Search results for: ball machine

Authors: Bi Zhao

Abstract:

Neural network technology has greatly improved the output of machine translation in terms of both fluency and accuracy, which greatly increases its appeal for young users. The present exploratory study aims to find out how the Chinese undergraduates perceive and use machine translation in their daily life. A survey is conducted to collect data from 100 undergraduate students from multiple Chinese universities and with varied academic backgrounds, including arts, business, science, engineering, and medicine. The survey questions inquire about their use (including frequency, scenarios, purposes, and preferences) of and attitudes (including trust, quality assessment, justifications, and ethics) toward machine translation. Interviews and tasks of evaluating machine translation output are also employed in combination with the survey on a sample of selected respondents. The results indicate that Chinese undergraduate students use machine translation on a daily basis for a wide range of purposes in academic, communicative, and entertainment scenarios. Most of them have preferred machine translation tools, but the availability of machine translation tools within a certain scenario, such as the embedded machine translation tool on the webpage, is also the determining factor in their choice. The results also reveal that despite the reportedly limited trust in the accuracy of machine translation output, most students lack the ability to critically analyze and evaluate such output. Furthermore, the evidence is revealed of the inadequate awareness of ethical responsibility as machine translation users among Chinese undergraduate students.

Keywords: Chinese undergraduates, machine translation, trust, usage

Procedia PDF Downloads 98

Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

Procedia PDF Downloads 238

Authors: Marcel Lehr, Andreas Binder

Abstract:

This paper compares three different permanent magnet synchronous machines (Doubly-Salient-Permanent-Magnet-Machine (DSPM), Flux-Reversal-Permanent-Magnet-Machine (FRPM), Flux-Switching-Permanent-Magnet-Machine (FSPM)) with the permanent magnets in the stator of the machine for use as an industrial drive for 400 V Y, 45 kW and 1000 ... 3000 min-1. The machines are compared based on the magnetic co-energy and Finite-Element-Method-Simulations regarding the torque density. The results show that the FSPM provides the highest torque density of the three machines. Therefore, an FSPM prototype was built, tested on a test bench and finally compared with an already built conventional permanent magnet synchronous machine (PMSM) of the same size (stator outer diameter dso = 314 mm, axial length lFe = 180 mm) and rating with surface-mounted rotor magnets. These measurements show that the conventional PMSM and the FSPM machine are roughly equivalent in their electrical behavior.

Keywords: doubly-salient-permanent-magnet-machine, flux-reversal-permanent-magnet-machine, flux-switching-permanent-magnet-machine, industrial drive

Procedia PDF Downloads 338

Authors: Ahmed A. D. Sarhan, S. R. Besharaty, Javad Akbaria, M. Hamdi

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The capability of CNC gantry milling machines in manufacturing long components has caused the expanded use of such machines. On the other hand, the machines’ gantry rigidity can reduce under severe loads or vibration during operation. Indeed, the quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. For this reason, this type of machines has always been used prudently and are non efficient. Therefore, they can usually be employed for rough machining and may not produce adequate surface finishing. In this paper, a CNC gantry milling machine with the potential to produce good surface finish has been designed and analyzed. The lowest natural frequency of this machine is 202 Hz at all motion amplitudes with a full range of suitable frequency responses. Meanwhile, the maximum deformation under dead loads for the gantry machine is 0.565µm, indicating that this machine tool is capable of producing higher product quality.

Keywords: frequency response, finite element, gantry machine, gantry design, static and dynamic analysis

Procedia PDF Downloads 323

Authors: Fatima S. Rodriguez, Victorino T. Taylan, Manolito C. Bulaong, Helen F. Gavino, Vitaliana U. Malamug

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In sundrying the quality of the grains are greatly reduced when paddy grains were caught by the rain unsacked and unstored resulting to reduced profit. The objectives of this study were to design and fabricate a quick covering machine for grain drying pavement; to test and evaluate the operating characteristics of the machine according to its deployment speed, recovery speed, deployment time, recovery time, power consumption, aesthetics of laminated sack; and to conduct partial budget and cost curve analysis. The machine was able to cover the grains in a 12.8 m x 22.5 m grain drying pavement at an average time of 17.13 s. It consumed 0.53 W-hr for the deployment and recovery of the cover. The machine entailed an investment cost of $1,344.40 and an annual cost charge of $647.32. Moreover, the savings per year using the quick covering machine was $101.83.

