Concept Of Machine Research Articles

Torque Enhancement Principle of Stator PM Vernier Machine by Consequent Pole Structure

In this study, a torque enhancement principle for a stator permanent-magnet (PM) Vernier machine with a consequent pole structure is proposed. The novelty of the manuscript is the explanation of how stator PM Vernier machines benefit from consequent pole structure. Although a similar concept of stator PM Vernier machines with a consequent pole structure has been investigated in previous studies, a clear torque enhancement principle was absent. The keys to torque enhancement are the decrement of nonworking harmonics and increment of working harmonics. To demonstrate these phenomena, the torque contributions from the harmonics were calculated. Subsequently, the performances of the conventional machine and consequent pole machine were compared to verify the enhancement principle. The electromagnetic performances, including the back electromotive force and torque, were compared. The results show that the stator PM Vernier machine benefits significantly from torque enhancement using the consequent pole structure, and the torque enhancement principle was verified.

Turing Meets Shannon: On the Algorithmic Construction of Channel-Aware Codes

A capacity result involves two parts: achievability and converse. The achievability proof is usually non-constructive and only the existence of capacity-achieving codes is shown invoking probabilistic techniques. Recently, capacity-achieving codes have been found for several channels demonstrating that such codes can actually be constructed algorithmically. To this end, each construction is designed for a pre-specified channel so that the corresponding algorithm is specifically tailored to it. This paper addresses the general question of whether or not it is possible to find algorithms that can construct capacity-achieving codes for a whole class of channels. To do so, the concept of Turing machines is used which provides the fundamental performance limits of digital computers and therewith fully specifies which tasks are algorithmically feasible in principle. It is shown that there exists no Turing machine that is able to construct capacity-achieving codes for a whole class of channels, where the channel realization from this class is given as an input to the Turing machine. It is further shown that such an algorithmic construction remains impossible when the optimality condition is dropped and codes only need to achieve a fraction of the capacity. Finally, implications on channel-aware transmission, link adaptation, and cross-layer optimization are discussed.

Energy-efficient double belt press with integrated inductive heating system

At the Aachen Centre for Integrative Lightweight Production (AZL) of RWTH Aachen University a new double belt press with inductive heating and elastomer-coated pressure rollers has been developed and optimised within industrial AZL joint partner research projects. This machine system is patented by the AZL and available for industrial trials and also as commercial product in license. This new machine concept enables an efficient, continuous pressing process in a small installation space. The induction allows for a rapid heating of the steel belt material up to 300 °C and the elastomer pressure rollers enable surface contact during pressure application. The double belt press differs from conventional systems as it uses closed-loop controlled inductive heat input and high-temperature resistant elastomer-coated rollers for applying specific pressures up to 23 bar at maximum process temperatures up to 300 °C (current development for up to 400 °C). In extensive trials with several partners from the AZL partner network and external companies, the machine has proven to be efficient for consolidating thermoplastic composite laminates as well as for impregnating both thermoset and thermoplastic composite laminates.

Establishment the equivalent model and parameter calculation of a new concept of high-speed permanent magnet synchronous machine with hybrid excitation on the stator

In order to solve the problem that the permanent magnet on the rotor of high-speed permanent magnet synchronous machine (PMSM) is easy to be damaged by centrifugal force and easy to be affected by high temperature, which leads to non-reverse demagnetization, a new concept of high-speed permanent magnet synchronous machine with hybrid excitation on the stator (PMSMHES) is introduced in this paper. And its structure and electromagnetic parts are designed. PMSMHES uses a hybrid excitation method, so that the air gap magnetic field of the permanent magnet motor can be adjusted, thereby solving the problem of a narrow constant power range when the motor is running. Secondly, the equivalent magnetoelectric model of PMSMHES is proposed and the calculation method of related parameters is proposed. Finally, the rationality of the equivalent model and the calculation method of each parameter is verified by finite element simulation.

Generation of Cantor sets from fractal squares : A mathematical prospective

Fractal square is a concept evolved from mathematics, which subsequently achieved its importance in the area of computer graphics, pattern recognition, and machine vision to analyze or generate complex objects. The self-similarity and self-affine nature of fractals was introduced by Mandelbrot to create different patterns. Furthermore, the multiple reduction copy machine (MRCM) concept has been utilized for a long time in the design of fractals. Apart from this, some new programs have recently been employed in this area. However, all the existing models were limited in terms of their topological properties and not even concerned with the connected and disconnected set of fractals. Even the fractal square that is used to distinguish different distinct patterns is not being studied deeply. In this paper, we have focused on fractal square to generate cantor set by using its different topological properties in terms of disconnected fractal sets, designing the process of various patterns with the help of fractal square and to make a topological classification among them.

