Part Of Complex Mechanism Research Articles

An investigation of prototype development using 3D printer: A digital fabrication approach

Abstract Additive manufacturing (AM) is a widely used technique in several industries for rapid prototyping and layer-by-layer fabrication of a new product. The influence of printer settings and print quality is essential for the performance of products in a variety of applications. The popularity of manufacturing using 3D printing is growing rapidly. In view of this, an investigation is carried out on the 3D printing techniques, their applications, and prototype materials for complex mechanical parts such as an impeller. The present study thoroughly considers the fundamental techniques in 3D printing technology, materials, and recent advancements applied to the current application and accepted trends. The 3D printing technology is advantageous as it accepts a wide range of designs, allows customized manufacturing, minimizes waste, builds intricate structures, and creates prototypes rapidly. Layer height of 0.2 mm, speed of 90 mm/s, and infill density of 80% were determined as the optimal print settings considering time, material cost, and properties. Considering the flexural qualities, the optimized values of layer height, print speed, and infill density were 0.15 mm, 70 mm/s, and 50%, respectively. It was observed that the uniform elongation (UEL) and ultimate stress (UTS) of a component increase as the layer thickness increases for the considered layers.

Isogeometric Size Optimization Design Based on Parameterized Volume Parametric Models

Traditional structural optimization design methods are based on the finite element analysis(FEA), which makes it difficult to construct a direct relationship between the design parameters and the design objective parameters in the structural design process. The FEA method needs to convert the models back and forth between the design model and the analysis or optimization model during the design process. It is a cumbersome and time-consuming work and also affects the analysis accuracy. We propose an integrated design method that seamlessly integrates process of design, simulation and optimization based on uniformity of design models, analysis models and optimization models by benefiting the advantages of volume parameterization and isogeometric analysis(IGA). The size parameters are input as high-level parameters, then the middle parameters are obtained through hierarchical mapping. Based on these parameters, the semantic feature framework composes of feature points, feature curves and feature surfaces and even feature volume is gradually constructed. By extracting paths and sections, the geometric feature framework is generated. The paths and sections are segmented to form the volume parametric sub-patches through volume parametric mapping. These sub-patches are merged into a whole volume parametric model that can be used for IGA and size driven deformation. Based on volume parametric model, a mathematical relationship is constructed between the design objective parameters and the size design parameters. Through the mathematical relationship, the sensitivity equations are derived for sensitivity analysis. Finally, an isogeometric size optimization process is complete. Thus, an integration of design process including geometric modeling, performance analysis, and structural optimization is achieved. Taking the maximum stiffness and the minimum stress as the size optimization objectives, the integrated design examples fall into four groups including single size optimization, multi sizes non-coupled optimization, multi sizes coupled optimization, and complex mechanical structure optimization. The optimization results prove that our method is effective, and it can be applied on complex mechanical parts. The designed results do not require reconstruction, thus achieving the integrated and optimized design of mechanical structures.

Correlation between Microstructural Properties and Electric Parameters of Micro-Arc Oxidation Coatings on 5052 Aluminum Alloys with Improving Wear and Corrosion Resistance

Aluminum (Al) alloys are lightweight and machinable and have been widely used in industrial applications, particularly the formation of complex mechanical parts. However, the 5052 Al alloy frequently encounters problems like corrosion and wear during its service life, significantly impacting the equipment’s longevity. This study investigated the effects of pulse voltage (320 to 400 V) and frequency (50 to 200 Hz) on the growth and surface morphology of 5052 Al alloy films formed through micro-arc oxidation (MAO) to improve their corrosion and wear resistance while maintaining a surface roughness of less than 1 μm. The results indicate that higher operating voltages and frequencies correlated with increased thickness in the resulting ceramic oxide films formed using MAO. In addition, as the pulse frequency increased, the distribution of the holes became more uniform across the surface. We examined the surface and cross-sectional morphology, as well as the thickness of the MAO coatings, through scanning electron microscopy (SEM). The corrosion and wear resistance of the MAO coatings formed under different electrical parameters were analyzed using electrochemical corrosion tests and scratch tests. The MAO coatings produced at 400 V and 200 Hz were the thickest, at approximately 4.8 μm, and demonstrated superior corrosion and wear resistance. These coatings demonstrate significantly reduced wear width, highlighting their exceptional resistance to corrosion and wear. Hole cracking occurred only above the top layer of the coating and not beneath the mid-layer, which protected the substrate from damage due to the direct passage of Cl ions through the holes.

