curve analysis method for the high-cycle fatigue life assessment of the last stage rotating blades, the dynamic stress levels of the last stage rotating blades fall within the safe zone of the Goodman curve,indicating that there is no risk of fatigue damage to the blades.

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.

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.

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.