Strojniški vestnik - Journal of Mechanical Engineering

Design of 3D Printed Below-Knee Prosthetic - A Finite Element and Topology Optimization Study

2024-09-06T10:31:58+00:00

There are approximately 35 to 40 million people worldwide who require assistive devices, including prosthetics and orthoses. Most amputee patients have a lower amputation. The high cost of prosthetics, long production and delivery times, the frequent need for prosthetics in growing children and limited accessibility to prosthetics are common complaints of amputees. This study aims to design and fabricate a lightweight, high-strength, low-cost and easily accessible three dimensional (3D) printed below-knee prosthetic leg without support material to improve the quality of life of amputees. First, a flexible and jointless one-piece below-knee prosthetic leg model was designed by considering the anthropometric data of children who frequently require prosthetics. Then, using the finite element and topology optimization methods, an optimized prosthetic leg model was developed according to the results of structural analyses performed by considering the loading conditions and boundary conditions during daily activities such as standing, walking, ascending and descending stairs. Finally, the prosthetic model was modified for a support-free additive manufacturing process and a socket and heel piece were added. The designed prosthetic leg model was fabricated using the additive manufacturing method with hard thermoplastic polyurethane (TPU) material. The final prosthetic leg design achieved a safety factor of 4.14 and a weight reduction of 50.37 % compared to the solid model. In addition, a 50 % reduction in material usage and a 32 % reduction in fabrication time were achieved through topology optimization and support-free design.

Acceleration Harmonic Estimation and Suppression for Hydraulic Load Simulator Based on Artificial Bee Colony with Chaotic Search Strategy

2024-08-05T05:33:26+00:00

This paper presents a new hybrid algorithm based on artificial bee colony (ABC) and chaotic search strategy (CSS), known as ABC-CSS to solve the harmonic estimation problems in the case of time varying acceleration response signal. The ABC algorithm simulates the intelligent behavior of bees in nature to find high-quality nectar sources according to different divisions of labor. Aiming at the lack of diversity, poor global and local search ability, as well as slow convergence speed of ABC, an improved ABC based on CSS is proposed. The algorithm generates new neighborhood points by the transformation of chaotic and decision variables by carrier mapping, which provides a broader search space and better location of nectar sources for bees and recruited observation bees, and enhances the diversity of bee colonies. At the same time, the investigation of a local honey bee search better solves the algorithm problem of the local minimum and improves the convergence property of the ABC. Simulation and experimental studies are conducted to validate the superiority of the proposed ABC-CSS in harmonic estimation.

Optimization of Outer-Rotor Flux-Switching Permanent Magnet Motor Using Response Surface Method

2024-06-19T09:21:37+00:00

Flux switching permanent magnet (FSPM) motors, especially outer-rotor FSPM (OR-FSPM), have caught our attention due to their advantages such as robust structure, torque density, energy density, and fault tolerance. However, the double salient pole structure of OR-FSPM motor causes large torque fluctuation, which will lead to the motor running unstably, poor working accuracy, and difficulty achieving good motor control. Therefore, this paper presents an optimization process for an OR-FSPM as motor/generator in flywheel energy storage systems (FESS). First, an initial 12/10 OR-FSPM is investigated through the finite element method (FEM). Second, the influences of single variables such as stator slot width, rotor tooth width, and air-gap length on the torque performance are studied. Third, a multi-variable optimization is processed through the response surface method (RSM) combined with FEM. Finally, the optimized 12/10 OR-FSPM is verified through FEM. The results of the initial structure and the optimized structure show that the average torque of the optimized motor is increased by 3.7 %, and the torque ripple is reduced by 36.06 %. In addition, the back-electromagnetic force (back-EMF) amplitude of the optimized motor is sharply reduced from 283.1 V to 192.8 V.

Improving the Efficiency of Steel Plate Surface Defect Classification by Reducing the Labelling Cost Using Deep Active Learning

2024-10-08T07:34:43+00:00

Efficient surface defects classification is one of the research hotpots in steel plate defect recognition. Compared with traditional methods, deep learning methods have been effective in improving classification accuracy and efficiency, but require a large amount of labeled data, resulting in limited improvement of detection efficiency. To reduce the labeling effort under the premise of satisfying the classification accuracy, a deep active learning method is proposed for steel plate surface defects classification. Firstly, a lightweight convolutional neural network is designed, which speeds up the training process and enhances the model regularization. Secondly, a novel uncertainty-based sampling strategy, which calculates Kullback-Leibler (KL) divergence between two kinds of distributions, is used as an uncertainty measure to select new samples for labeling. Finally, the performance of the proposed method is validated using the steel surface defects dataset from Northeastern University (NEU-CLS) and the milling steel surface defects dataset from a local laboratory. The proposed global pooling-based classifier with global average pooling (GAPC) network model combined with the Kullback-Leibler divergence sampling (KLS) strategy has the best performance in the classification of steel plate surface defects. This method achieves 97 % classification accuracy with 44 % labeled data on the NEU-CLS dataset and 92.3 % classification accuracy with 50 % labeled data on the milling steel surface defects dataset. The experimental results show that the proposed method can achieve steel surface defects classification accuracy of not less than 92 % with no more than 50 % of the dataset to be labeled, which indicates that this method has potential application in surface defect classification of industrial products.