Electro‐Reconfigurable Adaptive Microlens with Simultaneous Multidirectional Focal Adjustment and Zooming

AbstractElectrically reconfigurable lenses capable of focal adjustment and zooming require deformable adaptive optical components. However, existing electroactive optical devices that perform these functions are limited by fluid leakage or require complex mechanical parts. Although polyvinyl chloride (PVC) gel‐based lenses with variable focal lengths and zooming have recently been developed, focal adjustment can only be made in the horizontal axis. Herein, a PVC gel‐based adaptive microlens capable of controlling the focal length and focal point simultaneously in the vertical, horizontal, and diagonal directions without mechanical gears or liquid leakage is presented. By optimizing the characteristics of PVC gels plasticized with three different structured plasticizers, a PVC gel‐based adaptive microlens is fabricated. The produced microlens demonstrates the properties of multidirectional focal adjustment, variable focal length (+33.7 to −15.1 mm) at low input voltages (<300 V), excellent transparency (>90%), fast response (0.10 s at 100 V), silent operation, low power consumption (0.39 mW), and excellent potential for further miniaturization.

Large depth-of-field image fusion method for complex gyration class mechanical parts

The local regions of complex gyration class mechanical parts are largely different, which results in the problem that their surface images are partially clear. This problem directly affects the effectiveness of vision methods on detecting surface defects. To tackle this problem, a large depth-of-field (DoF) surface image fusion method is proposed to obtain a full-focus image of complex mechanical parts, such as gyration class mechanical parts. We design an image acquisition platform based on the characteristics of gyration class parts to acquire their surface images accurately and clearly. We then propose a feature detection-based image registration method, by which the registered image can represent the surface information of the part completely and accurately. Additionally, we adopt a convolutional neural network-based image fusion method to achieve a fused large DoF surface image. Experimental studies were conducted to evaluate the performance of the deep-learning-based methods. The experimental results show that the proposed method can completely and clearly fuse the large DoF surface images of complex gyration class mechanical parts. The quality of the fused images has a significant improvement, and the proposed method is significantly more efficient than traditional fusion methods and other deep-learning methods.

Plastic design and strength on automotive hard trims doghouse

Trims are the plastic parts installed on the inside and outside of a car. Interior trims are typically used to give the interior of a vehicle an aesthetic appearance.There are various types of trims used in automobiles. The door's inner mechanisms and the vehicle's interior are connected by the door panel, as are the passengers inside the car and the door. They must adhere to a number of design requirements in terms of functionality, appearance, and safety. They should also maintain the dashboard's material theme while hiding complex electrical and mechanical parts that control the vehicle's locks, windows, and other features. From a straightforward latch and winding mechanism in two parts, the door panel has developed into a more complex enclosure. Currently, doors have an inner full-width panel with speakers, electronic windows, and a central locking system. These panels typically have a foamed core that is covered in either plastic or textiles. Trim manufacturing requires a lot of essential plastic material properties, such as restraining the passengers from the sharp edges and corner points of the BIW parts and underlying components.

A New Approach of Modelling Bottom Edge Cutting in 4-Axis Rough Milling of Complex Parts and Its Application on Feed Rate Optimization.

Complex mechanical parts such as a blisk of aero-engines are commonly used in aerospace industry. These parts are complex in shape and their rough machining are conducted in 4-axis machine tools with end mills. The end mills are fully engaged into the workpiece material to be removed. Because of the complex cutter motion in 4-axis milling, the bottom edges of the end mills are involved in cutting with high possibility, resulting in an undesirable increase of cutting forces, tool deflection, and quick tool wear. To address this technical challenge, an analytical method is proposed to identify and evaluate the bottom edge cutting in 4-axis milling in this work. The motion of the cutter's tool tip with respect to the workpiece is analyzed and the equations are formulated based on a basic interpolation algorithm. An approach to identifying and evaluating the bottom edge cutting is proposed. The increment of the cutting forces caused by the bottom edge cutting is taken into consideration to precisely evaluate the overall cutting forces. A feed rate optimization model is then established to control the cutting forces. The simulation and the experiment of rough milling of a blisk verify that the bottom edge cutting can be identified and the cutting force can be controlled by optimizing the feed rates without losing much machining efficiency.

