Search results for: vapor sensors
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1645

Search results for: vapor sensors

475 The Effect of Artificial Intelligence on the Production of Agricultural Lands and Labor

Authors: Ibrahim Makram Ibrahim Salib

Abstract:

Agriculture plays an essential role in providing food for the world's population. It also offers numerous benefits to countries, including non-food products, transportation, and environmental balance. Precision agriculture, which employs advanced tools to monitor variability and manage inputs, can help achieve these benefits. The increasing demand for food security puts pressure on decision-makers to ensure sufficient food production worldwide. To support sustainable agriculture, unmanned aerial vehicles (UAVs) can be utilized to manage farms and increase yields. This paper aims to provide an understanding of UAV usage and its applications in agriculture. The objective is to review the various applications of UAVs in agriculture. Based on a comprehensive review of existing research, it was found that different sensors provide varying analyses for agriculture applications. Therefore, the purpose of the project must be determined before using UAV technology for better data quality and analysis. In conclusion, identifying a suitable sensor and UAV is crucial to gather accurate data and precise analysis when using UAVs in agriculture.

Keywords: agriculture land, agriculture land loss, Kabul city, urban land expansion, urbanization agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models drone, precision agriculture, farmer income

Procedia PDF Downloads 45
474 Self-Calibration of Fish-Eye Camera for Advanced Driver Assistance Systems

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

Procedia PDF Downloads 229
473 Biosensor Technologies in Neurotransmitters Detection

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

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Catecholamines are vital neurotransmitters that mediate a variety of central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, optical techniques for the detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid-modified enzymatic sensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence as well as electrochemical sensing strategy for catecholamines detection.

Keywords: biosensors, catecholamines, fluorescence, enzymes

Procedia PDF Downloads 93
472 An Enhanced SAR-Based Tsunami Detection System

Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

Procedia PDF Downloads 362
471 Secured Cancer Care and Cloud Services in Internet of Things /Wireless Sensor Network Based Medical Systems

Authors: Adeniyi Onasanya, Maher Elshakankiri

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In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

Procedia PDF Downloads 155
470 Experimental Study on Heat and Mass Transfer of Humidifier for Fuel Cell

Authors: You-Kai Jhang, Yang-Cheng Lu

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Major contributions of this study are threefold: designing a new model of planar-membrane humidifier for Proton Exchange Membrane Fuel Cell (PEMFC), an index to measure the Effectiveness (εT) of that humidifier, and an air compressor system to replicate related planar-membrane humidifier experiments. PEMFC as a kind of renewable energy has become more and more important in recent years due to its reliability and durability. To maintain the efficiency of the fuel cell, the membrane of PEMFC need to be controlled in a good hydration condition. How to maintain proper membrane humidity is one of the key issues to optimize PEMFC. We developed new humidifier to recycle water vapor from cathode air outlet so as to keep the moisture content of cathode air inlet in a PEMFC. By measuring parameters such as dry side air outlet dew point temperature, dry side air inlet temperature and humidity, wet side air inlet temperature and humidity, and differential pressure between dry side and wet side, we calculated indices obtained by dew point approach temperature (DPAT), water flux (J), water recovery ratio (WRR), effectiveness (εT), and differential pressure (ΔP). We discussed six topics including sealing effect, flow rate effect, flow direction effect, channel effect, temperature effect, and humidity effect by using these indices. Gas cylinders are used as sources of air supply in many studies of humidifiers. Gas cylinder depletes quickly during experiment at 1kW air flow rate, and it causes replication difficult. In order to ensure high stable air quality and better replication of experimental data, this study designs an air supply system to overcome this difficulty. The experimental result shows that the best rate of pressure loss of humidifier is 0.133×10³ Pa(g)/min at the torque of 25 (N.m). The best humidifier performance ranges from 30-40 (LPM) of air flow rates. The counter flow configured humidifies moisturizes the dry side inlet air more effectively than the parallel flow humidifier. From the performance measurements of the channel plates various rib widths studied in this study, it is found that the narrower the rib width is, the more the performance of humidifier improves. Raising channel width in same hydraulic diameter (Dh ) will obtain higher εT and lower ΔP. Moreover, increasing the dry side air inlet temperature or humidity will lead to lower εT. In addition, when the dry side air inlet temperature exceeds 50°C, the effect becomes even more obvious.

