Artigos - Engenharia Elétrica - FEB

URI Permanente para esta coleção

Navegar

Submissões Recentes

Agora exibindo 1 - 20 de 375
  • ItemResenha
    Sensors Applied to Bearing Fault Detection in Three-Phase Induction Motors†
    (2021-01-01) Lucas, Guilherme Beraldi [UNESP]; de Castro, Bruno Albuquerque [UNESP]; Serni, Paulo José Amaral [UNESP]; Riehl, Rudolf Ribeiro [UNESP]; Andreoli, André Luiz [UNESP]; Universidade Estadual Paulista (UNESP)
    Three-Phase Induction Motors (TIMs) are widely applied in industries. Therefore, there is a need to reduce operational and maintenance costs since their stoppages can impair production lines and lead to financial losses. Among all the TIM components, bearings are crucial in the machine operation once they couple rotor to the motor frame. Furthermore, they are constantly subjected to friction and mechanical wearing. Consequently, they represent around 41% of the motor fault, according to IEEE. In this context, several studies have sought to develop monitoring systems based on different types of sensors. Therefore, considering the high demand, this article aims to present the state of the art of the past five years concerning the sensing techniques based on current, vibration, and infra-red analysis, which are characterized as promising tools to perform bearing fault detection. The current and vibration analysis are powerful tools to assess damages in the inner race, outer race, cages, and rolling elements of the bearings. These sensing techniques use current sensors like hall effect-based, Rogowski coils, and current transformers, or vibration sensors such as accelerometers. The effectiveness of these techniques is due to the previously developed models, which relate the current and vibration frequencies to the origin of the fault. Therefore, this article also presents the bearing fault mathematical modeling for these techniques. The infra-red technique is based on heat emission, and several image processing techniques were developed to optimize bearing fault detection, which is presented in this review. Finally, this work is a contribution to pushing the frontiers of the bearing fault diagnosis area.
  • ItemArtigo
    Assessment of Partial Discharges Evolution in Bushing by Infrared Analysis †
    (2021-01-01) de Castro, Bruno Albuquerque [UNESP]; Lucas, Guilherme Beraldi [UNESP]; Fernandes, Gabriel Scota [UNESP]; Fraga, José Renato Castro Pompéia [UNESP]; Riehl, Rudolf Ribeiro [UNESP]; Andreoli, André Luiz [UNESP]; Universidade Estadual Paulista (UNESP)
    The quality of power systems is related to their capability to predict failures, avoid stoppages, and increase the lifetime of their components. Therefore, science has been developing monitoring systems to identify failures in induction motors, transformers, and transmission lines. In this context, one of the most crucial components of the electrical systems is the insulation devices such as bushings, which are constantly subjected to dust, thermal stresses, moisture, etc. These conditions promote insulation deterioration, leading to the occurrence of partial discharges. Partial discharges are localized dielectric breakdown that emits ultra-violet radiation, heat, electromagnet, and acoustics waves. The most traditional techniques to identify these flaws on bushings are based on the current, ultra high frequency, and acoustic emission analysis. However, thermal analysis stands out as a noise-resistant technique to monitor several components in the power systems. Although the thermal method is applied to detect different types of faults, such as bad contacts, overloads, etc, this technique has not been previously applied to perform partial discharge detection and evaluate its evolution on bushings. Based on this issue, this article proposes two new indexes to characterize the discharge evolution based on the infrared thermal analysis: the area ratio coefficient and the Red, Green, and Blue (RGB) ratio coefficient. Seven discharge levels were induced in a contaminated bushing, and an infrared thermal camera captured 20 images per condition, totalizing 140 images. New coefficients were used to perform the identification of discharge evolution. Results indicated that values of the new indexes increase with the partial discharge activity. Thus, the new imaging processing approach can be a promising contribution to literature, improving the reliability and maintenance planning for power transmission systems.