High-precision 3D reconstruction method for topography measurement of complex mechanical parts

High-precision 3D reconstruction method for topography measurement of complex mechanical parts

Nonlinear Identification with Constraints in Frequency Domain of Electric Direct Drive with Multi-Resonant Mechanical Part

Knowledge of a direct-drive model with a complex mechanical part is important in the synthesis of control algorithms and in the predictive maintenance of digital twins. The identification of two-mass drive systems with one low mechanical resonance frequency is often described in the literature. This paper presents an identification workflow of a multi-resonant mechanical part in direct drive with up to three high-frequency mechanical resonances. In many methods, the identification of a discrete time (DT) model is applied, and its results are transformed into a continuous-time (CT) representation. The transformation from a DT model to a CT model has limitations due to nonlinear mapping of discrete to continuous frequencies. This problem may be overcome by identification of CT models in the frequency domain. This requires usage of a discrete Fourier transform to obtain frequency response data as complex numbers. The main work presented in this paper is the appropriate fitting of a CT model of a direct-drive mechanical part to complex number datasets. Fitting to frequency response data is problematic due to the attraction of unexcited high frequency ranges, which lead to wrong identification results of multi-mass (high order) drive systems. Firstly, a CT fitting problem is a nonlinear optimization problem, and, secondly, complex numbers may be presented in several representations, which leads to changes in the formulation of the optimization problem. In this paper, several complex number representations are discussed, and their influence on the optimization process by simulation evaluation is presented. One of the best representations is then evaluated using a laboratory setup of direct drive with unknown parameters of three high mechanical resonance frequencies. The mechanical part of the examined direct drive is described by three mechanical resonances and antiresonances, which are characteristic of a four-mass drive system. The main finding is the addition of frequency boundaries in the identification procedure, which are the same as those in the frequency range of the excitation signal. Neither a linear least-square algorithm nor a nonlinear least-square algorithm is suitable for this approach. The usage of nonlinear least-square algorithm with constraints as a fitting algorithm allows one to solve the issue of modeling multi-mass direct-drive systems in the frequency domain. The second finding of this paper is a comparison of different cost functions evaluated to choose the best complex number representation for the identification of multi-mass direct-drive systems.

Research on Customized Method of Post-processing of DMU125P Five-axis Machine Tool

With the increasing improvement of China’s industrial production technology, more and more attention is paid to the application of new five-axis CNC machine tools, and it is also urgent to strengthen the post-processing design. However, there are still many problems in the post-processing of DMU125P five-axis machine tools at this stage. The method is analyzed by combining the post-processing requirements of the DMU125P five-axis machine tool. At the same time, most studies in recent years have found that the use of post-processing application design is critical to improving the processing of complex mechanical parts. This study will analyze the post-processing customization method of the DMU125P five-axis machine tool, and provide a basis for the next step of work.

A Framework for Cloud Inspection of Complex Mechanical Parts

Inspection plays an important role in quality control and trust of manufacturing service in the cloud manufacturing (CMfg) paradigm. To provide an inspection service for complex mechanical parts in CMfg, the concept of cloud inspection was defined as a multi-dimension extension of CMfg. A framework of cloud inspection consisting of the physical resource layer, the cloud inspection platform, and the application layer was constructed. The data model of cloud inspection, including the role model, resource model, and business model was constructed. Besides, a 4-phrase process model was built by integrating digital inspection technology into the cloud manufacturing environment. Inspection resources including hardware resources, software resources, and knowledge resources were connected to the cloud inspection platform. A four-level model was proposed for the encapsulation of inspection services. Enable toolsets for cloud inspection of complex mechanical parts, including the inspection planning toolset, measurement programming toolset, inspection process monitor toolset, and data analysis toolset were encapsulated. A prototype system was developed. A case study was given to verify the effectiveness and feasibility of the proposed framework. The framework for cloud inspection provides a solution for the inspection business of mechanical parts in CMfg.

