Search results for: condition based monitoring.

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events is important to improve safety and reliability of machine operations and reduce losses caused by failures. Improper set-ups or aligning of parts often leads to severe problems in many machines. The construction of prediction models for predicting faulty conditions is quite essential in making decisions on when to perform machine maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of machine measurement data. The calibration model is used to predict two faulty conditions from historical reference data. This approach utilizes genetic algorithms (GA) based variable selection, and we evaluate the predictive performance of several prediction methods using real data. The results shows that the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: Prediction, operation monitoring, on-line data, nonlinear statistical methods, empirical model.

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Authors: C. Lanzerstorfer

Abstract:

Liquid sprays of water are frequently used in air pollution control for gas cooling purposes and for gas cleaning. Twin-fluid nozzles with internal mixing are often used for these purposes because of the small size of the drops produced. In these nozzles the liquid is dispersed by compressed air or another pressurized gas. In high efficiency scrubbers for particle separation, several nozzles are operated in parallel because of the size of the cross section. In such scrubbers, the scrubbing water has to be re-circulated. Precipitation of some solid material can occur in the liquid circuit, caused by chemical reactions. When such precipitations are detached from the place of formation, they can partly or totally block the liquid flow to a nozzle. Due to the resulting unbalanced supply of the nozzles with water and gas, the efficiency of separation decreases. Thus, the nozzles have to be cleaned if a certain fraction of blockages is reached. The aim of this study was to provide a tool for continuously monitoring the status of the nozzles of a scrubber based on the available operation data (water flow, air flow, water pressure and air pressure). The difference between the air pressure and the water pressure is not well suited for this purpose, because the difference is quite small and therefore very exact calibration of the pressure measurement would be required. Therefore, an equation for the reference air flow of a nozzle at the actual water flow and operation pressure was derived. This flow can be compared with the actual air flow for assessment of the status of the nozzles.

Keywords: Twin-fluid nozzles, operation data, condition monitoring, flow equation.

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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: Qasim Khan, Furkan Ahmad, Asfar A. Khan, M. Saad Alam, Faiz Ahmad

Abstract:

In this paper, partial discharge analysis is performed in cavities artificially created in insulation. The setup is according with Cigre-II Method. Circular Samples created from Perspex Sheet with different configuration with changing number of cavities. Assessment of insulation health can be performed by Partial Discharge measurement as this has been found to be important means of condition monitoring. The experiments are done using MPD 540, which is a modern partial discharge measurement system. By analyzing the PD activity obtained for various voids/cavities, it is observed that the PD voltages show variation for cavity’s diameter, depth even for its ratios. This can be employed for scrutiny of insulation system.

Keywords: Partial discharges, condition monitoring, MPD 540, cavities/defects, degradation and corrosion, PMMA.

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Authors: S. Sendhilkumar, N. Mohanasundaram, M. Senthilkumar, S. N. Sivanandam

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The operational life of rotating machines has to be extended using a predictive condition maintenance tool. Among various condition monitoring techniques, vibration analysis is most widely used technique in industry. Signals are extracted for evaluating the condition of machine; further diagnostics is carried out with detected signals to extend the life of machine. With help of detected signals, further interpretations are done to predict the occurrence of defects. To study the problem of defects, a test rig with various possibilities of defects is constructed and experiments are performed considering the unbalanced condition. Further, this paper presents an approach for fault diagnosis of unbalance condition using Elman neural network and frequency-domain vibration analysis. Amplitudes with variation in acceleration are fed to Elman neural network to classify fault or no-fault condition. The Elman network is trained, validated and tested with experimental readings. Results illustrate the effectiveness of Elman network in rotor-bearing system.

Keywords: Elman neural network, fault detection, rotating machines, unbalance, vibration analysis.

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

Abstract:

Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: Ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear.

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: Artificial neural network, ANN, chromatic dispersion, delay-tap sampling, optical signal-to-noise ratio, OSNR.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Hyun-Woo Cho

Abstract:

Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: Mohammad Bakhshandeh

Abstract:

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, bridge health monitoring, sensor-based methods, machine-learning algorithms, model-based techniques, sensor placement, data acquisition, data analysis.

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Authors: M.Nafar, A.H.Gheisari, A.Alesaadi

Abstract:

Since large power transformers are the most expensive and strategically important components of any power generator and transmission system, their reliability is crucially important for the energy system operation. Also, Circuit breakers are very important elements in the power transmission line so monitoring the events gives a knowledgebase to determine time to the next maintenance. This paper deals with the introduction of the comparative method of the state estimation of transformers and Circuit breakers using continuous monitoring of voltage, current. This paper gives details a new method based on wavelet to apparatus insulation monitoring. In this paper to insulation monitoring of transformer, a new method based on wavelet transformation and neutral point analysis is proposed. Using the EMTP tools, fault in transformer winding and the detailed transformer winding model were simulated. The current of neutral point of winding was analyzed by wavelet transformation. It is shown that the neutral current of the transformer winding has useful information about fault in insulation of the transformer.