Modern Methodology for the Design of Advanced Electrical Machines and Electronics Units Based on FMEA Concept

In this work, a methodology for choosing the modern and advanced electrical machines and electronic units’ concept, based on FMEA, has been developed. The developed methodology for choosing the electrical machine and the electronic unit concept allows minimizing the probability of making an error at the initial stage of electrical machine and electronic unit design. As an example, the application of the developed methodology for choosing the modern and advanced electrical machine concept for small-sized aircraft generator has been considered. In order to verify the developed methodology for choosing the electrical machines and the electronic units’ concept, the small-sized aircraft generator has been designed according to the selected concept and the small-sized aircraft generator experimental studies have been carried out. The research results have proved the relevance of the application of the developed methodology for choosing the modern and the advanced electrical machines and electronic units’ concept.

Noise/fault aware regularization for incremental learning in extreme learning machines

This paper investigates noise/fault tolerant incremental algorithms for the extreme learning machine (ELM) concept. Existing incremental ELM algorithms can be classified into two approaches: non-recomputation and recomputation. This paper first formulates a noise/fault aware objective function for nonlinear regression problems. Instead of developing noise/fault aware algorithms for the two computational approaches in a one-by-one manner, this paper uses two representative incremental algorithms, namely incremental ELM (I-ELM) and error minimized ELM (EM-ELM), to develop two noise/fault aware incremental algorithms. The proposed algorithms are called generalized I-ELM (GI-ELM) and generalized EM-ELM (GEM-ELM). The GI-ELM adds k hidden nodes into the existing network at each incremental step without recomputing the existing weights. To have a fair comparison, we consider a modified version of I-ELM as a comparison algorithm. The simulation demonstrates that the noise/fault tolerance of the proposed GI-ELM is better than that of the modified I-ELM. In the GEM-ELM, k hidden nodes are added into the existing network at each incremental step. Meanwhile, all output weights are recomputed based on a recursive formula. We also consider a modified version of EM-ELM as a comparison algorithm. The simulation demonstrates that the noise/fault tolerance of the proposed GEM-ELM is better than that of the modified EM-ELM. Moreover, we demonstrate that the multiple set concept can further enhance the performance of the two proposed algorithms. Following our research results, one can make some non-noise/fault tolerant incremental algorithms to be noise/fault tolerant.

La dicotomía animal / humano en Canto villano (1978) de Blanca Varela

The animal / human dichotomy in Villain Song (1978) by Blanca Varela The article analyzes the work of Blanca Varela, the most important Peruvian poet of all time. She highlights the dichotomy between animal and human in her collection of poems Canto villano. The paper is based, above all, on the proposal of Giorgio Agamben, who questions the opposition between animal and human to suggest that there is a continuity between both living beings. Likewise, the concept of anthropology machine is used for the analysis of Blanca Varela’s poetry.

DESIGN AND CONSTRUCTION OF ROBOTIC ARM ON AUTOMATIC MIG WELDING ROBOT

Abstract: Tehnlogical advances to date have grown increasingly sophisticated technolgy, especially in robotic technogy which is currently developed to achieve work result that are make human work easier welding process with manual systems need to be switched to automatic systems. The mechanical concept of the arm that will be applied to Automatic Welding Carrier Machine by applying the mechanical concept of a 3D machine which is expected to increase mobility, working range of the tool as well as increasing the quality of automatic welding results. In this research, the method used is experimental research methods and simulations that aim to know the results of the analysis on the mechanics of the robot arm. The data generated after performing calculations with provide a load on the leadscrew of the compressive stress that occurs i the leadscrew is , the voltage bending is and the shear stress that occurs is , so that the lead crew is said to be able to encourge maximum allowable amount of . The torque required by the motor drive to push the received load on the Z ( ) axis is equal to , then the selection of the nema23 stepper motor is stated very capable as a robotic arm mover because have torque . With the loading of the 2020 profile arm rod at using ansys simulation, the maximum total deformation that may occur is , so that the 2020 profile rod can be said to be safe for use on Automatic Welding Carrier Machine.