  • ItemArtigo
    Assessment of Rogowski Coils for Measurement of Full Discharges in Power Transformers †
    (2021-01-01) Riehl, Rudolf Ribeiro [UNESP]; de Castro, Bruno Albuquerque [UNESP]; Fraga, José Renato Castro Pompéia [UNESP]; Puccia, Victor [UNESP]; Lucas, Guilherme Beraldi [UNESP]; Andreoli, André Luiz [UNESP]; Universidade Estadual Paulista (UNESP)
    Science and industry have sought to develop systems aiming to avoid total failures in power transformers since these machines can be working under overloads, moisture, mechanical and thermal stresses, among others. These non-conformities can promote the degradation of the insulation system and lead the transformer to total failure. In the incipient stages of these faults, it is common to detect Full Discharges (FDs), which are short circuits between degraded coils. Therefore, several techniques were developed to perform FD diagnosis using UHF, acoustics, and current sensors. In this scenario, this article presents a mathematical model for Rogowski coils and compares two different types of cores: Ferrite and Teflon. For this purpose, FDs were induced in an oil-filled transformer. The sensitivity and frequency response of the Rogowski coils were compared. This analysis was achieved using the Power Spectrum Density (PSD) and the energy of the acquired signals. Additionally, the Short-Time Fourier Transform (STFT) was applied to detect repetitive discharges. The results indicated that the Ferrite core increases the sensitivity by 50 times in the frequency band between 0 and 1 MHz. However, the Teflon core showed higher sensitivity between 5 and 10 MHz.
  • ItemArtigo
    A Tunable CMOS Image Sensor with High Fill-Factor for High Dynamic Range Applications †
    (2020-01-01) Campos, Fernando de Souza [UNESP]; Castro, Bruno Albuquerque de [UNESP]; Swart, Jacobus W.; Universidade Estadual Paulista (UNESP); Center of Semiconductor Components and Nanotechnologies
    Several CMOS imager sensors were proposed to obtain high dynamic range imager (>100 dB). However, as drawback these imagers implement a large number of transistors per pixel resulting in a low fill factor, high power consumption and high complexity CMOS image sensors. In this work, a new operation mode for 3 T CMOS image sensors is presented for high dynamic range (HDR) applications. The operation mode consists of biasing the conventional reset transistor as active load to photodiode generating a reference current. The output voltage achieves a steady state when the photocurrent becomes equal to the reference current, similar to the inverter operation in the transition region. At a specific bias voltage, the output swings from o to Vdd in a small light intensity range; however, high dynamic range is achieve using multiple readout at different bias voltage. For high dynamic range operation different values of bias voltage can be applied from each one, and the signal can be captured to compose a high dynamic range image. Compared to other high dynamic range architectures this proposed CMOS image pixel show as advantage high fill-factor (3 T) and lower complexity. Moreover, as the CMOS pixel does not operate in integration mode, de readout can be performed at higher speed. A prototype was fabricated at 3.3 V 0.35 µm CMOS technology. Experimental results are shown by applying five different control voltage from 0.65 to 1.2 V is possible to obtain a dynamic range of about 100 dB.
  • ItemArtigo
    New Algorithm Applied to Transformers’ Failures Detection Based on Karhunen-Loève Transform
    (2023-01-01) Castro, Bruno Albuquerque de; Binotto, Amanda; Ardila-Rey, Jorge Alfredo; Fraga, Jose Renato Castro Pompeia; Smith, Colin; Andreoli, Andre Luiz; Universidade Estadual Paulista (UNESP)
    Industry and science have been growing attention to developing systems that ensure the integrity of high voltage devices like power transformers. The goal is to avoid unexpected stoppages by detecting incipient failures before they become a major problem. In this context, the detection of discharge activity is an effective way to assess the condition operation of power transformers since this type of flaw can lead the transformer to total failure. The effectiveness of the fault diagnosis systems is related to their capability to distinguish the types of discharges since different flaws require different maintenance planning. This article proposes a new data analysis which combined the frequency spectrum of the signals with the Karhunen-Loève Transform to perform self-organization maps. The effectiveness of this analysis was validated by comparing it with the Fundamental Signals Properties Classification Technique, which is widely applied for pattern recognition.Two types of sensing techniques were assessed in order to enhance the capability of the new approach. Results indicated that the new methodology presented lower standard deviation for data classification, being a promising tool to monitoring systems.
