Mostrar el registro sencillo del ítem
dc.contributor.author | Corominas, Lluís | es_ES |
dc.contributor.author | Villez, Kris | es_ES |
dc.contributor.author | Aguado García, Daniel | es_ES |
dc.contributor.author | Rieger, Leiv | es_ES |
dc.contributor.author | Rosén, Christian | es_ES |
dc.contributor.author | Vanrolleghem, Peter A. | es_ES |
dc.date.accessioned | 2013-12-23T10:10:54Z | |
dc.date.issued | 2011-02 | |
dc.identifier.issn | 0006-3592 | |
dc.identifier.uri | http://hdl.handle.net/10251/34668 | |
dc.description.abstract | Several methods to detect faults have been developed in various fields, mainly in chemical and process engineering. However, minimal practical guidelines exist for their selection and application. This work presents an index that allows for evaluating monitoring and diagnosis performance of fault detection methods, which takes into account several characteristics, such as false alarms, false acceptance, and undesirable switching from correct detection to non-detection during a fault event. The usefulness of the index to process engineering is demonstrated first by application to a simple example. Then, it is used to compare five univariate fault detection methods (Shewhart, EWMA, and residuals of EWMA) applied to the simulated results of the Benchmark Simulation Model No. 1 long-term (BSM1_LT). The BSM1_LT, provided by the IWA Task Group on Benchmarking of Control Strategies, is a simulation platform that allows for creating sensor and actuator faults and process disturbances in a wastewater treatment plant. The results from the method comparison using BSM1_LT show better performance to detect a sensor measurement shift for adaptive methods (residuals of EWMA) and when monitoring the actuator signals in a control loop (e.g., airflow). Overall, the proposed index is able to screen fault detection methods. © 2010 Wiley Periodicals, Inc. | es_ES |
dc.description.sponsorship | This research is supported by the Canada Research Chair in Water Quality Modeling and a NSERC Special Research Opportunities grant as part of the Canadian contribution to the European Union 6th framework project NEPTUNE. Lluis Corominas benefits from the postdoctoral fellowship "Beatriu de Pinos" of the Government of Catalonia. The authors would like to thank Ulf Jeppsson for his contribution to the development of the BSM1_LT platform and the evaluation index. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Wiley-Blackwell | es_ES |
dc.relation.ispartof | Biotechnology and Bioengineering | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Activated sludge | es_ES |
dc.subject | Data quality | es_ES |
dc.subject | Mathematical modeling | es_ES |
dc.subject | Monitoring | es_ES |
dc.subject | Process control | es_ES |
dc.subject | Actuator signals | es_ES |
dc.subject | Adaptive methods | es_ES |
dc.subject | Control loop | es_ES |
dc.subject | Control strategies | es_ES |
dc.subject | Detection methods | es_ES |
dc.subject | False acceptance | es_ES |
dc.subject | False alarms | es_ES |
dc.subject | Fault event | es_ES |
dc.subject | Method comparison | es_ES |
dc.subject | Monitoring and diagnosis | es_ES |
dc.subject | Non-detection | es_ES |
dc.subject | Performance evaluation | es_ES |
dc.subject | Practical guidelines | es_ES |
dc.subject | Process disturbances | es_ES |
dc.subject | Sensor and actuators | es_ES |
dc.subject | Sensor measurements | es_ES |
dc.subject | Shewhart | es_ES |
dc.subject | Simulated results | es_ES |
dc.subject | Simulation model | es_ES |
dc.subject | Simulation platform | es_ES |
dc.subject | Task groups | es_ES |
dc.subject | Univariate | es_ES |
dc.subject | Wastewater treatment plants | es_ES |
dc.subject | Wastewater treatment process | es_ES |
dc.subject | Activated sludge process | es_ES |
dc.subject | Actuators | es_ES |
dc.subject | Computer simulation | es_ES |
