Advances in Mechanical Engineering

Hoyos, Elizabeth; Serna, María Camila; Gutiérrez, Sebastián; Montoya, Yesid; Córdoba, Jorge Hernán; Palacio, Mauricio Enrico; Álvarez, Iván

doi: 10.1177/16878132241307275pmid: N/A

Urban transportation systems, such as Metro de Medellín’s aerial cableways, play a key role in improving city connectivity. This study presents a Finite Element Analysis (FEA) of critical mechanical components that connect cable cars to ropeways, specifically focusing on the Connection and Suspension assembly, referred to as the J-H assembly. The primary aim was to identify potential operational vulnerabilities. The analysis follows the BS EN 13796-1:2017 standard, which provides design guidelines for cable car structural components, and evaluates cases 8, 9 and 10 as benchmarks. FEA results indicate safety factors ranging from 1.62 to 2.24, with case 9 exhibiting a 31.3% deviation from the standard’s reference values. Stress concentrations were consistently found at the J-H assembly connection across all cases.

Punyakaew, Surat

doi: 10.1177/16878132241302029pmid: N/A

This paper presents a comprehensive analysis of an active pendulum vibration absorber (APVA) that utilizes a rotating inertia actuator (RIA) and takes into account the time delay in the position feedback. Here, the primary system is represented as a base-excited system, which includes a linear spring, damper, and mass. The absorber consists of a pendulum with a rotating inertia actuator attached to one end, a spring-damping system attached to the pendulum mass, and a delayed controller. The active control force is generated by the RIA in the proposed model, thereby preventing stroke saturation, an issue that may result in feedback controller instability. This is because, unlike proof mass actuators, the RIA does not have end-stops that limit its motion. The equations of motion describing the dynamical behavior of the primary system and APVA were derived and simulated in MATLAB Simscape and Simulink. Multi- frequency and harmonic base excitations are utilized as inputs. The simulation results show that the proposed APVA can greatly reduce vibration induced by the excitation of both single and multiple frequencies.

Wang, Baohua; Zhang, Jiacheng; Zhang, Yu; Wang, Weilong

doi: 10.1177/16878132241273524pmid: N/A

This paper introduced a hierarchical control strategy for direct yaw moment (DYC) to enhance the handling and stability of distributed drive electric vehicles (DDEVs) at medium to high speeds. The upper controller entailed a speed-following PI controller and an adaptive fuzzy linear quadratic regulator (AFLQR) controller, with the control objectives centered on reducing the absolute value of the sideslip angle and tracking the desired yaw rate. The proposed approach utilizes a fuzzy logic-based AFLQR controller, which could dynamically adjust the weighting parameters for sideslip angle and yaw rate in response to the vehicle speed and sideslip angle, offering better adaptability to varying driving conditions. At the lower control level, a tire-dynamic-load-based torque distribution method was applied. The control strategy’s efficacy was demonstrated through co-simulation involving CarSim and Simulink. This evaluation compared AFLQR control against non-yaw control, conventional LQR control and sliding mode control (SMC), focusing on handling and stability during sinusoidal steering wheel input test and double lane change maneuver. Results highlight that AFLQR reduces the sideslip angle by 7.88% and the yaw rate error by 84.29% compared to LQR, enhancing vehicle handling and stability. Lastly, a hardware-in-the-loop (HIL) experiment verified the control strategy’s validity.

Salazar, Maxwell; Rosero, Ricardo; Zambrano, Oscar; Portero, Paola

doi: 10.1177/16878132241307065pmid: N/A

This article explores the impact of 3D printing technology on prototyping low-cost robotic arm prosthetic. The research begins with a thorough analysis of the robotic arms currently available on the market, with the aim of identifying their characteristics, costs, and limitations. Based on this review, an in-house design is developed using simplified CAD software, tailored to optimize both functionality and production efficiency. The construction of the prototype is carried out using 3D printing, taking advantage of the capabilities of this technology to reduce costs and manufacturing times compared to traditional methods. The article details the design and printing process, highlighting key decisions made to maximize the economic viability of the project. Finally, a detailed analysis of the costs associated with the project is carried out, comparing the results obtained with the initial reference data. This analysis allows us to evaluate the effectiveness of 3D printing as a low-cost solution in the development of robotic prostheses, highlighting its economic benefits and potential areas for improvement. The findings suggest that 3D printing represents a promising alternative for the creation of accessible robotic prosthetic, with significant implications for cost reduction and democratization of access to new technologies.

Hou, Junming; Wang, Baosheng; Lv, Dongsheng; Xu, Changhong

doi: 10.1177/16878132241305588pmid: N/A

Machining chatter is likely to occur during milling of thin-walled parts. The structural differences in thin-walled parts and the magnitude of the milling force can lead to varying degrees of chatter in different areas of the machining process. Predicting machining stability using dynamic modeling methods can be time-consuming. In this study, a method for establishing a particle swarm optimization-back propagation (PSO-BP) neural network model is proposed to predict the modal parameters of thin-walled parts and the surface vibration of machined parts. Based on measurements of the length, height, wall thickness, and position of the thin-walled parts, the modal parameters of the workpiece were predicted using the PSO-BP neural network model. Additionally, the average milling force was included as an input parameter to predict the displacement of surface vibrations on thin-walled parts using the PSO-BP model. The predictive results of the modal parameters and surface vibration displacement are evaluated using the evaluation function, which indicates that the PSO-BP neural network model can reliably predict the modal parameters and surface vibration depth of thin-walled parts.