Application of Machine Learning in Animal Disease Analysis and Prediction

Major animal diseases pose a great threat to animal husbandry and human beings. With the deepening of globalization and the abundance of data resources, the prediction and analysis of animal diseases by using big data are becoming more and more important. The focus of machine learning is to make computers how to learn from data and use the learned experience to analyze and predict. Firstly, this paper introduces the animal epidemic situation and machine learning. Then it briefly introduces the application of machine learning in animal disease analysis and prediction. Machine learning is mainly divided into supervised learning and unsupervised learning. Supervised learning includes support vector machines, naive bayes, decision trees, random forests, logistic regression, artificial neural networks, deep learning, and AdaBoost. Unsupervised learning has maximum expectation algorithm, principal component analysis hierarchical clustering algorithm and maxent. Through the discussion of this paper, people have a clearer concept of machine learning and an understanding of its application prospect in animal diseases.

RANCANG BANGUN MESIN PENGIRIS DAUN BAWANG DENGAN KAPASITAS 300 GRAM PER MENIT

<p class="TTPAbstract">The need for sliced scallions is relatively large, so a tool that can assist in the slicing process is more effective both in terms of energy and time spent. Based on these problems, the idea was born to design a scallion slicing machine to help the community in slicing scallions, especially food sellers who need scallions such as egg martabak sellers, and food sellers.</p><p class="TTPAbstract">The method used is literature study (library), field observations, and problem-solving methods in the form of design which includes pre-planning in the form of machine sketches, machine concept planning, calculations, making working drawings, procurement of materials and components, toolmaking, assembly, and testing.</p><p class="TTPSectionHeading">The output of this final project is the manufacture of a scallion slicing machine that is simple and effective by not forgetting the safety and hygiene factors so that it can support the slicing process at the scale of traders and home industries. This tool has a capacity of 300 grams per minute using a DC 775 motor and is sourced from four 18650 li-ion batteries.</p>

Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients

We address a new numerical method based on machine learning and in particular based on the concept of the so-called Extreme Learning Machines, to approximate the solution of linear elliptic partial differential equations with collocation. We show that a feedforward neural network with a single hidden layer and sigmoidal transfer functions and fixed, random, internal weights and biases can be used to compute accurately enough a collocated solution for such problems. We discuss how one can set the range of values for both the weights between the input and hidden layer and the biases of the hidden layer in order to obtain a good underlying approximating subspace, and we explore the required number of collocation points. We demonstrate the efficiency of the proposed method with several one-dimensional diffusion–advection–reaction benchmark problems that exhibit steep behaviors, such as boundary layers. We point out that there is no need of iterative training of the network, as the proposed numerical approach results to a linear problem that can be easily solved using least-squares and regularization. Numerical results show that the proposed machine learning method achieves a good numerical accuracy, outperforming central Finite Differences, thus bypassing the time-consuming training phase of other machine learning approaches.

Design Rules for Hybrid Additive Manufacturing Combining Selective Laser Melting and Micromilling.

We report on a comprehensive study to evaluate fundamental properties of a hybrid manufacturing approach, combining selective laser melting and high speed milling, and to characterize typical geometrical features and conclude on a catalogue of design rules. As for any additive manufacturing approach, the understanding of the machine properties and the process behaviour as well as such a selection guide is of upmost importance to foster the implementation of new machining concepts and support design engineers. Geometrical accuracy between digitally designed and physically realized parts made of maraging steel and dimensional limits are analyzed by stripe line projection. In particular, we identify design rules for numerous basic geometric elements like walls, cylinders, angles, inclinations, overhangs, notches, inner and outer radii of spheres, chamfers in build direction, and holes of different shape, respectively, as being manufactured by the hybrid approach and compare them to sole selective laser melting. While the cutting tool defines the manufacturability of, e.g., edges and corners, the milling itself improves the surface roughness to Ra < 2m. Thus, the given advantages of this hybrid process, e.g., space-resolved and custom-designed roughness and the superior geometrical accuracy are evaluated. Finally, we exemplify the potential of this particular promising hybrid approach by demonstrating an injection mold with a conformal cooling for a charge socket for an electro mobile.

