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This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors’ sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.
Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring. Sensors 2021, 21, 3581 .
AMA StyleRachid Laref, Etienne Losson, Alexandre Sava, Maryam Siadat. Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring. Sensors. 2021; 21 (11):3581.
Chicago/Turabian StyleRachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. 2021. "Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring." Sensors 21, no. 11: 3581.
The research work presented in this paper proposes a data-driven modeling method for bearings remaining useful life estimation based on Takagi-Sugeno (T-S) fuzzy inference system (FIS). This method allows identifying the parameters of a classic T-S FIS, starting with a small quantity of data. In this work, we used the vibration signals data from a small number of bearings over an entire period of run-to-failure. The FIS model inputs are features extracted from the vibration signals data observed periodically on the training bearings. The number of rules and the input parameters of each rule of the FIS model are identified using the subtractive clustering method. Furthermore, we propose to use the maximum likelihood method of mixture distribution analysis to calculate the parameters of clusters on the time axis and the probability corresponding to rules on degradation stages. Based on this result, we identified the output parameters of each rule using a weighted least square estimation. We then benchmarked the proposed method with some existing methods from the literature, through numerical experiments conducted on available datasets to highlight its effectiveness.
Fei Huang; Alexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. Fuzzy model identification based on mixture distribution analysis for bearings remaining useful life estimation using small training data set. Mechanical Systems and Signal Processing 2020, 148, 107173 .
AMA StyleFei Huang, Alexandre Sava, Kondo Hloindo Adjallah, Zhouhang Wang. Fuzzy model identification based on mixture distribution analysis for bearings remaining useful life estimation using small training data set. Mechanical Systems and Signal Processing. 2020; 148 ():107173.
Chicago/Turabian StyleFei Huang; Alexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. 2020. "Fuzzy model identification based on mixture distribution analysis for bearings remaining useful life estimation using small training data set." Mechanical Systems and Signal Processing 148, no. : 107173.
Real-time detection of early chatter is a vital strategy to improve machining quality and material removal rate in the high-speed milling processes. This paper proposes a maximum entropy (MaxEnt) feature-based reliability model method for real-time detection of early chatter based on multiple sampling per revolution (MSPR) technique and second-order reliability method (SORM). To enhance the detection reliability, the MSPR is used to acquire multiple sets of once-per-revolution sampled data (i.e., MSPR data) and to overcome the shortcoming of the once-per-revolution sampling. The proposed MaxEnt feature-based reliability model method solves the issue of the real-time detection of early chatter while ensuring its reliability. The failure hazard function (FHF) is estimated as a chatter indicator by using the SORM with the MaxEnt feature. The proposed method consists of five steps. First, set the prior parameters. Then collect data by using the MSPR technique. Next, calculate a set of the standard deviation of the data collected as a chatter feature and estimate the chatter indicator FHF by applying the SORM with the MaxEnt feature. Finally, implement the real-time detection of early chatter based on the estimated chatter indicator FHF and the threshold FHF0. The proposed method is applied to the high-speed milling process. Two examples prove that the proposed method can detect two kinds of early chatter: the early-stage of a severe chatter and the slightly intolerable chatter.
Yanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. MaxEnt feature-based reliability model method for real-time detection of early chatter in high-speed milling. ISA Transactions 2020, 113, 39 -51.
AMA StyleYanqing Zhao, Kondo Hloindo Adjallah, Alexandre Sava, Zhouhang Wang. MaxEnt feature-based reliability model method for real-time detection of early chatter in high-speed milling. ISA Transactions. 2020; 113 ():39-51.
Chicago/Turabian StyleYanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. 2020. "MaxEnt feature-based reliability model method for real-time detection of early chatter in high-speed milling." ISA Transactions 113, no. : 39-51.
Condition-based maintenance of rotating mechanics requests efficient bearings degradation monitoring. The accuracy of bearings degradation measure depends largely on degradation indicators. To extract efficient indicators, in this paper we propose a method based on the discarded projected space information and piecewise linear representation (PLR) to build three bearings degradation monitoring indicators which are named SDHT
Fei Huang; Alexandre Sava; Kondo H. Adjallah; Zhouhang Wang. Bearings degradation monitoring indicators based on discarded projected space information and piecewise linear representation. International Journal of Mechatronics and Automation 2020, 7, 23 .