  • ItemArtigo
    New Signal Processing-Based Methodology for Optimal Feature Selection of Corona Discharges Measurement in HVDC Systems
    (2023-01-01) David, Gabriel Augusto [UNESP]; Junior, Pedro Oliveira Conceicao; Dotto, Fabio Romano Lofrano; Santos, Benedito Roberto Dos; Universidade Estadual Paulista (UNESP); Universidade de São Paulo (USP); Farol Pesquisa; Interligação Elétrica Do Madeira S.A.
    This article presents a new method based on the combination of digital signal processing parameters for the selection of optimal characteristics of corona discharges in high voltage direct current (HVDC) systems, particularly for linearization of the discharge model for applications that require a simplified computational approach. The proposed method implements a new metric from the coefficient of variation (CV), CV $_{\mathbf {STFT}}$ , based on the short-time Fourier transform (STFT) and the Hinkley criterion to measure the spectral variability and determine the corona discharge profile in different situations. An experimental analysis was performed by applying voltages between ±30 and ±100 kV in a conductor, and electrical current signals proportional to the corona effect were collected through a data acquisition system. The results indicated that the application of the new method was successful in quantifying, in a simple way, the percentage of growth of corona discharges as a function of the voltage applied within the range of 40-80 kHz. Moreover, it showed 90%, 91%, 92%, 97%, 89%, 92%, and 93% of reliability in calculating the root-mean-square deviation (RMSD) based on approximation by a linear model. The frequency band resulting from this study proved to be favorable to establishing a threshold for the percentage of corona discharge growth according to its profile or condition of application, indicating this information may be useful in the construction of mobile devices with low consumption and computational performance, meeting the demands of Industry 4.0 and the Internet of Things.
  • ItemArtigo
    A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
    (2023-04-15) Lucas, Guilherme Beraldi [UNESP]; De Castro, Bruno Albuquerque [UNESP]; Ardila-Rey, Jorge Alfredo; Glowacz, Adam; Leao, Jose Vital Ferraz [UNESP]; Andreoli, Andre Luiz [UNESP]; Universidade Estadual Paulista (UNESP); Universidad Técnica Federico Santa María; Agh University of Science and Technology
    Noninvasive fault diagnosis of three-phase induction motors (TIMs) is widely used in industrial applications to ensure the integrity of processes. Among different types of TIM failures, transient interturn short circuits (ITSCs) are incipient stator winding faults characterized as short circuits between two or more turns of the coils, that can lead the winding to progressive deterioration and, consequently, the TIM to total failure. In this context, this article proposes a novel approach by using piezoelectric transducers (PZTs), which performs the transient ITSC detection, phase identification, and magnitude classification by using the acoustic emission (AE) technique. To accomplish this analysis, a new statistical index based on the cross-correlation function was proposed to detect the ITSC and classify its magnitude. Besides, wavelet transform and principal component analysis (PCA) stood out as promising tools to identify which phase was affected by the short circuits. A TIM was subjected to ITSCs, and the experimental results showed that the proposed algorithm successfully performed the transient ITSC detection, phase identification, and evolution classification. In addition, this work improve the capabilities of traditional AE systems, since no AE signal processing algorithm has ever been proposed for a comprehensive diagnosis of transient ITSC.
