Search results for: topographic monitoring.

Authors: Oliver Ohneiser, Francesca De Crescenzio, Gianluca Di Flumeri, Jan Kraemer, Bruno Berberian, Sara Bagassi, Nicolina Sciaraffa, Pietro Aricò, Gianluca Borghini, Fabio Babiloni

Abstract:

An increasing degree of automation in air traffic will also change the role of the air traffic controller (ATCO). ATCOs will fulfill significantly more monitoring tasks compared to today. However, this rather passive role may lead to Out-Of-The-Loop (OOTL) effects comprising vigilance decrement and less situation awareness. The project MINIMA (Mitigating Negative Impacts of Monitoring high levels of Automation) has conceived a system to control and mitigate such OOTL phenomena. In order to demonstrate the MINIMA concept, an experimental simulation set-up has been designed. This set-up consists of two parts: 1) a Task Environment (TE) comprising a Terminal Maneuvering Area (TMA) simulator as well as 2) a Vigilance and Attention Controller (VAC) based on neurophysiological data recording such as electroencephalography (EEG) and eye-tracking devices. The current vigilance level and the attention focus of the controller are measured during the ATCO’s active work in front of the human machine interface (HMI). The derived vigilance level and attention trigger adaptive automation functionalities in the TE to avoid OOTL effects. This paper describes the full-scale experimental set-up and the component development work towards it. Hence, it encompasses a pre-test whose results influenced the development of the VAC as well as the functionalities of the final TE and the two VAC’s sub-components.

Keywords: Automation, human factors, air traffic controller, MINIMA, OOTL, Out-Of-The-Loop, EEG, electroencephalography, HMI, human machine interface.

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Authors: Omid A. Zargar

Abstract:

Vibration analysis is the most important factor in preventive maintenance. Gas turbine vibration analysis is also one of the most challenging categories in most critical equipment monitoring systems. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of this kind of equipment developed too much in recent years. On the other hand, too much operation condition consideration in this kind of equipment should be adjusted properly like inlet and outlet pressure and temperature for both turbine and compressor. In this paper the most important tools and hypothesis used for analyzing of gas turbine power plants discussed in details through a real case history related to an Alstom Typhoon gas turbine power plant in Iran oil industries. In addition, the basic principal of vibration behavior caused by mechanical unbalance in gas turbine rotor discussed in details.

Keywords: Vibration analysis, gas turbine, time wave form (TWF), fast Fourier transform (FFT), phase angle.

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Authors: Toshihiko Sasama, Takao Kawamura, Kazunori Sugahara

Abstract:

Using Internet communication, new home electronics have functions of monitoring and control from remote. However in many case these electronics work as standalone, and old electronics are not followed. Then, we developed the total remote system include not only new electronics but olds. This systems node is a adapter of electrical power plug that embed relay switch and some sensors, and these nodes communicate with each other. the system server was build on the Internet, and users access to this system from web browsers. To reduce the cost to set up of this system, communication between adapters are used ZigBee wireless network instead of wired LAN cable[3]. From measured RSSI(received signal strength indicator) information between each nodes, the system can estimate roughly adapters were mounted on which room, and where in the room. So also it reduces the cost of mapping nodes. Using this system, energy saving and house monitoring are expected.

Keywords: outlet, remote monitor, remote control, mobile ad hocnetwork, sensor network, zigbee.

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Authors: F. M. Pisano, M. Ciminello

Abstract:

Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Mongkorn Klingajay, Tawatchai Jitson

Abstract:

The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.

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Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

Abstract:

This paper presents a 4-DOF nonlinear model of a cracked de Laval rotor-stator system derived based on Energy Principles. The model has been used to simulate coupled torsionallateral response of the faulty system with multiple parametric excitations; rotor-stator-rub, a breathing transverse crack, eccentric mass and an axial force. Nonlinearity of a “breathing” crack is incorporated in the model using a simple hinge mechanism suitable for a shallow crack. Response of the system while passing via its critical speed with intermittent rotor-stator rub is analyzed. Effects of eccentricity with phase and acceleration are investigated. Features of crack, rub and eccentricity in vibration response are explored for condition monitoring. The presence of a crack and rub are observable in the power spectrum despite excitations by an axial force and rotor unbalance. Obtained results are consistent with existing literature and could be adopted into rotor condition monitoring strategies.

