Harsh Working Conditions Research Articles

Static analysis and non-probabilistic reliability evaluation of supporting structure of insulation platform

Abstract The insulation platform is a kind of high-altitude live working equipment commonly used in complex terrain environments. Due to the harsh working conditions, the safety of the insulation platform is highly required. The supporting structure of the insulation platform is responsible for carrying the operators, which determines the safety performance of the insulation platform. In this paper, static analysis is conducted on the supporting structures of the rotary insulation platform and rotary lifting insulation platform to study their strength and stiffness properties. Then the reliability of supporting structures is analyzed based on the interval non-probabilistic reliability theory and the reliability of structures is evaluated under different size conditions.

Stability analysis of micro-probe landings in complex terrain

Abstract Addressing the problem of landing stability of the micro-probes on the surface of extraterrestrial objects, combined with the geometric properties of the orthotetrahedron, this paper proposes a structural design method of the four-spine microprobe landing bracket that can adapt to the complex terrain and carries out the analysis of the landing stability of the four-spine bracket under the state of three-legged landing and the optimization of the structure for combined terrain of stones and slopes. Referring to the ZMP theory, the harsh working conditions of the four-spine bracket when landing are sorted out and determined. Based on the kinematics theory, the collision mechanism between the four-spine bracket and the ground is analyzed, and a landing model suitable for the micro-probes is established, which provides the basis for determining the landing stability of the micro-probe. Around the collision mechanism and landing model, the dimension optimization of the four-spine bracket is carried out, and the results of Adams dynamics simulation analysis and prototype test show that the landing stability of the four-spine bracket is improved, which verifies the validity of the optimization idea.

Order-difference of normalized square envelope spectrum and its applications in early chatter detection of roll grinder

Roll grinder is widely demanded in grinding the surface of rolls that will be used to mill steel strips for high-quality automobile outer panels. The grinding chatter generally leads to poor machining accuracy and massive economic losses. The significance of roll grinder vibration monitoring is to detect the early grinding chatter. However, in harsh working conditions, some chatter detection methods inevitably confuse the fault components and interference components in vibration signals and the chatter feature information cannot be extracted exactly. The dynamical model of roll grinder system reveals that the spectrums of vibration signals contain intrinsic frequency components and chatter frequency components under health and chatter conditions. Based on the analytical modelling, a new health index order-difference of normalized square envelope spectrum (ODNSES) is proposed to detect early chatter and evaluate the health degradation of the roll grinder. The normalized square envelope spectrum (SES) is used as the pretreatment of ODNSES to compare the frequency components in vibration signals under health and early chatter conditions. Furthermore, order-difference of normalized SES is proposed to suppress the noise interference and to enable ODNSES to characterize the grinding chatter process. The detailed simulation research is performed to verify three important properties of ODNSES. The experimental results show that ODNSES would not be interfered by background noise significantly and it is on average 29.12% more sensitivity to impulse amplitudes than classical health indexes. The testing results on actual roll grinder exhibit that ODNSES can detect the early chatter and quantify the abnormal vibration in the grinding process.

“Precarious status: illegality and mental health among immigrants during the COVID-19 pandemic”

Purpose During the COVID-19 pandemic, immigrants faced new challenges that increased their precarity which often perpetuated existing social and health-related inequities. This compounded inadequate access to healthcare, harsh working conditions, marginalization due to legal status and fear of deportation, all of which were worsened during the height of the pandemic. This article aims to examine how existing social factors that marginalize immigrant populations were affected by the COVID-19 pandemic based on a study with immigrant farmworkers in Apopka, Florida. Design/methodology/approach The author analyzes how they were affected by stress both before and during the pandemic, and how these factors affected their mental health. Findings The author concludes that im/migrants’ often precarious status negatively affects their experiences with mental health, and that this was heightened during the COVID-19 pandemic. Despite the long-term nature of precarity for this vulnerable population, this study captures these issues as they were experienced during the COVID-19 pandemic. Originality/value This research contributes to emerging scholarship concerning social factors and mental health during the pandemic by examining the experiences of one of the most marginal populations in the United States.

