Mechanical Structure Research Articles

Controller design and experimental validation of walking for a musculoskeletal bipedal lower limb robot based on the spring-loaded inverted pendulum model

In the study of PAM (McKibben-type pneumatic artificial muscle)-driven bipedal robots, it is essential to investigate whether the intrinsic properties of the PAM contribute to achieving stable robot motion. Furthermore, it is crucial to determine if this contribution can be achieved through the interaction between the robot’s mechanical structure and the PAM. In previous research, a PAM-driven bipedal musculoskeletal robot was designed based on the principles of the spring-loaded inverted pendulum (SLIP) model. The robot features low leg inertia and concentrated mass near the hip joint. However, it is important to note that for this robot, only the design principles were based on the SLIP model, and no specialized controller was specifically designed based on the model. To address this issue, based on the characteristics of the developed robot, a PAM controller designed also based on the SLIP model is developed in this study. This model-based controller regulates ankle flexion PAM to adjust the direction of the ground reaction force during robot walking motion. The results indicate that the proposed controller effectively directs the leg ground reaction force towards the center of mass during walking.

Reliability Analysis of Complex Structures Under Multi-Failure Mode Utilizing an Adaptive AdaBoost Algorithm

A reliability analysis can become intricate when addressing issues related to nonlinear implicit models of complex structures. To improve the accuracy and efficiency of such reliability analyses, this paper presents a surrogate model based on an adaptive AdaBoost algorithm. This model employs an adaptive method to determine the optimal training sample set, ensuring it is as evenly distributed as possible on both sides of the failure curve and fully contains the information it represents. Subsequently, with the integration and iterative characteristics of the AdaBoost algorithm, a simple binary classifier is iteratively applied to build a high-precision alternative model for complex structural fault diagnosis to cope with multiple failure modes. Then, the Monte Carlo simulation technique is employed to meticulously assess the failure probability. The accuracy and stability of the proposed method’s iterative convergence process are validated through three numerical examples. The findings of the study illuminate that the proposed method is not only remarkably precise but also exceptionally efficient, capable of addressing the challenges related to the reliability evaluation of complex structures under multi-failure mode. The method proposed in this paper enhances the application of mechanical structures and facilitates the utilization of complex mechanical designs.

Amoeba-Inspired Soft Robot for Integrated Tumor/Infection Therapy and Painless Postoperative Drainage.

Tumor recurrence and wound infection are devastating complications of wide excision surgery for melanoma, and deep postoperative wound drainage typically increases pain. An amoeba-inspired magnetic soft robot (ASR) with switchable dormant and active phases is developed to address the aforementioned challenges. The dormant ASR supports wounds through its solid-like elasticity and regulates reactive oxygen species (ROS) levels bidirectionally, promoting healing in infected wounds and eliminating residual tumors. It solves the challenge caused by the contradictory need for ROS scavenging in wound healing and ROS amplification in tumor/infection management. The active ASR removes absorbed wound exudate by crawling out from irregular wounds; interestingly, this crawling motion prevents damage to fragile tissues and alleviates wound pain via "non-direct friction." More importantly, ASR switches different states in response to an alternating magnetic field owing to its magnetothermal properties, and this process also exerts synergistic antitumor and bacteriostatic effects. Due to the appropriate mechanical structure (cohesive force) of ASR, the content of magnetic nanoparticles required to drive the ASR is ten-fold lower than that of conventional magnetic soft robots, enabling in vivo degradation. These outcomes highlight the vantage of the ASR for treating post-tumor excision wounds and underscore their potential for clinical application.

On the orthogonal matrix in the Casas-Ibarra parametrization for the Yukawa interactions of Majorana neutrinos

The Casas-Ibarra (CI) parametrization of the Yukawa coupling matrix of Majorana neutrinos is generalized by considering the exact seesaw relation and including non-unitarity of the 3×3 Pontecorvo-Maki-Nakagawa-Sakata (PMNS) flavor mixing matrix. With the help of a full 6×6 Euler-like block description of the flavor structure for the seesaw mechanism, we find that the orthogonal matrix O in the CI parametrization can be expressed as Oij=Mj/miFij with mi and Mj being the masses of light and heavy Majorana neutrinos and Fij consisting of the PMNS and active-sterile flavor mixing parameters (for i,j=1,2,3). Assuming a specific pattern of O is therefore equivalent to imposing some special conditions on the seesaw parameter space.

