Small Machine Research Articles

Research on Electrochemical Machining Technology of Deep Small Hole using Suction Electrode

Aiming at the problem of deep small hole machining for difficult-to-machine material, a suction electrode electrochemical machining method is used to solve the problems of slow electrolyte renewal and poor stability during the electrochemical machining of deep small holes. This paper mainly uses the multi-physics coupling software COMSOL to establish a multi-physics coupling model for the electrochemical machining of deep small holes with a suction electrode and simulates the forming process of the deep small hole and the distribution of the flow field and electric field during the machining process. This model verifies the feasibility of electrochemical machining technology of deep small holes using a suction electrode.

A Novel ECG Automatic Detection Using LongShort-Term Memory Network and Internet of Things Technology

The early detection of cardiovascular diseases based on electrocardiogram (ECG) is very important for the timely treatment of cardiovascular patients, which increases the survival rate of patients. ECG is a visual representation that describes changes in cardiac bioelectricity and is the basis for detecting heart health. With the rise of edge machine learning and Internet of Things (IoT) technologies, small machine learning models have received attention. This study proposes an ECG automatic classification method based on Internet of Things technology and LSTM network to achieve early monitoring and early prevention of cardiovascular diseases. Specifically, this paper first proposes a single-layer bidirectional LSTM network structure. Make full use of the timing-dependent features of the sampling points before and after to automatically extract features. The network structure is more lightweight and the calculation complexity is lower. In order to verify the effectiveness of the proposed classification model, the relevant comparison algorithm is used to verify on the MIT-BIH public data set. Secondly, the model is embedded in a wearable device to automatically classify the collected ECG. Finally, when an abnormality is detected, the user is alerted by an alarm. The experimental results show that the proposed model has a simple structure and a high classification and recognition rate, which can meet the needs of wearable devices for monitoring ECG of patients.

Heritage connector: A machine learning framework for building linked open data from museum collections

AbstractAs with almost all data, museum collection catalogues are largely unstructured, variable in consistency and overwhelmingly composed of thin records. The form of these catalogues means that the potential for new forms of research, access and scholarly enquiry that range across multiple collections and related datasets remains dormant. In the project Heritage Connector: Transforming text into data to extract meaning and make connections, we are applying a battery of digital techniques to connect similar, identical and related objects within and across collections and other publications. In this article, we describe a framework to create a Linked Open Data knowledge graph from digital museum catalogues, perform record linkage to Wikidata, and add new entities to this graph from textual catalogue record descriptions (information retrieval). We focus on the use of machine learning to create these links at scale with a small amount of labelled data, and models which are small enough to run inference on datasets the size of museum collections on a mid‐range laptop or a small cloud virtual machine. Our method for record linkage against Wikidata achieves 85%+ precision with the Science Museum Group (SMG) collection, and our method for information retrieval is shown to improve NER performance compared with pretrained models on the SMG collection with no labelled training data. We publish open‐source software providing tools to perform these tasks.

A review paper on wireless sensor network techniques in Internet of Things (IoT)

In recent times, it has been witnessed that wireless systems based on IoT-based have developed rapidly in various sectors. The IoT (Internet of Things) is the network in which physical devices, equipment, sensors and other objects can communicate among themselves without human involvement. The WSN (Wireless Sensor Network) is a central component of the IoT, which has proliferated into several different applications in real-time. The IoT and WSNs now have various critical and non-critical applications impacting nearly every area of our everyday life. WSN nodes are usually small and battery-driven machines. Thus, the energy effective data aggregation techniques that increase the lifespan of the network are highly significant. Various approaches and algorithms for energy-efficient data aggregation in IoT-WSN systems were presented. This paper reviews the literature with specific attention to aspects of wireless networking for the preservation of energy and aggregation of data.

One-step fabrication of fine surfaces via femtosecond laser on sliced SiC

A one-step, facile approach of femtosecond laser polishing for achieving fine surface in sliced SiC is reported. The effect of wavelength and pulse number on formation mechanism of surface morphology and composition are studied firstly. On the basis of relationship between removal depth and defect depth, variation on surface profile investigating, fine surface is obtained by fine-tuning processing parameters. Regular grooves formed by wire saw on subsurface is eliminated completely but no damage generates. Not only that, curves of indentation indicate that quality on subsurface is improved. The improvement both in surface and subsurface benefits from small thermal effect and high machining accuracy of femtosecond laser. Homogeneous structure/composition on subsurface after polishing has higher stable friction coefficient，which will be beneficial to the subsequent ultra-precision polishing.