A fault diagnosis method for bearings and gears in rotating machinery based on data fusion and transfer learning

Abstract Rotating machinery is a crucial component of industrial equipment, and the fault diagnosis of bearings and gears, as vital elements of rotating machinery, is essential since they often fail under harsh working conditions, leading to significant property losses and serious personal safety problems. However, fault data for gears and bearings are often sparse in actual condition, and it is a challenge to ensure the reliability and stability of fault diagnosis results by extracting the features of a single data. To solve the above problems, this paper proposes a fault diagnosis method that combines Transfer Learning and data fusion techniques. Firstly, in this method, two kinds of fault signals are transformed into Gramian Angular Difference Fields and Recurrence Plot. Next, a U-shaped feature fusion dual discriminator generative adversarial network is used to fuse two-dimensional images from multiple sensor data. Its feature fusion module deeply integrates the features of the two images, thereby solving the impact of single data on the reliability and stability of fault diagnosis. Moreover, open-source datasets are used for Transfer Learning training to tackle the small sample problem. Finally, a decision-level information fusion classifier, the Dual-Branch Dempster-Shafer Classifier (DB-DSC), classifies the fused images. This classifier incorporates an improved soft threshold function and D-S evidence theory to achieve adaptive gradient changes and improve the robustness and accuracy of classification results. The experimental results show the effectiveness and stability of the proposed method, and the generated images get high score in several metrics. The average classification accuracy of the classification network reaches 93% and 92.5% on the two datasets, Therefore, the proposed method exhibits strong fault diagnosis capabilities under the small sample conditions of bearings and gears.

Cybersecurity risks of automated (and autonomous) offshore oil and gas units—the IMO cybersecurity rules framework

Abstract Automated and/or autonomous offshore platforms or units are becoming more important in the energy sector, whether they are being used for oil and gas extraction or for carbon storage purposes. Automation means that harsh working conditions and risks of personal injury to crew could be cut to virtually zero. Automation also provides significant cost savings and helps make less attractive oil and gas fields more economically viable to exploit. However, automation does come with its own set of challenges—the notable one being the cybersecurity threat. Any regulation or international standard dealing with the cybersecurity risk which is relevant to automated offshore units is usually framed within those rules that apply to ships. This article examines to what extent that regulatory approach, especially that of the International Maritime Organisation’s (IMO) regime, could and should apply to automated or autonomous offshore platforms. It argues that whilst, for now, the IMO cybersecurity guidelines are relevant, a more targeted regulatory approach is needed.

Measurement of tritium production in the helium cooled pebble bed test blanket module mock-up at JET during DTE2

Quite often, detectors for measuring nuclear performance and radiation quantities of relevance in fusion experiments are requested to withstand harsh working conditions due to intense neutron and gamma radiation fields. High temperature constitutes a further harsh element in some locations of the machine, where it is necessary to perform some on-line measurements, as expected in the breeding blanket. This is an essential component in future fusion power plants to provide tritium self-sufficiency and its performance must be continuously monitored. Some Test Blanket Modules (TBMs) will be installed in ITER to provide the first experimental data to validate the predictions on tritium production and recovery. In the meantime, within EUROfusion program, the mock-up of the Helium Cooled Pebble Bed Test Blanket Module (HCPB TBM), previously used for the TBM experiment at the Frascati Neutron Generator (FNG), had been installed at JET to test some detectors and for benchmarking numerical codes used for breeding blanket assessment during DTE2 campaign. A diamond detector, calibrated to measure the tritium production through neutron detection inside the HCPB TBM mock-up, was tested during some plasma pulses of the DTE2 campaign at JET. The main outcome is that, as far as neutron emission rate is below 1015 s−1, neutrons are properly detected along the plasma discharge evolution by TBM diamond detector, consistently with the JET neutron monitor KN1. Moreover, the amount of tritium measured (E) is 1.40 × 10–12 tritons per source neutron and the comparison with MCNP radiation transport simulation (C) gives a ratio C/E = 0.77. Such measurements, considered promising, and their comparison with calculations are discussed in the present work. Criticalities emerged are analyzed and some improvements proposed with the main purpose of speeding up signal processing to make the system capable of working at higher plasma neutron emission rates.