Seismic random noise suppression via mining multi-scale local and global information

Suppressing random noise is critical for revealing real subsurface structures. Convolutional neural networks (CNNs), the leading seismic data denoising methods, excel at extracting local features but struggle to capture global representations. Unet can extract and reuse multi-scale features, aiding in the precise detection of details and semantic information; however, being based on convolutional operations, it struggles to capture global information. To capture global representations, researchers normally employ Transformers in high-level visual tasks, owing to their self-attention mechanisms. This paper introduces a method for mining multi-scale local and global information based on hybrid-gated Unet (HGUnet), which integrates Transformer, CNN, and Unet architectures to enhance the feature representation capability for seismic random noise suppression tasks. HGUnet comprises hybrid-gated blocks (HGB) embedded within a U-shaped architecture, employing a concurrent structure of Octave convolution and lightweight multi-head self-attention mechanism to efficiently extract multi-scale local and global features simultaneously. Moreover, at the conclusion of the HGB, to precisely leverage information and reduce computing costs, a gated feedforward network is designed to retain valuable information and prune redundancies for feature fusion. Synthetic and field experimental results demonstrate that HGUnet improves denoising quality over traditional and CNN methods without adding significant computing costs.

Sunflower pith inspired dual-gradient cellular polyurethane architecture with amplified mechanical functions

Artificial cellular materials with various mechanical functions are attracting increasing attentions from aerospace, transportation, and industrialization. However, many artificial cellular materials, despite of the hierarchically ordered structures and even unique performance to some, still lag behind many natural ones in amplification of mechanical functions owing to the limitations in intrinsic mechanical performance and sophisticated structural design. Herein, inspired with lightweight and high strength of sunflower piths, we proposed a dual-gradient structure consisting of pore size gradient and wall thickness gradient to engineer cellular architectures with desirable mechanical performance by harnessing vat photopolymerization 3D printing of double crosslinking networks polyurethane elastomer. The double-gradient cellular polyurethane architecture displays more exceptional capability in load-bearing and energy absorption compared with non– and single gradient structures. Besides, the specific compressive strength and energy absorption of the dual-gradient cellular architectures are 4 times higher than those of traditional mechanical metamaterial structures such as octet-truss lattice, gyroid lattice, and porous structure prepared with the same material. Potential mechanisms such as dual-gradient cellular structures to obtain selective flexural deformation behaviour increasing their energy absorption and dissipation capacity are fully elucidated. As the potential paradigms, we demonstrated the mechanical functions of biomimetic mechanical cellular architectures for efficient impact protection and noise isolation, which offered a promising perspective toward developing soft metamaterials with excellent mechanical functions for potential soft machines and engineering applications.

Design of a linear motor-based magnetic levitation train prototype

<span>This study explores the modelling of a magnetic levitation train and its implementation using a microcontroller. Magnetic levitation (maglev) is a technology that enables vehicles to levitate and move without wheels. Maglev research has been conducted globally, but maglev trains haven't received much attention. Due to the sophisticated linear motor technology for contactless transit, building a maglev train requires enormous investments. This paper is crucial for understanding the linear motor technologies necessary for levitation and propulsion. The primary objectives of this study include creating a model of the maglev train using a linear motor circuit, investigating the maglev effect concerning different coil and magnet types, and monitoring the train's propulsion and levitation using a microcontroller. This work constructs a linear motor system for the maglev train, comprising a mechanical structure with a permanent magnet for levitation and electromagnets for propulsion. A microcontroller is employed to sense the magnetic field, produced by the permanent magnet and electromagnets. In summary, this paper successfully designed a maglev train prototype using a linear motor circuit to establish the repulsive mechanism for both levitation and propulsion, with levitation~1 cm from the track and demonstrated the ability to move along a 30 cm track.</span>

Research on Digital Technology of Mechanical Structure Fault Diagnosis of Power Transformer Based on Comprehensive Feature Extraction and SABO-PNN

Research on Digital Technology of Mechanical Structure Fault Diagnosis of Power Transformer Based on Comprehensive Feature Extraction and SABO-PNN