Acoustic bubble-based drug manipulation: Carrying, releasing and penetrating for targeted drug delivery using an electromagnetically actuated microrobot

This paper presents a new type of microrobotic drug delivery technology where an electromagnetically actuated untethered microrobot swimming inside human blood vessels performs targeted drug delivery operations: carrying, releasing, and penetrating drugs to target tissues using acoustic excitation of bubbles. The novel microrobot is capable of not only transporting liquid forms of drugs in an aqueous medium but also wirelessly manipulating drugs without using complex mechanical parts. For the electromagnetic actuation of a microrobot, an electromagnetic system consisting of a pair of Helmholtz and Maxwell electric coils is fabricated. Using the developed electromagnetic system, the actuation of the microrobot made of a cylindrical neodymium magnet is successfully demonstrated in a T-shaped channel. For the drug manipulation, selective acoustic excitation of bubbles is investigated. The drug release actuation is studied using a microtube which is a drug container consisting of two bubbles with different volumes. Then, the effect of acoustic bubble-induced microstreaming on the drug penetration to tissues is investigated for three different conditions: pure diffusion, penetration with an acoustic wave, and microstreaming using an agarose gel. As a proof of concept, the proposed sequential drug manipulation (carrying, releasing, and penetrating) is experimentally demonstrated using the prototype of a microrobot enabling propulsion in a low Reynolds number environment using an electromagnetic system and drug manipulation using acoustic bubbles in a C-shaped channel filled with liquid. The proposed microrobot can be applied to various biomedical applications such as targeted drug delivery, cell manipulation, and microsurgery.

Powder Bed Fusion of Biomedical Co-Cr-Mo and Ti-6Al-4V Alloys: Microstructure and Mechanical Properties

Powder bed fusion (PBF) is an additive manufacturing technique, which allows to build complex functional mechanical parts layer-by-layer, starting from a computer-aided design (CAD) model. PBF is particularly attractive for biomedical applications, where a high degree of individualization is required. In this work, the microstructure of two biomedical alloys, namely Co-Cr-Mo and Ti-6Al-4V, were studied by X-ray diffraction and electron microscopy techniques. Hardness and tensile tests were performed on the sintered parts.

Parametric Study on Vibration Response for Automobile Crankshaft

In the interest of utilized more stable automobile components at high speed for reduction the vibration of mechanical system, dynamic characteristics analysis plays a vital role in complex mechanical parts. Factors influencing on the level of vibration response were determined and optimized by the approach of experimental design. Based on golbal and local proerties of crankshaft structural properties, it was found that main journal diameter and Young’s modulus were recommended as inital values. Modification of crankshaft structure was performed carefully with the aspect of compatitablity for engine equipment. The reduction of vibration response was achieved and structure resonance has been shifted toward higher frequency domain. This approach proposed for the optimizing the structural parameters and would provide potential value basis to qualitative measure of parameters and determination of optimized structure.

Neural State Estimator for Complex Mechanical Part of Electrical Drive: Neural Network Size and Performance of State Estimation

Abstract This paper presents the results of simulation research of an off-line-trained, feedforward neural-network-based state estimator. The investigated system is the mechanical part of an electrical drive characterised by elastic coupling with a working machine, modelled as a dual-mass system. The aim of the research was to find a set of neural network structures giving useful and repeatable results of the estimation. The mechanical resonance frequency of the system has been adopted at the level of 9.3-10.3 Hz. The selected state variables of the mechanical system are load, speed and stiffness torque of the shaft.

A 2-Speed Small Transmission Mechanism Based on Twisted String Actuation and a Dog Clutch

In this letter, we propose a 2-speed small transmission mechanism based on twisted string actuation (TSA). The proposed mechanism achieves a compact and simplified two-stage transmission ratio by adjusting the radius of the twisted string. This transmission mechanism does not require the complex mechanical parts and mechanisms of conventional transmission systems. In addition, the mechanism can achieve a braking effect without an additional mechanical component via the nonlinearity of the rotational-linear transmission provided by TSA. The prototype is sufficiently small to be embedded in a robot hand and can be easily installed in a small robotic system. This mechanism can provide an energy-efficient driving strategy and a wider driving range for small robot systems.

Rapamycin increases oxidative metabolism and enhances metabolic flexibility in human cardiac fibroblasts.