A Hardware Circuit for Extracting Weak Damage Characteristics of Steel Wire Rope Using an Asymmetric Monostable System

ABSTRACTNon‐destructive testing of steel wire rope is significant in lifting machinery. However, it is still challenging to extract weak damage characteristics of steel wire rope under noise caused by harsh working conditions. Currently, extracting damage characteristics mostly involves secondary processing through software, which is cumbersome and inefficient. Stochastic resonance is a typical stochastic dynamic phenomenon of a nonlinear system, and it can extract weak damage characteristics through the cooperation of noise, weak signals, and nonlinear system models. Among different nonlinear system models, the asymmetric monostable system, which has only one fixed point, is advantageous for achieving a more stable response under pulse excitation. In this work, a hardware circuit based on an asymmetric monostable system is constructed to extract weak damage characteristics of steel wire rope. This hardware circuit can efficiently extract damage characteristics without secondary processing. Additionally, the denoising performance of the nonlinear circuit, focusing on weak signals with damage characteristics under a noisy background, is evaluated using the cross‐correlation coefficient and local cross‐correlation coefficient. The results demonstrate that the proposed method provides high recovery in the non‐destructive testing of steel wire rope.

Network Data Intrusion Detection and Data Feature Extraction of Electromechanical Facilities from Machine Learning

With the rapid development of Internet technology, network security issues have become more complex and changeable. Various intrusion methods threaten the information network environment in the Electromechanical Facility (EF) system. This paper focuses on EF to study the relevant detection methods and data feature extraction in complex network intrusions. Firstly, four common machine learning algorithms are used to calculate the data set. The advantages and disadvantages of each algorithm are analyzed after tuning and comparison. Secondly, a network intrusion detection algorithm is proposed based on Recursive Feature Elimination (RFE) principal component analysis. It uses RFE to reduce the number of features and improve the elimination judgment index to align with the detection requirements of information network datasets. Finally, a fault diagnosis method is proposed based on empirical pattern decomposition and support vector machine under Renyi entropy complexity measurement. This method trains and identifies the Renyi entropy of several basic pattern components obtained by decomposing empirical patterns as feature vectors. The results show that the RFE method judged by random forest removes irrelevant features, and the evaluation index is improved to align with the network dataset’s detection requirements. It reduces the data dimension, reduces the operation time, and improves the accuracy of a few attack types. The comprehensive final detection effect is better than other algorithms. Additionally, the embedded operating system construction method based on the protection mechanism realizes the separate storage of the operating system and key data. Also, it can prevent the network system from being maliciously invaded, ensuring the stability of the instrument operation under harsh working conditions.

An Analysis on Caste Practices and the Vulnerabilities Faced by Burial Ground Workers in Sivagangai District, Tamil Nadu

Tamil Nadu is a state combined with multi-religious, multi-ethnic and inequality. Formally, Caste is being an indispensable part of cremation process. Whether it is traditional or new techniques it all based on the caste practices followed by each community. The aim of the study is to analysis the caste practices and the vulnerabilities faced by cremation ground workers. It deals with the burying process and preparation of crematorium. The purpose of this analysis is to examine the status and caste differences faced by the crematorium workers in Sivagangai District of Tamil Nadu. The objectives of the Study have discussed to study the discrimination faced by burial ground workers. To analysis the impact of discrimination and the status of crematory workers. To Enact an inclusive policy to build up the marginalized cremation workforce in Sivagangai District of Tamil Nadu. Result of the study implementing the policy measures to create a more inclusive, social and economic equality for the burial ground workers, addressing longstanding gender and caste disparities. These policies aim to create a more inclusive and equitable environment for burial ground workers by addressing gender and caste disparities. Formalizing employment, enacting anti-discrimination laws, and ensuring job security will offer stability and recognition for those in this essential industry, fostering social justice and equality. Findings of the study on Caste intersects with class, gender, and religion, creating complex layers of discrimination that particularly affect burial ground workers, who often face social stigma and marginalization. Predominantly from lower caste, these workers endure systemic discrimination, low wages, job insecurity, and significant occupational hazards, such as exposure to pathogens and harsh working conditions, all while playing a crucial role in public health and the execution of cultural and religious rituals. Living in segregated communities, their families experience social ostracism and limited access to essential services, yet they demonstrate resilience through community solidarity, with local organizations advocating for their rights and improved conditions. Conclusion of the study have the caste system's deep-rooted influence continues to affect Indian society, highlighting the need for ongoing efforts toward social justice. Burial ground workers play a critical, yet often overlooked, role, facing social stigma and poor working conditions. Addressing these challenges requires a multifaceted approach that includes legal, social, and economic interventions. Recognizing their contributions and vulnerabilities has been essential for fostering greater inclusivity and equality in the society. This study emphasizes the importance of acknowledging and supporting these workers to promote social progress.