Keywords: Axial force, Crack, Nonlinear, Rotor-Stator, Rub.

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Authors: Raúl Pereda García, Julio Manuel de Luis Ruiz, Elena Castillo López, Rubén Pérez Álvarez, Felipe Piña García

Abstract:

New technologies for the capture of point clouds have experienced a great advance in recent years. In this way, its use has been extended in geomatics, providing measurement solutions that have been popularized without there being, many times, a detailed study of its accuracy. This research focuses on the study of the viability of topographic works with drones incorporating different sensors sensitive to the visible spectrum. The fundamentals have been applied to a road, located in Cantabria (Spain), where a platform extension and the reform of a riprap were being constructed. A total of six flights were made during two months, all of them with GPS as part of the photogrammetric process, and the results were contrasted with those measured with total station. The obtained results show that the choice of the camera and the planning of the flight have an important impact on the accuracy. In fact, the representations with a level of detail corresponding to 1/1000 scale are admissible, depending on the existing vegetation, and obtaining better results in the area of the riprap. This set of techniques is, therefore, suitable for the control of earthworks in road works but with certain limitations which are exposed in this paper.

Keywords: Drone, earth movement control, global position system, surveying technology.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

Abstract:

Brain Computer Interface (BCI) has been recently increased in research. Functional Near Infrared Spectroscope (fNIRs) is one the latest technologies which utilize light in the near-infrared range to determine brain activities. Because near infrared technology allows design of safe, portable, wearable, non-invasive and wireless qualities monitoring systems, fNIRs monitoring of brain hemodynamics can be value in helping to understand brain tasks. In this paper, we present results of fNIRs signal analysis indicating that there exist distinct patterns of hemodynamic responses which recognize brain tasks toward developing a BCI. We applied two different mathematics tools separately, Wavelets analysis for preprocessing as signal filters and feature extractions and Neural networks for cognition brain tasks as a classification module. We also discuss and compare with other methods while our proposals perform better with an average accuracy of 99.9% for classification.

Keywords: functional near infrared spectroscope (fNIRs), braincomputer interface (BCI), wavelets, neural networks, brain activity, neuroimaging.

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Authors: Chuan Li, Ming Liang

Abstract:

Oil debris signal generated from the inductive oil debris monitor (ODM) is useful information for machine condition monitoring but is often spoiled by background noise. To improve the reliability in machine condition monitoring, the high-fidelity signal has to be recovered from the noisy raw data. Considering that the noise components with large amplitude often have higher frequency than that of the oil debris signal, the integral transform is proposed to enhance the detectability of the oil debris signal. To cancel out the baseline wander resulting from the integral transform, the empirical mode decomposition (EMD) method is employed to identify the trend components. An optimal reconstruction strategy including both de-trending and de-noising is presented to detect the oil debris signal with less distortion. The proposed approach is applied to detect the oil debris signal in the raw data collected from an experimental setup. The result demonstrates that this approach is able to detect the weak oil debris signal with acceptable distortion from noisy raw data.

Keywords: Integral transform, empirical mode decomposition, oil debris, signal processing, detection.

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

Abstract:

Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: Accuracy, classical topographic, 3D model, photogrammetry, UAV.

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Authors: Abegunde Linda, Adedeji Oluwatola, Tope-Ajayi Opeyemi

Abstract:

Maize constitutes a major agrarian production for use by the vast population but despite its economic importance; it has not been produced to meet the economic needs of the country. Achieving optimum yield in maize can meaningfully be supported by land suitability analysis in order to guarantee self-sufficiency for future production optimization. This study examines land suitability for maize production through the analysis of the physicochemical variations in soil properties and other land attributes over space using a Geographic Information System (GIS) framework. Physicochemical parameters of importance selected include slope, landuse, physical and chemical properties of the soil, and climatic variables. Landsat imagery was used to categorize the landuse, Shuttle Radar Topographic Mapping (SRTM) generated the slope and soil samples were analyzed for its physical and chemical components. Suitability was categorized into highly, moderately and marginally suitable based on Food and Agricultural Organisation (FAO) classification, using the Analytical Hierarchy Process (AHP) technique of GIS. This result can be used by small scale farmers for efficient decision making in the allocation of land for maize production.

