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Implementation of model-based fault diagnosis systems can be a difficult task due to the complex dynamics of most systems, an appealing alternative to avoiding modeling is to use machine learning-based techniques for which the implementation is more affordable nowadays. However, the latter approach often requires extensive data processing. In this paper, a hybrid approach using recent developments in neural ordinary differential equations is proposed. This approach enables us to combine a natural deep learning technique with an estimated model of the system, making the training simpler and more efficient. For evaluation of this methodology, a nonlinear benchmark system is used by simulation of faults in actuators, sensors, and process. Simulation results show that the proposed methodology requires less processing for the training in comparison with conventional machine learning approaches since the data-set is directly taken from the measurements and inputs. Furthermore, since the model used in the essay is only a structural approximation of the plant; no advanced modeling is required. This approach can also alleviate some pitfalls of training data-series, such as complicated data augmentation methodologies and the necessity for big amounts of data.
Luis Enciso-Salas; Gustavo Pérez-Zuñiga; Javier Sotomayor-Moriano. Fault Diagnosis via Neural Ordinary Differential Equations. Applied Sciences 2021, 11, 3776 .
AMA StyleLuis Enciso-Salas, Gustavo Pérez-Zuñiga, Javier Sotomayor-Moriano. Fault Diagnosis via Neural Ordinary Differential Equations. Applied Sciences. 2021; 11 (9):3776.
Chicago/Turabian StyleLuis Enciso-Salas; Gustavo Pérez-Zuñiga; Javier Sotomayor-Moriano. 2021. "Fault Diagnosis via Neural Ordinary Differential Equations." Applied Sciences 11, no. 9: 3776.
In automated plants, particularly in the petrochemical, energy, and chemical industries, the combined management of all of the incidents that can produce a catastrophic accident is required. In order to do this, an alarm management methodology can be formulated as a discrete event sequence recognition problem, in which time patterns are used to identify the safe condition of the process, especially in the start-up and shutdown stages. In this paper, a new layer of protection (a Super-Alarm), based on the diagnostic stage to industrial processes is presented. The alarms and actions of the standard operating procedures are considered to be discrete events involved in sequences; the diagnostic stage corresponds to the recognition of the situation when these sequences occur. This provides operators with pertinent information about the normal or abnormal situations induced by the flow of the alarms. Chronicles Based Alarm Management (CBAM) is the methodology used in this document to build the chronicles that will permit us to generate the Super-Alarms; in addition, a case study of the petrochemical sector using CBAM is presented in order to build one chronicle that represents the scenario of an abnormal start-up of an oil transport system. Finally, the scenario’s validation for this case is performed, showing the way in which, a Super-Alarm is generated.
John Vásquez; Gustavo Pérez-Zuñiga; Javier Sotomayor-Moriano; Adalberto Ospino. Super-Alarms with Diagnosis Proficiency Used as an Additional Layer of Protection Applied to An Oil Transport System. Entropy 2021, 23, 139 .
AMA StyleJohn Vásquez, Gustavo Pérez-Zuñiga, Javier Sotomayor-Moriano, Adalberto Ospino. Super-Alarms with Diagnosis Proficiency Used as an Additional Layer of Protection Applied to An Oil Transport System. Entropy. 2021; 23 (2):139.
Chicago/Turabian StyleJohn Vásquez; Gustavo Pérez-Zuñiga; Javier Sotomayor-Moriano; Adalberto Ospino. 2021. "Super-Alarms with Diagnosis Proficiency Used as an Additional Layer of Protection Applied to An Oil Transport System." Entropy 23, no. 2: 139.
Currently, the use of industrial seawater reverse osmosis desalination (ISROD) plants has increased in popularity in light of the growing global demand for freshwater. In ISROD plants, any fault in the components of their control systems can lead to a plant malfunction, and this condition can originate safety risks, energy waste, as well as affect the quality of freshwater. This paper addresses the design of a fault detection and isolation (FDI) system based on a structural analysis approach for an ISROD plant located in Lima (Peru). Structural analysis allows obtaining a plant model, which is useful to generate diagnostic tests. Here, diagnostic tests via fault-driven minimal structurally overdetermined (FMSO) sets are computed, and then, binary integer linear programming (BILP) is used to select the FMSO sets that guarantee isolation. Simulations shows that all the faults of interest (sensors and actuators faults) are detected and isolated according to the proposed design.
Gustavo Pérez-Zuñiga; Raul Rivas-Perez; Javier Sotomayor-Moriano; Victor Sánchez-Zurita. Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant. Processes 2020, 8, 1100 .
AMA StyleGustavo Pérez-Zuñiga, Raul Rivas-Perez, Javier Sotomayor-Moriano, Victor Sánchez-Zurita. Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant. Processes. 2020; 8 (9):1100.