Keywords: PEM fuel cell, water management, membrane humidifier, heat and mass transfer, humidifier performance

Procedia PDF Downloads 151
469 Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors

Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest bene t based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

Procedia PDF Downloads 143
468 Investigation of Factors Affecting the Total Ionizing Dose Threshold of Electrically Erasable Read Only Memories for Use in Dose Rate Measurement

Authors: Liqian Li, Yu Liu, Karen Colins

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The dose rate present in a seriously contaminated area can be indirectly determined by monitoring radiation damage to inexpensive commercial electronics, instead of deploying expensive radiation hardened sensors. EEPROMs (Electrically Erasable Read Only Memories) are a good candidate for this purpose because they are inexpensive and are sensitive to radiation exposure. When the total ionizing dose threshold is reached, an EEPROM chip will show signs of damage that can be monitored and transmitted by less susceptible electronics. The dose rate can then be determined from the known threshold dose and the exposure time, assuming the radiation field remains constant with time. Therefore, the threshold dose needs to be well understood before this method can be used. There are many factors affecting the threshold dose, such as the gamma ray energy spectrum, the operating voltage, etc. The purpose of this study was to experimentally determine how the threshold dose depends on dose rate, temperature, voltage, and duty factor. It was found that the duty factor has the strongest effect on the total ionizing dose threshold, while the effect of the other three factors that were investigated is less significant. The effect of temperature was found to be opposite to that expected to result from annealing and is yet to be understood.

Keywords: EEPROM, ionizing radiation, radiation effects on electronics, total ionizing dose, wireless sensor networks

Procedia PDF Downloads 158
467 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 155
466 [Keynote Talk]: Morphological Analysis of Continuous Graphene Oxide Fibers Incorporated with Carbon Nanotube and MnCl₂

Authors: Nuray Ucar, Pelin Altay, Ilkay Ozsev Yuksek

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Graphene oxide fibers have recently received increasing attention due to their excellent properties such as high specific surface area, high mechanical strength, good thermal properties and high electrical conductivity. They have shown notable potential in various applications including batteries, sensors, filtration and separation and wearable electronics. Carbon nanotubes (CNTs) have unique structural, mechanical, and electrical properties and can be used together with graphene oxide fibers for several application areas such as lithium ion batteries, wearable electronics, etc. Metals salts that can be converted into metal ions and metal oxide can be also used for several application areas such as battery, purification natural gas, filtration, absorption. This study investigates the effects of CNT and metal complex compounds (MnCl₂, metal salts) on the morphological structure of graphene oxide fibers. The graphene oxide dispersion was manufactured by modified Hummers method, and continuous graphene oxide fibers were produced with wet spinning. The CNT and MnCl₂ were incorporated into the coagulation baths during wet spinning process. Produced composite continuous fibers were analyzed with SEM, SEM-EDS and AFM microscopies and as spun fiber counts were measured.

Keywords: continuous graphene oxide fiber, Hummers' method, CNT, MnCl₂

Procedia PDF Downloads 154
465 Polyvinyl Alcohol Incorporated with Hibiscus Extract Microcapsules as Combined Active and Intelligent Composite Film for Meat Preservation

Authors: Ahmed F. Ghanem, Marwa I. Wahba, Asmaa N. El-Dein, Mohamed A. EL-Raey, Ghada E.A. Awad

Abstract:

Numerous attempts are being performed in order to formulate suitable packaging materials for meat products. However, to the best of our knowledge, the incorporation of free hibiscus extract or its microcapsules in the pure polyvinyl alcohol (PVA) matrix as packaging materials for meats is seldom reported. Therefore, this study aims at protection of the aqueous crude extract of hibiscus flowers utilizing spry drying encapsulation technique. Fourier transform infrared (FTIR), scanning electron microscope (SEM), and zetasizer results confirmed the successful formation of assembled capsules via strong interactions, spherical rough microparticles, and ~ 235 nm of particle size, respectively. Also, the obtained microcapsules enjoy high thermal stability, unlike the free extract. Then, the obtained spray-dried particles were incorporated into the casting solution of the pure PVA film with a concentration 10 wt. %. The segregated free-standing composite films were investigated, compared to the neat matrix, with several characterization techniques such as FTIR, SEM, thermal gravimetric analysis (TGA), mechanical tester, contact angle, water vapor permeability, and oxygen transmission. The results demonstrated variations in the physicochemical properties of the PVA film after the inclusion of the free and the extract microcapsules. Moreover, biological studies emphasized the biocidal potential of the hybrid films against microorganisms contaminating the meat. Specifically, the microcapsules imparted not only antimicrobial but also antioxidant activities to PVA. Application of the prepared films on the real meat samples displayed low bacterial growth with a slight increase in the pH over the storage time up to 10 days at 4 oC which further proved the meat safety. Moreover, the colors of the films did not significantly changed except after 21 days indicating the spoilage of the meat samples. No doubt, the dual-functional of prepared composite films pave the way towards combined active/smart food packaging applications. This would play a vital role in the food hygiene, including also quality control and assurance.

Keywords: PVA, hibiscus, extraction, encapsulation, active packaging, smart and intelligent packaging, meat spoilage

Procedia PDF Downloads 67
464 Design and Implementation of a 94 GHz CMOS Double-Balanced Up-Conversion Mixer for 94 GHz Imaging Radar Sensors

Authors: Yo-Sheng Lin, Run-Chi Liu, Chien-Chu Ji, Chih-Chung Chen, Chien-Chin Wang

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A W-band double-balanced mixer for direct up-conversion using standard 90 nm CMOS technology is reported. The mixer comprises an enhanced double-balanced Gilbert cell with PMOS negative resistance compensation for conversion gain (CG) enhancement and current injection for power consumption reduction and linearity improvement, a Marchand balun for converting the single LO input signal to differential signal, another Marchand balun for converting the differential RF output signal to single signal, and an output buffer amplifier for loading effect suppression, power consumption reduction and CG enhancement. The mixer consumes low power of 6.9 mW and achieves LO-port input reflection coefficient of -17.8~ -38.7 dB and RF-port input reflection coefficient of -16.8~ -27.9 dB for frequencies of 90~100 GHz. The mixer achieves maximum CG of 3.6 dB at 95 GHz, and CG of 2.1±1.5 dB for frequencies of 91.9~99.4 GHz. That is, the corresponding 3 dB CG bandwidth is 7.5 GHz. In addition, the mixer achieves LO-RF isolation of 36.8 dB at 94 GHz. To the authors’ knowledge, the CG, LO-RF isolation and power dissipation results are the best data ever reported for a 94 GHz CMOS/BiCMOS up-conversion mixer.

Keywords: CMOS, W-band, up-conversion mixer, conversion gain, negative resistance compensation, output buffer amplifier

Procedia PDF Downloads 514
463 A Mechanical Diagnosis Method Based on Vibration Fault Signal down-Sampling and the Improved One-Dimensional Convolutional Neural Network

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

Abstract:

Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 111
462 A Cellular-Based Structural Health Monitoring Device (HMD) Based on Cost-Effective 1-Axis Accelerometers

Authors: Chih-Hsing Lin, Wen-Ching Chen, Chih-Ting Kuo, Gang-Neng Sung, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

Abstract:

This paper proposes a cellular-based structure health monitoring device (HMD) for temporary bridge monitoring without the requirement of power line and internet service. The proposed HMD includes sensor node, power module, cellular gateway, and rechargeable batteries. The purpose of HMD focuses on short-term collection of civil infrastructure information. It achieves the features of low cost by using three 1-axis accelerometers with data synchronization problem being solved. Furthermore, instead of using data acquisition system (DAQ) sensed data is transmitted to Host through cellular gateway. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 50.5% cost saving with high sensitivity 2000mv/g. In addition to fit different monitoring environments, the proposed system can be easily replaced and/or extended with different PCB boards, such as communication interfaces and sensors, to adapt to various applications. Therefore, with using the proposed device, the real-time diagnosis system for civil infrastructure damage monitoring can be conducted effectively.