A review of the future transport labour market: An EU approach

Mobility and transportation are a fundamental cornerstone of societies. They cannot be performed without a specific and varied workforce that keep all modes functioning. However, the transport sector currently faces many challenges including volatile high energy prices, labour and skills shortages, harsh working conditions, an ageing work force, and many labour relations’ issues. There are also deep and widespread market changes to confront in relation to automation and digitalisation, the move towards greener, cleaner technologies and sustainability. The risk of unemployment for certain jobs is evident. Transport workers and transport undertakings are thus confronted with the very challenging landscape to decarbonise the sector but also to address social sustainability and remain competitive in a fast-changing environment. This study makes use of a systematic review to analyse the main challenges that the land transport sector faces. This paper informs policy makers and relevant stakeholders on the current trends; highlights challenges and opportunities for transport workers and provides recommendations to help achieve that will result in a digital and fair, ethical, just, and green transition not only for the transport sector but also for the society as a whole.

Research status on the effect of energy density on the forming microstructure and properties of nickel-based superalloys for laser additive manufacturing

Abstract Nickel-based superalloys have excellent high-temperature mechanical properties, corrosion resistance and oxidation resistance, and strong machinability. It is widely used in aerospace, submarine and shipbuilding, petrochemical, electronic industry and other industries. However, there are still challenges in the popularization and application of nickel-based superalloys for alloy components with complex structures and extremely harsh working conditions. In this paper, the research status of the influence of energy density on the microstructure and properties of laser additive fabrication of nickel-based superalloys at home and abroad is reviewed. The influence of energy density on the microstructure evolution behavior and mechanical properties improvement effect of laser additive manufacturing nickel-based superalloys is summarized. The mechanism of energy density was discussed from the perspectives of microstructure evolution and macroscopic performance change. Based on the individual effects and synergistic effects of each process parameter, the influence of laser energy density on dendrite growth, phase precipitation characteristics, element distribution and porosity defect control effect of nickel-based superalloy was expounded, as well as the influence mechanism on microhardness, wear resistance and residual stress. Finally, the energy density optimization and development prospect of laser additive fabrication of nickel-based superalloys are prospected.

Fabrication and tribological behavior of laser cladding Cu/Ti3SiC2 reinforced CoCrW matrix composite coatings on Inconel718 surface

To satisfy the need for high wear resistance of Inconel718 alloy under harsh working conditions, laser cladding technique was adopted to fabricate the Cu/Ti3SiC2-CoCrW metal matrix composite coatings on that surface. The phase composition, microstructure, microhardness, surface energy, and tribological properties of the composite coatings were systematically analyzed by characterization methods such as XRD/ SEM/ EDS/ XPS and performance test methods such as high-temperature friction and wear test, and the wear mechanism at different temperatures was deeply discussed. The research results indicate that the microhardness of coatings is increased by 2.2–2.9 times compared to the substrate, which is mainly owing to the solid solution strengthening effect and the diffusely distributed hard reinforcing phases such as Cr7C3, WCx, and TiC. Regarding the wear resistance, the wear rate of coatings is significantly reduced by 1–2 orders of magnitude over the substrate. Among them, the Co-based coating adding 10 wt% Cu - 10 wt% Ti3SiC2 exhibited the lowest wear rates at room and high temperatures, which were 0.22 and 3.23 × 10−5 mm3/ N·m, respectively, with 98.22 % and 88.19 % reductions in comparison with the substrate. The low surface energy (27.94 mN/m) was one of the main reasons for the good tribological properties. When the friction environment changes from room temperature to 600 °C, the primary wear mechanism of coatings changes from abrasive and adhesive wear to oxidative wear.

Ultra-short running-in period and robust lubricity constructed by dynamic disulfide and hydrogen bonds from ionic liquid polyethylene glycol lubrication

Polyethylene glycol (PEG) system behave the characteristics of non-toxic, non-irritating and good compatibility with various substances, so the improvement and stability of lubrication property and comprehensive performance is vital for PEG system under harsh working conditions. Here, highly reactive ionic liquids (ILs) are designed and introduced with a specifically designed molecular structure, the ultra-short running-in period and robust lubricity can be obtained by dynamic disulfide and hydrogen bonds from the constructed IL-PEG200 lubrication system. Combined with analytical techniques (XPS, FIB-TEM, Nanoindentation, Raman, TOF-SIMS), their interaction was explored to further clarify the interfacial self-assembly behavior. The superior bearing capacity is mainly ascribed to the synergistic effect of carbon-like film, dynamic disulfide bond, hydrogen bonding and interfacial tribochemical reaction.