A Newly Proposed Prospective and Robust Computer Networking Model Architecture Based on the Infrastructure of Cloud Computing Contrivance

Abstract: Computer Networking Play’s a major role for data communication or data sharing and data transmissions from one location to another, which are geographically differ, but in today’s scenario where the main and primary major concerns are not to data transfer but also utilize all resources with greater efficiency and also preserves the confidentiality and integrity of the messages with respect to speed and time with lower Bandwidth and also consume a very low computational costs with low power supply and redirect to optimality. Cloud Computing also play’s a significant role to access data at geographically different locations. So In this paper we create a fusion of Computer Networking Architecture and Cloud Computing Architecture and released a very much superior fundamentally strong Cloud computing based Computer Networking model, which works on the concepts of ‘Virtualization’. Because when the number of hardware components (Servers) drastically increases all factors which are responsible to make possible networking among nodes are also consume each resources at extreme level, and networking becomes complex and slow, that’s why we used the concept of Virtual Machine. In this paper we proposed a Computer Networking model using the concepts of Cloud Computing. This model also suitable for data transmission but also take concern the most significant feature of Computer Networking, which is Data Security. This model also used some Proxy servers/ firewalls to take concern some security mechanisms. In this paper we also proposed Communication Oriented model among the Intercluster domains that how one node which belongs to another CLOUD cluster make possible communication among other InterCLOUD clusters with respect to data security measures. In this paper we proposed three models related to this networking model, which is CLOUD Networking Infrastructure, Connection Oriented model, Communication Oriented model. The detailed description of all three models are in the upcoming sections of this paper. Keywords: Cloud computing based computer networking model, A virtual model for computer networking, Computer Networking model based on virtualization, Virtualization based computer networking model.

Load Sharing Scheme Incorporating Power Security Margins for Parallel Operation of Voltage Source Inverters

The interconnection of distributed energy resources (DERs) in microgrids (MGs) operating in both islanded and grid-connected modes require coordinated control strategies. DERs are interfaced with voltage source inverters (VSIs) enabling interconnection. This paper proposes a load demand sharing scheme for the parallel operation of VSIs in an islanded voltage source inverter-based microgrid (VSI-MG). The ride-through capability of a heavily loaded VSI-MG, where some of the VSIs are fully loaded due to the occurrence of an event is investigated. In developing analytical equations to model the VSI, the concept of virtual synchronous machines (VSM) is applied to enable the VSI mimic the inertia effect of synchronous machines. A power frame transformation (PFT) that takes the line ratios of the MG network into account is also incorporated to yield satisfactory transient responses of both network frequency and bus voltages in the MG network. A Jacobian-based method is then developed to take into account the operational capacity of each VSI in the VSI-MG. The resulting amendable droop control constrains the VSIs within their power capabilities when an event occurs. Simulation results presented within demonstrate the effectiveness of the proposed procedure which has great potential to facilitate efforts in maintaining system reliability and resiliency.

PREDIKSI FITUR KEMASAN PRODUK MINYAK KAYU PUTIH DENGAN SUPPORT VECTOR MACHINE (SVM)

UD Sinar Baru has eucalyptus oil products with various sizes from 30 ml to 550 ml, and the size of 550 ml is the most consumed eucalyptus oil product. However, this product has been criticized by consumers for its packaging which has not met their expectations. This study aims to obtain an accurate method of classifying consumer sentiment and obtain features that affect the redesign of the 550 ml eucalyptus oil product packaging. Collecting data using an online survey method from social media Facebook to get consumer comments using power queries. Data analysis uses the concept of the Support Vector Machine (SVM) method with the support of the WEKA application to provide sentiment analysis and accuracy of consumer comments. The results of the study present the tendency of comments on each attribute with an assessment of 83% accuracy for the entire class, 3% for positive class comments, and 57% comments for negative class. The sentiment that shows the packaging tends to be normal at 20% which is interpreted as neutral. The conclusion from the results of this study is that SMO has a very accurate prediction rate to analyze consumer sentiment about the features of the 550 ml eucalyptus oil packaging, and it is necessary to redesign the current packaging by considering the features of shape, color, size, and efficiency.

