High-end Equipment Research Articles

Optimization of microstructure and mechanical properties of 7075 aluminum alloy by equal channel angular pressing technology

Abstract The equal channel angular pressing technology, as an effective technique for modifying the surface of a material, has had a significant impact on the microstructure and mechanical properties of the 7075 aluminum alloy. The study achieved the refinement of 7075 aluminum alloy grains and the homogenization of the second phase particle distribution through equal channel angular pressing technology, thereby significantly improving the strength and plasticity of the material. Through orthogonal experimental design, the effects of extrusion angle, extrusion speed, and remelting temperature on material properties were studied. The results showed that appropriate ECAP parameters could effectively regulate the microstructure of 7075 aluminum alloy, thereby optimizing its mechanical properties. Especially in the analysis of equivalent strain rate, when the extrusion angle was 50°, the position of the maximum equivalent strain rate at the forefront point remained unchanged, but the equivalent strain rate decreased to 0.107-1. In the aging hardness analysis, when the number of equal channel angular pressing passes was 3, the aging hardness of G group 7075 aluminum alloy increased to 195HV in the first 5 minutes. The equal channel angular pressing technology can optimize the internal structure of 7075 aluminum alloy and improve the material's plasticity and mechanical properties. The research provides important technical support for the application of 7075 aluminum alloy in high-end equipment manufacturing.

Measurement of stress optical coefficients for GFRP based on terahertz time-domain spectroscopy

Glass Fiber-Reinforced Polymer (GFRP) finds extensive applications in the high-end equipment manufacturing industry owing to its advantages of light weight, high strength, and corrosion resistance. Since the residual stress in GFRP builds up during the curing process and affect its mechanical properties and service life, the characterization of the residual stress in GFRP is crucial. In this study, we establish a theoretical model based on the anisotropic stress-optics law for the orthorhombic crystalline system to describe the terahertz-elasticity of GFRP and calibrate the stress optical coefficients of GFRP. First, the residual stress in GFRP at different curing temperatures are measured by fiber Bragg grating sensors. Then, the refractive index of GFRP with different residual stress are obtained based on transmission-type THz-TDS. Finally, based on the proposed photoelastic model of GFRP, the stress optical coefficients of GFRP are measured by combining the measurement results of residual stress and refractive index. The experimental results show that the refractive index of GFRP decreases with the increase of residual stress; the stress optical coefficients of GFRP are determined as q11 = −5.612 × 10−9 Pa−1, q12 = −2.548 × 10−9 Pa−1, q21 = −1.305 × 10−8 Pa−1, q22 = −1.408 × 10−9 Pa−1. The modeling of terahertz photoelasticity in GFRP and the determination of stress optical coefficients provide a basis for characterizing residual stress in GFRP by THz-TDS.

Structural digital Twin for damage detection of CFRP composites using meta transfer Learning-based approach

Using deep learning approaches to identify and locate defects in composite structures made of Carbon Fiber Reinforced Plastics (CFRP) is becoming increasingly popular. However, when the training data is limited, the existing deep learning methods do not work well. Moreover, the lack of data for damaged conditions of CFRP structures causes a severe data imbalance, which makes this problem even harder. In this paper, we present a novel damage detection method called DFMTR which stands for Digital Twin based Few-shot Meta Transfer Learning. It creates numerical model as the digital twin to generate a large amount of virtual data under different damage conditions for model training. Then, it applies relational network and domain adaptive techniques to achieve effective few-shot transfer. That means, it can detect damage accurately with only a very small amount of real data. This is very useful and practical for damage detection of high-end CFRP equipment. In experiments, our approach outperforms existing methods in all commonly used metrics. The classification accuracy can be improved to more than 82% from 55% by using only 4 real samples, and the accurate localization of damaged area is also successfully achieved.

