Search results for: sensor fault

Authors: Nastaran Cheshmehkaboodi, Lotfi Guizani, Noureddine Ghlamallah

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Seismic isolation proves to be a powerful technology in reducing seismic hazards and enhancing overall structural resilience. However, the performance of the technology can be influenced by various factors, including seismic inputs and soil conditions. This research aims to investigate the effects of moderate and strong earthquakes associated with different distances of the source on the seismic responses of conventional and isolated bridges, considering the soil-structure interaction effects. Two groups of moderate and strong near-fault records are applied to the conventional and isolated bridges, with and without considering the underlying soil. For this purpose, using the direct method, three soil properties representing rock, dense, and stiff soils are modeled in Abaqus software. Nonlinear time history analysis is carried out, and structural responses in terms of maximum deck acceleration, deck displacement, and isolation system displacement are studied. The comparison of dynamic responses between both earthquake groups demonstrates a consistent pattern, indicating that the bridge performance and the effects of soil-structure interaction are primarily influenced by the ground motions and their frequency contents. Low ratios of PGA/PGV are found to significantly impact all dynamic responses, resulting in higher force and displacement responses, regardless of the distance associated with the ruptured fault. In addition, displacement responses increase drastically on softer soils. Thus, meticulous consideration is crucial in designing isolation systems to avoid underestimating displacement demands and to ensure sufficient displacement capacity. Despite a lower PGA value in high seismicity areas in this study, the acceleration demand during strong earthquakes is up to 1.3 times higher in conventional bridges and up to 3 times higher in isolated bridges than in moderate earthquakes. Additionally, the displacement demand in strong earthquakes is up to 2 times higher in conventional bridges and up to 5 times higher in isolated bridges compared to moderate earthquakes, highlighting the increased force and displacement demand in strong earthquakes.

Keywords: bridges, seismic isolation, near-fault, earthquake characteristics, soil-structure interaction

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Authors: Anwar H. Radwan, Jan Mrlina, El-Sayed A. Issawy, Ali Rayan, Salah M. Mahmoud

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Geodynamic investigations in the Aswan Lake region were started after the M=5.5 earthquake in 1981, triggered by the lake water fluctuations. Besides establishing the seismological networks, also the geodetic observations focused on the Kalabsha and Sayal fault zones were started. It was found that the Kalabsha fault is an active dextral strike-slip with normal component indicating uplift on its southern side. However, the annual velocity rates in both components do not exceed 2 mm/y, and do not therefore represent extremely active faulting. We also launched gravity monitoring in 1997, and performed another two campaigns in 2000 and 2002. The observed non- tidal temporal gravity changes indicate rather the flood water infiltration into the porous Nubian sandstone, than tectonic stress effect. The station nearest to the lake exhibited about 60 μGal positive gravity change within the 1997-2002 period.

Keywords: gravity monitoring, surface movements, Lake Aswan, groundwater change

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

Procedia PDF Downloads 192

Authors: Rajkumar Ghosh

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Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

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Authors: Erhan Zor, Funda Copur, Asli I. Dogan, Haluk Bingol

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Current trends in the wide-scale sensing technologies rely on the development of miniaturized, rapid and easy-to-use sensing platforms. Quantum dots (QDs) with strong and easily tunable luminescence and high emission quantum yields have become a well-established photoluminescent nanomaterials for sensor applications. Although the majority of the reports focused on the cadmium-based QDs which have toxic effect on biological systems and eventually would cause serious environmental problems, carbon-based quantum dots (CQDs) that do not contain any toxic class elements have attracted substantial research interest in recent years. CQDs are small carbon nanostructures (less than 10 nm in size) with various unique properties and are widely-used in different fields during the last few years. In this respect, chiral nanostructures have become a promising class of materials in various areas such as pharmacology, catalysis, bioanalysis and (bio)sensor technology due to the vital importance of chirality in living systems. We herein report the synthesis of chiral CQDs with D- or L-tartaric acid as precursor materials. The optimum experimental conditions were examined and the purification procedure was performed using ethanol/water by column chromatography. The purified chiral CQDs were characterized by UV-Vis, FT-IR, XPS, PL and TEM techniques. The resultants display different photoluminescent characteristics due to the size and conformational difference. Considering the results, it can be concluded that chiral CQDs is expected to be used as optical chiral sensor in different platforms.