Keywords: AHP, GIS, MCE, Suitability, Zea mays.

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Authors: Maryam Kargar, Neamatolah Khorasani, Mahmoud Karami, Gholam-Reza Rafiee, Reza Naseh

Abstract:

Interpolated contour maps drawn for aluminum, copper and molybdenum in downstream monitoring boreholes of water dam in Miduk Copper Complex and the values of pH, redox potential (Eh) and distance from water dam indicate different trends of variation and behavior of these three elements in downward groundwater resources. As these maps exhibit, aluminum is dominant in the most alkaline (pH = 9-11) borehole (MB5) to water dam. The highest concentration of molybdenum is found in the nearest borehole (MB6) to water dam. Main concentration of copper is observed in the most oxidized borehole (MB3 with Eh=293.2mV). The spatial difference among sampling stations can be attributed to the existence of faults and diaclases in the geologic structure of Miduk region which causes the groundwater sampling sites to be impressed by different contamination sources (toe seepage and upper seepage water originated from different zones of tailings dump).

Keywords: Contour maps, Monitoring borehole, Toe seepage, Upper seepage.

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Authors: Nasrin Farajiparvar

Abstract:

In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.

Keywords: Condition-based maintenance, Economic savings, Iran industries, Machine life prediction software.

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Authors: Hasan Kalyoncu, Burcu Şerbetci

Abstract:

Diatoms are an important group of aquatic ecosystems and diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. Although the studies are very limited about Turkish rivers, diatom indices were used for monitoring rivers in different basins. In the present study, we used OMNIDIA program for estimation of stream quality. Some indices have less sensitive (IDP, WAT, LOBO, GENRE, TID, CEE, PT), intermediate sensitivities (IDSE, DESCY, IPS, DI-CH, SLA, IDAP), the others higher sensitivities (SID, IBD, SHE, EPI-D). Among the investigated diatom communities, only a few taxa indicated alfa-mesosaprobity and polysaprobity. Most of the sites were characterized by a great relative contribution of eutraphent and tolerant ones as well as oligosaprobic and betamesosaprobic diatoms. In general, SID and IBD indices gave the best results. This study suggests that the structure of benthic diatom communities and diatom indices, especially SID, can be applied for monitoring rivers in Southern Turkey. 

Keywords: Diatom, Darı stream, OMNIDIA, Turkey, Water quality.

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Authors: Rahim Sotoudeh Bahreini, Alireza Foroughi Nematollahi, Akbar Jafari

Abstract:

This study investigates the mechanism of a Gyratory crusher-located in Golgohar mining and industrial Co. specifically with a focus on stresses distribution and fatigue failure of its main shaft. At first step, the cross section of the fractured shaft is studied, and the crack growth is analyzed. Then, the rotational motion of the shaft and the oil temperature of oil circuit of equipment are monitored. Condition monitoring is used to help finding a better modification. Based on the results of this study, the main causes of shaft failure are identified, and corrective solution is offered to increase crusher performance, especially its main shaft life. To predict the efficiency of the proposed modification, finite element simulation is performed, and its results are compared with the similar modified cases. The comparison and interpretation of simulation results confirm the efficiency of proposed corrective method.

Keywords: Fatigue failure, finite element method, gyratory crusher, condition monitoring.

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Authors: Jaharah A. Ghani, Muhammad Rizal, Ahmad Sayuti, Mohd Zaki Nuawi, Mohd Nizam Ab. Rahman, Che Hassan Che Haron

Abstract:

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the IKaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases when the tool wear increases. This method can be used for real time tool wear monitoring.