dc.subject | Fault detection | es_ES |
dc.subject | Process engineering | es_ES |
dc.subject | Sensors | es_ES |
dc.subject | Wastewater | es_ES |
dc.subject | Wastewater treatment | es_ES |
dc.subject | Water treatment plants | es_ES |
dc.subject | Airflow | es_ES |
dc.subject | Article | es_ES |
dc.subject | Engineering | es_ES |
dc.subject | Evaluation | es_ES |
dc.subject | Sensor | es_ES |
dc.subject | Simulation | es_ES |
dc.subject | Waste water management | es_ES |
dc.subject | Waste water treatment plant | es_ES |
dc.subject | Algorithms | es_ES |
dc.subject | Benchmarking | es_ES |
dc.subject | Quality Control | es_ES |
dc.subject | Waste Disposal, Fluid | es_ES |
dc.subject | Water Purification | es_ES |
dc.subject.classification | TECNOLOGIA DEL MEDIO AMBIENTE | es_ES |
dc.title | Performance Evaluation of Fault Detection Methods for Wastewater Treatment Processes | es_ES |
dc.type | Artículo | es_ES |
dc.embargo.lift | 10000-01-01 | |
dc.embargo.terms | forever | es_ES |
dc.identifier.doi | 10.1002/bit.22953 | |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP6/36845/EU/New sustainable concepts and processes for optimization and upgrading municipal wastewater and sludge treatment/NEPTUNE/ | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient | es_ES |
dc.description.bibliographicCitation | Corominas, L.; Villez, K.; Aguado García, D.; Rieger, L.; Rosén, C.; Vanrolleghem, PA. (2011). Performance Evaluation of Fault Detection Methods for Wastewater Treatment Processes. Biotechnology and Bioengineering. 108(2):333-344. doi:10.1002/bit.22953 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://onlinelibrary.wiley.com/doi/10.1002/bit.22953/pdf | es_ES |
dc.description.upvformatpinicio | 333 | es_ES |
dc.description.upvformatpfin | 344 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 108 | es_ES |
dc.description.issue | 2 | es_ES |
dc.relation.senia | 39910 | |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat de Catalunya | es_ES |
dc.contributor.funder | Natural Sciences and Engineering Research Council of Canada | es_ES |
dc.contributor.funder | Social Sciences and Humanities Research Council of Canada | es_ES |
dc.description.references | Aguado, D., & Rosen, C. (2008). Multivariate statistical monitoring of continuous wastewater treatment plants. Engineering Applications of Artificial Intelligence, 21(7), 1080-1091. doi:10.1016/j.engappai.2007.08.004 | es_ES |
dc.description.references | Aguado, D., Ferrer, A., Ferrer, J., & Seco, A. (2007). Multivariate SPC of a sequencing batch reactor for wastewater treatment. Chemometrics and Intelligent Laboratory Systems, 85(1), 82-93. doi:10.1016/j.chemolab.2006.05.003 | es_ES |
dc.description.references | BSM 2009 http://www.benchmarkwwtp.org | es_ES |
dc.description.references | Genovesi, A., Harmand, J., & Steyer, J.-P. (1999). A fuzzy logic based diagnosis system for the on-line supervision of an anaerobic digestor pilot-plant. Biochemical Engineering Journal, 3(3), 171-183. doi:10.1016/s1369-703x(99)00015-7 | es_ES |
dc.description.references | Lee, D. S., & Vanrolleghem, P. A. (2003). Monitoring of a sequencing batch reactor using adaptive multiblock principal component analysis. Biotechnology and Bioengineering, 82(4), 489-497. doi:10.1002/bit.10589 | es_ES |
dc.description.references | Lee, D. S., Park, J. M., & Vanrolleghem, P. A. (2005). Adaptive multiscale principal component analysis for on-line monitoring of a sequencing batch reactor. Journal of Biotechnology, 116(2), 195-210. doi:10.1016/j.jbiotec.2004.10.012 | es_ES |
dc.description.references | Lennox, J., & Rosen, C. (2002). Adaptive multiscale principal components analysis for online monitoring of wastewater treatment. Water Science and Technology, 45(4-5), 227-235. doi:10.2166/wst.2002.0593 | es_ES |