Keywords: carbon quantum dots, chirality, sensor, tartaric acid

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Authors: Hassan Gholibeigian, Kazem Gholibeigian

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In this paper, our goal is determination of loading versus time in crust. For this goal, we present a computational procedure to propose a cumulative strain energy time profile which can be used to predict the approximate location and time of the next major earthquake (M > 4.5) along a specific fault, which we believe, is more accurate than many of the methods presently in use. In the coming pages, after a short review of the research works presently going on in the area of earthquake analysis and prediction, earthquake mechanisms in both the jerk and sequence earthquake direction is discussed, then our computational procedure is presented using differential equations of equilibrium which govern the nonlinear dynamic response of a system of finite elements, modified with an extra term to account for the jerk produced during the quake. We then employ Von Mises developed model for the stress strain relationship in our calculations, modified with the addition of an extra term to account for thermal effects. For calculation of the strain energy the idea of Pulsating Mantle Hypothesis (PMH) is used. This hypothesis, in brief, states that the mantle is under diurnal cyclic pulsating loads due to unbalanced gravitational attraction of the sun and the moon. A brief discussion is done on the Denali fault as a case study. The cumulative strain energy is then graphically represented versus time. At the end, based on some hypothetic earthquake data, the final results are verified.

Keywords: pulsating mantle hypothesis, inner core’s dislocation, outer core’s bulge, constitutive model, transient hydro-magneto-thermo-mechanical load, diurnal stress, jerk, fault behaviour

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: Svilen Dimitrov, Manthan Pancholi, Norbert Schmitz, Didier Stricker

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This paper presents the end-to-end development of a wearable motion sensing harness consisting of computational unit and four inertial measurement units to control three smartphone therapeutic games for children. The inertial data is processed in real time to obtain lower body motion information like knee raises, feet taps and squads. By providing a Wi-Fi connection interface the sensor harness acts wireless remote control for smartphone applications. By performing various lower body movements the users provoke corresponding game state changes. In contrary to the current similar offers, like Nintendo Wii Remote, Xbox Kinect and Playstation Move, this product, consisting of the sensor harness and the applications on top of it, are fully wearable, which means they do not rely on the user to be bound to concrete soft- or hardwareequipped space.

Keywords: wearable harness, inertial measurement units, smartphone therapeutic games, motion tracking, lower-body activity monitoring

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Shalini Menon, K. Girish Kumar

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Norepinephrine (NE) is one of the naturally occurring catecholamines which act both as a neurotransmitter and a hormone. Catecholamine levels are used for the diagnosis and regulation of phaeochromocytoma, a neuroendocrine tumor of the adrenal medulla. The development of simple, rapid and cost-effective sensors for NE still remains a great challenge. Herein, a dual-channel sensor has been developed for the determination of NE. A mixture of AgNO₃, NaOH, NH₃.H₂O and cetrimonium bromide in appropriate concentrations was taken as the working solution. To the thoroughly vortexed mixture, an appropriate volume of NE solution was added. After a particular time, the fluorescence and absorbance were measured. Fluorescence measurements were made by exciting at a wavelength of 400 nm. A dual-channel optical sensor has been developed for the colorimetric as well as the fluorimetric determination of NE. Metal enhanced fluorescence property of nanoparticles forms the basis of the fluorimetric detection of this assay, whereas the appearance of brown color in the presence of NE leads to colorimetric detection. Wide linear ranges and sub-micromolar detection limits were obtained using both the techniques. Moreover, the colorimetric approach was applied for the determination of NE in synthetic blood serum and the results obtained were compared with the classic high-performance liquid chromatography (HPLC) method. Recoveries between 97% and 104% were obtained using the proposed method. Based on five replicate measurements, relative standard deviation (RSD) for NE determination in the examined synthetic blood serum was found to be 2.3%. This indicates the reliability of the proposed sensor for real sample analysis.