A novel cross-receptive field fusion cascade network with adaptive mask update for transfer health state diagnosis of manipulators

Manipulators, particularly planar parallel manipulators, are widely employed in high-end precision equipment to conduct precise positioning and operation tasks due to their advantages of high stiffness, high precision, and high load. Moreover, they are also frequently exposed to changeable working circumstances, which significantly cause inconsistent health state data distribution. Although transfer learning can successfully offset the above distribution discrepancies, it remains unclear how to identify and quantify the source domain knowledge’s contribution to the transfer process. To overcome these challenges, a novel transfer health state diagnosis framework, named cross-receptive field fusion cascade network with adaptive mask update (CFFCN-AMU), is developed and employed for manipulators. Specifically, a unique cross-receptive field fusion cascade module (CFFCM), in which the receptive field self-evaluator and channel attention mechanism are jointly designed, is constructed initially to achieve adaptive extraction and fusion of cascaded features. Subsequently, in the target domain fine-tuning stage, an adaptive mask update (AMU) strategy is implemented to evaluate the contribution of source domain knowledge and selectively guide the parameter updating process. Finally, some mechanistic model-driven cross-working condition transfer scenarios are investigated. Multiple sets of excellent transfer diagnosis results fully illustrate the transferability and superiority of the constructed CFFCN-AMU model.

A novel platform for mutation detection in colorectal cancer using a PNA-LNA molecular switch

Detection of KRAS mutation in colorectal cancer (CRC) is important in the prediction of response to target therapy. The study aims to develop a novel mutation detection platform called the “PNA-LNA molecular switch” for the detection of KRAS mutation in CRC. We employed the enhanced binding specificity of peptide nucleic acid (PNA) and locked nucleic acid (LNA) in conjunction with a loop-mediated isothermal amplification (LAMP) approach to identify the mutation status of KRAS oncogene codon 12 (c.35G>T/G12V and c.35G>A/G12D) using synthetic oligonucleotides and colon cancer cell lines (Caco-2 and SW480). This method specifically blocked the amplification of the wild-type sequences while substantially amplifying the mutated ones, which was visualized by both colorimetric and fluorescence assays. We then checked the mutation profile of KRAS codon 12 in the DNA derived from tumor tissue samples (number of samples, n = 30) and circulating tumor cells (n = 24) from CRC patients. Finally, we validated the results by comparing them with the data obtained from DNA sequencing of colon tumors (n = 21) of the same CRC patients. This method showed excellent sensitivity (1 DNA copy/μl), reproducibility [relative standard deviation (%RSD) < 5%, for n = 3], and linear dynamic range (1 ag/μl-10 pg/μl, R2 = 0.94). This platform is significantly faster, relatively cheaper, has superior sensitivity and specificity, and does not require any high-end equipment. To conclude, this method has the potential to be translated into clinical settings for the detection of mutations in diverse diseases and conditions.

Multi-Directional Strain Measurement in Fiber-Reinforced Plastic Based on Birefringence of Embedded Fiber Bragg Grating.

Embedded fiber Bragg gratings are increasingly applied for in-situ strain measurement in fiber-reinforced plastics, integral to high-end aerospace equipment. Existing research primarily focuses on in-plane strain measurement, limited by the fact that fiber Bragg gratings are mainly sensitive to axial strain. However, out-of-plane strain measurement is equally important for comprehending structural deformation. The birefringence of fiber Bragg gratings shows promise for addressing this problem; yet, the strain transfer relationship between composites and optical fibers, along with the decoupling method for multi-directional strains, remains inadequately explored. This study introduces an innovative method for multi-directional strain measurement in fiber-reinforced plastics using the birefringence of a single-fiber Bragg grating. The strain transfer relationship between composites and embedded optical fibers was derived based on Kollar's analytical model, leading to the development of a multi-directional strain decoupling methodology. This method was experimentally validated on carbon fiber/polyetherimide laminates under thermo-mechanical loading. Its reliability was confirmed by comparing experimental results and finite element simulations. These findings significantly broaden the application scenarios of fiber Bragg gratings, advancing the in-situ measurement technology crucial for the next generation of high-end aerospace equipment.

Multi-modal signal adaptive time-reassigned multisynchrosqueezing transform of mechanism

High-end mechanical equipment often operates under non-stationary conditions, such as varying loads, changing speeds, and transient impacts, which can lead to failures. Time-frequency analysis (TFA) integrates time and frequency parameters, allowing for detailed signal analysis and is widely used in this context. To improve the accuracy of assessing the operational status of mechanical equipment, this paper proposed a multi-modal signal adaptive time reassignment multiple synchrosqueezing transform (MSST) TFA method. This method enhances the MSST method by using a local maximum technique to address energy ambiguity in TFA. Additionally, the optimal window width for each function is determined through iterative processes to better concentrate energy in the TFA. Multi-modal signals are jointly analyzed using an impulse feature extraction method for signal reconstruction, enabling multi-dimensional fault analysis. The proposed method is validated with both simulation and experimental data from a planar parallel mechanism (PPM) and is compared against classical and advanced techniques. The results show that the method effectively captures shock features in multi-modal signals, offering a more consolidated time-frequency representation (TFR) than existing TFA algorithms.