Design and optimization for a longitudinal-flow corn ear threshing device of low loss and low energy consumption

The traditional corn grain harvester threshing device has the problems of high grain breakage rate, high unthreshed grain rate and high energy consumption when harvesting high water content corn ears. A longitudinal-flow corn ear threshing device and its measurement and control system were proposed to overcome these problems. The working performance and energy consumption of the threshing device were optimized by conducting three factors and five levels corn ear threshing experiments. The experiments took the threshing cylinder speed (X1), threshing gap (X2), and guide vane angle (X3) as the experimental factors, and the grain breakage rate (Y1), unthreshed grain rate (Y2), unit energy consumption (Y3), and threshing concave pressure (Y4) as the experimental indicators. According to the experimental results, the quadratic polynomial regression models between experimental indicators and experimental factors were established. Through models optimization, the optimal working parameters for the threshing device were obtained as X1 at 392.40 r/min, X2 at 40.70 mm, and X3 at 33.16°. Through conducting verification experiment, it was found that under the optimal parameters, the experimental indicators were Y1 at 2.32 ± 0.06 %, Y2 at 0.48 ± 0.04 %, Y3 at 2.14 ± 0.10 kJ/kg, and Y4 at 46.28 ± 3.23N. The errors between the experimental results and the quadratic polynomial regression models were less than 5 %, which indicated that the models had high prediction accuracy. Compared with the unoptimized experimental indicators, the optimized experimental indicators Y1, Y2, Y3 and Y4 decreased by 36.26 %, 39.24 %, 14.74 % and 16.27 %, respectively. The working performance of the threshing device was significantly improved, and the energy consumption was significantly reduced. The relevant research could provide reference for the optimization of the mechanical structure and working parameters of the corn ear threshing device.

EVALUATION OF FISSION FRAGMENT MOMENTS OF INERTIA FOR SPONTANEOUS FISSION OF CF-252

Abstract The paper discusses methods for estimating the moments of inertia of fission fragments for spontaneous fission of the isotope Cf-252, in particular, two main approaches are mentioned: statistical and microscopic. In addition, the methods of the classical and superfluid approaches to the calculation of the moments of inertia are discussed, as well as their application to different models of nuclei. Within this framework, the influence of different vibrational modes and nucleon exchange on the moments of inertia and spin distributions of fission fragments is evaluated. The paper emphasizes the need for a comparative analysis of theoretical predictions with experimental data for a deeper understanding of the internal structure of nuclei and fission mechanisms.

Study on the Influence of Lightweight Mechanical Structure on UAV Dynamic Response Characteristics and Control Strategy Optimization

Study on the Influence of Lightweight Mechanical Structure on UAV Dynamic Response Characteristics and Control Strategy Optimization

Machine Learning based Pointing Corrections for Radio/Sub-millimeter Telescopes

Radio, sub-millimeter and millimeter ground-based telescopes are powerful instruments for studying the gas and dust-rich regions of the Universe that are invisible at optical wavelengths, but the pointing accuracy is crucial for obtaining high-quality data. Pointing errors are small deviations of the telescope’s orientation from its desired direction. The telescopes use linear regression pointing models to correct for these errors, taking into account various factors such as weather conditions, telescope mechanical structure, and the target’s position in the sky. However, residual pointing errors can still occur due to factors that are hard to model accurately, such as thermal and gravitational deformation and environmental conditions like humidity and wind. Here we present a proof-of-concept for reducing pointing error for the Atacama Pathfinder EXperiment (APEX) telescope in the high-altitude Atacama Desert in Chile based on machine learning. Using historic pointing data from 2022, we trained eXtreme Gradient Boosting (XGBoost) models that reduced the root-mean-square errors (RMSE) for azimuth and elevation (horizontal and vertical angle) pointing corrections by 4.3% and 9.5%, respectively, on hold-out test data. Our results will inform operations of current and future facilities such as the next-generation Atacama Large Aperture Submillimeter Telescope (AtLAST)

Phase-Shifted Fiber Bragg Grating by Selective Pitch Slicing

This paper presents a new type of phase-shifted Fiber Bragg Grating (FBG): the sliced-FBG (SFBG). The fabrication process involves cutting a standard FBG inside its grating region. As a result, the last grating pitch is shorter than the others. The optical output signal consists of the overlap between the FBG reflection and the reflection at the fiber-cleaved tip. This new fiber optic device has been studied as a vibration sensor, allowing for the characterization of this sensor in the frequency range of 150 Hz to 70 kHz. How the phase shift in the FBG can be controlled by changing the length of the last pitch is also shown. This device can be used as a filter and a sensing element. As a sensing element, we will demonstrate its application as a vibration sensor that can be utilized in various applications, particularly in monitoring mechanical structures.