AMA StyleFei Huang, Alexandre Sava, Kondo H. Adjallah, Zhouhang Wang. Bearings degradation monitoring indicators based on discarded projected space information and piecewise linear representation. International Journal of Mechatronics and Automation. 2020; 7 (1):23.
Chicago/Turabian StyleFei Huang; Alexandre Sava; Kondo H. Adjallah; Zhouhang Wang. 2020. "Bearings degradation monitoring indicators based on discarded projected space information and piecewise linear representation." International Journal of Mechatronics and Automation 7, no. 1: 23.
Fei Huang; Alexandre Sava; Kondo H. Adjallah; Zhouhang Wang. Data Piecewise Linear Approximation for Bearings Degradation Monitoring. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2019, 1 .
AMA StyleFei Huang, Alexandre Sava, Kondo H. Adjallah, Zhouhang Wang. Data Piecewise Linear Approximation for Bearings Degradation Monitoring. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2019; ():1.
Chicago/Turabian StyleFei Huang; Alexandre Sava; Kondo H. Adjallah; Zhouhang Wang. 2019. "Data Piecewise Linear Approximation for Bearings Degradation Monitoring." 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) , no. : 1.
Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. Field Evaluation of Low Cost Sensors Array for Air Pollution Monitoring. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2019, 1 .
AMA StyleRachid Laref, Etienne Losson, Alexandre Sava, Maryam Siadat. Field Evaluation of Low Cost Sensors Array for Air Pollution Monitoring. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2019; ():1.
Chicago/Turabian StyleRachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. 2019. "Field Evaluation of Low Cost Sensors Array for Air Pollution Monitoring." 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) , no. : 1.
Yanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. Online Incipient Chatter Detection Based on Once-Per-Revolution Sampling and Dynamic Threshold Variant. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2019, 1 .
AMA StyleYanqing Zhao, Kondo Hloindo Adjallah, Alexandre Sava, Zhouhang Wang. Online Incipient Chatter Detection Based on Once-Per-Revolution Sampling and Dynamic Threshold Variant. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2019; ():1.
Chicago/Turabian StyleYanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. 2019. "Online Incipient Chatter Detection Based on Once-Per-Revolution Sampling and Dynamic Threshold Variant." 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) , no. : 1.
Boudy Bilal; Kondo Hloindo Adjallah; Alexandre Sava. Data-Driven Fault Detection and Identification in Wind Turbines Through Performance Assessment. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2019, 1 .
AMA StyleBoudy Bilal, Kondo Hloindo Adjallah, Alexandre Sava. Data-Driven Fault Detection and Identification in Wind Turbines Through Performance Assessment. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2019; ():1.
Chicago/Turabian StyleBoudy Bilal; Kondo Hloindo Adjallah; Alexandre Sava. 2019. "Data-Driven Fault Detection and Identification in Wind Turbines Through Performance Assessment." 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) , no. : 1.
In high-speed milling process, the early detection of chatter contains two aspects, one is the fast detection of the initial symptom of the chatter, the other is to recognize the slight chatter embedded in the noisy signal. This paper presents an online cumulative chatter detection method for high-speed milling process based on once-per-revolution sampling, maximum entropy (MaxEnt) principle and sequential probability ratio test (SPRT). The method allows for coping with these two aspects of early chatter detection. This method has less computational complexity and is independent of the cutting conditions. The procedure consists of four steps. First, the prior knowledge of early chatter is determined. Secondly, once-per-revolution sampling data is sampled from the vibration signal. Thirdly, the MaxEnt principle is used to estimate the MaxEnt of the once-per-revolution sampling data as a chatter indicator. Finally, the SPRT cumulates the information of the estimated MaxEnt, and then detect the early chatter by using the prior knowledge. The proposed strategy is applied to a high-speed milling process, and two simulation experiments allowed to assess the effectiveness of the early chatter detection method.
Yanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. Early Chatter Detection using MaxEnt and SPRT. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT) 2019, 1550 -1555.
AMA StyleYanqing Zhao, Kondo Hloindo Adjallah, Alexandre Sava, Zhouhang Wang. Early Chatter Detection using MaxEnt and SPRT. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT). 2019; ():1550-1555.
Chicago/Turabian StyleYanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava; Zhouhang Wang. 2019. "Early Chatter Detection using MaxEnt and SPRT." 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT) , no. : 1550-1555.
Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization.
Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring. Sensors 2018, 18, 3716 .
AMA StyleRachid Laref, Etienne Losson, Alexandre Sava, Maryam Siadat. Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring. Sensors. 2018; 18 (11):3716.
Chicago/Turabian StyleRachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. 2018. "Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring." Sensors 18, no. 11: 3716.
This paper investigates the effects of both intermittent wave amplitude and sampling frequency ratio (between sampling frequency and maximum frequency in the signal) on the mode mixing alleviation performance for improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The root relative squared error (RRSE) and the mean absolute error (MAE) are used to evaluate and study the influence of both intermittent wave amplitude and sampling frequency ratio on the mode mixing alleviation performance. The analysis results show that the intermittent wave amplitude and sampling frequency ratio dramatically affect the mode mixing alleviation performance of ICEEMDAN, and that the suitable sampling frequency ratio for alleviating mode mixing varies with the intermittent wave amplitude. The optimal selection of the sampling frequency ratio according to the amplitude of intermittent wave can improve the mode mixing alleviation performance.
Yanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava. Influence study of the intermittent wave amplitude vs. the sampling frequency ratio on ICEEMDAN mode mixing alleviation performance. 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) 2018, 1 -5.
AMA StyleYanqing Zhao, Kondo Hloindo Adjallah, Alexandre Sava. Influence study of the intermittent wave amplitude vs. the sampling frequency ratio on ICEEMDAN mode mixing alleviation performance. 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP). 2018; ():1-5.
Chicago/Turabian StyleYanqing Zhao; Kondo Hloindo Adjallah; Alexandre Sava. 2018. "Influence study of the intermittent wave amplitude vs. the sampling frequency ratio on ICEEMDAN mode mixing alleviation performance." 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) , no. : 1-5.
Condition-based maintenance of rotating mechanics requests efficient bearings degradation monitoring. The accuracy of bearings degradation measure depends largely on degradation indicators. This research aims to extract an indicator which can efficiently characterize the degradation of bearings. To that extent, in this paper we propose a method based on the segmented discarded Hotelling T square (SDHT 2 ) with a piecewise linear representation (PLR) approach. First, we used time domain common features extracted from the bearing vibration signal to roughly describe the bearing degradation. Then, several characteristic values are used to represent the whole historical degradation process by processing the vibration signal based time domain common features through the PLR approach. The SDHT 2 values are used as the characteristic values. The degradation indicator, named (VSDHT 2 ), is a vector where each entry is the discarded Hotelling T square value of a segment. Naturally, the new indicator VSDHT 2 describes the whole degradation process history and also carries the real-time information of bearings degradation. For illustration, a benchmark data set is used in this paper. The results show that the new indicator VSDHT 2 is sensitive and monotonic during the bearings whole lifecycle, which is promising to monitor bearings degradation.
Fei Huang; Alexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. Bearings Degradation Monitoring Indicator Based on Segmented Hotelling T Square and Piecewise Linear Representation. 2018 IEEE International Conference on Mechatronics and Automation (ICMA) 2018, 1389 -1394.
AMA StyleFei Huang, Alexandre Sava, Kondo Hloindo Adjallah, Zhouhang Wang. Bearings Degradation Monitoring Indicator Based on Segmented Hotelling T Square and Piecewise Linear Representation. 2018 IEEE International Conference on Mechatronics and Automation (ICMA). 2018; ():1389-1394.
Chicago/Turabian StyleFei Huang; Alexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. 2018. "Bearings Degradation Monitoring Indicator Based on Segmented Hotelling T Square and Piecewise Linear Representation." 2018 IEEE International Conference on Mechatronics and Automation (ICMA) , no. : 1389-1394.
This paper deals with the prediction of wind turbines power output and proposes an approach to building a prediction model using the Artificial Neural Networks (ANN). The wind speed and output power measured on the site of Sendou, in Senegal, were used to identify the structure of the ANN. Spatiotemporal data on the climatic variables (wind speed, solar radiation, temperature, humidity, wind direction) collected on the same site were used to train the ANN. Data collected on three other sites (Goback, Keur Abdoul Ndoye and Sine Moussa Abdou), located on the northwest coast of Senegal, were used to validate the model and to analyze the influence of the spatial climatic variables on the performance of the model. Results showed the interest of considering climatic variables (wind speed, wind direction, solar radiation, temperature and humidity) as inputs to the ANN for wind turbines output power prediction. Further, this study showed that the prediction of the produced power depends strongly on the characteristics of the sites and the direction of the wind.
