Search results for: vibration sensor

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: S. Vignesh, K. S. Rangasamy

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The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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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

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Authors: J.Das, Gyan Wrat

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Leakage is the main gradual failure in the fluid power system, which is usually caused by the impurity in the oil and wear of matching surfaces between parts and lead to the change of the gap value. When leakage occurs in the system, the oil will flow from the high pressure chamber into the low pressure chamber through the gap, causing the reduction of system flow as well as the loss of system pressure, resulting in the decreasing of system efficiency. In the fluid power system, internal leakage may occur in various components such as gear pump, reversing valve and hydraulic cylinder, and affect the system work performance. Therefore, component leakage in the fluid power system is selected as the study to characterize the leakage and the effect of leakage on the system. Effect of leakage on system pressure and cylinder displacement can be obtained using pressure sensors and the displacement sensor. The leakage can be varied by changing the orifice using a flow control valve. Hydraulic circuit for leakage will be developed in Matlab/Simulink environment and simulations will be done by changing different parameters.

Keywords: leakage causes, effect, analysis, MATLAB simulation, hydraulic circuit

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Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

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Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

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This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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Authors: Reza Taherlouei Safa, Mohammad Aboonajmi

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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: drone, precision agriculture, farmer income, UAV

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Authors: Z. Ž. Lazarević, D. L. Sekulić, V. N. Ivanovski, N. Ž. Romčević

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NiFe2O4 (nickel ferrite), ZnFe2O4 (zinc ferrite) and Ni0.5Zn0.5Fe2O4 (nickel-zinc ferrite) were prepared by mechanochemical route in a planetary ball mill starting from mixture of the appropriate quantities of the Ni(OH)2/Fe(OH)3, Zn(OH)2/Fe(OH)3 and Ni(OH)2/Zn(OH)2/Fe(OH)3 hydroxide powders. In order to monitor the progress of chemical reaction and confirm phase formation, powder samples obtained after 25 h, 18 h and 10 h of milling were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), IR, Raman and Mössbauer spectroscopy. It is shown that the soft mechanochemical method, i.e. mechanochemical activation of hydroxides, produces high quality single phase ferrite samples in much more efficient way. From the IR spectroscopy of single phase samples it is obvious that energy of modes depends on the ratio of cations. It is obvious that all samples have more than 5 Raman active modes predicted by group theory in the normal spinel structure. Deconvolution of measured spectra allows one to conclude that all complex bands in the spectra are made of individual peaks with the intensities that vary from spectrum to spectrum. The deconvolution of Raman spectra allows to separate contributions of different cations to a particular type of vibration and to estimate the degree of inversion.

Keywords: ferrites, Raman spectroscopy, IR spectroscopy, Mössbauer measurements

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Authors: V. Giacometti, R. Mirabelli, V. Patera, D. Pinci, A. Sarti, A. Sciubba, G. Traini, M. Marafini