Keywords: norepinephrine, colorimetry, fluorescence, silver nanoparticles

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Authors: Faisal AlShammari, Abdulmajid Addali, Mosab Alrashed

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It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm, and such machines are important to the industry. However, the overwhelming proportion of studies have investigated the use of AE techniques for condition monitoring of higher-speed machines (typically several hundred rpm, or even higher). Few researchers have investigated the application of these techniques to low-speed machines ( < 100 rpm). This paper addressed this omission and has established which, of the available, AE techniques are suitable for the detection of incipient faults and measurement of fault growth in low-speed bearings. The first objective of this paper program was to assess the applicability of AE techniques to monitor low-speed bearings. It was found that the measured statistical parameters successfully monitored bearing conditions at low speeds (10-100 rpm). The second objective was to identify which commonly used statistical parameters derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify the onset of a fault in the out race. It was found that these parameters effectually identify the presence of a small fault seeded into the outer races. Also, it is concluded that rotational speed has a strong influence on the measured AE parameters but that they are entirely independent of the load under such load and speed conditions.

Keywords: acoustic emission, condition monitoring, NDT, statistical analysis

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Authors: Nicolay Zarutskiy, Roman Bulkin

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The paper deals with the existing methods of force-torque sensor calibration with a number of components from one to six, analyzed their advantages and disadvantages, the necessity of introduction of a calibration method. Calibration method and its constructive realization are also described here. A calibration method allows performing automated force-torque sensor calibration both with selected components of the main vector of forces and moments and with complex loading. Thus, two main advantages of the proposed calibration method are achieved: the automation of the calibration process and universality.

Keywords: automation, calibration, calibration device, calibration method, force-torque sensors

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Authors: Dawei Cai

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In this paper, we present an autonomous guidance service by combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: NFC, ubiquitous computing, guide sysem, MEMS

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Authors: João Filipe Papel, Tatsuji Munaka

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With society's aging and the number of elderly with dementia rising, researchers have been actively studying how to support the elderly in the early stages of dementia with the objective of allowing them to have a better life quality and as much as possible independence. To make this possible, most researchers in this field are using the Internet Of Things to monitor the elderly activities and assist them in performing them. The most common sensor used to monitor the elderly activities is the Camera sensor due to its easy installation and configuration. The other commonly used sensor is the sound sensor. However, we need to consider privacy when using these sensors. This research aims to develop a system capable of predicting the early stages of dementia based on monitoring and controlling the elderly activities of daily living. To make this system possible, some issues need to be addressed. First, the issue related to elderly privacy when trying to detect their Activities of Daily Living. Privacy when performing detection and monitoring Activities of Daily Living it's a serious concern. One of the purposes of this research is to achieve this detection and monitoring without putting the privacy of the elderly at risk. To make this possible, the study focuses on using an approach based on using Magnet Sensors to collect binary data. The second is to use the data collected by monitoring Activities of Daily Living to predict the early stages of Dementia. To make this possible, the research team suggests developing a proprietary ontology combined with both data-driven and knowledge-driven.

Keywords: dementia, activity recognition, magnet sensors, ontology, data driven and knowledge driven, IoT, activities of daily living

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Authors: L. Parisi

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A blood pressure monitor or sphygmomanometer can be either manual or automatic, employing respectively either the auscultatory method or the oscillometric method. The manual version of the sphygmomanometer involves an inflatable cuff with a stethoscope adopted to detect the sounds generated by the arterial walls to measure blood pressure in an artery. An automatic sphygmomanometer can be effectively used to monitor blood pressure through a pressure sensor, which detects vibrations provoked by oscillations of the arterial walls. The pressure sensor implemented in this device improves the accuracy of the measurements taken.