B. Bilal; M. Ndongo; Kondo Hloindo Adjallah; A. Sava; C. M. F. Kébé; P. A. Ndiaye; V. Sambou. Wind turbine power output prediction model design based on artificial neural networks and climatic spatiotemporal data. 2018 IEEE International Conference on Industrial Technology (ICIT) 2018, 1085 -1092.
AMA StyleB. Bilal, M. Ndongo, Kondo Hloindo Adjallah, A. Sava, C. M. F. Kébé, P. A. Ndiaye, V. Sambou. Wind turbine power output prediction model design based on artificial neural networks and climatic spatiotemporal data. 2018 IEEE International Conference on Industrial Technology (ICIT). 2018; ():1085-1092.
Chicago/Turabian StyleB. Bilal; M. Ndongo; Kondo Hloindo Adjallah; A. Sava; C. M. F. Kébé; P. A. Ndiaye; V. Sambou. 2018. "Wind turbine power output prediction model design based on artificial neural networks and climatic spatiotemporal data." 2018 IEEE International Conference on Industrial Technology (ICIT) , no. : 1085-1092.
The present paper deals with gas concentration monitoring based on an electronic nose. The proposed approach investigates two regression methods for gas concentration estimation: the first is the most used in gas quantification with electronic nose and known as the partial least squares (PLS) and the second, known as the support vector machine (SVM) regression, is recently used by the electronic nose community. Data used in this work are collected using an E-nose device developed in our laboratory and responding to various concentrations of pine essential oil vapours. The comparison between the two regression methods studied in this paper is related to the accuracy, the universality as well as the number of samples needed for learning. The results are analyzed in order to select the more suitable prediction model for gas concentration estimation.
R. Laref; E. Losson; A. Sava; Kondo Hloindo Adjallah; M. Siadat. A comparison between SVM and PLS for E-nose based gas concentration monitoring. 2018 IEEE International Conference on Industrial Technology (ICIT) 2018, 1335 -1339.
AMA StyleR. Laref, E. Losson, A. Sava, Kondo Hloindo Adjallah, M. Siadat. A comparison between SVM and PLS for E-nose based gas concentration monitoring. 2018 IEEE International Conference on Industrial Technology (ICIT). 2018; ():1335-1339.
Chicago/Turabian StyleR. Laref; E. Losson; A. Sava; Kondo Hloindo Adjallah; M. Siadat. 2018. "A comparison between SVM and PLS for E-nose based gas concentration monitoring." 2018 IEEE International Conference on Industrial Technology (ICIT) , no. : 1335-1339.
This paper addresses the problem of damage monitoring system for buried ductile steel pipeline subject to earthquakes. To determine the capacity of a pipeline to perform its mechanical functions face to occasional or incidental damages, such as earthquakes, it is needed to evaluate the structural integrity of pipe and to track relevant environment parameters. This may be performed through intelligent monitoring system of earthquakes environment. For risk prevention decision support, it is necessary to collect and analyze data to predict the failures and damages, and to provide data. First, we propose a model for the steel pipes structural behavior under earthquake strengths. Simulation result, allowed identifying key parameters to be monitored and to suggest sensors based instrumentation and placement for data collection and risk assessment. Then we suggest an intelligent data acquisition system with a strategy following 3 phases of earthquake impact of buried pipes: damage accumulation, crack initiation and crack propagation. The analysis results of the current study suggest that an intelligent data acquisition system requires intelligent sensors based instrumentation with an appropriate technology for buried ductile steel pipeline subjected to earthquakes. The resulting intelligent instrumentation system requires solving an optimal positioning problem of networked smart wireless sensors, under uncertainties constraints, with self-adaptive and remote monitoring operational capacities.
Anca Coseru; Kondo Hloindo Adjallah; Alexandre Sava; Valentin Zichil; Anca Coseru Tuluca. Characterisation, monitoring and failure risks assesment of buried ductile steel pipeline subject to earthquakes by using wireless sensors. 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2017, 1, 194 -199.