Fatigue investigations of elastomers developed for high-pressure hydrogen gas environments

Hydrogen possesses many characteristics to be an ideal candidate as a more sustainable energy carrier, especially for the transport sector. For a proper optimization of this abundant resource, hydrogen needs to be compressed, and stored in high-pressure conditions, which demands improvement in technology and the development of appropriate materials. In this context, elastomeric sealing components play a critical role and they need to withstand harsh working conditions, for example, high-pressure, wide temperature range, cyclic exposure conditions, etc. In this work, eight different grades designed for this application were analyzed in terms of fatigue behavior and long-term performance. This was verified through fatigue crack growth experiments, the energy dissipation, and temperature increase during crack propagation were analyzed and correlated with micro-structural differences of materials. Furthermore, the materials were investigated at large and small deformations through uniaxial tensile tests and Dynamic Mechanical Analysis (DMA), respectively. It was found that only with the addition of a coupling agent can silica-filled NBR have properties similar to carbon black (CB) filled NBR, despite a reduction in both fatigue strength and energy dissipation. Coupling agents also involved an increase in bound rubber. Regarding CB-filled compounds, with peroxide crosslinking a reduction in fatigue strength was found, while no effect on the quantity of bound rubber was observed. Increased CB content in NBR grades led to decreased fatigue resistance and higher energy dissipation; higher bound rubber content was found as well. Also for EPDM grades, increased CB content resulted in reduced fatigue resistance. Despite an increase in energy dissipation, the content of bounded rubber was the same even with higher CB content.

Acoustic signal adversarial augmentation for pressure pipeline leakage detection

Pressure pipelines are prone to leakage under harsh working condition for a long time, and the leakage detection reaches unsatisfactory performance due to influence of background noise and insufficient sample for acoustic signals. Therefore, the acoustic signals adversarial augmentation method is proposed for pressure pipeline leakage detection based on noise reduction and sample generation. By deeply connecting with generative adversarial network (GAN), denoising autoencoder (DAE) and residual network (ResNet), the adversarial denoising and generation model (ADGM) is established to reduce the noise of acoustic signal. In addition, the trained DAE of ADGM is applied to augment the acoustic samples, thereby completing adversarial augmentation of acoustic signal, which is significant for pressure pipeline leakage detection. Besides, the pipeline leakage experiment is implemented to validate the proposed method on noise reduction and sample generation, which can reach pressure pipeline detection accuracy of 93.02% based on augmented acoustic signal. Further, the effectiveness and superiority of the proposed method are tested by ablation experiments and comparative methods.

Examining the Impact of Employee Welfare on Organizational Performance of Kenya Power and Lightening Company Limited Kitale, Kenya

This article examines the impact of employee welfare on the organizational performance of Kenya Power and Lightening Company Limited in Kitale, Kenya. The article revealed that a poor working environment, a lack of motivation, and overworking were the causes of poor employee performance. However, the welfare of employees at Kenya Power and Lightening Company is not bad. This was based on the responses received from the respondents. Furthermore, a significant proportion of respondents, specifically 41.7%, reported receiving all welfare benefits, including food, health, and school benefits. The study suggests that Kenya Power and Lightening Company should prioritize maintaining and enhancing employee welfare to boost the team's productivity. This, in turn, leads to improved organizational performance. More so, organisations like Kenya Power and Lightening Company and others in the same category. Furthermore, companies such as Kenya Power and Lightening Company, along with others in the same sector, consistently offer their employees welfare benefits. They should also strive to reduce harsh and unfriendly working conditions, as this can demotivate employees and result in poor organisational performance. Finally, the government should formulate policies that favour employees in the workplace. These policies should focus on creating a good working environment for employees, as this will ultimately lead to improved organisational performance. Keywords: Employee, Employee performance, Environment, Organization, Working condition.

Evaluating the influence of ambient conditions in the cooking space of railway pantry car using selected thermal indices and physiological parameter.