Keywords: cellular-based structural health monitoring, cost-effective 1-axis accelerometers, short-term monitoring, structural engineering

Procedia PDF Downloads 498
461 Wireless Sensor Network for Forest Fire Detection and Localization

Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

Procedia PDF Downloads 246
460 Identification and Control the Yaw Motion Dynamics of Open Frame Underwater Vehicle

Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

Procedia PDF Downloads 515
459 Airflow Characteristics and Thermal Comfort of Air Diffusers: A Case Study

Authors: Tolga Arda Eraslan

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The quality of the indoor environment is significant to occupants’ health, comfort, and productivity, as Covid-19 spread throughout the world, people started spending most of their time indoors. Since buildings are getting bigger, mechanical ventilation systems are widely used where natural ventilation is insufficient. Four primary tasks of a ventilation system have been identified indoor air quality, comfort, contamination control, and energy performance. To fulfill such requirements, air diffusers, which are a part of the ventilation system, have begun to enter our lives in different airflow distribution systems. Detailed observations are needed to assure that such devices provide high levels of comfort effectiveness and energy efficiency. This study addresses these needs. The objective of this article is to observe air characterizations of different air diffusers at different angles and their effect on people by the thermal comfort model in CFD simulation and to validate the outputs with the help of data results based on a simulated office room. Office room created to provide validation; Equipped with many thermal sensors, including head height, tabletop, and foot level. In addition, CFD simulations were carried out by measuring the temperature and velocity of the air coming out of the supply diffuser. The results considering the flow interaction between diffusers and surroundings showed good visual illustration.

Keywords: computational fluid dynamics, fanger’s model, predicted mean vote, thermal comfort

Procedia PDF Downloads 94
458 Root Mean Square-Based Method for Fault Diagnosis and Fault Detection and Isolation of Current Fault Sensor in an Induction Machine

Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef

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Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.

Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation

Procedia PDF Downloads 172
457 Automated End-to-End Pipeline Processing Solution for Autonomous Driving

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

Procedia PDF Downloads 85
456 Study of Human Upper Arm Girth during Elbow Isokinetic Contractions Based on a Smart Circumferential Measuring System

Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

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As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental study, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain

Procedia PDF Downloads 323
455 Analysis of Radial Pulse Using Nadi-Parikshan Yantra

Authors: Ashok E. Kalange

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Diagnosis according to Ayurveda is to find the root cause of a disease. Out of the eight different kinds of examinations, Nadi-Pariksha (pulse examination) is important. Nadi-Pariksha is done at the root of the thumb by examining the radial artery using three fingers. Ancient Ayurveda identifies the health status by observing the wrist pulses in terms of 'Vata', 'Pitta' and 'Kapha', collectively called as tridosha, as the basic elements of human body and in their combinations. Diagnosis by traditional pulse analysis – NadiPariksha - requires a long experience in pulse examination and a high level of skill. The interpretation tends to be subjective, depending on the expertise of the practitioner. Present work is part of the efforts carried out in making Nadi-Parikshan objective. Nadi Parikshan Yantra (three point pulse examination system) is developed in our laboratory by using three pressure sensors (one each for the Vata, Pitta and Kapha points on radial artery). The radial pulse data was collected of a large number of subjects. The radial pulse data collected is analyzed on the basis of relative amplitudes of the three point pulses as well as in frequency and time domains. The same subjects were examined by Ayurvedic physician (Nadi Vaidya) and the dominant Dosha - Vata, Pitta or Kapha - was identified. The results are discussed in details in the paper.