AMA StyleAnca Coseru, Kondo Hloindo Adjallah, Alexandre Sava, Valentin Zichil, Anca Coseru Tuluca. Characterisation, monitoring and failure risks assesment of buried ductile steel pipeline subject to earthquakes by using wireless sensors. 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2017; 1 ():194-199.
Chicago/Turabian StyleAnca Coseru; Kondo Hloindo Adjallah; Alexandre Sava; Valentin Zichil; Anca Coseru Tuluca. 2017. "Characterisation, monitoring and failure risks assesment of buried ductile steel pipeline subject to earthquakes by using wireless sensors." 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 1, no. : 194-199.
To confront the rapid change in manufacturing environments, companies need a Reconfigurable Manufacturing System (RMS) which combines the high production volume of Dedicated Manufacturing Lines (DML) with the large variety of products of Flexible Manufacturing System (FMS). In this paper, we propose a state of art of recent research work on RMS. After highlighting the advantages of RMS compared to existing manufacturing systems, we outline different issues discussed in the context of RMSs and what it brings as solutions. Finally we present the main idea of a new approach for reconfiguration process following a predictive monitoring.
Chiraz Bettaieb; Achraf Jabeur Telmoudi; Alexandre Sava; Lotfi Nabli. Reconfigurable manufacturing system: Overview and proposition of new approach. 2017 International Conference on Control, Automation and Diagnosis (ICCAD) 2017, 534 -539.
AMA StyleChiraz Bettaieb, Achraf Jabeur Telmoudi, Alexandre Sava, Lotfi Nabli. Reconfigurable manufacturing system: Overview and proposition of new approach. 2017 International Conference on Control, Automation and Diagnosis (ICCAD). 2017; ():534-539.
Chicago/Turabian StyleChiraz Bettaieb; Achraf Jabeur Telmoudi; Alexandre Sava; Lotfi Nabli. 2017. "Reconfigurable manufacturing system: Overview and proposition of new approach." 2017 International Conference on Control, Automation and Diagnosis (ICCAD) , no. : 534-539.
The quality of data is recognized to be a key issue for the assets management in enterprises as data is the foundation of any decision making process. Recent research work has established that the quality of data is highly dependent on the knowledge one has on the socio-technical system being considered. Three modes of knowledge have been identified: knowing what, knowing how and knowing why. In this paper we focus on how to manage these modes of knowledge in durable socio-technical systems to enhance the data quality face to technological progress and employees turnover. We believe that an organization based on ISO 9001 international standard can provide a valuable framework to provide the data quality needed to an efficient decision making process. This framework has been applied to design the data quality management system within a high education socio-technical system. The most important benefits that have been noticed are: 1) a shared vision on the external clients of the system with a positive impact on the definition of the strategy and the objectives of the system and 2) a deep understanding of the data client-supplier relationship inside the socio-technical system. A direct consequence of these achievements was the increasing knowledge on “know-what” data to collect, “know-why” to collect that data and “know-how” to collect it.
Alexandre Sava; Kondo Adjallah; Valentin Zichil. ISO 9001 International Standard, a Tool to Enhance Data Quality in Durable Socio-Technical Systems. Applied Mechanics and Materials 2015, 809-810, 1528 -1534.
AMA StyleAlexandre Sava, Kondo Adjallah, Valentin Zichil. ISO 9001 International Standard, a Tool to Enhance Data Quality in Durable Socio-Technical Systems. Applied Mechanics and Materials. 2015; 809-810 ():1528-1534.
Chicago/Turabian StyleAlexandre Sava; Kondo Adjallah; Valentin Zichil. 2015. "ISO 9001 International Standard, a Tool to Enhance Data Quality in Durable Socio-Technical Systems." Applied Mechanics and Materials 809-810, no. : 1528-1534.
Armored steel sheets have various uses in civil and military industry. For the last one, especially in aeronautics, a better determination of the lifetime for the fatigue and shock loaded parts, is a major challenge. Several methods for fatigue calculus are known: safe-life, fail-safe, crack propagation method. All of this methods are not considering in any way the shocks that can accidentally occur, so in the calculation of lifetime, the role of impact multiplier is null. The authors propose a corrected formula for the calculus of the lifetime for 2P armor steel, based on the internal energy developed into the test specimens, through the impact multiplier.
