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Biomedical Sciences instrumentation 2024年第1期60卷 116-121页

作者： Madan, S. Nishanth, K. Arunganesh, K. Sivakumaran, N. Karthick, P.A. Department of Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli Tamilnadu India Department of Production Engineering National Institute of Technology Tiruchirappalli Tamilnadu India Periyar Maniammai Institute of Science and Technology Thanjavur India

People who have lost lower limbs due to accidents, trauma, or diseases often need aid in carrying out the daily life activities. Patients with transfemoral amputations use passive prosthetic limb. In the recent times, researchers have shown paramount interest in surface electromyography (sEMG) control enabled prosthestic knee for the better life. However, the extraction of prominent EMG biomarkers for the accurate detection of locomotion modes remains to be challenging. In this work, an attempt has been made to classify the wireless sEMG signals of lower limb muscles into level walking, stair ascent and descent, and ramp ascent and descent using prominent time domain features and CatBoost classification algorithm. The sEMG of six lower limb muscles namely, rectus femoris, biceps femoris, tibialis anterior, medial gastronomies, vastus lateralis, and semitendinosus are considered. Time domain features such as root mean square, integrated EMG, mean absolute value, waveform length, Willison amplitude, skewness, entropy, and zero crossing, and variance are extracted and used for training the CatBoost and support vector machine (SVM). The study revealed SVM and CatBoost algorithms effectively classify these movements, employing 10 fold cross-validations for accuracy and stability assessment. The results show that the features are distinct in all five locomotion modes significant of (p © 2024 IAE All rights reserved.

关键词： Support vector machines

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Image Registration Guided Brain Tumour Segmentation and Advancements

Image Registration Guided Brain Tumour Segmentation and Adva...

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2024 International Conference on Innovations and Challenges in Emerging Technologies, ICICET 2024

作者： Mundada, Kapil Badgujar, Mayur Sarde, Atharva Athalye, Gargee Kulkarni, Jayant Vishwakarma Institute of Technology Department of Instrumentation & Control Engineering Maharashtra Pune India

ISBN: (纸本)9798350319019

In the field of medical imaging, detecting brain tumors through image registration poses a formidable challenge. Automated tools play a vital role in non- invasively identifying and documenting tumors. Significant advancements in medical image processing, facilitated by advanced image registration techniques, have greatly contributed to improved brain tumor detection. Based on such techniques this study discusses image registration-based brain tumor segmentation and their advancements. This experimental validation is performed with MRI images of 100 patients from BraTS2020 (Brain Tumor Segmentation) dataset, it involves training models without registered images (35 epochs) and with registered images (20,35 and 40 epochs). This research presents a unique image registration approach that sets it apart from existing methods by employing the Gradient Descent Linear Search algorithm for optimization and using Mutual Information as the Similarity Metric, our method demonstrates superior performance compared to conventional techniques. The integration of Linear Interpolation, 3D Euler Transformation, and Advanced Resampling distinguishes our work, further providing a more comprehensive and accurate solution for multi- dimensional image alignment. © 2024 IEEE.

关键词： Image registration

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Correlating Solar PV Technical Metrics and Financial Outcomes: A Year-Long Study of System Performance 4

Correlating Solar PV Technical Metrics and Financial Outcome...

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4th IEEE International Conference on Applied Electromagnetics, Signal processing, and Communication, AESPC 2024

作者： Tomar, Anuradha Kumar, Hritik Netaji Subhas University of Technology Department of Instrumentation & Control Engineering Delhi India

ISBN: (纸本)9798331528171

The efficiency of photovoltaic (PV) systems is an important component in delivering high revenue to achieve the necessary goals at minimum cost and to overcome various climatic conditions in different areas. This paper aims to provide detailed techno-economic investigation of a PV system installed in a university in Delhi, India for one year. The analysis targets fundamental technical parameters namely AC power inverter indications, solid and baseline solar irradiation data, real-time yield as well as possible output. A comparison is then made of the expected production levels at 100% efficiency, 80% efficiency, and 60% efficiency then comparing the forecasted values with the production rates while considering breakdown losses, performance deviations, and energy losses during communication downtimes. In parallel, qualitative assessment validates the impact of operational inefficiencies on the profitability of the organization, and numerical assessment of ROI, the operation and manufacturing costs, and consequences of production inefficiency. The additional combination of both technical and financial data provides a comprehensive understanding of system performance by showing how technical variations including those in the solar irradiation and in the efficiency of the system have impacts on financial aspects in the long run. Thus, providing correlation of these technical and financial parameters of this study will create a framework of how to enhance performance of the PV system and how to make good financial decisions. The findings help to enhance the knowledge of actual performance of PV systems and provide useful information for enhancement of PV systems design, control and economic assessment in the renewable power generation industry. © 2024 IEEE.