  • ItemArtigo
    Time-Domain Analysis of Acoustic Emission Signals during the First Layer Manufacturing in FFF Process †
    (2022-01-01) Lopes, Thiago Glissoi [UNESP]; Aguiar, Paulo Roberto [UNESP]; França, Thiago Valle [UNESP]; Conceição Júnior, Pedro de Oliveira; Soares Junior, Cristiano [UNESP]; Antonio, Zaqueu Ricardo Fernando [UNESP]; Universidade Estadual Paulista (UNESP); Universidade de São Paulo (USP)
    Additive manufacturing (AM) has been playing a crucial role in the fourth industrial revolution. Sensor-based monitoring technologies are essential for detecting defects and providing feedback for process control. Acoustic emission (AE) sensors have been used for a long time in a wide range of processes and fields, but they are still a challenge in AM processes. This work presents a study on the AE signals in the time-domain—raw and root mean square (RMS) values—regarding their behavior during the manufacture of a single-layer part in the fused filament fabrication process for two infill patterns. The tests were conducted on a cartesian 3D printer using polylactic acid material. The AE sensor was attached to the printer table through a magnetic coupling, and the signal was collected by an oscilloscope at 1 MHz sampling frequency. It was found that the raw AE signals behaved quite differently not just for the two infill patterns, but within the same pattern. The raw and RMS AE signals contained many spikes along the whole process, but the higher ones were those generally occurring at the end and/or start of a fabrication line. The RMS values, however, were useful for finding the start and end times of each fabricated line for both patterns. The mean RMS values showed nearly constant but distinct averages for the extruder-only, table-only and extruder–table movements.
  • ItemTrabalho apresentado em evento
    Ultrasonic Damage Assessment Using Virtual Time Reversal Indices and the RAPID Method
    (2023-01-01) de Castro, Bruno Albuquerque [UNESP]; Baptista, Fabricio Guimarães [UNESP]; Ciampa, Francesco; Universidade Estadual Paulista (UNESP); University of Surrey
    Ultrasonic methods for damage imaging typically use baseline signals from the undamaged part, which are often affected by real operational conditions and may not always be available. This paper proposes a baseline-free damage imaging algorithm based on a combination of virtual time reversal (VTR) and the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) tomographic technique. VTR is an alternative to traditional time reversal as it reduces the burden of physically back-propagating re-mitted signals by applying signal operations between the transmitted and received waveforms. Spatial VTR-based damage indices were here proposed to enhance defect detection as they do not require the time domain reconstruction of re-emitted signals. Experimental results on damaged aluminium and composite specimens showed that the proposed VTR-based damage indices coupled to the RAPID imaging algorithm were able to localise material flaws with a maximum localisation error of ~6 mm and ~2 mm for aluminium and composite samples, respectively.
  • ItemArtigo
    An Application of Wavelet Analysis to Assess Partial Discharge Evolution by Acoustic Emission Sensor
    (2020-01-01) Santos, Vitor Vecina dos [UNESP]; Castro, Bruno Albuquerque de [UNESP]; Binotto, Amanda [UNESP]; Rey, Jorge Alfredo Ardila; Lucas, Guilherme Beraldi [UNESP]; Andreoli, André Luiz [UNESP]; Universidade Estadual Paulista (UNESP); Universidad Técnica Federico Santa María
    Under normal operation, insulation systems of high voltage electrical devices, like power transformers, are constantly subjected to multiple types of stresses (electrical, thermal, mechanical, environmental, etc.), which can lead to a degradation of the machine insulation. One of the main indicators of the dielectric degradation process is the presence of partial discharges (PD). Although it starts due to operational stresses, PD can cause a progressive insulation deterioration, since it is characterized by localized current pulses that emit heat, UV radiation, acoustic, and electromagnetic waves. In this sense, acoustic emission (AE) transducers are wildly applied in PD detection. The goal is to reduce maintenance costs by predictive actions and avoid total failures. Becasue of the progressive deterioration, the assessment of the PD evolution is crucial for improving the maintenance planning and ensure the operation of the transformer. Based on this issue, this article presents a new wavelet -based analysis in order to characterize the PD evolution. Three levels of failures were carried out in a transformer and the acoustic signals captured by a lead zirconate titanate piezoelectric transducer were processed by discrete wavelet transform. The experimental results revealed that the energy of the approximation levels increasing with the failure evolution. More specifically, levels 4, 6, 7, and 10 presented a linear fit to characterize the phenomena, enhancing the applicability of the proposed approach to transformer monitoring.