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The particle therapy (PT) is a very modern technique of non invasive radiotherapy mainly devoted to the treatment of tumours untreatable with surgery or conventional radiotherapy, because localised closely to organ at risk (OaR). Nowadays, PT is available in about 55 centres in the word and only the 20\% of them are able to treat with carbon ion beam. However, the efficiency of the ion-beam treatments is so impressive that many new centres are in construction. The interest in this powerful technology lies to the main characteristic of PT: the high irradiation precision and conformity of the dose released to the tumour with the simultaneous preservation of the adjacent healthy tissue. However, the beam interactions with the patient produce a large component of secondary particles whose additional dose has to be taken into account during the definition of the treatment planning. Despite, the largest fraction of the dose is released to the tumour volume, a non-negligible amount is deposed in other body regions, mainly due to the scattering and nuclear interactions of the neutrons within the patient body. One of the main concerns in PT treatments is the possible occurrence of secondary malignant neoplasm (SMN). While SMNs can be developed up to decades after the treatments, their incidence impacts directly life quality of the cancer survivors, in particular in pediatric patients. Dedicated Treatment Planning Systems (TPS) are used to predict the normal tissue toxicity including the risk of late complications induced by the additional dose released by secondary neutrons. However, no precise measurement of secondary neutrons flux is available, as well as their energy and angular distributions: an accurate characterization is needed in order to improve TPS and reduce safety margins. The project MONDO (MOnitor for Neutron Dose in hadrOntherapy) is devoted to the construction of a secondary neutron tracker tailored to the characterization of that secondary neutron component. The detector, based on the tracking of the recoil protons produced in double-elastic scattering interactions, is a matrix of thin scintillating fibres, arranged in layer x-y oriented. The final size of the object is 10 x 10 x 20 cm3 (squared 250µm scint. fibres, double cladding). The readout of the fibres is carried out with a dedicated SPAD Array Sensor (SBAM) realised in CMOS technology by FBK (Fondazione Bruno Kessler). The detector is under development as well as the SBAM sensor and it is expected to be fully constructed for the end of the year. MONDO will make data tacking campaigns at the TIFPA Proton Therapy Center of Trento, at the CNAO (Pavia) and at HIT (Heidelberg) with carbon ion in order to characterize the neutron component and predict the additional dose delivered on the patients with much more precision and to drastically reduce the actual safety margins. Preliminary measurements with charged particles beams and MonteCarlo FLUKA simulation will be presented.

Keywords: secondary neutrons, particle therapy, tracking detector, elastic scattering

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Authors: M. K. Deore

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The thick films of undoped and Al2O3 doped- ZnO were prepared by screen printing technique. AR grade (99.9 % pure) Zinc Oxide powder were mixed mechanochemically in acetone medium with Aluminium Chloride (AlCl2) material in various weight percentages such as 0.5, 1, 3 and 5 wt % to obtain Al2O3 - ZnO composite. The prepared materials were sintered at 1000oC for 12h in air ambience and ball milled to ensure sufficiently fine particle size. The electrical, structural and morphological properties of the films were investigated. The X-ray diffraction analysis of pure and doped ZnO shows the polycrystalline nature. The surface morphology of the films was studied by SEM. The final composition of each film was determined by EDAX analysis. The gas response of undoped and Al2O3- doped ZnO films were studied for different gases such as CO, H2, NH3, and H2S at operating temperature ranging from 50 oC to 450 o C. The pure film shows the response to H2S gas (500ppm) at 300oC while the film doped with 3 wt.% Al2O3 gives the good response to H2S gas(ppb) at 350oC. The selectivity, response and recovery time of the sensor were measured and presented.

Keywords: thick films, ZnO-Al2O3, H2S gas, sensitivity, selectivity, response and recovery time

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Authors: F. Messaoudi, O. Haddad, R. Bouras, S. Kaci

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The development of self-compacting concrete (SCC) marks a huge step towards improved efficiency and working conditions on construction sites and in the precast industry. SCC flows easily into more complex shapes and through reinforcement bars, reduces the manpower required for the placement; no vibration is required to ensure correct compaction of concrete. This concrete contains a high volume of binder which is controlled by their rheological behavior. The paste consists of binders (Portland cement with or without supplementary cementitious materials), water, chemical admixtures and fillers. In this study, two series of tests were performed on self-compacting cement pastes made with marble waste additions as the mineral addition. The first series of this investigation was to determine the flow time of paste using Marsh cone, the second series was to determine the rheological parameters of the same paste namely yield stress and plastic viscosity using the rheometer Haake RheoStress 1. The results of this investigation allowed us to study the evolution of the yield stress, viscosity and the flow time Marsh cone paste as a function of the composition of the paste. A correlation between the results obtained on the flow test Marsh cone and those of the plastic viscosity on the mottled different cement pastes is proposed.