关键词： Solar irradiance

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Bearing Fault Detection Using Autoregressive Modeling 1

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control instrumentation System Conference, CISCON 2023

作者： Patankar, Sanika S. Kamalapure, Prithiviraj Dayanand Department of Instrumentation and Control Engineering Vishwakarma Institute of Technology Maharashtra Pune India

ISBN: (数字)9789819758661

ISBN: (纸本)9789819758654

Typical components of rotating machinery include bearings with rolling parts. Vibration analysis is widely used to assess the overall health and condition of spinning machinery. To achieve exceptionally dependable operations, finding faults is crucial. The vibration signals can be used to ascertain the health and status of the bearing. Bearing faults in rotating machinery can lead to serious operational issues and result in costly downtime and maintenance. To avoid unexpected failures and maximize maintenance plans, early diagnosis and detection of bearing defects are essential. A novel approach for bearing fault detection using autoregressive (AR) modeling is presented in this paper. The AR model effectively identifies the bearing faults by capturing the dynamic behavior of bearing vibration data. Experimental results indicate that the proposed method of the autoregression technique exhibits excellent results in comparison to the Fast Fourier Transform technique in identifying various bearing faults. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rotating machinery

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A Generalized Review Of Human-Computer Interaction Using Electromyogram Signals

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Recent Patents on engineering 2023年第4期17卷 16-25页

作者： Maity, Sourav Veer, Karan Department of Instrumentation and Control Engineering Dr. BR Ambedkar National Institute of Technology Punjab Jalandhar India

The primary use of human-computer interaction is in the smart home as well as in industry 4.0. Communication between computers and humans can be benefitted from a spontaneous interchange of emotions. The objective of the work is to provide an idea regarding the process of identifying various emotions using facial electromyography signals through the electrode placement method. Here, one contemplated the facial electromyography on masticatory function assessment and emotional articulation monitoring. Furthermore, we have also presented the measurement of facial electromyography including the selection of electrode, location of the electrode, and reduction of noise. Facial emotions have a significant effect on the cognitive process of the human brain such as doubt perception, ability to solve problems, learning capabilities, emotional interactions, and memory which is beneficial while interacting with patients suffering from depression and stress. Through the use of rehabilitation applications, patients are directed through their recovery process while becoming accustomed to their emotional state or wellbeing, which has the dual effect of boosting motivation and accelerating recovery. This review paper will motivate and inspire researchers and engineers for finding more suitable systems for various applications. © 2023 Bentham Science Publishers.

关键词： Electrodes

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Enhanced Shopping Experience: Integrating Load Cell technology with Arduino in Smart Trolley Systems 2

Enhanced Shopping Experience: Integrating Load Cell Technolo...

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2nd International Conference on Emerging Trends in Information technology and engineering, ic-ETITE 2024

作者： Mundada, Kapil Gaikwad, Ankita Deshpande, Dipti Deshpande, Vedant Dhumal, Siddhi BRACT'S Vishwakarma Institute of Technology Department of Instrumentation and Control Engineering Pune India

ISBN: (纸本)9798350328202

Shopping malls and supermarkets are popular choices for purchasing essential items, drawing in a larger customer base compared to retail shops. Traditional billing and shopping systems lack time-saving approaches and fail to provide adequate security measures against theft and duplication. A smart shopping solution integrated with the Internet of Things (IoT) has been developed in response to these issues. This paper introduces a pioneering fusion of load cell technology and Arduino microcontrollers within smart trolley systems, aiming to redefine the shopping experience. Integrating load cells into smart trolleys, combined with Arduino's computational capabilities, presents an advanced solution for precise weight measurement and efficient inventory management. Utilizing load cells to detect weight fluctuations during product addition or removal from the trolley, and harnessing Arduino's processing prowess, this integrated system ensures precise real-time item monitoring. This integration not only facilitates effective inventory oversight but also bolsters security measures by cross-validating item identification with their respective weights. The research delves into the technical intricacies of this amalgamation, emphasizing its potential to optimize shopping encounters, simplify checkout processes, and heighten overall customer satisfaction within retail settings. © 2024 IEEE.