Keywords: blood pressure, blood saturation, sensors, actuators, design improvement

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Authors: Min Kyung An

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In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

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Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandr, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine enginesrequiresa good control of its component temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system is significantly important to elongatethe lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate 2D surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement, such as thermocouples, thermal wall paints, pyrometry, and phosphors, have shown disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve two-dimensional high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of combustor in gas-turbine engines.

Keywords: borescope, engine, long-wave-infrared, sensor

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Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

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Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

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Authors: Sk Shamim Hasan Abir, Karen Lozano, Mohammed Jasim Uddin

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Over the last few years, nanofiber-based triboelectric nanogenerator (TENG) has caught great attention among researchers all over the world due to its inherent capability of converting mechanical energy to usable electrical energy. In this study, poly(vinylidene fluoride) (PVDF) and thermoplastic polyurethane (TPU) nanofiber prepared by Forcespinning® (FS) technique were used to fabricate TENG for self-charging energy storage device and biomechanical body motion sensor. The surface of the TPU nanofiber was modified by uniform deposition of thin gold film to enhance the frictional properties; yielded 254 V open-circuit voltage (Voc) and 86 µA short circuit current (Isc), which were 2.12 and 1.87 times greater in contrast to bare PVDF-TPU TENG. Moreover, the as-fabricated PVDF-TPU/Au TENG was tested against variable capacitors and resistive load, and the results showed that with a 3.2 x 2.5 cm2 active contact area, it can quick charge up to 7.64 V within 30 seconds using a 1.0 µF capacitor and generate significant 2.54 mW power, enough to light 75 commercial LEDs (1.5 V each) by the hand tapping motion at 4 Hz (240 beats per minutes (bpm)) load frequency. Furthermore, the TENG was attached to different body parts to capture distinctive electrical signals for various body movements, elucidated the prospective usability of our prepared nanofiber-based TENG in wearable body motion sensor application.

Keywords: biomotion sensor, forcespinning, nanofibers, triboelectric nanogenerator

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Authors: Marco Lopes, Pedro D. Gaspar, Maria P. Simões

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This paper reviews the different concepts that have been investigated concerning the mechanization of fruit thinning as well as multiple working principles and solutions that have been developed for feature extraction of horticultural products, both in the field and industrial environments. The research should be committed towards selective methods, which inevitably need to incorporate some kinds of sensor technology. Computer vision often comes out as an obvious solution for unstructured detection problems, although leaves despite the chosen point of view frequently occlude fruits. Further research on non-traditional sensors that are capable of object differentiation is needed. Ultrasonic and Near Infrared (NIR) technologies have been investigated for applications related to horticultural produce and show a potential to satisfy this need while simultaneously providing spatial information as time of flight sensors. Light Detection and Ranging (LIDAR) technology also shows a huge potential but it implies much greater costs and the related equipment is usually much larger, making it less suitable for portable devices, which may serve a purpose on smaller unstructured orchards. Portable devices may serve a purpose on these types of orchards. In what concerns sensor methods, on-tree fruit detection, major challenge is to overcome the problem of fruits’ occlusion by leaves and branches. Hence, nontraditional sensors capable of providing some type of differentiation should be investigated.