A novel weighted-guided tensor completion missing data imputation method for health monitoring data of planar parallel mechanism

Abstract High-end mechanical equipment plays a crucial role in the manufacturing industry, making the monitoring of its operational status highly significant. Due to various factors such as environmental influences, the absence of monitoring signals in mechanical equipment status is a common issue, leading to a decline in data quality. To ensure data quality, this paper proposes an adaptive weighted low-rank tensor missing data imputation method. Firstly, based on the motion characteristics of a planar parallel mechanism (PPM), a new low-rank tensor model is established using periodicity, sliding windows, and time series. Secondly, the tensor truncation nuclear norm is defined, and a novel rate parameter is introduced to control the truncation degree of all tensor modes, thereby obtaining weights for each dimension. Finally, within the framework of the alternating direction method of multipliers (ADMM), adaptive weights for each dimension are obtained during each iteration, completing the filling of missing data. Two types of missing patterns are studied on a PPM experimental platform, and the results showed that as the missing rate increased, the mean absolute percentage error is less than 0.018, and root mean square error is less than 0.001, and the rate of change is less than 0.08, which was significantly better than other compared algorithms.

Optimizing Oil Distributor Port for Low-Pulsation Cam-Lobe Hydraulic Motors

High-end equipment always operate in low-speed and heavy-load working environments, highlighting the need for cam-lobe hydraulic motors with excellent speed stability (< 1 r/min) and ultrahigh-power rotary output (> 1 MW). The successful operation of cam-lobe hydraulic motors relies on the circulation supply of high- and low-pressure oil. However, the switching between high-/low-pressure oil controlled by the oil distributor inevitably causes an obvious pressure impact and speed pulsation, which directly reduces the speed stability of hydraulic motors. Therefore, an optimization design approach for the oil distributor port is proposed to minimize the speed pulsation of cam-lobe hydraulic motors. In the proposed approach, a simulation model that links the oil distributor port structural parameters with the hydraulic motor speed pulsation was developed to clarify the effect of the oil distributor structural parameters on speed pulsation. Then, an orthogonal analysis method was used to identify the optimized oil distributor port structural parameters while minimizing the hydraulic motor’s speed pulsation as much as possible. Finally, several experiments were conducted to validate the effectiveness and accuracy of the proposed optimization design approach. The experimental results indicate that the pulsation rate of the hydraulic motor equipped with the optimized oil distributor was 62.5% lower than that of the original motor at a working pressure of 25 MPa, which is consistent with the simulation results using the proposed optimization design approach. The findings of this study offer a feasible and effective approach to guide the design optimization of the oil distributor port for low-pulsation hydraulic motors.

Comparative Study on the Performance of Gel Grease for High-End Equipment Based on the Synergistic Effect of Friction-Reducing Agents.

In the field of high-end equipment, the synergistic effect of friction-reducing agents plays an important role in the performance study of gel grease. Exploring its tribological and rheological properties can not only significantly reduce the coefficient of friction of mechanical components and enhance its viscosity at high temperatures but also effectively reduce energy consumption, thus improving the service life of high-end equipment. In this study, Schaeffler Load 460 gel grease was mixed with polysiloxane viscosity modifier (PV611) and molybdenum dialkyl dithiocarbamate (RFM3000) according to (3:1, 1:1, and 1:3), and its tribological properties and rheological properties were investigated by the MRS-10G friction and wear tester, MCR302 rotational rheometer, and crossover test. Comparative analyses of tribological and rheological properties were carried out. The results showed that the average coefficient of friction of Schaeffler Load 460 grease was reduced by 57.2%, 60%, and 71.9%, respectively, with the addition of two different ratios of friction reducers; the average diameter of abrasive spots was reduced by 44.5%, 55.4%, and 61.3%; and the shear stress and viscosity were increased by 117.94 Pa and 1295.02 mPa∙s, respectively, compared with that of the original grease, which is a good example for the lubrication of gel grease in the high-end equipment industry. This study provides a new direction and idea for the lubrication research of gel grease in the high-end equipment industry.