Synchronization characteristics and stable states of four co-rotating vibrators with balanced slanted elliptical trajectory

In the petroleum drilling and mining screening industries, our goal is to enhance excitation force, integrate circular screening with rectilinear transport to obtain the balanced slanted elliptical trajectory (BSET), and reduce screen mesh clogging. This work investigates the synchronization characteristics and stable states of four co-rotating vibrators. The novelty of this work lies in using a novel vibration model to achieve the BSET in the synchronization state and in further considering the influence of a new skewing angle between two eccentric rotors (ERs), which are few in previous vibration screening field. Initially, the vibration model is extracted from the designed prototype. Then, in accordance with Routh–Hurwitz criterion, the synchronization and stability are theoretically analyzed using small parameters of vibrator velocity and phase differences (PDs). The synchronization characteristics related to mechanical structures are discussed via numerical calculation and experimental verification. Results reveal that the synchronization implementation is adversely affected by the skewing angle, even leading to unordered behaviors. Achieving zero-phase or in-phase synchronization with four vibrators is only feasible with a larger symmetric distance and installation angle. This work can contribute a foundation for designing some new types of large vibration screening and material conveyance machines.

Modeling, Simulation, and Kinematic Validation of Transfemoral Prosthetic Mechanism With Ankle Varus–Valgus Characteristic

Abstract Inspired by the kinesiology of human bionic joints, a transfemoral prosthetic mechanism based on a functional structure of parallel mechanism is developed for the transfemoral amputees. The walking interactive simulation is implemented based on human-prosthesis modeling to verify the kinematics of the designed prosthetic mechanism, as well as to explore compatibility between the amputees and prosthesis. Then, simulation-based prosthetic optimization is performed to pursue an optimized human-prosthesis model with economic metabolic consumption while eliminating compatibility errors including the joints' misalignment error between the affected limb and healthy limb, and the assembly error between human and prosthesis, so that the potential physical health problems can be avoided efficiently. This method is valuable for the optimal design of interactive rehabilitation robots. Finally, a developed proportional-integral-derivative-based (PID-based) finite-state machine (FSM) strategy is used, and the kinematic validation is carried out. The results show that the designed prosthesis possesses ankle varus–valgus characteristic, and it has a high human-like motion accuracy due to the FSM control can track prosthetic motion in each gait event. What's more, the prosthetic optimization can be an efficient method to enhance the biomechanical performance of human-prosthetic model so that the amputees have a more natural and symmetry gait.

Mechanics-informed autoencoder enables automated detection and localization of unforeseen structural damage

Structural health monitoring ensures the safety and longevity of structures like buildings and bridges. As the volume and scale of structures and the impact of their failure continue to grow, there is a dire need for SHM techniques that are scalable, inexpensive, can operate passively without human intervention, and are customized for each mechanical structure without the need for complex baseline models. We present a novel “deploy-and-forget” approach for automated detection and localization of damage in structures. It is a synergistic integration of entirely passive measurements from inexpensive sensors, data compression, and a mechanics-informed autoencoder. Once deployed, the model continuously learns and adapts a bespoke baseline model for each structure, learning from its undamaged state’s response characteristics. After learning from just 3 hours of data, it can autonomously detect and localize different types of unforeseen damage. Results from numerical simulations and experiments indicate that incorporating the mechanical characteristics into the autoencoder allows for up to a 35% improvement in the detection and localization of minor damage over a standard autoencoder. Our approach holds significant promise for reducing human intervention and inspection costs while enabling proactive and preventive maintenance strategies. This will extend the lifespan, reliability, and sustainability of civil infrastructures.

