Documents disponibles écrits par cet auteur

Assessment of charge-air cooler health in diesel engines using nonlinear time series analysis of intake manifold temperature / Alok A. Joshi in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 131 N° 4 (Juillet 2009) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 4 (Juillet 2009) . - 11 p. Titre : Assessment of charge-air cooler health in diesel engines using nonlinear time series analysis of intake manifold temperature Type de document : texte imprimé Auteurs : Alok A. Joshi, Auteur ; Scott James, Auteur ; Peter Meckl, Auteur Année de publication : 2009 Article en page(s) : 11 p. Note générale : dynamic systems Langues : Anglais (eng) Mots-clés : charge-air  cooler;  turbocharged  diesel  engine;  degradation Résumé : Degradation in the cooling effectiveness of a charge-air cooler (CAC) in a medium-duty turbocharged diesel engine has significant impact on engine performance. This degradation lowers the boost pressure and raises the intake manifold temperature. As a result, the engine provides lower horsepower and higher hydrocarbon levels than the rated values. The objective of this research is to monitor the health of the charge-air cooler by analyzing the intake manifold temperature signal. Experiments were performed on a Cummins ISB series turbocharged diesel engine, a 6-cylinder inline configuration with a 5.9 l displacement volume. Air flowing over the cooler was blocked by varying amounts, while various engine temperatures and pressures were monitored at different torque-speed conditions. Similarly, data were acquired without the introduction of any fault in the engine. For the construction of the manifold temperature trajectory vector, average mutual information estimates and a global false nearest neighbor analysis were used to find the optimal time parameter and embedding dimensions, respectively. The prediction of the healthy temperature vector was done by local linear regression using torque, speed, and their interaction as exogenous variables. Analysis of residuals generated by comparing the predicted healthy temperature vector and the observed temperature vector was successful in detecting the degradation of the charge-air cooler. This degradation was quantified by using box plots and probability density functions of residuals generated by comparing intake manifold temperature of healthy and faulty charge-air coolers. The general applicability of the model was demonstrated by successfully diagnosing a fault in the exhaust gas recirculation cooler of a different engine. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26497&di [...] [article] Assessment of charge-air cooler health in diesel engines using nonlinear time series analysis of intake manifold temperature [texte imprimé] / Alok A. Joshi, Auteur ; Scott James, Auteur ; Peter Meckl, Auteur . - 2009 . - 11 p. dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 4 (Juillet 2009) . - 11 p. Mots-clés : charge-air  cooler;  turbocharged  diesel  engine;  degradation Résumé : Degradation in the cooling effectiveness of a charge-air cooler (CAC) in a medium-duty turbocharged diesel engine has significant impact on engine performance. This degradation lowers the boost pressure and raises the intake manifold temperature. As a result, the engine provides lower horsepower and higher hydrocarbon levels than the rated values. The objective of this research is to monitor the health of the charge-air cooler by analyzing the intake manifold temperature signal. Experiments were performed on a Cummins ISB series turbocharged diesel engine, a 6-cylinder inline configuration with a 5.9 l displacement volume. Air flowing over the cooler was blocked by varying amounts, while various engine temperatures and pressures were monitored at different torque-speed conditions. Similarly, data were acquired without the introduction of any fault in the engine. For the construction of the manifold temperature trajectory vector, average mutual information estimates and a global false nearest neighbor analysis were used to find the optimal time parameter and embedding dimensions, respectively. The prediction of the healthy temperature vector was done by local linear regression using torque, speed, and their interaction as exogenous variables. Analysis of residuals generated by comparing the predicted healthy temperature vector and the observed temperature vector was successful in detecting the degradation of the charge-air cooler. This degradation was quantified by using box plots and probability density functions of residuals generated by comparing intake manifold temperature of healthy and faulty charge-air coolers. The general applicability of the model was demonstrated by successfully diagnosing a fault in the exhaust gas recirculation cooler of a different engine. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26497&di [...]

Data-dimensionality reduction using information-theoretic stepwise feature selector / Alok A. Joshi in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 131 N° 4 (Juillet 2009) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 4 (Juillet 2009) . - 05 p. Titre : Data-dimensionality reduction using information-theoretic stepwise feature selector Type de document : texte imprimé Auteurs : Alok A. Joshi, Auteur ; Peter Meckl, Auteur ; Galen King, Auteur Année de publication : 2009 Article en page(s) : 05 p. Note générale : dynamic systems Langues : Anglais (eng) Mots-clés : information-theoretic  stepwise  feature  selector;  diesel  engine Résumé : A novel information-theoretic stepwise feature selector (ITSFS) is designed to reduce the dimension of diesel engine data. This data consist of 43 sensor measurements acquired from diesel engines that are either in a healthy state or in one of seven different fault states. Using ITSFS, the minimum number of sensors from a pool of 43 sensors is selected so that eight states of the engine can be classified with reasonable accuracy. Various classifiers are trained and tested for fault classification accuracy using the field data before and after dimension reduction by ITSFS. The process of dimension reduction and classification is repeated using other existing dimension reduction techniques such as simulated annealing and regression subset selection. The classification accuracies from these techniques are compared with those obtained by data reduced by the proposed feature selector. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26497&di [...] [article] Data-dimensionality reduction using information-theoretic stepwise feature selector [texte imprimé] / Alok A. Joshi, Auteur ; Peter Meckl, Auteur ; Galen King, Auteur . - 2009 . - 05 p. dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 4 (Juillet 2009) . - 05 p. Mots-clés : information-theoretic  stepwise  feature  selector;  diesel  engine Résumé : A novel information-theoretic stepwise feature selector (ITSFS) is designed to reduce the dimension of diesel engine data. This data consist of 43 sensor measurements acquired from diesel engines that are either in a healthy state or in one of seven different fault states. Using ITSFS, the minimum number of sensors from a pool of 43 sensors is selected so that eight states of the engine can be classified with reasonable accuracy. Various classifiers are trained and tested for fault classification accuracy using the field data before and after dimension reduction by ITSFS. The process of dimension reduction and classification is repeated using other existing dimension reduction techniques such as simulated annealing and regression subset selection. The classification accuracies from these techniques are compared with those obtained by data reduced by the proposed feature selector. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26497&di [...]