Inhibition of mTOR signaling using rapamycin has been shown to increase lifespan and healthspan in multiple model organisms; however, the precise mechanisms for the beneficial effects of rapamycin remain uncertain. We have previously reported that rapamycin delays senescence in human cells and that enhanced mitochondrial biogenesis and protection from mitochondrial stress is one component of the benefit provided by rapamycin treatment. Here, using two models of senescence, replicative senescence and senescence induced by the presence of the Hutchinson-Gilford progeria lamin A mutation, we report that senescence is accompanied by elevated glycolysis and increased oxidative phosphorylation, which are both reduced by rapamycin. Measurements of mitochondrial function indicate that direct mitochondria targets of rapamycin are succinate dehydrogenase and matrix alanine aminotransferase. Elevated activity of these enzymes could be part of complex mechanisms that enable mitochondria to resume their optimal oxidative phosphorylation and resist senescence. This interpretation is supported by the fact that rapamycin-treated cultures do not undergo a premature senescence in response to the replacement of glucose with galactose in the culture medium, which forces a greater reliance on oxidative phosphorylation. Additionally, long-term treatment with rapamycin increases expression of the mitochondrial carrier protein UCP2, which facilitates the movement of metabolic intermediates across the mitochondrial membrane. The results suggest that rapamycin impacts mitochondrial function both through direct interaction with the mitochondria and through altered gene expression of mitochondrial carrier proteins.

Prediction Model of Machining Failure Trend Based on Large Data Analysis

The mechanical processing has high complexity, strong coupling, a lot of control factors in the machining process, it is prone to failure, in order to improve the accuracy of fault detection of large mechanical equipment, research on fault trend prediction requires machining, machining fault trend prediction model based on fault data. The characteristics of data processing using genetic algorithm K mean clustering for machining, machining feature extraction which reflects the correlation dimension of fault, spectrum characteristics analysis of abnormal vibration of complex mechanical parts processing process, the extraction method of the abnormal vibration of complex mechanical parts processing process of multi-component spectral decomposition and empirical mode decomposition Hilbert based on feature extraction and the decomposition results, in order to establish the intelligent expert system for the data base, combined with large data analysis method to realize the machining of the Fault trend prediction. The simulation results show that this method of fault trend prediction of mechanical machining accuracy is better, the fault in the mechanical process accurate judgment ability, it has good application value analysis and fault diagnosis in the machining process.

Structure and Mechanical Properties of Aluminium Alloys AlSi10 and AlSi5Mg

The article presents the microstructure and mechanical properties of two types of aluminium alloys AlSi10 and AlSi5Mg. The structure and mechanical properties as a tensile test of two alloys AlSi10 and AlSi5Mg were studied and compared. Gravity casting is very good process for making complex mechanical parts of low density metals like aluminium alloys. Therefore our samples are prepared by gravity casting technology. Light metals have come to the forefront in the automotive industry and improved fuel economy. Therefore, we compared the AlSi5Mg alloy with a commonly used alloy AlSi10. This type of alloy AlSi5Mg has excellent casting and technological properties (good machinability and corrosion resistance). We are engaged with the issue of the production of castings for the automotive industry, at our department the Department of Engineering Technology-Technical University of Liberec, many years. Currently, we are focusing on aluminium alloys, their metallurgy and crystallization conditions with minimal internal defects.

The Role of WD40-Repeat Protein 62 (MCPH2) in Brain Growth: Diverse Molecular and Cellular Mechanisms Required for Cortical Development

Genetic disruptions of spindle/centrosome-associated WD40-repeat protein 62 (WDR62) are causative for autosomal recessive primary microcephaly (MCPH) and a broader range of cortical malformations. Since the identification of WDR62 as encoded by the MCPH2 locus in 2010, recent studies that have deleted/depleted WDR62 in various animal models of cortical development have highlighted conserved functions in brain growth. Here, we provide a timely review of our current understanding of WDR62 contributions in the self-renewal, expansion and fate specification of neural stem and progenitor cells that are critical for neocortical development. Recent studies have revealed multiple functions for WDR62 in the regulation of spindle organization, mitotic progression and the duplication and biased inheritance of centrosomes during asymmetric divisions. We also discuss recently elaborated WDR62 interaction partners that include Aurora and c-Jun N-terminal kinases as part of complex signalling mechanisms that may define its neural functions. These studies provide new insights into the molecular and cellular processes that are required for brain formation and implicated in the genesis of primary microcephaly.