Keywords: Wavelet, Power Transformer, EMTP, CircuitBreaker, Monitoring

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Authors: Yi-Haur Shiau, Sun-In Lin, Shi-Wei Lo, Hsiu-Mei Chou, Yi-Hsuan Chen

Abstract:

This paper proposes a novel multi-format stream grid architecture for real-time image monitoring system. The system, based on a three-tier architecture, includes stream receiving unit, stream processor unit, and presentation unit. It is a distributed computing and a loose coupling architecture. The benefit is the amount of required servers can be adjusted depending on the loading of the image monitoring system. The stream receive unit supports multi capture source devices and multi-format stream compress encoder. Stream processor unit includes three modules; they are stream clipping module, image processing module and image management module. Presentation unit can display image data on several different platforms. We verified the proposed grid architecture with an actual test of image monitoring. We used a fast image matching method with the adjustable parameters for different monitoring situations. Background subtraction method is also implemented in the system. Experimental results showed that the proposed architecture is robust, adaptive, and powerful in the image monitoring system.

Keywords: Motion detection, grid architecture, image monitoring system, and background subtraction.

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Authors: A. Almasi

Abstract:

Reciprocating compressors are flexible to handle wide capacity and condition swings, offer a very efficient method of compressing almost any gas mixture in wide range of pressure, can generate high head independent of density, and have numerous applications and wide power ratings. These make them vital component in various units of industrial plants. In this paper optimum reciprocating compressor configuration regarding interstage pressures, low suction pressure, non-lubricated cylinder, speed of machine, capacity control system, compressor valve, lubrication system, piston rod coating, cylinder liner material, barring device, pressure drops, rod load, pin reversal, discharge temperature, cylinder coolant system, performance, flow, coupling, special tools, condition monitoring (including vibration, thermal and rod drop monitoring), commercial points, delivery and acoustic conditions are presented.

Keywords: Design, optimum, reciprocating compressor.

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Authors: Kitti Leangkrua

Abstract:

This paper presents a risk-based maintenance strategy of a power transformer in order to optimize operating and maintenance costs. The methodology involves the study and preparation of a database for the collection the technical data and test data of a power transformer. An evaluation of the overall condition of each transformer is performed by a program developed as a result of the measured results; in addition, the calculation of the main equipment separation to the overall condition of the transformer (% HI) and the criteria for evaluating the importance (% ImI) of each location where the transformer is installed. The condition assessment is performed by analysis test data such as electrical test, insulating oil test and visual inspection. The condition of the power transformer will be classified from very poor to very good condition. The importance is evaluated from load criticality, importance of load and failure consequence. The risk matrix is developed for evaluating the risk of each power transformer. The high risk power transformer will be focused firstly. The computerized program is developed for practical use, and the maintenance strategy of a power transformer can be effectively managed.

Keywords: Asset management, risk-based maintenance, power transformer, health index.

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Authors: Kaiwan S. Ismael, Ergun Ercelebi, Majeed Nader

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This paper describes the design and implementation of a hardware setup for online monitoring of 24 refrigerators inside blood bank center using the microcontroller and CAN bus for communications between each node. Due to the security of locations in the blood bank hall and difficulty of monitoring of each refrigerator separately, this work proposes a solution to monitor all the blood bank refrigerators in one location. CAN-bus system is used because it has many applications and advantages, especially for this system due to easy in use, low cost, providing a reduction in wiring, fast to repair and easily expanding the project without a problem.

Keywords: Control Area Network (CAN), monitoring blood bank center, PIC microcontroller, MPLAB IDE.

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Authors: Arne Koschel, Irina Astrova

Abstract:

Heterogeneity has to be taken into account when integrating a set of existing information sources into a distributed information system that are nowadays often based on Service- Oriented Architectures (SOA). This is also particularly applicable to distributed services such as event monitoring, which are useful in the context of Event Driven Architectures (EDA) and Complex Event Processing (CEP). Web services deal with this heterogeneity at a technical level, also providing little support for event processing. Our central thesis is that such a fully generic solution cannot provide complete support for event monitoring; instead, source specific semantics such as certain event types or support for certain event monitoring techniques have to be taken into account. Our core result is the design of a configurable event monitoring (Web) service that allows us to trade genericity for the exploitation of source specific characteristics. It thus delivers results for the areas of SOA, Web services, CEP and EDA.

Keywords: ECA, CEP, SOA, and Web services.

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

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Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore, many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology IPT. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to align monitoring activities. Current as well as planned product, production and material technologies and existing skills, capabilities and resources form the basis for derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: Monitoring radar, search field, technology intelligence, technology monitoring.

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Authors: S. Fujiwara, T. Kaburagi, K. Kobayashi, K. Watanabe, Y. Kurihara

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This paper describes a novel sensor device, a pressure pulse wave meter, which uses a bidirectional condenser microphone. The microphone work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economic. Currently aging is becoming a serious social issue in Japan causing increased medical expenses in the country. Hence, it is important for elderly citizens to check health condition at home, and to care the health conditions through daily monitoring. Given this circumstances, we developed a novel pressure pulse wave meter based on a bidirectional condenser microphone: this device is used as a measuring instrument of health conditions.