Keywords: fruit thinning, horticultural field, portable devices, sensor technologies

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Authors: Bernstein Ran, Shafir Tal, Tsachor Rachelle, Studd Karen, Schuster Assaf

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Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban movement analysis, multitask learning, Kinect sensor, machine learning

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Authors: Waheeda Jabbar, Ali Gul, Rida Noor, Sania Kurd, Saba Gulzar

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Hundreds of miners die from mining accidents each year due to poisonous gases found underground mining areas. This paper proposed an idea to protect the precious lives of mining workers. A supervising system is designed which is based on ZigBee wireless technique along with the smart protective helmets to detect real-time surveillance and it gives early warnings on presence of different poisonous gases in order to save mineworkers from any danger caused by these poisonous gases. A wireless sensor network is established using ZigBee wireless technique by integrating sensors on the helmet, apart from this helmet have embedded heartbeat sensor to detect the pulse rate and be aware of the physical or mental strength of a mineworker to increase the potential safety. Radio frequency identification (RFID) technology is used to find the location of workers. A ZigBee based base station is set-upped to control the communication. The idea is implemented and results are verified through experiment.

Keywords: Arduino, gas sensor (MQ7), RFID, wireless ZigBee

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Authors: Alaeddin Ebrahimi, Narasimman Sundararajan, Bernhard Pracejus

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Development of salt domes, often a rising from depths of some 10 km or more, causes an intense faulting of the surrounding host rocks (salt tectonics). The fractured rocks then present ideal space for oil that can migrate and get trapped. If such moving of hydrocarbons passes uranium-carrying rock units (e.g., shales), uranium is collected and enriched by organic carbon compounds. Brines from the salt body are also ideal carriers for oxidized uranium species and will further dislocate uranium when in contact with uranium-enriched oils. Uranium then has the potential to mineralize in the vicinity of the dome (blue halite is evidence for radiation having affected salt deposits elsewhere in the world). Based on this knowledge, the Qarat Kibrit salt dome was investigated by a well-established geophysical method like very low frequency electromagnetic (VLF-EM) along five traverses approximately 250 m in length (10 m intervals) in order to identify subsurface fault systems. In-phase and quadrature components of the VLF-EM signal were recorded at two different transmitter frequencies (24.0 and 24.9 kHz). The images of Fraser filtered response of the in-phase components indicate a conductive zone (fault) in the southeast and southwest of the study area. The Karous-Hjelt current density pseudo section delineates subsurface faults at depths between 10 and 40 m. The stacked profiles of the Fraser filtered responses brought out two plausible trends/directions of faults. However, there seems to be no evidence for uranium enrichment has been recorded in this area.

Keywords: salt dome, uranium, fault, in-phase component, quadrature component, Fraser filter, Karous-Hjelt current density

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Julien Romieux, Fabio Verdicchio

Abstract:

Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: N. Ullah, A. Haddad, F. Van Der Linde

Abstract:

This paper investigates the effects of breaks in bonds, breaks in the earthing system and breaks in earth wire on the rise of the earth potential (EPR) in a substation and at the transmission tower bases using various models of an L6 tower. Different approaches were adopted to examine the integrity of the earthing system and the terminal towers. These effects were investigated to see the associated difference in the EPR magnitudes with respect to a healthy system at various locations. Comparisons of the computed EPR magnitudes were then made between the healthy and unhealthy system to detect any difference. The studies were conducted at power frequency for a uniform soil with different soil resistivities. It was found that full breaks in the double bond of the terminal towers increase the EPR significantly at the fault location, while they reduce EPR at the terminal tower bases. A fault on the isolated section of the grid can result in EPR values up to 8 times of those on a healthy system at higher soil resistivities, provided that the extended earthing system stays connected to the grid.

Keywords: bonding, earthing, EPR, integrity, system

Procedia PDF Downloads 315

Authors: Abdelaziz Beddiaf

Abstract:

In this work, we present an analysis based on the study of mobility which is a very important electrical parameter of a piezoresistor and which is directly bound to the piezoresistivity effect in piezoresistive pressure sensors. We determine how the temperature affects mobility when the electric potential is applied. For this, a theoretical approach based on mobility in a p-type Silicon piezoresistor with that of a finite difference model for self-heating is developed. So, the evolution of mobility has been established versus time for different doping levels and with temperature rise provoked by self-heating using a numerical model combined with that of mobility. Furthermore, it has been calculated for some geometrical parameters of the sensor, such as membrane side length and thickness. Also, it is computed as a function of bias voltage. It was observed that mobility is strongly affected by the temperature rise induced by the applied potential when the sensor is actuated for a prolonged time as a consequence of drifting in the output response of the sensor. Finally, this work makes it possible to predict their temperature behavior due to self-heating and to improve this effect by optimizing the geometric properties of the device and by reducing the voltage source applied to the bridge.