Integrated MADM of low-carbon structural design for high-end equipment based on attribute reduction considering incomplete interval uncertainties

With the increasingly severe energy supply and environmental pressures, high-end equipment is gradually adopted to reduce the carbon emissions of manufacturing industry which makes its low-carbon structural design a critical research hotspot. The best structural scheme can be got by multi-attribute decision-making (MADM) with design requirements. However, the decision-making attributes in the structural design of high-end equipment are too many at first and low-carbon attributes are seldom fully considered. Moreover, there are a large amount of related data with linguistic vagueness, interval uncertainty, and information incompleteness, which fail to be handled simultaneously. There, this paper proposes an integrated MADM method of low-carbon structural design for high-end equipment based on attribute reduction considering incomplete interval uncertainties. First, distribution reduction of low-carbon structural design is carried out to obtain the minimum attribute set and encompass low-carbon attributes comprehensively. Second, a collaborative filtering algorithm is utilized to complete the missing data in the subsequent design process. Third, interval rough numbers (IRNs) are integrated into DEMATEL-ANP (DANP) and multi-attribute border approximation area comparison (MABAC) to quickly rank the alternative schemes for high-end equipment and determine which is the best. The rationality and robustness of the proposed method are verified through the case study and comparative analysis of a hydraulic forming machine.

Phyformer: A degradation physics-informed self-data driven approach to machinery prognostics

Machinery degradation prognostics methods have been suffering the “dilemma” that both physics and data-driven methods have their own limitations. On one hand, constructing accurate close-form mathematical physics models are prohibitively difficult for a complex system. On the other hand, for pure data driven models such as deep learning models, due to the lack of physics guidance, their extrapolation capability decays over time and even yield unexplainable predictions that violate common cognition. Therefore, relaxing the pursuit for the perfect and accurate degradation model, and instead coupling general degradation model with deep learning model, fully leveraging the advantages from both physics-based prognostics and data-driven prognostics, is a promising way to solve the “dilemma”. Driven by this motivation, this paper proposes Phyformer, a general degradation physics-informed self-data-driven method for machinery prognostics. A backbone deep learning model based on auto-correlation and Transformer architecture is developed for time series data prediction. Multiple local physical models that are constructed with data in sliding time windows are embedded into the backbone model in the form of loss function. Only the historical data of the machine itself are used to extrapolate the future, which is significant especially for high-end equipment since their run-to-fail data are scarce. Then the predicted data are mapped to degradation stage by an unsupervised clustering model Gath-Geva adaptively without the requirement of knowing the number of degradation stages in advance. Due to the above nature, Phyformer is high flexibility, easy to be deployed in different applications, working condition-independent and simple. Two typical prognostics tasks are studied, which use direct and indirect condition monitoring data as input, respectively. Comparisons with other state-of-the-art machinery prognostics models show the advances of Phyformer.

Research on Application and Quality Evaluation of Intelligent Teaching Model of AI Three Teachers in the Course of Motion Control Technology

Motion control technology is an important branch of automation, and is one of the important development directions of the emerging industry of high-end equipment manufacturing. As a comprehensive discipline with the intersection of mechanical, electrical and electronic, its teaching mode faces many challenges. There are practical problems that need to be solved, such as teaching content not matching seamlessly with post knowledge and skill literacy requirements, teaching project design is not high in modularity, and teaching evaluation system is not perfect. These problems seriously restrict the cultivation of students' technical practical ability. This project proposes the "intelligent teaching model of AI three teachers for the course of Motion Control Technology", which emphasizes student-centered, builds a core curriculum system that connects with the technology of field engineers in enterprises, and proposes the three-way collaborative teaching and education strategy of "vocational school Teacher + Al Teacher + enterprise tutor" to enable students to participate in learning in an all-round way. And timely access to feedback information, the formation of continuous improvement of the teaching cycle. Optimize the teaching team and teaching mode, improve the teaching quality, meet the diversified learning needs of students, and promote the continuous innovation and development of education and teaching.

