scholarly journals On the energy efficiency of electromechanical systems with an electromagnetic vibration exciter

2020 ◽  
Vol 216 ◽  
pp. 01108
Author(s):  
А. К. Nuraliev ◽  
T. Amirov ◽  
А.J. Esenbekov
Keyword(s):  
Energy Efficiency ◽  
Electric Power ◽  
High Reliability ◽  
Vibration Exciter ◽  
Production Lines ◽  
Electromechanical Systems ◽  
Electromagnetic Vibration ◽  
Magnetic Chain ◽  
Wide Range ◽  
Wide Circle

Study shake the phenomena in the electromechanical systems (EMS) are presented by permanent interest for the wide circle of researchers. The most effective source of vibrations in many cases is an electromagnetic causative vibration exciters (EMCV) in that there is transformation of electric power to energy of mechanical vibrations, that is related to the change of inductance. Electromagnetic vibration exciters have a number of significant advantages over other types of exciters. Due to the absence of rubbing parts they have high reliability and durability. They allow you to smoothly adjust the amplitude of vibrations over a wide range. EMCV are easy to integrate into production lines, they have easy maintenance, low operating costs and extensive automation capabilities. This phenomenon presents interest at development of electromechanics devices for intensive vibrotechnologies. Especially development guided on frequency of resonant EMCV promotes the economy of consumption of electric power and productivity of vibrotechnique. To the article the results of theoretical and experimental researches are driven on the increase of energy efficiency of EMCV and determination of output-input ratio. It is shown that losses of electric power in EMS with EMCV related to the origin of permanent constituents and ultra-harmonics of current, choice of magnetic chain and dynamic.

A Resonant Electromagnetic Vibration Exciter of Oscillations with a Feedback

Vestnik MEI ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 62-66
Author(s):  
Mukhtorkhan Ibadullaev ◽  
◽  
Almikhan K. Nuraliev ◽  
Azamat Zh. Esenbekov ◽  
Alisher Zh. Nazarov ◽  
...  
Keyword(s):  
Vibration Exciter ◽  
Electromagnetic Vibration

Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

2020 ◽  
Vol 14 ◽  
Author(s):  
M. Sivaram ◽  
V. Porkodi ◽  
Amin Salih Mohammed ◽  
S. Anbu Karuppusamy
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Artificial Bee Colony ◽  
Trust Model ◽  
Sensor Nodes ◽  
Remote Areas ◽  
Bee Colony ◽  
Important Concern ◽  
Wide Range ◽  
Iot Devices

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities help to reduce the constraint demands of the current security protocols. Aim: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem in IoT and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, energy efficiency in WSNs has been an important concern. Methods: Hence, in this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

scholarly journals Forecasting for Ultra-Short-Term Electric Power Load Based on Integrated Artificial Neural Networks

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1063 ◽  
Author(s):  
Horng-Lin Shieh ◽  
Fu-Hsien Chen
Keyword(s):  
Energy Efficiency ◽  
Electric Power ◽  
Production Efficiency ◽  
Load Forecasting ◽  
Short Term ◽  
Inference System ◽  
Power Load ◽  
Power Load Forecasting ◽  
New Energy ◽  
Electric Power Load

Energy efficiency and renewable energy are the two main research topics for sustainable energy. In the past ten years, countries around the world have invested a lot of manpower into new energy research. However, in addition to new energy development, energy efficiency technologies need to be emphasized to promote production efficiency and reduce environmental pollution. In order to improve power production efficiency, an integrated solution regarding the issue of electric power load forecasting was proposed in this study. The solution proposed was to, in combination with persistence and search algorithms, establish a new integrated ultra-short-term electric power load forecasting method based on the adaptive-network-based fuzzy inference system (ANFIS) and back-propagation neural network (BPN), which can be applied in forecasting electric power load in Taiwan. The research methodology used in this paper was mainly to acquire and process the all-day electric power load data of Taiwan Power and execute preliminary forecasting values of the electric power load by applying ANFIS, BPN and persistence. The preliminary forecasting values of the electric power load obtained therefrom were called suboptimal solutions and finally the optimal weighted value was determined by applying a search algorithm through integrating the above three methods by weighting. In this paper, the optimal electric power load value was forecasted based on the weighted value obtained therefrom. It was proven through experimental results that the solution proposed in this paper can be used to accurately forecast electric power load, with a minimal error.