The jig is up for small soft machines.

A watchmaker's approach yields small, agile, soft machines.

Research on water jet-guided laser micro-hole machining of 6061 aluminum alloy

With the rapid development of the information age, electronic components are developing toward miniaturization, which makes the manufacturing of chips more and more difficult. Water jet-guided laser processing technology (WJGL) is a composite processing technology that combines pulsed laser and water jet, which can ensure the accuracy and efficiency of processing while small size parts machining. This paper is based on the “element birth and death” technique in the finite element method and the three-dimensional transient temperature field and subsequent material removal model of 6061 aluminum alloy are established. The effects of laser average power, pulse repetition frequency, and pulse action time on the transient thermal distribution, aperture, taper, and other forming qualities with the two technologies of fixed-point drilling and spiral drilling, respectively, are studied. Combining the experimental process, the general rule of morphology change of the micro-hole is obtained. The results show that WJGL of micro-hole is based on the combined effect of thermal ablation and real-time cooling. Spiral drilling can maintain a better hole shape but fixed-point drilling can achieve a smaller hole taper. With the increase of laser power, the hole taper increases, reaching saturation at 8 W. The repetition frequency is between 50 and 70 kHz to obtain better hole morphology while maintaining better processing efficiency, and the minimum hole taper is 8.21°.

Spiking neural P systems with autapses

• Present SN P systems with autapses as a new variant of SN P systems by introducing autapses. • Prove SN P systems with autapses are Turing universal as natural number generators . • Construct an SN P systems with autapses with 53 neurons for computing functions. • A simulator is developed and used to check the correctness of universal SNP-AU systems. Inspired by the structure and communication method of neural systems, a parallel computing model, spiking neural P systems (SN P systems, for short), was proposed in 2006. A new class of SN P systems, SN P systems with autapses (SNP-AU systems), is presented in this work. Autapses are a special kind of synapses, connecting the axon of a neuron onto itself. We prove that SNP-AU systems can generate Turing-computable numbers, through the simulation of the modules of universal register machines. This result improves significantly the results given by classical SN P systems in terms of the number of neurons and rules, while preserving simplicity and power to a reasonable extent. Moreover, we construct an SNP-AU system using 53 neurons, proving its universality for computing functions. Finally, going beyond the design of the building blocks of register machines, a whole universal machine is provided. Thus, a simulator is developed and used to check the correctness of two universal SNP-AU systems proposed in this paper, complementing the theoretical proof with the experimental validation of our systems with respect to the reference example appearing in the foundational paper of small register machines.

Investigation of Different Machine Learning Algorithms to Determine Human Sentiment Using Twitter Data

In recent years, with the advancement of the internet, social media is a promising platform to explore what going on around the world, sharing opinions and personal development. Now, Sentiment analysis, also known as text mining is widely used in the data science sector. It is an analysis of textual data that describes subjective information available in the source and allows an organization to identify the thoughts and feelings of their brand or goods or services while monitoring conversations and reviews online. Sentiment analysis of Twitter data is a very popular research work nowadays. Twitter is that kind of social media where many users express their opinion and feelings through small tweets and different machine learning classifier algorithms can be used to analyze those tweets. In this paper, some selected machine learning classifier algorithms were applied on crawled Twitter data after applying different types of preprocessors and encoding techniques, which ended up with satisfying accuracy. Later a comparison between the achieved accuracies was showed. Experimental evaluations show that the Neural Network Classifier’ algorithm provides a remarkable accuracy of 81.33% compared with other classifiers.