Keywords: adjuvant, rheological parameter, self-compacting cement pastes, waste marble

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Authors: M. Masłowski, M. Zaborski

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Magnetorheological elastomer composites based on micro- and nano-sized Fe3O4 magnetoactive fillers in silicone rubber are reported and studied. To improve the dispersion of applied fillers in polymer matrix, ionic liquids such as 1-ethyl-3-methylimidazolium diethylphosphate, 1-butyl-3-methylimidazolium hexafluorophosphate, 1-hexyl-3-methylimidazolium chloride, 1-butyl-3-methylimidazolium trifluoromethanesulfonate,1-butyl-3-methylimidazolium tetrafluoroborate, trihexyltetradecylphosphonium chloride were added during the process of composites preparation. The method of preparation process influenced the specific properties of MREs (isotropy/anisotropy), similarly to ferromagnetic particles content and theirs quantity. Micro and non-sized magnetites were active fillers improving the mechanical properties of elastomers. They also changed magnetic properties and reinforced the magnetorheological effect of composites. Application of ionic liquids as dispersing agents influenced the dispersion of magnetic fillers in the elastomer matrix. Scanning electron microscopy images used to observe magnetorheological elastomer microstructures proved that the dispersion improvement had a significant effect on the composites properties. Moreover, the particles orientation and their arrangement in the elastomer investigated by vibration sample magnetometer showed the correlation between MRE microstructure and their magnetic properties.

Keywords: magnetorheological elastomers, iron oxides, ionic liquids, dispersion

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Authors: Eva Savy, Anthony Ruiz

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In extrusion blow molding, there is great variability in product quality due to the sensitivity of the machine settings. These variations lead to unnecessary rejects and loss of time. Yet production control is a major challenge for companies in this sector to remain competitive within their market. Current quality control methods only apply to finished products (vision control, leak test...). It has been shown that material melt temperature, blowing pressure, and ambient temperature have a significant impact on the variability of product quality. Since blowing is a key step in the process, we have studied this parameter in this paper. The objective is to determine if airflow analysis allows the identification of quality problems before the full completion of the manufacturing process. We conducted tests to determine if it was possible to identify a leakage defect and an obstructed defect, two common defects on products. The results showed that it was possible to identify a leakage defect by airflow analysis.

Keywords: extrusion blow molding, signal, sensor, defects, detection

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Authors: Anisha Mandal, Swambabu Varanasi

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Lead is one of the most prevalent toxic heavy metal ions, and its pollution poses a significant threat to the environment and human health. On the other hand, Ethylenediaminetetraacetic acid is a widely used metal chelating agent that, due to its poor biodegradability, is an incessant pollutant to the environment. For the first time, a green, simple, and cost-effective approach is used to hydrothermally synthesise photoluminescent carbon dots using Moringa Oleifera Gum in a single step. Then, using Moringa Oleifera Gum-derived carbon dots, a photoluminescent "ON-OFF-ON" mechanism for dual mode detection of trace Pb2+ and EDTA was proposed. MOG-CDs detect Pb2+ selectively and sensitively using a photoluminescence quenching mechanism, with a detection limit (LOD) of 0.000472 ppm. (1.24 nM). The quenched photoluminescence can be restored by adding EDTA to the MOG-CD+Pb2+ system; this strategy is used to quantify EDTA at a level of detection of 0.0026 ppm. (8.9 nM). The quantification of Pb2+ and EDTA in actual samples encapsulated the applicability and dependability of the proposed photoluminescent probe.

Keywords: carbon dots, photoluminescence, sensor, moringa oleifera gum

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Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

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Zirconium alloys are used as core components of nuclear reactors due to their high wear resistance, good corrosion properties, and good mechanical stability at high temperatures. Water flows inside the pressure tube through fuel claddings, which produces vibration of these core components and results in the wear of some components. Some components are subjected to the environment of coolant water containing LiOH which results in the corrosion of these components. The present work simulates some of these conditions to determine the failure mechanisms under these conditions and the effect of various parameters on them. Friction and wear experiments were performed varying the surrounding environment (room temperature, high temperature, and water submerged), duration, frequency, and displacement amplitude. Electrochemical corrosion experiments were performed by varying the concentration of LiOH in water. The worn and corroded surfaces were analyzed using scanning electron microscopy (SEM) to analyze the wear and corrosion mechanism and energy dispersive x-ray spectroscopy (EDS) and Raman spectroscopy to analyze the tribo-oxide layer formed during the wear and oxide layer formed during the corrosion. Wear increases with frequency and amplitude, and corrosion increases with LiOH concentration in water.