Keywords: quick covering machine, grain drying pavement, laminated polypropylene, recovery time

Procedia PDF Downloads 289

Authors: Jeremy Faludi, Zhongyin Hu, Shahd Alrashed, Christopher Braunholz, Suneesh Kaul, Leulekal Kassaye

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Environmental impacts of six 3D printers using various materials were compared to determine if material choice drove sustainability, or if other factors such as machine type, machine size, or machine utilization dominate. Cradle-to-grave life-cycle assessments were performed, comparing a commercial-scale FDM machine printing in ABS plastic, a desktop FDM machine printing in ABS, a desktop FDM machine printing in PET and PLA plastics, a polyjet machine printing in its proprietary polymer, an SLA machine printing in its polymer, and an inkjet machine hacked to print in salt and dextrose. All scenarios were scored using ReCiPe Endpoint H methodology to combine multiple impact categories, comparing environmental impacts per part made for several scenarios per machine. Results showed that most printers’ ecological impacts were dominated by electricity use, not materials, and the changes in electricity use due to different plastics was not significant compared to variation from one machine to another. Variation in machine idle time determined impacts per part most strongly. However, material impacts were quite important for the inkjet printer hacked to print in salt: In its optimal scenario, it had up to 1/38th the impacts coreper part as the worst-performing machine in the same scenario. If salt parts were infused with epoxy to make them more physically robust, then much of this advantage disappeared, and material impacts actually dominated or equaled electricity use. Future studies should also measure DMLS and SLS processes / materials.

Keywords: 3D printing, additive manufacturing, sustainability, life-cycle assessment, design for environment

Procedia PDF Downloads 464

Authors: Samaneh Rahsepar, Mehrzad Moghadasi

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To evaluate the effect of Test Pump supplement on the physiological and functional performance of futsal women, twenty female futsal subjects were divided into two groups: placebo (n = 10) and supplement (n = 10) and were given buccal tablets for 7 days and 12 g daily supplement each day. The placebo group used starch powder during this period. Speed, agility with ball, agility without ball and dribbling time were measured before and after supplementation. In addition, the rate of heart rate and blood pressure changes were measured before and after the YOYO test. The results showed that the test pump had no significant effect on improving speed, agility with ball, agility without ball, dribbling time and heart rate changes and diastolic blood pressure, and only affect the maximum oxygen consumption and systolic blood pressure (P <0.05). In general, the use of the test-pump supplement does not have a significant effect on the physiological and functional performance of futsal women. The results of this study showed that the use of supplementary pump tests on women's futsal heart rate changes after loading period had a significant difference between the two groups in resting heart rate with heart rate after exercise and 5 minutes after exercise. However, it did not have a significant effect on the increase in heart rate. Supplementation significantly increased systolic blood pressure after exercise compared to resting blood pressure, as well as a significant increase in systolic blood pressure after exercise compared to resting systolic blood pressure and 5 minutes after exercise in both groups from the loading period. On the other hand, there was a significant difference in systolic blood pressure in both placebo and supplemented groups.

Keywords: test pump supplement, women, speed, dribble, agility, maximum oxygen consumption, cardiovascular

Procedia PDF Downloads 147

Authors: P. Hari Prasad Reddy, Shimna Paulose, V. Sai Kumar, C. H. Rama Vara Prasad

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Soil environment gets contaminated due to rapid industrialisation, agricultural-chemical application and improper disposal of waste generated by the society. Unexpected volume changes can occur in soil in the presence of certain contaminants usually after the long duration of interaction. Alkali is one of the major soil contaminant that has a considerable effect on behaviour of soils and capable of inducing swelling potential in soil. Chemical heaving of clayey soils occurs when they are wetted by aqueous solutions of alkalis. Mineralogical composition of the soil is one of the main factors influencing soil- alkali interaction. In the present work, studies are carried out to understand the swell potential of soils due to soil-alkali interaction with different concentrations of NaOH solution. Locally available soil, namely, red earth containing kaolinite which is of non-swelling nature is selected for the study. In addition to this, two commercially available clayey soils, namely ball clay and china clay containing mainly of kaolinite are selected to understand the effect of alkali interaction in various kaolinitic soils. Non-swelling red earth shows maximum swell at lower concentrations of alkali solution (0.1N) and a slightly decreasing trend of swelling with further increase in concentration (1N, 4N, and 8N). Marginal decrease in swell potential with increase in concentration indicates that the increased concentration of alkali solution exists as free solution in case of red earth. China clay and ball clay both falling under kaolinite group of clay minerals, show swelling with alkaline solution. At lower concentrations of alkali solution both the soils shows similar swell behaviour, but at higher concentration of alkali solution ball clay shows high swell potential compared to china clay which may be due to lack of well ordered crystallinity in ball clay compared to china clay. The variations in the results obtained were corroborated by carrying XRD and SEM studies.