Fusion gain from cylindrical liner-driven implosions of field reversed configurations

MagLIF experiments [M.R. Gomez et al., Phys. Plasmas 22, 056306 (2015)] on Z have demonstrated the basic principles of Magneto-Inertial Fusion (MIF) for wall confined plasmas. Other MIF schemes have been proposed based on the liner implosion of closed field magnetically confined plasmas such as Field Reversed Configurations (FRCs) [T. P. Intrator et al., Phys. Plasmas 15, 042505 (2008)]. We present a semi-analytical model of liner driven FRC implosions that predicts the fusion gain of such systems. The model predicts a fusion gain near unity for an FRC imploded by a liner driven by the Z Machine. We show that FRCs could be formed and imploded at the Z facility using the AutoMag liner concept [S. A. Slutz et al., Phys. Plasmas 24, 012704 (2017)]. An initial bias magnetic field can be supplied by the external magnets used in MagLIF experiments. The reverse field is then supplied by an AutoMag liner, which has helical conducting paths imbedded in an insulating substance. Experiments [Shipley et al., Phys. Plasmas 26, 052705 (2019)] have demonstrated that AutoMag can generate magnetic fields greater than 30 Tesla inside of the liner. We have performed 2D Radiation MHD simulations of the formation and implosion of an FRC, which are in good agreement with the analytical model. The FRC formation process could be studied on small pulsed power machines delivering about 1 MA.

Optimizing autonomous thermal machines powered by energetic coherence

The characterization and control of quantum effects in the performance of thermodynamic tasks may open new avenues for small thermal machines working in the nanoscale. We study the impact of coherence in the energy basis in the operation of a small thermal machine which can act either as a heat engine or as a refrigerator. We show that input coherence may enhance the machine performance and allow it to operate in otherwise forbidden regimes. Moreover, our results also indicate that, in some cases, coherence may also be detrimental, rendering optimization of particular models a crucial task for benefiting from coherence-induced enhancements.

INCREASING THE EFFICIENCY OF TECHNOLOGIES AND TECHNICAL MEANS OF QUALITY CONTROL RESTORATION OF SMALL-SIZED ENGINES

Mechanization of labor on small farms and individual farms is a very important issue of modern agriculture. The use of small agricultural machinery with a capacity of up to 16 kW is quite relevant today. Small-sized machinery is divided into: small 4-wheeled tractors, 2-wheeled motoblocks, cultivators, machines and equipment. With the help of this technique perform various agricultural and other types of work in crop production, horticulture, gardening on small plots, livestock and more. Despite its rather small size, small equipment also has various mechanisms that fail over time. Most often, the parts of the internal combustion engine fail. In general, the cost of repairing the internal combustion engine during operation may exceed the total cost of the engine by 5-6 times. Thus, there is a question of improving the system of technical service of engines of small tractors. This article considers the issue of increasing the efficiency of operation of internal combustion engines for small tractors, due to the effective conduct of after-sales or post-repair running-in and improving the maintenance system. Types of small-sized equipment are presented. The analysis of possible loading and speed modes of cold and hot running-in of internal combustion engines and means for their realization is carried out. Technical means for running-in and testing of internal combustion engines are analyzed. The following formulas are given for determination: smoke of exhaust gases at running-in of engines; light transmission of exhaust gases; speed control range; load torque; the content of harmful substances (Q) in the exhaust gases on the j-th components. The necessity of bench running-in of engines of small-sized agricultural machinery is substantiated. The functional scheme of the stand for running-in and testing of internal combustion engines is considered. The stages of cold and hot running-in of small-sized engines are described. With the help of the received information, the results are made and the analysis of methods of running-in of internal combustion engines of small-sized agricultural machinery is carried out.

Autonomous Mowing and Complete Floor Cover for Weed Control in Vineyards

Enhancing vineyards sustainability and reducing herbicides usage is a crucial theme, thus alternative weed management methods are starting to be studied. Cover crops have been shown to provide for several environmental services such as performing an efficient weed control and promoting biodiversity, thus improving the sustainability of the overall management system. However, the use of cover crops is usually confined to the interrow area in order to avoid competition with vines. Under-trellis weed management in vineyards is an important challenge, conventionally fulfilled by cultivation or repeated herbicides applications. Autonomous mowers are small autonomous machines that have shown a great efficiency when employed in agricultural contexts. Due to their reduced size, they can easily prevent the excessive vertical growth of weeds both in the interrows and under trellis without the use of chemical applications. The aim of this trial was to evaluate if the combination of cover crop species and autonomous mowers management could improve vineyard sustainability. Vineyard floor cover that was managed with an autonomous mower had a shorter canopy height and a lower weed dry biomass compared to the conventionally managed vineyard floor cover. Vineyard floor management providing cover crops and autonomous mowing had a significantly lower weed cover percentage compared to conventional floor management, especially under-trellis. The results of this trial suggest that the combination of cover crops and autonomous mowers may be a sustainable and reliable technique to include in vineyards floor management.