Keywords: mathematical model, I-kaz method, tool wear

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Authors: Reza Mokhtari Malekabadi, Leila Jalalabadi, Zahra Kiyani Ghaleh No

Abstract:

Today, systems of management and urban planning, attempt to reach more sustainable development through monitoring developments, urban development and development plans. Monitoring of changes in the urban places and sustainable urban development accounted a base for the realization of worthy goals urban sustainable development. The importance of women in environmental protection programs is high enough that in 21 agenda has been requested from all countries to allocate more shares to women in their policies. On the other hand, urban waste landfill has become one of the environmental concerns in modern cities. This research assumes that the impact of women on recycling, reduction and proper waste landfill is much more than men. For this reason, three districts; Yousef Abad, Heshmatieh & Nezam Abad are gauged through questionnaire and using the analytical research hypothesis model. This research will be categorized as functional research. The results have shown that noticing the power of women, their participation towards realization of the development objectives and programs can be used in solving their problems.

Keywords: Citizens (Urban), Environmental, Sustainability, Solid waste, Tehran.

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Authors: H.K. Luk, Y.M. Lai, L. Qin, C.W. Chan, Z. Liu, Y.P. Huang, Y.P. Zheng

Abstract:

Ultrasound is useful in demonstrating bone mineral density of regenerating osseous tissue as well as structural alterations. A proposed ultrasound method, which included ultrasonography and acoustic parameters measurement, was employed to evaluate its efficacy in monitoring the bone callus changes in a rabbit tibial distraction osteogenesis (DO) model. The findings demonstrated that ultrasonographic images depicted characteristic changes of the bone callus, typical of histology findings, during the distraction phase. Follow-up acoustic parameters measurement of the bone callus, including speed of sound, reflection and attenuation, showed significant linear changes over time during the distraction phase. The acoustic parameters obtained during the distraction phase also showed moderate to strong correlation with consolidated bone callus density and micro-architecture measured by micro-computed tomography at the end of the consolidation phase. The results support the preferred use of ultrasound imaging in the early monitoring of bone callus changes during DO treatment.

Keywords: Bone Callus Growth, Rabbit Tibial DistractionOsteogenesis, Ultrasonography, Ultrasonometry

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Authors: Muhibul Haque Bhuyan

Abstract:

Diabetes disease that arises from the higher glucose level due to insulin shortage or insulin opposition in the human body has become a common disease in the world. No medicine can cure it completely. However, by taking medicine, maintaining diets, and having exercises regularly, a diabetes patient can keep his glucose level within the specified limits and in this way, he/she can lead a normal life like a healthy person. But to control glucose levels, a patient needs to monitor them regularly. Various techniques are being used over the last four decades. This modern review article aims to provide a comparative study report on various blood glucose monitoring techniques in a very concise and organized manner. The review mainly emphasizes working principles, cost, technology, sensors, measurement types, measurement accuracy, advantages, and disadvantages, etc. of various techniques and then compares among each other. Besides, the use of algorithms and simulators for the growth of this technology is also presented. Finally, current research trends of this measurement technology have also been discussed.

Keywords: blood glucose measurement, sensors, measurement devices, invasive and non-invasive techniques

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective of meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence base for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research significantly changed over time and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable only to fixed effect model (FEM) of meta-analysis. For random-effects model (REM), the analysis incorporates the heterogeneity variance, τ 2 and its estimation create complications. In this paper we study the use of a truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring in REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of applications.

Keywords: Meta-analysis, random-effects model, sequential testing, temporal changes in effect sizes.

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Authors: Peter Rothenpieler, Daniela Kruger, Dennis Pfisterer, Stefan Fischer, Denise Dudek, Christian Haas, Martina Zitterbart

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In the project FleGSens, a wireless sensor network (WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information security. The intended prototype consists of 200 sensor nodes for monitoring a 500m long land strip. The system is focused on ensuring integrity and authenticity of generated alarms and availability in the presence of an attacker who may even compromise a limited number of sensor nodes. In this paper, two of the main protocols developed in the project are presented, a tracking protocol to provide secure detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols and particularly demonstrating the impact and cost of several attacks.