  • ItemArtigo
    Optimization of Ceramics Grinding
    (Intech Europe, 2011-01-01) Bianchi, Eduardo Carlos [UNESP]; Aguiar, Paulo Roberto de [UNESP]; Diniz, Anselmo Eduardo; Canarim, Rubens Chinali [UNESP]; Sikalidis, C.; Universidade Estadual Paulista (UNESP); Universidade Estadual de Campinas (UNICAMP)
  • ItemArtigo
    Application of Minimum Quantity Lubrication in Grinding
    (Iste Ltd, 2010-01-01) Bianchi, Eduardo Carlos [UNESP]; Aguiar, Paulo Roberto de [UNESP]; Silva, Leonardo Roberto da; Canarim, Rubens Chinali [UNESP]; Davim, J. P.; Universidade Estadual Paulista (UNESP); CEFET
    This chapter deals with the application of minimum quantity lubrication (MQL) in grinding. This work aims to present some previous research results of the application of MQL in grinding by considering material to be ground (steels or ceramics) and type of grinding (surface, internal, and external cylindrical grinding).
  • ItemArtigo
    Optimization-Based Models for Estimating Residual Demand Curves for a Price-Maker Company
    (2022-01-01) Cabana, Tiago G.; Baptista, Edmea C.; Soler, Edilaine M.; Martins, Andre C. P.; Balbo, Antonio R.; Nepomuceno, Leonardo; Universidade Estadual Paulista (UNESP)
    The Residual Demand Curve (RDC) aims to estimate the day-ahead market clearing prices given the quotas scheduled for a price-maker generation company in the market. Traditionally, this curve has been obtained by the difference between the inverse functions of aggregated demand and aggregated supply. An important drawback of such approach is that constraints related to complex-bid markets cannot be directly represented in the RDC. In this paper we interpret the traditional RDC as an optimization model and propose Optimization-Based Residual Demand (OBRD) models which represent a series of market clearing procedures where the residual demand is progressively increased. Differently from traditional methods, the proposed approach allows for explicit representation of complex-bid markets. We show that under certain conditions the RDC obtained by the proposed OBRD model is equivalent to that provided by traditional methods. We also propose a methodology for comparing the quality of different RDCs in what regards their ability to predict market clearing prices and the company's profits. Results show that the RDCs obtained by the OBRD model are significantly more accurate than those obtained by traditional approaches for complex-bid markets.
  • ItemArtigo
    Development of a portable corona current measuring device for high voltage detection in HVDC systems
    (2022-01-01) Lofrano DOTTO, Fabio ROMANO; Oliveira Conceicao Junior, Pedro; Andreoli, Andre Luiz; De Oliveira Junior, Reinaldo Gotz; Roberto Dos Santos, Benedito Roberto; Universidade Estadual Paulista (UNESP)
    The purpose of this work is to present a technological alternative based on the study and development of a simple and portable electronic device to enable the detection and quantification of high voltage and polarity in HVDC systems. The principle of this solution is based on the detection of corona current by means of an aluminum tip held at a distance of about 5 mm from the energized surface through a radial contact rod. The detected electrical current signal is collected and processed through an electronic measuring system. The performance of the proposed device was analyzed by means of corona discharge models and high voltage experimental tests in real-world conditions. The results demonstrated the satisfactory response of the proposed approach in the detection, quantification, and identification of polarity in a 600 kV HVDC transmission system, with an error varying from 1.79% to 2.72% compared to theoretical values, as well as its ability to withstand the influence of temperature variations between 18C to 29C, relative humidity between 56% and 78%, and an atmospheric pressure kept constant at 101.6 kPa. The proposed approach contributes to HVDC monitoring, helping to ensure their operation and suitability and the physical safety of operators.
  • ItemErrata
    Sem título
    (2022-09-01) Souza, Rafael R. [UNESP]; Balbo, Antonio R. [UNESP]; Martins, André C.P. [UNESP]; Soler, Edilaine M. [UNESP]; Baptista, Edméa C. [UNESP]; Silva, Diego N.; Nepomuceno, Leonardo [UNESP]; Universidade Estadual Paulista (UNESP); IFSP ˗ Presidente Epitácio
    The authors regret the mistake in the surname of one of the authors. The correct name is Diego N. Silva, and not Diego N. Sousa, as is incorrectly writhen in the final version of the paper. The authors would like to apologise for any inconvenience caused.