scholarly journals The Comprehensive Autistic Trait Inventory (CATI): development and validation of a new measure of autistic traits in the general population

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael C. W. English ◽  
Gilles E. Gignac ◽  
Troy A. W. Visser ◽  
Andrew J. O. Whitehouse ◽  
James T. Enns ◽  
...  
Keyword(s):  
Factor Analysis ◽  
General Population ◽  
Measurement Invariance ◽  
High Reliability ◽  
Predictive Ability ◽  
Autistic Traits ◽  
Autism Spectrum ◽  
Autism Spectrum Quotient ◽  
Sensory Sensitivity ◽  
Wide Range

Abstract Background Traits and characteristics qualitatively similar to those seen in diagnosed autism spectrum disorder can be found to varying degrees in the general population. To measure these traits and facilitate their use in autism research, several questionnaires have been developed that provide broad measures of autistic traits [e.g. Autism-Spectrum Quotient (AQ), Broad Autism Phenotype Questionnaire (BAPQ)]. However, since their development, our understanding of autism has grown considerably, and it is arguable that existing measures do not provide an ideal representation of the trait dimensions currently associated with autism. Our aim was to create a new measure of autistic traits that reflects our current understanding of autism, the Comprehensive Autism Trait Inventory (CATI). Methods In Study 1, 107 pilot items were administered to 1119 individuals in the general population and exploratory factor analysis of responses used to create the 42-item CATI comprising six subscales: Social Interactions, Communication, Social Camouflage, Repetitive Behaviours, Cognitive Rigidity, and Sensory Sensitivity. In Study 2, the CATI was administered to 1068 new individuals and confirmatory factor analysis used to verify the factor structure. The AQ and BAPQ were administered to validate the CATI, and additional autistic participants were recruited to compare the predictive ability of the measures. In Study 3, to validate the CATI subscales, the CATI was administered to 195 new individuals along with existing valid measures qualitatively similar to each CATI subscale. Results The CATI showed convergent validity at both the total-scale (r ≥ .79) and subscale level (r ≥ .68). The CATI also showed superior internal reliability for total-scale scores (α = .95) relative to the AQ (α = .90) and BAPQ (α = .94), consistently high reliability for subscales (α > .81), greater predictive ability for classifying autism (Youden’s Index = .62 vs .56–.59), and demonstrated measurement invariance for sex. Limitations Analyses of predictive ability for classifying autism depended upon self-reported diagnosis or identification of autism. The autistic sample was not large enough to test measurement invariance of autism diagnosis. Conclusions The CATI is a reliable and economical new measure that provides observations across a wide range of trait dimensions associated with autism, potentially precluding the need to administer multiple measures, and to our knowledge, the CATI is also the first broad measure of autistic traits to have dedicated subscales for social camouflage and sensory sensitivity.

Friction Tests of Ball Bearings with Comparison of Lubricants

2017 ◽  
Vol 866 ◽  
pp. 375-378
Author(s):  
Sathitbunanan Sumate ◽  
Wirote Ritthong
Keyword(s):  
Energy Efficiency ◽  
Electric Power ◽  
Ball Bearing ◽  
Maximum Load ◽  
Engine Oil ◽  
Ball Bearings ◽  
Hydraulic Oil ◽  
Proper Size ◽  
Transmission Fluid ◽  
Moving Parts

The ball bearings are the rotating components which are widely spread to moving parts for all machinery operation in general industry. This paper presents the ball bearing resistance tool which has a proper size and can handle the maximum load of 300 kg by using an electric power. The ball bearing resistance tool was used to test the bearings No. 6011 cm. The series of tests was performed in the ball bearings lubricated; engine oil SAE 10W/40, auto transmission fluid Dexron, and hydraulic oil. The rotational speeds for testing were vary; 500, 600 and 700 rpm respectively. At each speed, there were various weight; 50, 70, 90,110,130,150, and 170 kg respectively. The results show that the hydraulic oil generated the smallest coefficients of friction and energy efficiency for ball bearing operation.

scholarly journals Online Thread and Data Mapping Using a Sharing-Aware Memory Management Unit