Keywords: zirconium alloys, wear, oxide layer, corrosion, EIS, linear polarization

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Authors: Muhammad Fezan Afzal, Imran Khan, Salma Imtiaz

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The need for human verification and identification requires from centuries for authentication. Since it is being used in big institutes like financial, government and crime departments, a continued struggle is important to make this system more efficient to prevent security breaches. Therefore, multiple devices are used to authenticate the biometric for each individual. A large number of devices are required to cover a large number of users. As the number of devices increases, cost will automatically increase. Furthermore, it is time-consuming for biometrics due to the devices being insufficient and are not available at every door. In this paper, we propose the framework and algorithm where the mobile of each individual can also perform the biometric authentication of attendance and security. Every mobile has a biometric authentication system that is used in different mobile applications for security purposes. Therefore, each individual can use the biometric system mobile without moving from one place to another. Moreover, by using the biometrics mobile, the cost of biometric systems can be removed that are mostly deployed in different organizations for the attendance of students, employees and for other security purposes.

Keywords: fingerprint, fingerprint authentication, mobile verification, mobile biometric verification, mobile fingerprint sensor

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Authors: Emie A. Salamangkit-Mirasol, Rinlee Butch M. Cervera

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Rice hull or rice husk (RH) is an agricultural waste obtained from milling rice grains. Since RH has no commercial value and is difficult to use in agriculture, its volume is often reduced through open field burning which is an environmental hazard. In this study, amorphous nanosilica from Philippine waste RH was prepared via acid precipitation method. The synthesized samples were fully characterized for its microstructural properties. X-ray diffraction pattern reveals that the structure of the prepared sample is amorphous in nature while Fourier transform infrared spectrum showed the different vibration bands of the synthesized sample. Scanning electron microscopy (SEM) and particle size analysis (PSA) confirmed the presence of agglomerated silica particles. On the other hand, transmission electron microscopy (TEM) revealed an amorphous sample with grain sizes of about 5 to 20 nanometer range and has about 95 % purity according to EDS analyses. The elemental mapping also suggests that leaching of rice hull ash effectively removed the metallic impurity such as potassium element in the material. Hence, amorphous nanosilica was successfully prepared via a low-cost acid precipitation method from Philippine waste rice hull. In addition, initial electrode performance of the synthesized samples as an anode material in Lithium Battery have been investigated.

Keywords: agricultural waste, anode material, nanosilica, rice hull

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Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

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Authors: Sudip Kumar Sinha, Saptarshi Ghosh