Zhou, Ruihu

doi: 10.1177/16878132241307714pmid: N/A

Due to the complexity of analyzing residual stress, which involves numerous cutting parameters encompassing both mechanical and thermal stresses, various modeling and simulation methods, including analytical, numerical, and machine learning approaches have been summarized. An analytical model for predicting 2D orthogonal cutting and 3D milling residual stress is presented based on the cutting mechanism as well as the loading and unloading history of the stress field. The advancement in computational methods has prompted a review of finite element methods and mesh-free methods along with their principles, advantages, disadvantages, and application fields. Furthermore, machine learning models are employed to predict and control cutting residual stress based on data-driven approaches. These include support vector regression machines, artificial neural networks, and gradient boosted trees. A significant challenge for future work lies in addressing multi-scale size cutting residual stresses through hybrid methodologies.

Qi, Yang; Meng, Zhiyong

doi: 10.1177/16878132241304256pmid: N/A

The manipulation of large workpieces often requires manipulators with complex structures and high stiffness to ensure stability and precision during operation. In situ processing equipment is typically employed for this purpose, comprising a mobile carriage (CGA), mechanical arms, and parallel processing units. The end mechanism of in situ processing equipment must exhibit high rigidity and a wide range of motion in order to effectively satisfy the high-efficiency processing requirements of large and complex structural components. This paper presents a comprehensive process for the topology synthesis of double-layer parallel mechanisms and conducts research on its topology synthesis. Firstly, a comprehensive analysis is conducted on the number and types of degrees of freedom required for basic tasks such as stretching, derotating, twisting, and grasping. This results in the simplest mathematical expression for continuous motion corresponding to the processing tasks. Subsequently, the double-layer superimposition principle of the parallel mechanism is elucidated in accordance with the requirements of the processing tasks. Proposed are anticipated motion patterns and allocation methods. Furthermore, the standard chains are analyzed and characterized based on the desired motion patterns. Derived standard chains that satisfy the desired motion patterns are obtained through joint equivalent transformations. Finally, the assembly conditions are determined in order to obtain the various available configuration structures that satisfy the processing requirements. This study proposes a novel manipulator design that can precisely control the motion of the end platform using only one set of drives, significantly improving the stability and precision of large workpiece manipulation, a challenge that has not been fully addressed in the existing literature. This provides a robust theoretical foundation for the subsequent development of in situ processing equipment.

Abbas, Munawar; Alotaibi, Hammad; Muhammad, Taseer; Ghazi, Hafiz Muhammad

doi: 10.1177/16878132241304602pmid: N/A

Graphical abstract

Wang, Fengfeng; Fan, Yechen

doi: 10.1177/16878132241304610pmid: N/A

The development of a versatile and reliable robotic arm for agricultural picking is essential for modern farming. This study presents the design of a picking robotic arm inspired by bionics principles. The end-effector features a parallel gripper structure to efficiently pick crops of various shapes and sizes, with finite element simulations confirming its structural rationality. The gripping force is measured by an LDTI-028K PVDF piezoelectric thin-film sensor, adjustable within a crop-safe range to prevent damage. Additionally, a new signal conditioning circuit is proposed to improve the signal-to-noise ratio by amplifying the sensor’s output signal and minimizing noise, addressing the relatively low surface charge produced by the PVDF film under external pressure. Adams simulation analyses show that the end-effector is highly adaptable. Furthermore, picking experiments demonstrate that the robotic arm can reduce costs and lower the attrition rate by approximately 23.2 ± 5% compared to manual picking, while also exhibiting high reliability and stability.

Zhufeng, Lei; Jialei, Wang; Yanlan, Guo; Xiaofang, Lei; Chuanghui, Zhou

doi: 10.1177/16878132241304606pmid: N/A

With the continuous development of economy and society, factors such as the variety of underwater targets and the high level of environmental noise have a great impact on the classification accuracy of underwater target radiation noise, and the traditional classification method based on signal features can no longer meet the requirements of underwater target identification. In this paper, we propose an underwater target radiation noise classification method based on enhanced image and convolutional neural network. First, the underwater target radiation noise signal is converted into enhanced image by various methods, then the converted image data set is used as the input of convolutional neural network for model training, and finally the great advantage of convolutional neural network in image classification is used to accurately classify underwater target radiation noise. In order to propose an optimal augmented image transformation method, this paper uses several augmented image transformation methods and compares the classification results. The experimental results show that the augmented image and convolutional neural network methods based on lagomorphs and corner fields have the highest classification accuracy and the best classification efficiency.