Gear Differential Flank Modification Design Method for Low Noise

2024-09-16T07:44:59+00:00

To address the limitations of existing gear tooth modification methods, a differentiated tooth modification method is proposed, where the modification amount of adjacent teeth varies according to a sine function. Initially, a mathematical model of the gear tooth profile varying according to a sine function is established. Then, using Adams software, a simulation analysis of the dynamic characteristics such as centroid angular acceleration, meshing force, and transmission error of gear pairs is conducted. The dynamic transmission performance of three sets of gear pairs—unmodified, normally modified, and differentially modified—is compared. Additionally, Simcenter 3D software is used to analyze the noise characteristics of these gear pairs. The results show that the differentially modified gear pairs, compared to the normally modified ones, have a maximum reduction of 2.47 % in sound power level at the fundamental meshing frequency amplitude. This proves that the differentiated modification method enhances the dynamic transmission performance of gears, offering a new method for gear vibration and noise reduction.

The Impact of Micro-texture Distribution on the Frictional Performance of Straight Bevel Cylindrical Gears

2024-09-09T09:41:59+00:00

In order to alleviate wear on the tooth surfaces during gear transmission and to enhance the anti-seizing capabilities of the tooth faces, this paper proposes micro-textured gears as a solution to this challenge. Firstly, three types of micro-textured gears were designed based on the mechanism of action of micro-textures and the meshing positions during gear transmission. Secondly, finite element simulation tests were conducted with and without micro-textured gears, and the stresses, strains, and wear levels experienced by the micro-textured gears during transmission were analyzed. The study found that torque and rotational speed have a direct impact on the gear surface. Compared to traditional gears, gears with micro-textures distributed above the pitch circle promoted a 51.57% reduction in stress and a 61.81% reduction in strain, also altering the concentration locations of stress and strain on the tooth surfaces, which led to a 50.51% reduction in wear. This research has significant implications for improving the frictional performance of gears, with micro-textures on the tooth surfaces acting as containers for lubricants and metal filings, preventing abrasive wear of the friction pairs on the tooth faces and enhancing the durability of the gears.

Experimental Investigation on SS202 using Tubular and Double D Tubular Electrode Tool in Electrical Discharge Drilling Machining

2024-10-04T12:07:02+00:00

To meet the demands of the manufacturing industry, a more robust approach is needed for current manufacturing processes. Machining of very hard materials with excellent dimensional accuracy and surface integrity is a challenging task, Currently, the electrical discharge machining (EDM) process is the optimal solution for machining such materials. Electrical discharge drilling machines find applications in various sectors such as aerospace, automobile and medicine. In this research, two different brass electrode geometries are considered: tubular electrode tool (TET) and double D tubular electrode tool (DDTET) on an SS202 work-piece. The input parameters of peak current (PI), pulse time ON (PONT), and pulse time OFF (POFFT) were varied. The output response measured and compared were material removal rate (MRR) and over cut (OC). The Taguchi technique was used to design the l16 orthogonal array (OA) experiment, and analysis of variance (ANOVA) was employed for result analysis using Minitab20 statistical software package. The results showed that the DDTET method produced significantly better MRR and OC improvements of 21.66 % and 2.28 % respectively. Additionally, a study was conducted on the formation of the recast layer (RL) and the heat affected zone (HAZ).

The Impact of the Geometry of Cellular Structure Made of Glass-Filled Polyamide on the Energy-Absorbing Properties of Design Elements

2024-06-19T12:31:37+00:00

Energy-absorbing properties of cellular materials with D, G, IWP*, N, P, Q, PJ triply minimal energy surface geometries were investigated. Materials were made of glass-filled polyamide by selective laser sintering. Mechanical properties of cellular structures were determined depending on the geometry: the highest specific compressive strength σsp.max >8 MPa∙cm3/g is possessed by samples with the geometry IWP* and PJ; the highest specific energy absorption Asp = 14.5 MJ/m3 is in the sample with the geometry N. A mass-strength criterion for cellular structures is proposed. The maximal values of mass-strength criterion are from samples with geometries N, IWP* and PJ; 4.16 MPa2/g, 3.51 MPa2/g, and 2.88 MPa2/g. The adequacy of applying the Gibson-Ashby equation for fabricated cellular materials with triply periodic minimal surfaces (TPMS) geometry has been proven.