Keywords: alkali, kaolinite, swell potential, XRD, SEM

Procedia PDF Downloads 463

Authors: Anek Apipatkul, Paphakorn Pitayachaval

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Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

Procedia PDF Downloads 71

Authors: Nurtekin Erkmen, Turgut Kaplan, Halil Taskin, Ahmet Sanioglu, Gokhan Ipekoglu

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The aim of this study was to determine the effects of an 8 week soccerspecific technical training with limited vision perception on postural control and technical parameters in 10-12 aged soccer players. Subjects in this study were 24 male young soccer players (age: 11.00 ± 0.56 years, height: 150.5 ± 4.23 cm, body weight: 41.49 ± 7.56 kg). Subjects were randomly divided as two groups: Training and control. Balance performance was measured by Biodex Balance System (BBS). Short pass, speed dribbling, 20 m speed with ball, ball control, juggling tests were used to measure soccer players’ technical performances with a ball. Subjects performed soccer training 3 times per week for 8 weeks. In each session, training group with limited vision perception and control group with normal vision perception committed soccer-specific technical drills for 20 min. Data analyzed with t-test for independent samples and Mann-Whitney U between groups and paired t-test and Wilcoxon test between pre-posttests. No significant difference was found balance scores and with eyes open and eyes closed and LOS test between training and control groups after training (p>0.05). After eight week of training there are no significant difference in balance score with eyes open for both training and control groups (p>0.05). Balance scores decreased in training and control groups after the training (p<0.05). The completion time of LOS test shortened in both training and control groups after training (p<0.05). The training developed speed dribbling performance of training group (p<0.05). On the other hand, soccer players’ performance in training and control groups increased in 20 m speed with a ball after eight week training (p<0.05). In conclusion; the results of this study indicate that soccer-specific training with limited vision perception may not improves balance performance in 10-12 aged soccer players, but it develops speed dribbling performance.

Keywords: Young soccer players, vision perception, postural control, technical

Procedia PDF Downloads 447

Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

Procedia PDF Downloads 157

Authors: Chee Sun Won

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This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

Procedia PDF Downloads 387

Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

Procedia PDF Downloads 139

Authors: Daniel Karthik, Vijay Baheti, Jiri Militky, Sundaramurthy Palanisamy

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Fibre based nano particles are presently considered as one of the potential filler materials for the improvement of mechanical and physical properties of polymer composites. Due to high matrix-filler interfacial area there will be uniform and homogeneous dispersion of nanoparticles. In micro/nano filler reinforced composites, resin material is usually tailored by organic or inorganic nanoparticles to have improved matrix properties. The objective of this study was to compare the potential of reinforcement of different organic and inorganic micro/nano fillers in epoxy composites. Industrial and agricultural waste of fibres like Agave Americana, cornhusk, jute, basalt, carbon, glass and fly ash was utilized to prepare micro/nano particles. Micro/nano particles were obtained using high energy planetary ball milling process in dry condition. Milling time and ball size were kept constant throughout the ball milling process. Composites were fabricated by hand lay method. Particle loading was kept constant to 3% wt. for all composites. In present study, loading of fillers was selected as 3 wt. % for all composites. Dynamic mechanical properties of the nanocomposite films were performed in three-point bending mode with gauge length and sample width of 50 mm and 10 mm respectively. The samples were subjected to an oscillating frequency of 1 Hz, 5 Hz and 10 Hz and 100 % oscillating amplitude in the temperature ranges of 30°C to 150°C at the heating rate of 3°C/min. Damping was found to be higher with the jute composites. Amongst organic fillers lowest damping factor was observed with Agave Americana particles, this means that Agave americana fibre particles have betters interface adhesion with epoxy resin. Basalt, fly ash and glass particles have almost similar damping factors confirming better interface adhesion with epoxy.

Keywords: ball milling, damping factor, matrix-filler interface, particle reinforcements

Procedia PDF Downloads 243

Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

Procedia PDF Downloads 22

Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine

Procedia PDF Downloads 226

Authors: O. E. Akay, E. Güzel, M. T. Özcan

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The pepper has quite a rich variety. The development of a single harvesting machine for all kinds of peppers is a difficult research topic. By development of harvesting mechanisms, we could be able to facilitate the pepper harvesting problems. In this study, an experimental harvesting machine was designed for chili pepper. Four-bar mechanism was used for the design of the prototype harvesting machine. At the result of harvest trials, 80% of peppers were harvested and 8% foreign materials were collected. These results have provided some tips on how to apply to large-scale pepper Four-bar mechanism of the harvest machine.