Keywords: Nadi Parikshan Yantra, Tridosha, Nadi Pariksha, human pulse data analysis

Procedia PDF Downloads 177
454 Impact of Alternative Fuel Feeding on Fuel Cell Performance and Durability

Authors: S. Rodosik, J. P. Poirot-Crouvezier, Y. Bultel

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With the expansion of the hydrogen economy, Proton Exchange Membrane Fuel Cell (PEMFC) systems are often presented as promising energy converters suitable for transport applications. However, reaching a durability of 5000 h recommended by the U.S. Department of Energy and decreasing system cost are still major hurdles to their development. In order to increase the system efficiency and simplify the system without affecting the fuel cell lifetime, an architecture called alternative fuel feeding has been developed. It consists in a fuel cell stack divided into two parts, alternatively fed, implemented on a 5-kW system for real scale testing. The operation strategy can be considered close to Dead End Anode (DEA) with specific modifications to avoid water and nitrogen accumulation in the cells. The two half-stacks are connected in series to enable each stack to be alternatively fed. Water and nitrogen accumulated can be shifted from one half-stack to the other one according to the alternative feeding frequency. Thanks to the homogenization of water vapor along the stack, water management was improved. The operating conditions obtained at system scale are close to recirculation without the need of a pump or an ejector. In a first part, a performance comparison with the DEA strategy has been performed. At high temperature and low pressure (80°C, 1.2 bar), performance of alternative fuel feeding was higher, and the system efficiency increased. In a second part, in order to highlight the benefits of the architecture on the fuel cell lifetime, two durability tests, lasting up to 1000h, have been conducted. A test on the 5-kW system has been compared to a reference test performed on a test bench with a shorter stack, conducted with well-controlled operating parameters and flow-through hydrogen strategy. The durability test is based upon the Fuel Cell Dynamic Load Cycle (FC-DLC) protocol but adapted to the system limitations: without OCV steps and a maximum current density of 0.4 A/cm². In situ local measurements with a segmented S++® plate performed all along the tests, showed a more homogeneous distribution of the current density with alternative fuel feeding than in flow-through strategy. Tests performed in this work enabled the understanding of this architecture advantages and drawbacks. Alternative fuel feeding architecture appeared to be a promising solution to ensure the humidification function at the anode side with a simplified fuel cell system.

Keywords: automotive conditions, durability, fuel cell system, proton exchange membrane fuel cell, stack architecture

Procedia PDF Downloads 127
453 Automatic Identification and Monitoring of Wildlife via Computer Vision and IoT

Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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452 Studying the Dynamical Response of Nano-Microelectromechanical Devices for Nanomechanical Testing of Nanostructures

Authors: Mohammad Reza Zamani Kouhpanji

Abstract:

Characterizing the fatigue and fracture properties of nanostructures is one of the most challenging tasks in nanoscience and nanotechnology due to lack of a MEMS/NEMS device for generating uniform cyclic loadings at high frequencies. Here, the dynamic response of a recently proposed MEMS/NEMS device under different inputs signals is completely investigated. This MEMS/NEMS device is designed and modeled based on the electromagnetic force induced between paired parallel wires carrying electrical currents, known as Ampere’s Force Law (AFL). Since this MEMS/NEMS device only uses two paired wires for actuation part and sensing part, it represents highly sensitive and linear response for nanostructures with any stiffness and shapes (single or arrays of nanowires, nanotubes, nanosheets or nanowalls). In addition to studying the maximum gains at different resonance frequencies of the MEMS/NEMS device, its dynamical responses are investigated for different inputs and nanostructure properties to demonstrate the capability, usability, and reliability of the device for wide range of nanostructures. This MEMS/NEMS device can be readily integrated into SEM/TEM instruments to provide real time study of the fatigue and fracture properties of nanostructures as well as their softening or hardening behaviors, and initiation and/or propagation of nanocracks in them.