Keywords: Bidirectional microphone, pressure pulse wave meter, health condition.

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Authors: Nam Lethanh, Bryan T. Adey

Abstract:

In this paper, the potential use of an exponential hidden Markov model to model a hidden pavement deterioration process, i.e. one that is not directly measurable, is investigated. It is assumed that the evolution of the physical condition, which is the hidden process, and the evolution of the values of pavement distress indicators, can be adequately described using discrete condition states and modeled as a Markov processes. It is also assumed that condition data can be collected by visual inspections over time and represented continuously using an exponential distribution. The advantage of using such a model in decision making process is illustrated through an empirical study using real world data.

Keywords: Deterioration modeling, Exponential distribution, Hidden Markov model, Pavement management

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Authors: M. Mahli, A.I. Che-Ani, M.Z. Abd-Razak. N.M. Tawil, H. Yahaya

Abstract:

Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.

Keywords: building condition, CSP1 Matrix, assessment, school, Malaysia

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Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

Abstract:

The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: Condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network.

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Authors: Samir Avdakovic, Amir Nuhanovic

Abstract:

Low frequency power oscillations may be triggered by many events in the system. Most oscillations are damped by the system, but undamped oscillations can lead to system collapse. Oscillations develop as a result of rotor acceleration/deceleration following a change in active power transfer from a generator. Like the operations limits, the monitoring of power system oscillating modes is a relevant aspect of power system operation and control. Unprevented low-frequency power swings can be cause of cascading outages that can rapidly extend effect on wide region. On this regard, a Wide Area Monitoring, Protection and Control Systems (WAMPCS) help in detecting such phenomena and assess power system dynamics security. The monitoring of power system electromechanical oscillations is very important in the frame of modern power system management and control. In first part, this paper compares the different technique for identification of power system oscillations. Second part analyzes possible identification some power system dynamics behaviors Using Wide Area Monitoring Systems (WAMS) based on Phasor Measurement Units (PMUs) and wavelet technique.

Keywords: Power system oscillations, Modal analysis, Prony, Wavelet, PMU, Wide Area Monitoring System.

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Authors: Breda M. Kiernan, Stephen Beirne, Cormac Fay, Dermot Diamond

Abstract:

An autonomous environmental monitoring system (Smart Landfill) has been constructed for the quantitative measurement of the components of landfill gas found at borehole wells at the perimeter of landfill sites. The main components of landfill gas are the greenhouse gases, methane and carbon dioxide and have been monitored in the range 0-5 % volume. This monitoring system has not only been tested in the laboratory but has been deployed in multiple field trials and the data collected successfully compared with on-site monitors. This success shows the potential of this system for application in environments where reliable gas monitoring is crucial.

Keywords: Environmental monitoring, greenhouse gas, landfill gas, sensor deployment

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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: Omid A. Zargar

Abstract:

Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.

Keywords: Gas turbine, turbine compressor, vibration data collector, utility, condition monitoring, non-contact probe, Relative Vibration, Absolute Vibration, Split Resonance, Time Wave Form (TWF), Fast Fourier transform (FFT).

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Authors: Z. Khan, O. Moselhi, T. Zayed

Abstract:

Development of levels of service in municipal context is a flexible vehicle to assist in performing quality-cost trade-off analysis for municipal services. This trade-off depends on the willingness of a community to pay as well as on the condition of the assets. Community perspective of the performance of an asset from service point of view may be quite different from the municipality perspective of the performance of the same asset from condition point of view. This paper presents a three phased level of service based methodology for water mains that consists of :1)development of an Analytical Hierarchy model of level of service 2) development of Fuzzy Weighted Sum model of water main condition index and 3) deriving a Fuzzy logic based function that maps level of service to asset condition index. This mapping will assist asset managers in quantifying condition improvement requirement to meet service goals and to make more informed decisions on interventions and relayed priorities.

Keywords: Asset Management, Level of Service, Condition Index, Analytical Hierarchy, Fuzzy Logic.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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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: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: Cloud computing, cloud monitoring, performance optimization, high availability.

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Authors: Cem Karacal, Sohyung Cho, William Yu

Abstract:

In metal cutting industries, mathematical/statistical models are typically used to predict tool replacement time. These off-line methods usually result in less than optimum replacement time thereby either wasting resources or causing quality problems. The few online real-time methods proposed use indirect measurement techniques and are prone to similar errors. Our idea is based on identifying the optimal replacement time using an electronic nose to detect the airborne compounds released when the tool wear reaches to a chemical substrate doped into tool material during the fabrication. The study investigates the feasibility of the idea, possible doping materials and methods along with data stream mining techniques for detection and monitoring different phases of tool wear.

Keywords: Tool condition monitoring, cutting tool replacement, data stream mining, e-Nose.

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