  • ItemArtigo
    A Gradient-Based Approach for Solving the Stochastic Optimal Power Flow Problem with Wind Power Generation
    (2022-08-01) Souza, Rafael R. [UNESP]; Balbo, Antonio R. [UNESP]; Martins, André C. P. [UNESP]; Soler, Edilaine M. [UNESP]; Baptista, Edméa C. [UNESP]; Sousa, Diego N.; Nepomuceno, Leonardo [UNESP]; Universidade Estadual Paulista (UNESP); IFSP-Presidente Epitácio
    Although wind power generation improves decarbonization of the electricity sector, its increasing penetration poses new challenges for power systems planning, operation and control. In this paper, we propose a solution approach for Stochastic Optimal Power Flow (SOPF) models under uncertainty in wind power generation. Two complicating issues are handled: i) difficulties imposed by probability density functions used to formulate wind power costs and their derivatives; ii) the non-differentiability of the cost function for thermal units. Due to such issues, SOPF models cannot be solved by gradient-based approaches and have been solved by meta-heuristics only. We obtain exact analytical expressions for the first and second order derivatives of wind power costs and propose a technique for handling non-differentiability in thermal costs. The equivalent SOPF model that results from such recasting is a differentiable NLP problem which can be solved by efficient gradient-based algorithms. Finally, we propose a modified log-barrier primal-dual interior/exterior-point method for solving the equivalent SOPF model which, differently from meta-heuristic approaches, is able to calculate important dual variables such as energy prices. Our approach, which is applied to the IEEE 30-, 57- 118- and 300-bus systems, strongly outperforms a meta-heuristic approach in terms of computation times and optimality.
  • ItemArtigo
    A Comparative Analysis Applied to the Partial Discharges Identification in Dry-Type Transformers by Hall and Acoustic Emission Sensors
    (2022-03-01) de Castro, Bruno Albuquerque [UNESP]; Dos Santos, Vitor Vecina [UNESP]; Lucas, Guilherme Beraldi [UNESP]; Ardila-Rey, Jorge Alfredo; Riehl, Rudolf Ribeiro [UNESP]; Andreoli, André Luiz [UNESP]; Universidade Estadual Paulista (UNESP); Universidad Técnica Federico Santa María
    Dry-type insulated transformers stand out for their higher applicability in substations, high-voltage instrumentation systems, and electrical installations. In this machine, the insulation system is constituted of dielectric materials such as epoxy resin and Nomex paper. Some critical issues in the operation of this equipment, such as overload, moisture, or heat, can induce a slow degradation of the physical–chemical properties of the dielectric materials, which can culminate in the total failure of the transformer. However, before the transformer’s shutdown, it is common to detect discharge activity in the insulation system. Based on this issue, this work proposes an experimental and comparative analysis between acoustic emission and Hall-effect sensors, aiming at differentiating discharges in epoxy resin and Nomex paper, materials that constitute the insulation of the dry-type insulated transformers. Two signal processing techniques were studied: traditional frequency analysis and discrete wavelet transform. The objective is to develop signal processing techniques to differentiate each type of discharge since different discharges require different maintenance actions. The results obtained indicate that acoustic emission sensors and Hall sensors are promising in differentiating discharge in epoxy resin and Nomex paper. Furthermore, the pattern recognition tools presented by this work, which associated the wavelet levels energies and the energy of the full signals with the average band and the equivalent bandwidth, were effective to perform feature extraction of power transformer condition.