Keywords: kinematic simulation, four bar linkage, harvest mechanization, pepper harvest

Procedia PDF Downloads 318

Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 23

Authors: Jhe-Hao Huang, Kun-Da Wu, Wei-Cheng Shih, Jui-Pin Hung

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This study presented the investigation on the dynamic characteristics of a spindle tool system by experimental and finite element modeling approaches. As well known facts, the machining stability is greatly determined by the dynamic characteristics of the spindle tool system. Therefore, understanding the factors affecting dynamic behavior of a spindle tooling system is a prerequisite in dominating the final machining performance of machine tool system. To this purpose, a physical spindle unit was employed to assess the dynamic characteristics by vibration tests. Then, a three-dimensional finite element model of a high-speed spindle system integrated with tool holder was created to simulate the dynamic behaviors. For modeling the angular contact bearings, a series of spring elements were introduced between the inner and outer rings. The spring constant can be represented by the contact stiffness of the rolling bearing based on Hertz theory. The interface characteristic between spindle nose and tool holder taper can be quantified from the comparison of the measurements and predictions. According to the results obtained from experiments and finite element predictions, the vibration behavior of the spindle is dominated by the bending deformation of the spindle shaft in different modes, which is further determined by the stiffness of the bearings in spindle housing. Also, the spindle unit with tool holder shows a different dynamic behavior from that of spindle without tool holder. This indicates the interface property between tool holder and spindle nose plays an dominance on the dynamic characteristics the spindle tool system. Overall, the dynamic behaviors the spindle with and without tool holder can be successfully investigated through the finite element model proposed in this study. The prediction accuracy is determined by the modeling of the rolling interface of ball bearings in spindles and the interface characteristics between tool holder and spindle nose. Besides, identifications of the interface characteristics of a ball bearing and spindle tool holder are important for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: contact stiffness, dynamic characteristics, spindle, tool holder interface

Procedia PDF Downloads 265

Authors: Michael Hast

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Within their first year, infants can differentiate between objects based on their weight. By at least 5 years children hold consistent weight-related misconceptions about the physical world, such as that heavy things fall faster than lighter ones because of their weight. Such misconceptions are seen as a challenge for science education since they are often highly resistant to change through instruction. Understanding the time point of emergence of such ideas could, therefore, be crucial for early science pedagogy. The paper thus discusses two studies that jointly address the issue by examining young children’s search behaviour in hidden displacement tasks under consideration of relative object weight. In both studies, they were tested with a heavy or a light ball, and they either had information about one of the balls only or both. In Study 1, 88 toddlers aged 2 to 3½ years watched a ball being dropped into a curved tube and were then allowed to search for the ball in three locations – one straight beneath the tube entrance, one where the curved tube lead to, and one that corresponded to neither of the previous outcomes. Success and failure at the task were not impacted by weight of the balls alone in any particular way. However, from around 3 years onwards, relative lightness, gained through having tactile experience of both balls beforehand, enhanced search success. Conversely, relative heaviness increased search errors such that children increasingly searched in the location immediately beneath the tube entry – known as the gravity bias. In Study 2, 60 toddlers aged 2, 2½ and 3 years watched a ball roll down a ramp and behind a screen with four doors, with a barrier placed along the ramp after one of four doors. Toddlers were allowed to open the doors to find the ball. While search accuracy generally increased with age, relative weight did not play a role in 2-year-olds’ search behaviour. Relative lightness improved 2½-year-olds’ searches. At 3 years, both relative lightness and relative heaviness had a significant impact, with the former improving search accuracy and the latter reducing it. Taken together, both studies suggest that between 2 and 3 years of age, relative object weight is increasingly taken into consideration in navigating naïve physical concepts. In particular, it appears to contribute to the early emergence of misconceptions relating to object weight. This insight from developmental psychology research may have consequences for early science education and related pedagogy towards early conceptual change.