Hot and humid indoor environment of the kitchen affects worker performance. The Indian Railway's pantry car culinary is one of them that cooks food for the on-board passengers, which could be bothered by the hot indoor climate. The current study aimed to identify the indoor working environment of the railway "pantry car" using heat stress indices such as "Universal Thermal Climate Index-UTCI," "Wet-Bulb Globe Temperature-WBGT," "Discomfort Index-DI," "Tropical Summer Index-TSI," "Heat Index-HI," and Heart Rate-HR with clothing insulation. METHODS: The study was performed in 2018 (August-summer season) to collect field survey data on 6 railway pantry cars. Measurements were carried out during peak cooking times such as morning "7 : 00 am", day "11 : 30 am", evening "4 : 00 pm," and night "6 : 30 pm". This study's descriptive and Pearson's correlation analysis was accomplished using SPSS version 2016 software. The analysis results revealed that the average values were for UTCI (37.77±5.26°C), WBGT (30.42±2.28°C), DI (30.05±2.70°C), TSI (33.21±2.90°C), HI (48.53±4.86°C), correspondingly. During analysis, the strongest correlation association was observed between "TSI and DI" (r = 0.985, p < 0.000) and WBGT and TSI (r = 0.958, p < 0.000). A "significant correlation" was found between UTCI and HI (r = 0.637, p < 0.05). While no signification correlation was found between "heat stress indices and physiological parameters (p > 0.05)". In this study, all the heat stress index limit values showed highly harsh working conditions inside the pantry car, which created unfavorable circumstances for the culinarians. Inappropriate "ventilation design" could be a reason for discomfort in the railway pantry car.

A forecasting model with hybrid bidirectional long short-term memory for mooring line responses of semi-submersible offshore platforms

Semi-submersible offshore platforms are often produced in the deep sea far away from land, which results in high operating costs and difficult safety maintenance due to the harsh and complex working conditions. Adopting a neural network model for online accurate prediction of mooring tension of semi-submersible offshore platforms can adjust the ballast according to the advance of mooring tension change to keep the platform in a relatively smooth movement amplitude and improve production efficiency. In addition, it can also prevent catastrophic accidents caused by anchor chain breakage due to excessive mooring tension. However, the measured mooring tension of semi-submersible offshore platforms is characterized by complex nonlinear non-stationarity, which leads to insufficient prediction accuracy of a single prediction model. This paper develops a novel online prediction model of mooring tension for semi-submersible offshore platforms based on empirical modal decomposition (EMD), convolutional neural network (CNN), and bidirectional long and short-term memory neural network (BiLSTM). The proposed model is validated using the measured data of the first semi-submersible offshore platform in the South China Sea during operation. The experimental results show that the proposed model outperforms other comparative models currently mainstream for mooring tension prediction. In addition, the proposed method can also be used to predict complex nonlinear data in the field of ship and ocean engineering.

A new Ti–Al–Cr–Mo–Zr titanium alloy welding wire: Stability, microstructure and mechanical properties

In order to improve the plasticity of titanium alloy welded joints, relevant scholars currently focus primarily on studying the mechanism of action of alloying elements Mo and V, such as reducing the phase transition temperature of the welded seam and ensuring a certain amount of β phase residue in the welded seam. In addition to improving the stability and strengthening ability of titanium alloy welded joint, it can also maintain a certain degree of plasticity of the welded joint. However, the poor impact toughness is still the key problem that restricts its long-term stable service in the harsh environment. Our work designed and developed a new Ti–Al–Cr–Mo–Zr solid welding wire, with the synergistic effect of Al, Cr, Mo and Zr, the welded seam microstructure and grain can be refined while ensuring the enough stiffness of the welding wire and its flatness during wire feeding into the designated working area. It ensures good wetting and spreading flow performance of the liquid molten pool metal in the welding process, so better welded seam formation can be obtained. The relative contents of α′ martensite and β phase in the welded seam are 76.79% and 23.21%, respectively. The residual β phase is interspersed between the α′ martensite of the slats. The β phase provides a path for the plastic deformation of the welded joint, making it easier for dislocation slip to pass the β/α′ interface. At the same time, more dislocation slip channels and a small number of fine twins can be found in the interior of α′ martensite, which can ensure the strength while taking into account the toughness. After testing, it is found that the average tensile strength of welded joints is 901 MPa, which is close to 95% of the base metal (BM), the average post-fracture elongation of welded joints is 21%, and the impact toughness value at room temperature is distributed between 25 J and 33 J, which meets the requirements of the synergistic effect of welded joint strength and plastic toughness. It is suitable for long-term stable service of Ti64 titanium alloy welding structure under harsh working conditions.