MPFEM investigation on densification and mechanical structures during ferrous powder compaction

Metal powder compaction is a crucial process in powder metallurgy, significantly affecting the final properties of compacts. However, the quantitative characteristics of multi-scale mechanical structures and the microscopic densification behavior, taking into account the influence of friction conditions, remain unclear. This study utilises a two-dimensional multi-particle finite element method to analyse the ferrous powder compaction. The evolution of powder densification, powder deformation and multi-scale mechanical behaviour under different friction coefficient conditions are analyzed quantitatively and qualitatively. Results reveal that powder densification occurs in distinct stages, with lower friction coefficients promoting greater powder densification, as observed from relative density and coordination number. Additionally, as the axial strain increases, plastic strain gradually rises whilst roundness decreases. Higher friction coefficients are associated with higher equivalent plastic strain but lower powder roundness. The Von Mises stress exhibits different stages of increase with the increment of axial strain. Powders with lower friction coefficients exhibit lower levels of Von Mises stress. As axial strain increases, the number, length, strength and direction coefficient of force chains undergo different evolution processes. Force chains exhibit longer length, fewer numbers, lower strength and lower direction coefficients at lower friction coefficients.

Study on the Characteristics of Steel Slag and its Road Performance in Asphalt Mixture

Based on the characteristics of steel slag, the application progress of steel slag as aggregate in asphalt mixture is summarized. Firstly, the differences in mechanical properties, chemical composition and physical structure of steel slag aggregates treated by different methods are summarized. The surface structure of steel slag is rough and rich in edges and corners, showing good wear resistance and crushing resistance, but there are also problems such as high density, high water absorption and volume instability. Among them, volume instability is the key factor affecting the application of steel slag in asphalt mixture. Then, the effects of steel slag aggregate on the road performance of asphalt mixture, such as water stability, rutting resistance, high temperature stability and low temperature cracking resistance, are summarized in detail. It is found that steel slag instead of coarse aggregate in asphalt mixture can improve the performance of skid resistance, rutting resistance and fatigue resistance. The water damage performance is due to the different sources of steel slag, and the uncertainty of the change results is large. On the whole, steel slag instead of aggregate can improve the road performance to a certain extent, but the volume of steel slag aggregate is unstable, which may bring some variability. In the process of road application, targeted regulation should be carried out to ensure the stability of asphalt mixture performance.

Equivalent Simulation Study of Delta-Rotor Engine

The mechanical structure, movement mode, and combustion process of a triangular rotor engine differ from those of a conventional engine with a crank connecting rod mechanism as the core. This makes it impossible to directly use existing simulation software to simulate the performance of the entire engine, rendering it difficult to conduct structural evaluation and performance prediction during the engine development stage. Therefore, using existing performance simulation software to establish a performance-equivalent model for a triangular rotor engine is crucial. To solve the above problems, this study proposes a performance-equivalent simulation modelling method for a triangular rotor engine based on a three-dimensional simulation model and the operating principles of the triangular rotor and four-stroke engines. Compared to various performance indicators obtained from the three-dimensional simulation model, the results show that the equivalent model established in this study has sufficient accuracy for key indicators such as the cylinder pressure, cylinder temperature, and in-cylinder quality under various working conditions. This can satisfy the requirements of the complete machine-performance simulation of a triangular rotor engine.

A temperature rise calculation model of wind turbine gearbox gear considering crack fault and tooth number difference

AbstractThe crack fault of gear is usually accompanied by temperature rise. Therefore, to master the temperature characteristics of the cracked gear of the wind turbine gearbox, a temperature rise calculation model of wind turbine gearbox gear considering crack fault and tooth number difference is proposed. Firstly, the time‐varying meshing stiffness model of the cracked gear considering the tooth number difference is established based on the potential energy method. Secondly, the calculation method of the meshing surface normal load of the cracked gear is deduced. Thirdly, the temperature rise calculation model of the meshing surface of the cracked gear is constructed based on Blok flash temperature theory. Finally, the data of the high‐speed gear of a wind turbine gearbox in northern China is selected for simulation verification. By comparing with the finite element method, the effectiveness of the proposed method is verified. The simulation results reveal the gear temperature characteristics of the wind turbine gearbox with different crack ratios. The research can provide some theoretical support for the accurate fault diagnosis and maintenance of wind turbine gearbox, and can also be applied to the fault diagnosis of gear cracks in other mechanical structures with a large transmission ratio.