关键词： Customer satisfaction

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Bandwidth assessment of scheduled and unscheduled communication in hybrid networked control system

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Cyber-Physical Systems 2022年第4期8卷 321-346页

作者： Azad, S.M.A.K. Kannan, Srinivasan Department of Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli India

The large integrated industrial applications require unified communication to combine data from multiple domains forming a hybrid network. The scheduling of network access time to multi-domain data in an industrial hybrid network is a challenging task. This paper extends the contribution of the network model mentioned in the literature to assess the bandwidth of both the scheduled and unscheduled communication in hybrid networked control systems. This paper's contribution includes four phases as follows: a) simulation of a hybrid networked control system (h-NCS) consists of four domains with different bandwidth allocations for an application of transmitting a data packet over a network stack from wired node to the wireless node. b) the mathematical demonstration of TCP and IEEE802.11b related to domains incorporated in h-NCS for data transmission. c) the normalisation of the bandwidth of the network access time for both scheduled and unscheduled data packets of h-NCS by implementing Dempster’s rule of combination. d) comparison analysis of proposed h-NCS with the traditional NCS for network access time utilised by both the scheduled and unscheduled data transmission. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Networked control systems

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Improved Grey Wolf Optimization Abetting Fuzzy Logic controllers Used for Load Frequency control in Two-Area Interlinked Reheat Thermal Power Plants applying Governor Dead Band and Generation Rate Constraint Non-Linearity 2

Improved Grey Wolf Optimization Abetting Fuzzy Logic Control...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Shukla, Shasya Jha, Shyam Kant Netaji Subhas University of Technology Instrumentation and Control Engineering Department New Delhi India

ISBN: (纸本)9798350306415

The need of a fast, effective and economical controller for load frequency control has been established in this paper. The primary aim is to conduct an investigation into the effectiveness of P.I.D. and FUZZY LOGIC controller applied to load frequency control (LFC) of interlinked power system with non-linearity by applying optimization. As it is already known when certain input variables and the related output variables do not have a linear or proportional connection, this is referred to as non-linearity in power systems. In other words, changes in input parameters do not always correspond to changes in output parameters in a straight proportion. Instead, the system's behaviour displays nonlinear traits, which can make analysis and control more difficult and complicated. In order to preserve system stability, efficiency, and the capacity to maintain a constant frequency and voltage, dealing with non-linearity in power systems is crucial. Fuzzy logic, optimization, and adaptive control are examples of sophisticated modelling and control approaches that engineers and researchers frequently use to better understand and handle non-linear phenomena and guarantee the stable functioning of power systems. Considering the domain of global optimization and engineering design challenges, the Improved Grey Wolf Optimization (I-GWO) offers a highly effectual and sturdy approach. This improvement seeks to solve some of the drawbacks of the conventional Grey Wolf Optimizer (GWO) method while applying it to a system having GRC and GDB non-linearity. © 2024 IEEE.

关键词： Fuzzy controller I-GWO Load frequency control non-linearity optimization

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Exploring Modern Sensor in Robotics: A review

Exploring Modern Sensor in Robotics: A review

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Acharya, Vikas Raviraj Rao, Vidya S. Manipal Institute of Technology MAHE Department of Instrumentation and Control Engineering Karnataka Manipal India

ISBN: (纸本)9798350361537

This research paper offers a thorough analysis of modern sensors' significant influence on the robotics industry, encompassing a range of breakthroughs from basic discoveries to cutting-edge discoveries. It looks into how different optical, acoustic, and tactile sensors can help with perception, control, and navigation in robotic systems. The study also examines current developments in sensor technologies, emphasizing how robotics has been profoundly impacted by algorithms, computer vision, and artificial intelligence. The study highlights how crucial sensors are to advancing robotic systems development by carefully examining sensor applications in various fields, including space exploration, industrial automation, healthcare, and agriculture. © 2024 IEEE.

关键词： Space research

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Comparison of Soft Computing and Optimization Techniques in Classification of ECG Signal

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Recent Advances in Computer Science and Communications 2023年第2期16卷 37-43页

作者： Mathur, Prerak Sharma, Pooja Veer, Karan Department of Instrumentation and Control Engineering Dr. B.R. Ambedkar National Institute of Technology Jalandhar India

Electrocardiogram (ECG) is a visual representation of the heartbeat that can be used to detect cardiac problems. It helps in detection of a normal or abnormal state of heart diseases. Therefore, it is difficult to detect the cardiological status with naked eyes. So, features extraction from ECG signal is crucial to recognise heart disorders. After selecting significant features, classification can be done by Machine Learning (ML), and Deep Learning (DL). Most of the methods utilised to classify the electrocardiogram are based on 1-D electrocardiogram data. These methods focus on extracting the attributes wavelength and time of each waveform as input but but their behavior remains different during classification. Various ECG construal algorithms based on signal processing approaches have been planned in recent years. Few studies show how optimisation techniques are helpful for feature selection and classification with ML and DL. This work compares the studies based on ML and DL. It also depicts how optimisation methods increase the accuracy, sensitivity, and specificity of data. © 2023 Bentham Science Publishers.

关键词： Electrocardiograms

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