An Improved Winding Function Theory for Accurate Modeling of Small and Large Air-Gap Electric Machines

An improved winding function theory (IWFT) is presented in this article, which can be also used to calculate the self-inductance and mutual inductance of large air-gap electric machines, while accurately considering the air-gap length function and the magnetic saturation in iron parts, simultaneously. In IWFT, the radial length of flux path in different points inside air gap is calculated using the conformal mappings (CMs). The total air-gap length is the resultant of air-gap length at differential elements in the radial direction. A modified inverse air-gap function is then presented for a typical cage-rotor induction motor (CRIM) and a typical surface permanent magnet synchronous motor (SPMSM), which considers the real paths of flux lines in the slotted air gap. The high accuracy of these modified inverse air-gap functions is verified by comparing with the corresponding results obtained through the finite element method (FEM). To consider the magnetic saturation, a virtual winding function as a 2-D function is introduced in this article, which can consider the magneto-motive force (MMF) drops in iron parts of stator and rotor obtained through the magnetic equivalent circuit (MEC) model. By using IWFT, dependent on the structure of the relevant motor, a 2-D or 3-D lookup table is pre-calculated and stored for self/mutual inductances and their derivatives, and they are then used to model the running condition of CRIM and SPMSM under different loading conditions. Finally, the accuracy of IWFT results is verified by comparing them with the corresponding results obtained through FEM.

Five-Axis Machine Tool Volumetric and Geometric Error Reduction by Indirect Geometric Calibration and Lookup Tables

Abstract Modern CNC machine tools provide lookup tables to enhance the machine tool’s precision but the generation of table entries can be a demanding task. In this paper, the coefficients of the 25 cubic polynomial functions used to generate the LUTs entries for a five-axis machine tool are obtained by solving a linear system incorporating a Vandermonde expansion of the nominal control jacobian. The necessary volumetric errors within the working volume are predicted from the machine’s geometric errors estimated by the indirect error identification method based on the on-machine touch probing measurement of a reconfigurable uncalibrated master ball artifact (RUMBA). The proposed scheme is applied to a small Mitsubishi M730 CNC machine. Two different error models are used for modeling the erroneous machine tool, one estimating mainly inter-axis errors and the other including numerous intra-axis errors. The table-based compensation is validated through additional on-machine measurements. Experimental tests demonstrate a significant reduction in volumetric errors and in the effective machine error parameters. The LUTs reduce most of the dominant machine error parameters. It is concluded that although being effective in correcting some geometric errors, the generated LUTs cannot compensate for some axis misalignments such as EB(OX)A and EB(OX)Z. The root-mean-square of the translational volumetric errors is improved from 87.3, 75.4, and 71.5 µm down to 24.8, 18.8, and 22.1 µm in the X-, Y-, and Z-directions, respectively.

On the Use of Modern Engineering Codes for Designing a Small Wind Turbine: An Annotated Case Study

While most wind energy comes from large utility-scale machines, small wind turbines (SWTs) can still play a role in off-grid installations or in the context of distributed production and smart energy systems. Over the years, these small machines have not received the same level of aerodynamic refinement of their larger counterparts, resulting in a notably lower efficiency and, therefore, a higher cost per installed kilowatt. In an effort to reduce this gap during the design of a new SWT, the scope of the study was twofold. First, it aimed to show how to combine and best exploit the modern engineering methods and codes available in order to provide the scientific and industrial community with an annotated procedure for a full preliminary design process. Secondly, special focus was put on the regulation methods, which are often some of the critical points of a real design. A dedicated sensitivity analysis for a proper setting is provided, both for the pitch-to-feather and the stall regulation methods. In particular, it is shown that stall regulation (which is usually preferred in SWTs) may be a cost-effective and simple solution, but it can require significant aerodynamic compromises and results in a lower annual energy output in respect to a turbine making use of modern stall-regulation strategies. Results of the selected case study showed how an increase in annual energy production (AEP) of over 12% can be achieved by a proper aerodynamic optimization coupled with pitch-to-feather regulation with respect to a conventional approach.