  • ItemTrabalho apresentado em evento
    A new intelligent system architecture for energy saving in smart homes
    (2019-01-25) Ayres, Rodrigo Moura Juvenil [UNESP]; Souza, Andre Nunes De [UNESP]; Gastaldello, Danilo S.; Haroldo Do Amaral, L. M.; Ikeshoji, Marco Akio [UNESP]; Santana, Gustavo Vinicius [UNESP]; Universidade Estadual Paulista (UNESP); Universidade Do Sagrado Coração; Universidade de São Paulo (USP)
    Technologies to support the development of smarter energy systems and increase the opportunities for home energy management have increased in recent years. Through the addition of sensing, communication and drive components, devices and home appliances become increasingly smart so that they can communicate with each other, transmit data to end users and facilitate remote operation and automation, for example during periods of peak demand. This has the potential to provide energy-related benefits to end-users and network operators. One of the key benefits of intelligent techniques is the potential to support power reductions and demand side management. Within this context, this work aims to propose a system architecture for recommend suggestions to smart homes inhabitants (according to different user profiles), aiming cost reduction and energy efficiency. The work also includes the implementation of a RESTFul mining web service, which is part of the proposed architecture. The web service is used to release data mining, classifying data over the proposed recommender system. Through the data model transmission known as JSON (JavaScript Object Notation), the web service receives data and automatically convert to JSON Instances structures, processing the same with the data mining algorithms.
  • ItemCapítulo de livro
    Laterality and Usability: Biomechanical aspects in prehension strength
    (2012-01-01) Paschoarelli, Luis Carlos [UNESP]; Razza, Bruno Montanari [UNESP]; Lúcio, Cristina do Carmo [UNESP]; Ulson, José Alfredo Covolan [UNESP]; Silva, Danilo Corrêa [UNESP]; Universidade Estadual Paulista (UNESP)
    Although technological developments in recent decades have improved the quality of life for many, a number of user interface problems still exist. There are difficulties, for example, manipulating manual instruments by those with specific needs, especially left-handed users. The design of such instruments depends on scientific knowledge of biomechanical forces - especially prehension. The aim of this study was to analyze biomechanical effort during simulated manual activities (compression, traction and torque with 14 different manual interfaces) between dominant and non-dominant hands. Sixty individuals (30 left-handed) participated in the study. Measurements were taken with an advanced force gauge and a static torque transducer. The results indicate that right-handed individuals perform better (p = 0.05) with the dominant hand (in 12 manuals interfaces), while there were no significant strength differences among the left-handed (except for two manual interfaces). The reasons why left-handed individuals present little difference in strength between the dominant and non-dominant hands are not clear, but could be the result of frequent use of the non-dominant hand to perform many instrumental activities of daily living (IADLs). Moreover, it could be due to greater symmetry in the organization of brain hemispheres compared to the strong lateralization of righthanded individuals. The results provide insight into the dynamics of the manipulation of a number of manual instruments according to right and left-handed groups.
  • ItemCapítulo de livro
    Pulling strength with pinch grips: A variable for product design
    (2012-01-01) Razza, Bruno Montanari [UNESP]; Paschoarelli, Luis Carlos [UNESP]; Silva, Danilo Corrêa [UNESP]; Ulson, José Alfredo Covolan [UNESP]; Lucio, Cristina do Carmo [UNESP]; Universidade Estadual Paulista (UNESP)
    Pulling with pinch grips is an action frequently used in either occupational or daily living activities, especially in situations where the object is too small, the access to the object is restricted, the use of tools is prevented and situations such as pulling strips out of long-life packaging, removing seals from flask lids, tearing a plastic bag, etc. Excessive demands of strength in those actions may limit the user’s access to certain activities and even lead to injury. The objective of this study was to collect valid data of pulling strength with pinch grips to be applied to the design of safer and more comfortable products and tasks. Three handles of different heights (1 mm, 20mm and 40mm) were used in the study and three types of pinch grips were measured with both hands: pinch-2, chuck pinch and lateral pinch. The study included 30 men and 30 women, all right-handed and healthy, and the maximum voluntary isometric contraction was measured in the standing posture. The results showed that the type of pinch grip used influenced more greatly the pulling strength than the size of the handles. This study provides biomechanical data of an action often performed in many daily living activities and also in several occupational tasks, but has been still little explored.