Keywords: MEMS/NEMS devices, paired wire actuators and sensors, dynamical response, fatigue and fracture characterization, Ampere’s force law

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451 Effect of Annealing on Electrodeposited ZnTe Thin Films in Non-Aqueous Medium

Authors: Shyam Ranjan Kumar, Shashikant Rajpal

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Zinc Telluride (ZnTe) is a binary II-VI direct band gap semiconducting material. This semiconducting material has several applications in sensors, photo-electrochemical devices and photovoltaic solar cell. In this study, Zinc telluride (ZnTe) thin films were deposited on nickel substrate by electrodeposition technique using potentiostat/galvanostat at -0.85 V using AR grade of Zinc Chloride (ZnCl2), Tellurium Tetrachloride (TeCl4) in non-aqueous bath. The developed films were physically stable and showed good adhesion. The as deposited ZnTe films were annealed at 400ºC in air. The solid state properties and optical properties of the as deposited and annealed films were carried out by XRD, EDS, SEM, AFM, UV–Visible spectrophotometer, and photoluminescence spectrophotometer. The diffraction peak observed at 2θ = 49.58° with (111) plane indicate the crystalline nature of ZnTe film. Annealing improves the crystalline nature of the film. Compositional analysis reveals the presence of Zn and Te with tellurium rich ZnTe film. SEM photograph at 10000X shows that grains of film are spherical in nature and densely distributed over the surface. The average roughness of the film is measured by atomic force microscopy and it is nearly equal to 60 nm. The direct wide band gap of 2.12 eV is observed by UV-Vis spectroscopy. Luminescence peak of the ZnTe films are also observed in as deposited and annealed case.

Keywords: annealing, electrodeposition, optical properties, thin film, XRD, ZnTe

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450 Mapping of Alteration Zones in Mineral Rich Belt of South-East Rajasthan Using Remote Sensing Techniques

Authors: Mrinmoy Dhara, Vivek K. Sengar, Shovan L. Chattoraj, Soumiya Bhattacharjee

Abstract:

Remote sensing techniques have emerged as an asset for various geological studies. Satellite images obtained by different sensors contain plenty of information related to the terrain. Digital image processing further helps in customized ways for the prospecting of minerals. In this study, an attempt has been made to map the hydrothermally altered zones using multispectral and hyperspectral datasets of South East Rajasthan. Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion (Level1R) dataset have been processed to generate different Band Ratio Composites (BRCs). For this study, ASTER derived BRCs were generated to delineate the alteration zones, gossans, abundant clays and host rocks. ASTER and Hyperion images were further processed to extract mineral end members and classified mineral maps have been produced using Spectral Angle Mapper (SAM) method. Results were validated with the geological map of the area which shows positive agreement with the image processing outputs. Thus, this study concludes that the band ratios and image processing in combination play significant role in demarcation of alteration zones which may provide pathfinders for mineral prospecting studies.

Keywords: ASTER, hyperion, band ratios, alteration zones, SAM

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449 Mathematical Modelling of Biogas Dehumidification by Using of Counterflow Heat Exchanger

Authors: Staņislavs Gendelis, Andris Jakovičs, Jānis Ratnieks, Aigars Laizāns, Dāvids Vardanjans