Small mechanical vibration reduction system based on adaptive hydraulic gasket

This project designs an adaptive small mechanical damping system based on hydraulic gaskets. The main function is to realize the active damping of small sports machinery and the self-adaptive automatic centering of shafting machinery. The system is mainly composed of hydraulic gaskets, controllers, sensors, and external power sources. The hydraulic vibration reduction device is miniaturized and applied to small power machinery with low cost and high applicability. The vibration damping platform is based on a small power machine designed with a unique hydraulic gasket and an active and passive composite damping system is constructed.

Analysing the Feasibility of a\xa0Full-face Cutting Machine for the Robominers Project

Several methods of excavation have previously been studied to choose the most suitable approach to be applied in the Robominers project. Compared to drilling and blasting and partial-face cutting, the full-face cutting option is regarded as one of the methods which can offer, among others, high advance rates and a safer working environment for the machinery. Current technologies of these methods, however, suffer from several limitations, such as the inability to bore very hard rocks, significant lack of geometrical flexibility in mine working areas, and low mobility due to large and heavy components. In this study, two of the most commonly applied small diameter full-face machines including the pipe jacking and the Boxhole Boring Machine (BBM) are studied with regards to their performance parameters. The pipe jacking machine option with a cutterhead consisting of disc cutters exhibits higher efficiency in excavation with only slightly lower production rates compared to a BBM with strawberry cutters. They are also much lighter machines. Yet, using the jacking concept means a limited driving length and does not apply to the Robominers. Therefore, the introduction of small gripper or shielded Tunnel Boring Machines (TBMs) can significantly improve the mobility. Their application, however, requires considering the risks of jamming in difficult ground conditions and the possible requirements of a support installation. These rock mechanics issues need to be carefully considered in the design of such machines. In addition, further studies are required to employ assisted cutting methods in very hard rocks and to increase the geometrical flexibility of these machines by lowering their turning radius.

Design and Construction of Bamboo Stripping machine for Bamboo Basketry

Handicraft of bamboo weaving has been a tradition that has been inherited for a long time, by using bamboo strips to weave into shapes to make tools and appliances. The bamboo strips are from dividing the longitudinal bamboo trunks into thin strips. In which most farmers will make the strips by hand by using a big knife or sharp objects. As a result, it takes a long time to prepare the bamboo strips to be used in the weaving work. There is also a risk of accidents from the use of sharp objects, including the size of the bamboo strips that is not the same size. This research aims to design and construct bamboo strips by dividing the research into 2 steps: 1) designing and constructing bamboo strips and 2) testing the operation of the stripping machine. The designed machine can be easily moved because it is a small and lightweight machine which is designed using a single-phase electric motor with a voltage of 220 volts, 250 watts, etc. Power to drive the roller through the transmission belt to convey bamboo parts through two 7-degree sets of blades with sharp angles that are placed horizontally. The first blade acts to separate the bamboo parts with the bamboo strips and the second blade acts to sharpen the bamboo strips. The results of the working test of the stripping machine by adjusting the blade angle at 1 and the level into 4 values that are 3, 4, 5, and 6 degrees, it was found that the machine was able to produce bamboo strips in size 1.47, 1.20, 1.97 and 2.27 mm, respectively. The size of the punching line is suitable for weaving containers such as round bamboo basket, wicker basket, and bamboo basket, etc.

Thermodynamics of precision in quantum nanomachines.

Fluctuations strongly affect the dynamics and functionality of nanoscale thermal machines. Recent developments in stochastic thermodynamics have shown that fluctuations in many far-from-equilibrium systems are constrained by the rate of entropy production via so-called thermodynamic uncertainty relations. These relations imply that increasing the reliability or precision of an engine's power output comes at a greater thermodynamic cost. Here we study the thermodynamics of precision for small thermal machines in the quantum regime. In particular, we derive exact relations between the power, power fluctuations, and entropy production rate for several models of few-qubit engines (both autonomous and cyclic) that perform work on a quantized load. Depending on the context, we find that quantum coherence can either help or hinder where power fluctuations are concerned. We discuss design principles for reducing such fluctuations in quantum nanomachines and propose an autonomous three-qubit engine whose power output for a given entropy production is more reliable than would be allowed by any classical Markovian model.