Interfacial microstructure of dual-scale SiCp/A356 composites investigated by in situ TEM tensile testing

Silicon carbide particle (SiCp) reinforced Al matrix (SiCp/Al) composites have broad application prospects in high-end equipment manufacturing fields such as aerospace and automotive nowadays. The volume fraction and size of SiCp reinforcement play a decisive role in the physical and mechanical properties of the composites. Herein, we have prepared the dual-scale SiCp/Al composites through the powder metallurgy method. The interfacial microstructure and crystal orientation relationship at the interface was observed and analyzed. And then we have investigated the fracture behavior of the SiCp/Al interface by employing the in situ TEM tensile experiment. The results of the in situ TEM tensile testing show that when there exists a MgAl2O4 interface layer with thickness of 100 nm in the prepared SiC/Al composite, the microcracks are formd preferentially at the MgAl2O4/Al. And the interface bonding strength of the SiC/MgAl2O4 is higher than that of MgAl2O4/Al. Moreover, the microcracks are formed firstly at the sharp corners of micron SiCp and the interface. With the increaing load, the microcracks propagate along the micron SiCp and the interface. With the further increase of the load, connections and mergers will occur between the formed microcracks, which will eventually lead to the breakage of the specimen. Besides, the addition of the dual-scale SiCp can improve the yield strength of the A356 obviously.

Design and mechanical performance analysis of T-BCC lattice structures

The Body-Centered Cubic (BCC) lattice structure is commonly used in high-end equipment fields, such as aerospace, due to its superior mechanical properties, lightweight characteristics, and ease of processing. However, there is a need to improve the performance-to-weight ratio of the traditional BCC lattice structure. This study utilizes topology optimization to design a T-BCC lattice structure based on the BCC unit cell, with the aim of maximizing stiffness. A model proposing the characterization of the Young's modulus of BCC lattice structures is presented. The model is based on calculations of cell porosity and beam stress analysis, assuming a large cell. This approach indirectly enables the calculation of the Young's modulus of T-BCC lattice arrays in multiple dimensions. Simulation and experimental comparison were used to analyze the compressive performance and load-bearing modes of T-BCC lattice structures, revealing the mechanisms of compressive deformation and failure modes. The accuracy of the characterization model for Young's modulus was found to be 93.1%. Compared to BCC lattice structures designed by traditional methods, T-BCC lattice structures designed via topology optimization can increase the Young's modulus by up to 36% and yield strength by 37.2%. This suggests that T-BCC lattice structures are a more lightweight and efficient solution for designing components in high-end equipment fields.

Ultrasonic measurement method for three-dimensional assembly stress of aero-engine rotors

The precise measurement of three-dimensional stress in the rotor is a key means to ensure the assembly accuracy and operational safety of aero-engines. The unclear coupling influence mechanism of different directions of stress on ultrasonic propagation makes it challenging to establish a three-dimensional stress measurement model. This paper proposes a three-dimensional assembly stress measurement method for aero-engine rotors based on ultrasonic propagation time difference decoupling. The three-dimensional assembly stress is converted into the stress component parallel and perpendicular to the ultrasonic wave propagation direction in this method. The acoustoelastic equation including three-dimensional stress parameters is established based on the function model of different direction stress and ultrasonic wave propagation velocity. An innovative three-transducer stress measurement scheme is designed, which integrates ultrasonic wave transmitting and receiving transducers and time difference feedback transducers. The acoustoelastic equations in three propagation directions are constructed by rotating the transducer group to change the propagation direction of ultrasonic waves. Finally, the acoustoelastic equations are solved simultaneously to decouple the ultrasonic propagation time difference, thus achieving a three-dimensional assembly stress measurement of the aero-engine rotor. The experimental results show that the maximum deviation between the measured values and the simulation results in the x ,y, and z directions is 15.885 MPa, 14.113 MPa, and 17.093 MPa, respectively. This study provides effective theoretical and technical support for precisely measuring three-dimensional assembly stress in high-end equipment represented by aero-engines.

An inorganic-organic hybrid CQDs@PVP lubricant additive: Achieving low friction and wear in PEG and water

High-temperature lubrication has always been a hot topic in the lubricant and grease industry, and is also an essential concern in the high-end equipment sector to be addressed. Carbon quantum dots (CQDs) are an emerging material widely applied in the field of lubrication, owing to their exceptional lubricity and high load-bearing capacity. However, the vulnerability of CQDs to oxidation in air and reduced stability dramatically restrict their high-temperature application capability. In this study, a nanocomposite of amphiphilic polyvinyl pyrrolidone (PVP) homopolymer with excellent lubricating properties and thermal stability, which is hydrogen bonded to CQDs (CQDs@PVP), was designed to achieve low friction and wear of lubricants at high temperatures. The CQDs@PVP are consistently dispersed in both PEG400 and water, and exhibit superior lubricity compared to unmodified CQDs at high temperatures (ranging from 200–150 °C and 90.50 °C). Meanwhile, the dense carbon film on the wear surface and the chemically reactive film of iron compounds directly contribute to the enhanced lubrication performance. These analytical results demonstrate the powerful candidacy of CQDs@PVP as a lubrication additive and promote future high-temperature applications of CQDs in industrial production.