Keywords: Sensors, Piezoresistivity, Mobility, Bias voltage

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Authors: Vinda B. Manurung, Laila Warkhaida, David Hutabarat, Sentanu Wisnuwardhana, Christovik Simatupang, Dhani Sanjaya, Ashadi, Redha B. Putra, Kiki Yustendi

Abstract:

The geothermal drilling environment presents many obstacles that have limited the use of directional drilling and logging-while-drilling (LWD) technologies, such as borehole washout, mud losses, severe vibration, and high temperature. The case study presented in this paper demonstrates a practice to enhance data logging in geothermal drilling by deploying advanced telemetry and LWD technologies. This operation is aiming continuous improvement in geothermal drilling operations. The case study covers a 12.25-in. hole section of well XX-05 in Pad XX of the Sorik Marapi Geothermal Field. LWD string consists of electromagnetic (EM) telemetry, pressure while drilling (PWD), vibration (DDSr), and acoustic calliper (ACAL). Through this tool configuration, the operator acquired drilling mechanics and caliper logs in real-time and recorded mode, enabling effective monitoring of wellbore stability. Throughout the real-time acquisition, EM-PPM telemetry had provided a three times faster data rate to the surface unit. With the integration of Caliper data and Drilling mechanics data (vibration and ECD -equivalent circulating density), the borehole conditions were more visible to the directional driller, allowing for better control of drilling parameters to minimize vibration and achieve optimum hole cleaning in washed-out or tight formation sequences. After reaching well TD, the recorded data from the caliper sensor indicated an average of 8.6% washout for the entire 12.25-in. interval. Washout intervals were compared with loss occurrence, showing potential for the caliper to be used as an indirect indicator of fractured intervals and validating fault trend prognosis. This LWD case study has given added value in geothermal borehole characterization for both drilling operation and subsurface. Identified challenges while running LWD in this geothermal environment need to be addressed for future improvements, such as the effect of tool eccentricity and the impact of vibration. A perusal of both real-time and recorded drilling mechanics and caliper data has opened various possibilities for maximizing sensor usage in future wells.

Keywords: geothermal drilling, geothermal formation, geothermal technologies, logging-while-drilling, vibration, caliper, case study

Procedia PDF Downloads 107

Authors: Mike Dee

Abstract:

Urban public spaces are sutured with a range of surveillance and sensor technologies that claim to enable new forms of ‘data based citizen participation’, but also increase the tendency for ‘function-creep’, whereby vast amounts of data are gathered, stored and analysed in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces. A direct consequence of the increasingly security driven, policed, privatised and surveilled nature of public space is the exclusion or ‘unfavourable inclusion’ of those considered flawed and unwelcome in the ‘spectacular’ consumption spaces of many major urban centres. In the name of urban regeneration, programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’ city initiatives refashion public space as sites of selective inclusion and exclusion. In this context of monitoring and control procedures, in particular, children and young people’s use of space in parks, neighbourhoods, shopping malls and streets is often viewed as a threat to the social order, requiring various forms of remedial action. This paper suggests that cities, places and spaces and those who seek to use them, can be resilient in working to maintain and extend democratic freedoms and processes enshrined in Marshall’s concept of citizenship, calling sensor and surveillance systems to account. Such accountability could better inform the implementation of public policy around the design, build and governance of public space and also understandings of urban citizenship in the sensor saturated urban environment.

Keywords: citizenship, public space, surveillance, young people

Procedia PDF Downloads 433