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While there’s a perpetual buzz around zinc oxide (ZnO) superstructures for their unique optical features, the versatile material has been constantly utilized to manifest tailored electronic properties through rendition of distinct morphologies. And yet, the unorthodox approach of implementing the novel 1D nanostructures of ZnO (pristine or doped) for volatile sensing applications has ample scope to accommodate new unconventional morphologies. In the last two decades, solid-state sensors have attracted much curiosity for their relevance in identifying pollutant, toxic and other industrial gases. In particular gas sensors based on metal oxide semiconducting (wide Eg) nanomaterials have recently attracted intensive attention owing to their high sensitivity and fast response and recovery time. These materials when exposed to air, the atmospheric O2 dissociates and get absorb on the surface of the sensors by trapping the outermost shell electrons. Finally a depleted zone on the surface of the sensors is formed, that enhances the potential barrier height at grain boundary . Once a target gas is exposed to the sensor, the chemical interaction between the chemisorbed oxygen and the specific gas liberates the trapped electrons. Therefore altering the amount of adsorbate is a considerable approach to improve the sensitivity of any target gas/vapour molecule. Likewise, this study presents a spontaneous but self catalytic creation of Sn-doped ZnO hexagonal nanoprisms on Si (100) substrates through thermal evaporation-condensation method, and their subsequent deployment for volatile sensing. In particular, the sensors were utilized to detect molecules of ethanol, acetone and ammonia below their permissible exposure limits which returned sensitivities of around 85%, 80% and 50% respectively. The influence of Sn concentration on the growth, microstructural and optical properties of the nanoprisms along with its role in augmenting the sensing parameters has been detailed. The single-crystalline nanostructures have a typical diameter ranging from 300 to 500 nm and a length that extends up to few micrometers. HRTEM images confirmed the hexagonal crystallography for the nanoprisms, while SAED pattern asserted the single crystalline nature. The growth habit is along the low index <0001>directions. It has been seen that the growth mechanism of the as-deposited nanostructures are directly influenced by varying supersaturation ratio, fairly high substrate temperatures, and specified surface defects in certain crystallographic planes, all acting cooperatively decide the final product morphology. Room temperature photoluminescence (PL) spectra of this rod like structures exhibits a weak ultraviolet (UV) emission peak at around 380 nm and a broad green emission peak in the 505 nm regime. An estimate of the sensing parameters against dispensed target molecules highlighted the potential for the nanoprisms as an effective volatile sensing material. The Sn-doped ZnO nanostructures with unique prismatic morphology may find important applications in various chemical sensors as well as other potential nanodevices.

Keywords: gas sensor, HRTEM, photoluminescence, ultraviolet, zinc oxide

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Authors: Joseph C. Chen, Venkata Karthik Jakka

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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: injection molding processes, taguchi parameter design, tensile strength, high-density polyethylene(HDPE)

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Authors: McClain Thiel

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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

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Authors: B. Lee, B. H. Choi

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The loss of safety for reservoirs brought about by climate change and facility aging leads to reservoir failures, which results in the loss of lives and property damage in downstream areas. Therefore, it is necessary to provide a reservoir failure alert system for downstream residents to detect the early signs of failure (with sensors) in real-time and perform safety management to prevent and minimize possible damage. 10 case studies were carried out to verify the water level management criteria of four levels (attention, caution, alert, serious). Peak changes in water level data were analysed. The results showed that ‘Caution’ and ‘Alert’ were closed to 33% and 66% of difference in level between flood water level and full water level. Therefore, it is adequate to use initial water level management criteria of reservoir failure alert system for the first year. Acknowledgment: This research was supported by a grant (2017-MPSS31-002) from 'Supporting Technology Development Program for Disaster Management' funded by the Ministry of the Interior and Safety(MOIS)

Keywords: alert system, management criteria, reservoir failure, sensor

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

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The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: bonded rubber, quasi-static test, shape factor, apparent Young’s modulus

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

Abstract:

Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: Kwame Sarkodie, William Cheung, Andrew R. Fergursson

Abstract:

The characterization of multiphase flow has gained enormous attention for most petroleum and chemical industrial processes. In order to fully characterize fluid phases in a stream or containment, there needs to be a profound knowledge of the existing composition of fluids present. This introduces a problem for real-time monitoring of fluid dynamics such as fluid distributions, and phase fractions. This work presents a simple technique of correlating absorbance spectrums of water, oil and air bubble present in containment. These spectra absorption outputs are derived by using an Fourier Infrared spectrometer. During the testing, air bubbles were introduced into static water column and oil containment and with light absorbed in the infrared regions of specific wavelength ranges. Attenuation coefficients are derived for various combinations of water, gas and oil which reveal the presence of each phase in the samples. The results from this work are preliminary and viewed as a build up to the design of a multiphase flow rig which has an infrared sensor pair to be used for multiphase flow characterization.