2021 ◽  
Vol 5 (4) ◽  
pp. 1-28
Author(s):  
Eduardo H. M. Cruz ◽  
Matthias Diener ◽  
Laércio L. Pilla ◽  
Philippe O. A. Navaux
Keyword(s):  
Energy Efficiency ◽  
Memory Management ◽  
Substantial Reduction ◽  
Management Unit ◽  
Memory Access ◽  
Parallel Applications ◽  
Data Mapping ◽  
Wide Range ◽  
Memory Accesses ◽  
Level Parallelism

Current and future architectures rely on thread-level parallelism to sustain performance growth. These architectures have introduced a complex memory hierarchy, consisting of several cores organized hierarchically with multiple cache levels and NUMA nodes. These memory hierarchies can have an impact on the performance and energy efficiency of parallel applications as the importance of memory access locality is increased. In order to improve locality, the analysis of the memory access behavior of parallel applications is critical for mapping threads and data. Nevertheless, most previous work relies on indirect information about the memory accesses, or does not combine thread and data mapping, resulting in less accurate mappings. In this paper, we propose the Sharing-Aware Memory Management Unit (SAMMU), an extension to the memory management unit that allows it to detect the memory access behavior in hardware. With this information, the operating system can perform online mapping without any previous knowledge about the behavior of the application. In the evaluation with a wide range of parallel applications (NAS Parallel Benchmarks and PARSEC Benchmark Suite), performance was improved by up to 35.7% (10.0% on average) and energy efficiency was improved by up to 11.9% (4.1% on average). These improvements happened due to a substantial reduction of cache misses and interconnection traffic.

Schwingungsanalyse an Industrierobotern*/Vibration analysis of industrial robots

2019 ◽  
Vol 109 (09) ◽  
pp. 656-661
Author(s):  
A. Karim ◽  
C. Michalkowski ◽  
A. Lechler ◽  
A. Verl
Keyword(s):  
Modal Analysis ◽  
Active Control ◽  
Normal Mode ◽  
Vibration Analysis ◽  
Industrial Robots ◽  
Vibration Exciter ◽  
Dynamic Vibration ◽  
Vibration Behavior ◽  
Working Space ◽  
Electromagnetic Vibration

Dieser Beitrag untersucht experimentell das dynamische Schwingverhalten eines „KR-500–3 MT“ von Kuka mittels eines elektromagnetischen Schwingerregers (Shaker) an insgesamt 28 Messposen im Arbeitsraum. Diese Untersuchungsmethode ist neuartig, da die Ergebnisse mit einer Modalanalyse mit Impulshammeranregung verglichen werden. Ab der vierten Eigenmode entstehen Unterschiede aufgrund der Anregungsform. Zudem wird an jeder Pose eine Messung mit angezogener Motorbremse und eine mit aktiver Regelung durchgeführt und miteinander verglichen.   This paper explores experimentally the dynamic vibration behavior of a Kuka KR-500 MT, using an electromagnetic vibration exciter (shaker) on a total of 28 measuring poses in the working space. As such studies are not known, the results are compared to a modal analysis with impulse hammer excitation. Starting from the fourth normal mode, differences arise due to the form of excitation. Both measurements are performed and compared with each other on each pose with brakes applied as well as with active control.

The Research of GPRS-Based Remote Fault Monitoring System for CNC Machine Tools

2011 ◽  
Vol 328-330 ◽  
pp. 393-397
Author(s):  
Ming Liang Wu ◽  
Xiao Bing Wang ◽  
Shu Rong Yu
Keyword(s):  
Monitoring System ◽  
Communication Networks ◽  
Remote Monitoring ◽  
Data Transfer ◽  
High Reliability ◽  
Fast Response ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Remote Monitoring System ◽  
Wide Range

Based on GPRS network remote monitoring system which uses its two-way transmission performance, can easily monitor various electrical equipments and get information. Compare with the past remote monitoring systems, the system has the advantage of flexible networking, convenient, wide range of data transmission, high reliability, fast response time, and has great significance and value of research in CNC machine tool system with upgrade GPRS in the mobile communication networks, data services expand and data transfer capabilities.

Sign in / Sign up

Export Citation Format

Share Document