Parametric analysis of turning HSLA steel under minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL): a concept of one-step sustainable machining

The requirement of cost-effective and ecological production systems is crucial in the competitive market. In this regard, the focus is shifted towards sustainable and cleaner machining processes. Besides the clean technologies, effective parametric control is required for machining materials (such as High Strength Low Alloy Steels) specifically designed for high strength applications having superior physio-chemical properties. Therefore, the machinability complexities require optimized solutions to reduce temperature elevation and tooling costs and improve machining of these materials. Complying to the market needs, this research examines the effectiveness of nanofluid on tool life, wear mechanisms, surface roughness (Ra), surface morphology, and material removal rate (MRR) in turning of 30CrMnSiA (HSLA) using minimum quantity lubrication (MQL) and SiO2-H2O nanofluids (NF-MQL). A systematic investigation based on physical phenomena involved is carried out considering four process parameters (cutting speed (VC), feed rate (Fr), depth of cut (DOC), and mode of lubrication for machining. Fr is found as the vital parameter for surface roughness while MRR is highly influenced by DOC regardless of lubrication approach. One-step sustainability technique is applied, in which process variables used for roughing conditions are analogous to attain surface comparable to finished machining without compromising process efficiency and demonstrate its feasibility through optimal settings under NF-MQL. Multi-response optimization proved the NF-MQL machining condition as the best alternative which result in 28.34% and 5.09% improvements for surface roughness and MRR, respectively. Moreover, the use of SiO2 is recommended over MQL due to lower energy consumption, low tool wear, and better surface integrity, sustainable liquid, and related costs.

Micro-electrochemical jet machining of large area microtexturing with tool movement strategy

ABSTRACT Microtextured surfaces, particularly circular micropattern, significantly enhance the function and performance of microfabricated devices and engineering parts. A distinctive and inventive concept of maskless microelectrochemical jet machining (EJM) is utilized for producing the microcircular pattern over large area. In this research work, an advanced concept, i.e. maskless micro-EJM is presented to produce the microtextures on large area using the reusable masked tool movement strategy on stainless steel. One masked patterned tool can fabricate many high-quality micropatterned samples over large area using the tool movement strategy. High-pressure electrolyte flow through textured tool is developed to acquire the high-quality microtextures with controlled dimensions. The machining consequence of substantial input parameters, i.e. IEG, flow rate and frequency on microdimpled characteristics such as MRR, overcut, depth, and R a is explored. Microdimples of 5.3 mg/min MRR, 20.07 µm overcut, 13.5 µm depth, and 0.0601 µm surface roughness and 5.29 cm2 machining area are successfully fabricated using the reusable masked tool. The present study confirms that it is achievable to acquire the large area microtexturing using this innovative technique.

Physical Computational Complexity and First-order Logic

We present the concept of a theory machine, which is an atemporal computational formalism that is deployable within an arbitrary logical system. Theory machines are intended to capture computation on an arbitrary system, both physical and unphysical, including quantum computers, Blum-Shub-Smale machines, and infinite time Turing machines. We demonstrate that for finite problems, the computational power of any device characterisable by a finite first-order theory machine is equivalent to that of a Turing machine. Whereas for infinite problems, their computational power is equivalent to that of a type-2 machine. We then develop a concept of complexity for theory machines, and prove that the class of problems decidable by a finite first order theory machine with polynomial resources is equal to 𝒩𝒫 ∩ co-𝒩𝒫.

Preliminary Design Concept of Garbage Collecting Machine

Malaysia can only recycle about 1,150 tons of solid waste than 23,000 tons of solid waste disposed of every day. This amount is equivalent to 5% of the total solid waste disposed of. At the same time, 19% of waste is dumped into water drainages such as rivers, trench, and drains. This activity contributes to clogged drains, mosquito breeding, and the transmission of other diseases. Waste management is an important issue that is commonly discussed and highlighted in the media. The most common issue is how to efficiently and effectively collect garbage waste. The current method of collecting garbage is very time-consuming and requires many workforces. In addition, the existing machine is expensive, and its usage is limited to certain areas only. To save the energy of human resources and time, a new garbage collector design should be proposed. Usage of machines focused on the big flat area such as at a field and open area like parking lot area. This area is commonly used for significant events like a night market, expo, concert, or exhibition. Therefore, this concept design is intended to solve and surmount the stated problem by designing and developing the new design garbage collector machine. The concept design follows an essential design process that identifies needs, conceptual design, embodiment design, and detail design. This design can be developed for the expected result and proceed for proof-of-concept testing to test the functionality and capability.