Keywords: attenuation, infrared, multiphase, spectroscopy

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

Abstract:

Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 133

Authors: Behnam Madadnia

Abstract:

For several years, 3D-shaped electronics have been rising, with many uses in home appliances, automotive, and manufacturing. One of the biggest challenges in the fabrication of 3D shape electronics, which are made by thermoforming, is repeatable and accurate component positioning, and typically there is no control over the final position of the component. This paper aims to address this issue and present a reliable approach for guiding the electronic components in the desired place during thermoforming. We have proposed a heat-control mask in the thermoforming machine to control the heating of the polymer, not allowing specific parts to be formable, which can assure the conductive traces' mechanical stability during thermoforming of the substrate. We have verified our approach's accuracy by applying our method on a real industrial semi-sphere mold for positioning 7 LEDs and one touch sensor. We measured the LEDs' position after thermoforming to prove the process's repeatability. The experiment results demonstrate that the proposed method is capable of positioning electronic components in thermoformed 3D electronics with high precision.

Keywords: 3D-shaped electronics, electronic components, thermoforming, component positioning

Procedia PDF Downloads 90

Authors: Santos Cabrera, Halbert Yesid, Moncada Nino, Alvaro Fernando, Rincon Cuta, Yeisson Alexis

Abstract:

The present work evaluates the feasibility of implementing a health and use monitoring system (HUMS), based on vibration analysis as a condition-based maintenance program for the UH60L 'Blackhawk' helicopters. The mixed approach used consists of contributions from national and international experts, the analysis of data extracted from the software (Meridium), the correlation of variables derived from the diagnosis of availability, the development, and application of the HUMS system, the evaluation of the latter through of the use of instruments designed for the collection of information using the DELPHI method and data capture with the device installed in the helicopter studied. The results obtained in the investigation reflect the context of maintenance in aerial operations, a reduction of operation and maintenance costs of over 2%, better use of human resources, improvement in availability (5%), and fulfillment of the aircraft’s security standards, enabling the implementation of the monitoring system (HUMS) in the condition-based maintenance program. New elements are added to the study of maintenance based on condition -specifically, in the determination of viability based on qualitative and quantitative data according to the methodology. The use of condition-based maintenance will allow organizations to adjust and reconfigure their strategic, logistical, and maintenance capabilities, aligning them with their strategic objectives of responding quickly and adequately to changes in the environment and operational requirements.

Keywords: air transportation sustainability, HUMS, maintenance based condition, maintenance blackhawk capability

Procedia PDF Downloads 149

Authors: I. Sani, A. Abdulhamid, F. Bello, Isah M. Fakai

Abstract:

This research has focused on the application of green fluorescent protein (GFP) as a new technique for direct monitoring of fermentation processes involving cultured bacteria. To use GFP as a sensor for pH and oxygen, percentage ratio of red fluorescence to green (% R/G) was evaluated. Assessing the magnitude of the % R/G ratio in relation to low or high pH and oxygen concentration, the bacterial strains were cultivated under aerobic and anaerobic conditions. SCC1 strains of E. coli were grown in a 5 L laboratory fermenter, and during the fermentation, the pH and temperature were controlled at 7.0 and 370C respectively. Dissolved oxygen tension (DOT) was controlled between 15-100% by changing the agitation speed between 20-500 rpm respectively. Effect of reducing the DOT level from 100% to 15% was observed after 4.5 h fermentation. There was a growth arrest as indicated by the decrease in the OD650 at this time (4.5-5 h). The relative fluorescence (green) intensity was decreased from about 460 to 420 RFU. However, %R/G ratio was significantly increased from about 0.1% to about 0.25% when the DOT level was decreased to 15%. But when the DOT was changed to 100%, a little increase in the RF and decrease in the %R/G ratio were observed. Therefore, GFP can effectively detect and indicate any change in pH and oxygen level during fermentation processes.

Keywords: Escherichia coli SCC1, fermentation process, green fluorescent protein, red fluorescence

Procedia PDF Downloads 501

Authors: Jui-Pui Hung, Yu-Sheng Lai, Tzuo-Liang Luo, Kung-Da Wu, Yun-Ji Zhan

Abstract:

This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: dynamic stiffness, spindle-tool holder, interface stiffness, drawbar force

Procedia PDF Downloads 393