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Dehumidification of biogas at the biomass plants is very important to provide the energy efficient burning of biomethane at the outlet. A few methods are widely used to reduce the water content in biogas, e.g. chiller/heat exchanger based cooling, usage of different adsorbents like PSA, or the combination of such approaches. A quite different method of biogas dehumidification is offered and analyzed in this paper. The main idea is to direct the flow of biogas from the plant around it downwards; thus, creating additional insulation layer. As the temperature in gas shell layer around the plant will decrease from ~ 38°C to 20°C in the summer or even to 0°C in the winter, condensation of water vapor occurs. The water from the bottom of the gas shell can be collected and drain away. In addition, another upward shell layer is created after the condensate drainage place on the outer side to further reducing heat losses. Thus, counterflow biogas heat exchanger is created around the biogas plant. This research work deals with the numerical modelling of biogas flow, taking into account heat exchange and condensation on cold surfaces. Different kinds of boundary conditions (air and ground temperatures in summer/winter) and various physical properties of constructions (insulation between layers, wall thickness) are included in the model to make it more general and useful for different biogas flow conditions. The complexity of this problem is fact, that the temperatures in both channels are conjugated in case of low thermal resistance between layers. MATLAB programming language is used for multiphysical model development, numerical calculations and result visualization. Experimental installation of a biogas plant’s vertical wall with an additional 2 layers of polycarbonate sheets with the controlled gas flow was set up to verify the modelling results. Gas flow at inlet/outlet, temperatures between the layers and humidity were controlled and measured during a number of experiments. Good correlation with modelling results for vertical wall section allows using of developed numerical model for an estimation of parameters for the whole biogas dehumidification system. Numerical modelling of biogas counterflow heat exchanger system placed on the plant’s wall for various cases allows optimizing of thickness for gas layers and insulation layer to ensure necessary dehumidification of the gas under different climatic conditions. Modelling of system’s defined configuration with known conditions helps to predict the temperature and humidity content of the biogas at the outlet.

Keywords: biogas dehumidification, numerical modelling, condensation, biogas plant experimental model

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448 Fuzzy Inference-Assisted Saliency-Aware Convolution Neural Networks for Multi-View Summarization

Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

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447 Fabrication and Characterization of Al2O3 Based Electrical Insulation Coatings Around SiC Fibers

Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner

Abstract:

In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al2O3)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al2O3 respectively. Raman spectroscopic analyses produced no characteristic bands of Al2O3, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.

Keywords: Al₂O₃ thin film, electrical insulation coating, PVD process, SiC fibre, single fibre tensile test

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446 A Review of Atomization Mechanisms Used for Spray Flash Evaporation: Their Effectiveness and Proposal of Rotary Bell Atomizer for Flashing Application

Authors: Murad A. Channa, Mehdi Khiadani. Yasir Al-Abdeli

Abstract:

Considering the severity of water scarcity around the world and its widening at an alarming rate, practical improvements in desalination techniques need to be engineered at the earliest. Atomization is the major aspect of flashing phenomena, yet it has been paid less attention to until now. There is a need to test efficient ways of atomization for the flashing process. Flash evaporation together with reverse osmosis is also a commercially matured desalination technique commonly famous as Multi-stage Flash (MSF). Even though reverse osmosis is massively practical, it is not economical or sustainable compared to flash evaporation. However, flashing evaporation has its drawbacks as well such as lower efficiency of water production per higher consumption of power and time. Flash evaporation is simply the instant boiling of a subcooled liquid which is introduced as droplets in a well-maintained negative environment. This negative pressure inside the vacuum increases the temperature of the liquid droplets far above their boiling point, which results in the release of latent heat, and the liquid droplets turn into vapor which is collected to be condensed back into an impurity-free liquid in a condenser. Atomization is the main difference between pool and spray flash evaporation. Atomization is the heart of the flash evaporation process as it increases the evaporating surface area per drop atomized. Atomization can be categorized into many levels depending on its drop size, which again becomes crucial for increasing the droplet density (drop count) per given flow rate. This review comprehensively summarizes the selective results relating to the methods of atomization and their effectiveness on the evaporation rate from earlier works to date. In addition, the reviewers propose using centrifugal atomization for the flashing application, which brings several advantages viz ultra-fine droplets, uniform droplet density, and the swirling geometry of the spray with kinetically more energetic sprays during their flight. Finally, several challenges of using rotary bell atomizer (RBA) and RBA Sprays inside the chamber have been identified which will be explored in detail. A schematic of rotary bell atomizer (RBA) integration with the chamber has been designed. This powerful centrifugal atomization has the potential to increase potable water production in commercial multi-stage flash evaporators, where it would be preferably advantageous.

Keywords: atomization, desalination, flash evaporation, rotary bell atomizer

Procedia PDF Downloads 60