Small-size temperature/high-pressure integrated sensor via flip-chip method

Hydraulic technology with smaller sizes and higher reliability trends, including fault prediction and intelligent control, requires high-performance temperature and pressure-integrated sensors. Current designs rely on planar wafer- or chip-level integration, which is limited by pressure range, chip size, and low reliability. We propose a small-size temperature/high-pressure integrated sensor via the flip-chip technique. The pressure and temperature units are arranged vertically, and the sensing signals of the two units are integrated into one plane through silicon vias and gold–gold bonding, reducing the lateral size and improving the efficiency of signal transmission. The flip-chip technique ensures a reliable electrical connection. A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive effect. The temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation, which will improve the precision of the pressure unit. The integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated sensor. The integrated sensor is characterised, and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97 mV/MPa and −0.19% FS in the range of 0–20 MPa and −40 to 120 °C. The linearity, hysteresis, repeatability, accuracy, basic error, and zero-time drift are 0.16% FS, 0.04% FS, 0.06% FS, 0.18% FS, ±0.23% FS and 0.04% FS, respectively. The measurement error of the temperature sensor and temperature coefficient of resistance is less than ±1 °C and 3142.997 ppm/°C, respectively. The integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection, industrial equipment, and oil drilling platforms.

Leveraging existing mid-end ultrasound machine for point-of-care intestinal ultrasound in low-resource settings: Prospective, real-world impact on clinical decision-making.

Point-of-care ultrasound (POCUS) has transformed inflammatory bowel disease (IBD) management, but the cost to purchase high-end equipment can be prohibitive. To assess prospectively the feasibility of POCUS using pre-existing mid-end ultrasound equipment without incurring additional cost. Consecutive IBD patients underwent POCUS with or without faecal calprotectin (FCP) using a mid-end ultrasound machine. If POCUS with or without FCP could not guide management, we performed additional ileocolonoscopy or cross-sectional imaging. We evaluated the impact of POCUS on IBD management and its correlation with ileocolonoscopy or cross-sectional imaging. We analysed pregnant, paediatric and post-operative patients separately. Among 508 patients with IBD, we analysed 419 (60.4% Crohn's disease [CD]; 61.3% male, age [years]: 36 [18-78]) undergoing 556 POCUS sessions. POCUS with or without FCP independently influenced clinical management in 42.8% of patients with CD and 49.7% with ulcerative colitis (UC). POCUS helped avoid colonoscopy in 51.4% of patients with CD and 51.8% with UC, and cross-sectional imaging in 38.1% of suspected active small bowel CD. In patients with additional diagnostics, POCUS-based decisions remained unchanged in 81.2% with CD and 85% with UC. Sensitivity and specificity of POCUS compared to ileocolonoscopy were 80% and 94.4% for CD and 80.8% and 92.8% for UC, respectively. Sensitivity and specificity compared to cross-sectional imaging were 87.2% and 87.5%, respectively. POCUS using existing mid-end ultrasound equipment in low-resource settings influenced IBD clinical decision-making with excellent accuracy, often avoiding colonoscopy and cross-sectional imaging.

Numerical investigation of deformation and residual stress in vacuum brazing of titanium alloy plate-fin structure

Various high-end equipment relies on titanium alloy plate-fin structure (PFS) as core components, owing to their remarkable advantages in terms of low density, superior mechanical strength and enhanced corrosion resistance. Brazing assumes a pivotal function in PFS connections, whereby the localized concentrated heat during the welding procedure can precipitate intricate structural deformation and generate residual stresses. A thermo-mechanical coupling model was developed, taking into account the service performance criteria of PFS. The effects of process parameters and clamping methods on the post-welding residual stress and deformation of PFS were investigated. The analytical expressions for the relationship between the process parameters and the stress/deformation were obtained by using the simulation outcomes. The constraint on the partition in the vacuum brazing process determines the extent of deformation and residual stress of PFS, with higher constraint leading to lower values. PFS generates z-directional displacement and y-directional warping deformation, and the weld seam between the fin and the partition is prone to stress concentration. As the brazing temperature and holding time increase, the PFS induces more deformation, while the residual stress value decreases. However, the deformation amount reaches a plateau when the holding time exceeds 30 min.