Keywords: conceptual development, early science education, intuitive physics, misconceptions, object weight

Procedia PDF Downloads 172

Authors: İkbal Eski

Abstract:

This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

Procedia PDF Downloads 356

Authors: W. R. Li, J. K. Xia, R. Q. Peng, Z. Y. Guo, L. Jiang

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According to 3D magnetic circuit of the transverse flux PM linear machine, distribution law is presented, and analytical expression of axial end flux leakage is derived using numerical method. Maxwell stress tensor is used to solve detent force of mover. A 3D finite element model of the transverse flux PM machine is built to analyze the flux distribution and detent force. Experimental results of the prototype verified the validity of axial end flux leakage and detent force theoretical derivation, the research on axial end flux leakage and detent force provides a valuable reference to other types of linear machine.

Keywords: axial end flux leakage, detent force, flux distribution, transverse flux PM linear machine

Procedia PDF Downloads 417

Authors: Hamza Zidoum

Abstract:

This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 348

Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

Procedia PDF Downloads 194

Authors: T. Hirata, M. G. Silva, L. M. Rosa

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The balance ability during task kick in soccer is a determining factor in the execution of functional movements that require a high-performance motor coordination. The current experiment explored it during an instep soccer kick and functional task kicking. Their kicking performance was measured in terms of the sway characteristics using lateral and antero-posterior balance of the center of pressure (COP) for the supporting leg and the kinematic data, the supporting leg’s knee angle. The motion was realized with one-legged stance of five male indoor soccer players and using the trigger device ball controller. The results showed large balance in antero-posterior direction than in lateral direction. However, each player adopts a different way to kick the ball, and the media-lateral displacement of the COP showed no correlation with the balance skill.

Keywords: kicking performance, center of pressure, one-legged stance, balance ability

Procedia PDF Downloads 588

Authors: Yi Huang, Clemens Guehmann

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In order to monitor the thermal behavior of an asynchronous machine with squirrel cage rotor, a 9th-order extended Kalman filter (EKF) algorithm is implemented to estimate the temperatures of the stator windings, the rotor cage and the stator core. The state-space equations of EKF are established based on the electrical, mechanical and the simplified thermal models of an asynchronous machine. The asynchronous machine with simplified thermal model in Dymola is compiled as DymolaBlock, a physical model in MATLAB/Simulink. The coolant air temperature, three-phase voltages and currents are exported from the physical model and are processed by EKF estimator as inputs. Compared to the temperatures exported from the physical model of the machine, three parts of temperatures can be estimated quite accurately by the EKF estimator. The online EKF estimator is independent from the machine control algorithm and can work under any speed and load condition if the stator current is nonzero current system.

Keywords: asynchronous machine, extended Kalman filter, resistance, simulation, temperature estimation, thermal model

Procedia PDF Downloads 258

Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

Procedia PDF Downloads 118

Authors: Songul Cinaroglu

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Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

Procedia PDF Downloads 188

Authors: A. Djahbar, E. Bounadja, A. Zegaoui, H. Allouache

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In this paper, vector control of a series-connected two-machine drive system fed by a single inverter (CSI/VSI) is presented. The two stator windings of both machines are connected in series while the rotors may be connected to different loads, are called series-connected two-machine drive. Appropriate phase transposition is introduced while connecting the series stator winding to obtain decoupled control the two-machines. The dynamic decoupling of each machine from the group is obtained using the vector control algorithm. The independent control is demonstrated by analyzing the characteristics of torque and speed of each machine obtained via simulation under vector control scheme. The viability of the control techniques is proved using analytically and simulation approach.

Keywords: drives, inverter, multi-phase induction machine, vector control

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Authors: Misarah Abdelaziz, L Djenidi, Mergen H. Ghayesh, Rey Chin

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Measurements of a turbulent boundary layer over 3D sinusoidal roughness are performed for friction Reynolds numbers ranging from 650 < Reτ < 2700. This surface was fabricated by a Multicam CNC Router machine of an acrylic sheet to have an amplitude of k/2 = 0.8 mm and an equal wavelength of 8k in both streamwise and spanwise directions, a 0.6 mm stepover and 12 mm ball nose cutter was used. Single hotwire anemometry measurements are done at one location x=1.5 m downstream at different freestream velocities under zero-pressure gradient conditions. As expected, the roughness causes a downward shift on the wall-unit normalised streamwise mean velocity profile when compared to the smooth wall profile. The shift is increasing with increasing Reτ, 1.8 < ∆U+ < 6.2. The coefficient of friction is almost constant at all cases Cf = 0.0042 ± 0.0002. The results show a gradual reduction in the inner peak of profiles with increasing Reτ until fully destruction at Reτ of 2700.

Keywords: hotwire, roughness, TBL, ZPG

Procedia PDF Downloads 186