dc.description.references | Rieger, L., Alex, J., Winkler, S., Boehler, M., Thomann, M., & Siegrist, H. (2003). Progress in sensor technology - progress in process control? Part I: Sensor property investigation and classification. Water Science and Technology, 47(2), 103-112. doi:10.2166/wst.2003.0096 | es_ES |
dc.description.references | Rieger, L., Alex, J., Gujer, W., & Siegrist, H. (2006). Modelling of aeration systems at wastewater treatment plants. Water Science and Technology, 53(4-5), 439-447. doi:10.2166/wst.2006.100 | es_ES |
dc.description.references | Rosen, C., & Lennox, J. A. (2001). Multivariate and multiscale monitoring of wastewater treatment operation. Water Research, 35(14), 3402-3410. doi:10.1016/s0043-1354(01)00069-0 | es_ES |
dc.description.references | Rosen, C., Jeppsson, U., & Vanrolleghem, P. A. (2004). Towards a common benchmark for long-term process control and monitoring performance evaluation. Water Science and Technology, 50(11), 41-49. doi:10.2166/wst.2004.0669 | es_ES |
dc.description.references | Rosen, C., Rieger, L., Jeppsson, U., & Vanrolleghem, P. A. (2008). Adding realism to simulated sensors and actuators. Water Science and Technology, 57(3), 337-344. doi:10.2166/wst.2008.130 | es_ES |
dc.description.references | Rosen C Aguado D Comas J Alex J Copp JB Gernaey KV Jeppsson U Pons M-N Steyer J-P Vanrolleghem PA 2008b | es_ES |
dc.description.references | Schraa, O., Tole, B., & Copp, J. B. (2006). Fault detection for control of wastewater treatment plants. Water Science and Technology, 53(4-5), 375-382. doi:10.2166/wst.2006.143 | es_ES |
dc.description.references | Venkatasubramanian, V., Rengaswamy, R., Yin, K., & Kavuri, S. N. (2003). A review of process fault detection and diagnosis. Computers & Chemical Engineering, 27(3), 293-311. doi:10.1016/s0098-1354(02)00160-6 | es_ES |
dc.description.references | Venkatasubramanian, V., Rengaswamy, R., & Kavuri, S. N. (2003). A review of process fault detection and diagnosis. Computers & Chemical Engineering, 27(3), 313-326. doi:10.1016/s0098-1354(02)00161-8 | es_ES |
dc.description.references | Venkatasubramanian, V., Rengaswamy, R., Kavuri, S. N., & Yin, K. (2003). A review of process fault detection and diagnosis. Computers & Chemical Engineering, 27(3), 327-346. doi:10.1016/s0098-1354(02)00162-x | es_ES |
dc.description.references | Villez, K., Ruiz, M., Sin, G., Colomer, J., Rosén, C., & Vanrolleghem, P. A. (2008). Combining multiway principal component analysis (MPCA) and clustering for efficient data mining of historical data sets of SBR processes. Water Science and Technology, 57(10), 1659-1666. doi:10.2166/wst.2008.143 | es_ES |
dc.description.references | Yoo, C. K., Villez, K., Lee, I.-B., Rosén, C., & Vanrolleghem, P. A. (2007). Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor. Biotechnology and Bioengineering, 96(4), 687-701. doi:10.1002/bit.21220 | es_ES |
dc.relation.references | 10.1016/j.engappai.2007.08.004 | es_ES |
dc.relation.references | 10.1016/j.chemolab.2006.05.003 | es_ES |
dc.relation.references | 10.1016/S1369-703X(99)00015-7 | es_ES |
dc.relation.references | 10.1002/bit.10589 | es_ES |
dc.relation.references | 10.1016/j.jbiotec.2004.10.012 | es_ES |
dc.relation.references | 10.2166/wst.2002.0593 | es_ES |
dc.relation.references | 10.2166/wst.2003.0096 | es_ES |
dc.relation.references | 10.2166/wst.2006.100 | es_ES |
dc.relation.references | 10.1016/S0043-1354(01)00069-0 | es_ES |
dc.relation.references | 10.2166/wst.2004.0669 | es_ES |
dc.relation.references | 10.2166/wst.2008.130 | es_ES |
dc.relation.references | 10.2166/wst.2006.143 | es_ES |
dc.relation.references | 10.1016/S0098-1354(02)00160-6 | es_ES |
dc.relation.references | 10.1016/S0098-1354(02)00161-8 | es_ES |
dc.relation.references | 10.1016/S0098-1354(02)00162-X | es_ES |
dc.relation.references | 10.2166/wst.2008.143 | es_ES |
dc.relation.references | 10.1002/bit.21220 | es_ES |