Valentin Zichil; Adrian Judele; Aurelian Albut; Carol Schnakovszky; Alexandre Sava; Petru Lozovanu. Internal Energy Use in Calculating the Lifetime of 2P Armor Steel. Applied Mechanics and Materials 2015, 809-810, 537 -542.
AMA StyleValentin Zichil, Adrian Judele, Aurelian Albut, Carol Schnakovszky, Alexandre Sava, Petru Lozovanu. Internal Energy Use in Calculating the Lifetime of 2P Armor Steel. Applied Mechanics and Materials. 2015; 809-810 ():537-542.
Chicago/Turabian StyleValentin Zichil; Adrian Judele; Aurelian Albut; Carol Schnakovszky; Alexandre Sava; Petru Lozovanu. 2015. "Internal Energy Use in Calculating the Lifetime of 2P Armor Steel." Applied Mechanics and Materials 809-810, no. : 537-542.
The authors propose a methodology to assess the effectiveness of a maintenance strategy on the availability of a serial-parallel multi-physic system, using Monte Carlo simulation embedded in a Petri net model. The systems are composed of heterogenous components that are characterized by specific degradations and failure mechanisms. Building an effective maintenance strategy to improve the availability of such a system requires to monitoring the degradation of each component. We assume that each component is subject to stochastic degradations. Also, we consider that each component might have three health status, according to degradation thresholds, function of the component reliability: “healthy”, “degraded” and “failed”. The health condition of the overall system relies on the health status of each component. A model for tracking the status of each component has been worked out using a colored stochastic Petri net (CSPN). Each health status is modeled by a place within the CSPN model, where each component is modeled by a colored token. The degradation of each component of the system is evaluated based on the Monte Carlo simulation technique. Transition firing regarding a given color model the evolution of the associated component from a health condition to another due to the degradation mechanism or to a maintenance action aimed to restore partially or totally its performance. However, the degradation of each component does not have the same influence on the performance of the overall system. Operational performance indicators are introduced to quantify the influence of each component on the performance of the entire system. Furthermore, maintenance actions are defined taking into account the degradation level of each component, the influence that each component has on the performance of the system and the available repairman. The effectiveness of the maintenance strategy on the system availability is evaluated through simulation.
Alexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. Monte Carlo based Petri net simulation for maintenance strategies assessment in series-parallel-series multi-physic systems. 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2015, 2, 576 -581.
AMA StyleAlexandre Sava, Kondo Hloindo Adjallah, Zhouhang Wang. Monte Carlo based Petri net simulation for maintenance strategies assessment in series-parallel-series multi-physic systems. 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2015; 2 ():576-581.
Chicago/Turabian StyleAlexandre Sava; Kondo Hloindo Adjallah; Zhouhang Wang. 2015. "Monte Carlo based Petri net simulation for maintenance strategies assessment in series-parallel-series multi-physic systems." 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 2, no. : 576-581.
This paper proposes an approach of hybrid Petri nets modeling for hybrid renewable energy production systems structured in micro-grids. This approach is original in the sense that it enables to study the behavior of such systems under various reconfiguration constraints in order to fulfill energy demands for customers. The proposed Petri net model allows to considering the discreet events related to the availability of energy resources or to components' failures in the system as well in the discreet reconfiguration (structural or functional), for control strategies specifications. In addition, an operational research model for cost minimization and availability maximization through reconfiguration is also proposed. The joint implementation of both models should lead to a new approach of design of hybrid renewable energy systems and of their effective cost optimization.
Alexandre Sava; Kondo Hloindo Adjallah; Honore Lagaza. Hybrid Petri nets for modeling and control of multi-source energy conversion systems. 2014 International Conference on Control, Decision and Information Technologies (CoDIT) 2014, 516 -521.
AMA StyleAlexandre Sava, Kondo Hloindo Adjallah, Honore Lagaza. Hybrid Petri nets for modeling and control of multi-source energy conversion systems. 2014 International Conference on Control, Decision and Information Technologies (CoDIT). 2014; ():516-521.
Chicago/Turabian StyleAlexandre Sava; Kondo Hloindo Adjallah; Honore Lagaza. 2014. "Hybrid Petri nets for modeling and control of multi-source energy conversion systems." 2014 International Conference on Control, Decision and Information Technologies (CoDIT) , no. : 516-521.