Keywords: Wireless Sensor Network, Security, Trespass Detection, Testbed.

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

Abstract:

Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: Smart grid, EHV transmission tower, response spectrum, damage level monitoring.

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Authors: Harkishen Singh, Gavin Mangeni

Abstract:

This project aims at building an efficient and automatic power monitoring SCADA system, which is capable of monitoring the electrical parameters of high voltage powered devices in real time for example RMS voltage and current, frequency, energy consumed, power factor etc. The system uses RS-485 serial communication interface to transfer data over longer distances. Embedded C programming is the platform used to develop two hardware modules namely: RTU and Master Station modules, which both use the CC2540 BLE 4.0 microcontroller configured in slave / master mode. The Si8900 galvanic ally isolated microchip is used to perform ADC externally. The hardware communicates via UART port and sends data to the user PC using the USB port. Labview software is used to design a user interface to display current state of the power loads being monitored as well as logs data to excel spreadsheet file. An understanding of the Si8900’s auto baud rate process is key to successful implementation of this project.

Keywords: SCADA, RS485, CC2540, Labview, Si8900.

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Authors: Mohamad Muqtada Ali Khan, Nor Ashikin Shaari, Donny Adriansyah Bin Nazaruddin, Hafzan Eva Bt Mansoor

Abstract:

Floods play a key role in landform evolution of an area. This process is likely to alter the topography of the earth’s surface. The present study area, Kota Bharu is very prone to floods extends from upstream of Kelantan River near Kemubu to the downstream area near Kuala Besar. These flood events which occur every year in the study area exhibit a strong bearing on river morphological set-up. In the present study, three satellite imageries of different time periods have been used to manifest the post-flood landform changes. The pre-processing of the images such as subset, geometric corrections and atmospheric corrections were carried-out using ENVI 4.5 followed by the analysis processes. Twenty sets of cross sections were plotted using software Erdas 9.2, ERDAS and ArcGis 10 for the all three images. The results show a significant change in the length of the cross section which suggest that the geomorphological processes play a key role in carving and shaping the river banks during the floods. 

Keywords: Flood Induced, Geomorphic imprints, Kelantan river, Malaysia.

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Authors: Leila Jafari, Viliam Makis, Akram Khaleghei G.B.

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1 which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed, illustrated by a numerical example.

Keywords: Condition-Based Maintenance, Semi-Markov Decision Process, Multivariate Bayesian Control Chart, Partially Observable System, Two-unit System.

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Authors: Dingding Chen, Kazuo Arakawa, Masakazu Uchino, Changheng Xu

Abstract:

Vacuum assisted resin transfer moulding (VARTM) is a promising manufacture process for making large and complex fiber reinforced composite structures. However, the complexity of the flow of the resin in the infusion stage usually leads to nonuniform property distribution of the produced composite part. In order to control the flow of the resin, the situation of flow should be mastered. For the safety of the usage of the produced composite in practice, the understanding of the property distribution is essential. In this paper, we did some trials on monitoring the resin infusion stage and evaluation for the fiber volume fraction distribution of the VARTM produced composite using the digital image correlation methods. The results showthat3D-DIC is valid on monitoring the resin infusion stage and it is possible to use 2D-DIC to estimate the distribution of the fiber volume fraction on a FRP plate.

Keywords: Digital image correlation, VARTM, FRP, fiber volume fraction.

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Authors: T. S. Myers, J. Trevathan

Abstract:

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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Authors: Roohi Shabrin S., Devi Prasad B., Prabu D., Pallavi R. S., Revathi P.

Abstract:

Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application-s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing.

Keywords: Dynamic Memory Monitoring Agent (DMMA), Cluster Computing, Memory Leak, Fault Tolerant Framework, Dynamic Memory Leak Detection (DMLD).

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

Abstract:

Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: Bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks.

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