Chicago/Turabian StyleGustavo Pérez-Zuñiga; Raul Rivas-Perez; Javier Sotomayor-Moriano; Victor Sánchez-Zurita. 2020. "Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant." Processes 8, no. 9: 1100.
Decomposing is one way to gain efficiency when dealing with large scale systems. In addition, the breakdown into subsystems may be mandatory to reflect some geographic or confidentiality constraints. In this context, the selection of diagnostic tests must comply with decomposition and it is desired to minimize the number of subsystem interconnections while still guaranteeing maximal diagnosability. On the other hand, it should be noticed that there is often some flexibility in the way to decompose a system. By placing itself in the context of structural analysis, this paper provides a solution to the double overlinked problem of choosing the decomposition of the system by leveraging existing flexibility and of selecting the set of diagnostic tests so as to minimize subsystem interconnections while maximizing diagnosability.
Elodie Chanthery; Anna Sztyber; Louise Travé-Massuyès; Gustavo Perez-Zuñiga. Process Decomposition and Test Selection for Distributed Fault Diagnosis. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 914 -925.
AMA StyleElodie Chanthery, Anna Sztyber, Louise Travé-Massuyès, Gustavo Perez-Zuñiga. Process Decomposition and Test Selection for Distributed Fault Diagnosis. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():914-925.
Chicago/Turabian StyleElodie Chanthery; Anna Sztyber; Louise Travé-Massuyès; Gustavo Perez-Zuñiga. 2020. "Process Decomposition and Test Selection for Distributed Fault Diagnosis." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 914-925.
Often industrial variables can be difficult to measure due to such factors as extreme conditions or complex compositions. In such cases, soft sensors have been developed that use available system information and measurements to estimate these difficult-to-obtain variables. In practice, the measurements that are to be estimated by a soft sensor are often infrequently measured or delayed. Occasionally, these sampling times or delays are time varying. At present, most research has considered these parameters to be time invariant, and thus, there is a need to consider the time-varying case. Therefore, this paper will evaluate the impact of time-varying delays and sampling times for the design of a data-driven soft sensor. Modifications will be proposed that will increase the robustness and performance of the soft sensor. The reliability of the estimate will be shown using the Bauer–Premaratne–Durán Theorem. Furthermore, the proposed soft sensor system will be tested using simulations of a continuous stirred tank reactor (CSTR) and an reverse osmosis plant. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate for the CSTR and reverse osmosis plant.
Fritjof Griesing-Scheiwe; Yuri A.W. Shardt; Gustavo Pérez-Zuñiga; Xu Yang. Soft sensor design for variable time delay and variable sampling time. Journal of Process Control 2020, 92, 310 -318.
AMA StyleFritjof Griesing-Scheiwe, Yuri A.W. Shardt, Gustavo Pérez-Zuñiga, Xu Yang. Soft sensor design for variable time delay and variable sampling time. Journal of Process Control. 2020; 92 ():310-318.
Chicago/Turabian StyleFritjof Griesing-Scheiwe; Yuri A.W. Shardt; Gustavo Pérez-Zuñiga; Xu Yang. 2020. "Soft sensor design for variable time delay and variable sampling time." Journal of Process Control 92, no. : 310-318.
Simultaneous occurrences of events have been a crucial and hard problem since the beginning of the research about automaton and simulation theories of discrete event systems, for more than 50 years. This article addresses some diagnosis problems in industrial processes, situations such as simultaneity of events, false positives, and partial recognition of event sequences. V-nets are presented as a means to model dynamic processes without the state machine concept and, the robustness and capability to identify different sequences of discrete events. With the V-nets formalism, it is possible to identify the evolution of the discrete events, simultaneous occurrences of events, partial recognition, counting the number of times that each discrete event occurred in a temporal sequence and this formalism also has the capability to model sequences of sequences. An example of one industrial application is presented and a comparative analysis of the Time Petri Nets, Timed Automata, and Chronicles with the V-nets is exposed.
John William Vásquez Capacho; Carlos Gustavo Perez Zuñiga; Yecid Alfonso Muñoz Maldonado; Adalberto Ospino Castro. Simultaneous occurrences and false-positives analysis in discrete event dynamic systems. Journal of Computational Science 2020, 44, 101162 .
AMA StyleJohn William Vásquez Capacho, Carlos Gustavo Perez Zuñiga, Yecid Alfonso Muñoz Maldonado, Adalberto Ospino Castro. Simultaneous occurrences and false-positives analysis in discrete event dynamic systems. Journal of Computational Science. 2020; 44 ():101162.
Chicago/Turabian StyleJohn William Vásquez Capacho; Carlos Gustavo Perez Zuñiga; Yecid Alfonso Muñoz Maldonado; Adalberto Ospino Castro. 2020. "Simultaneous occurrences and false-positives analysis in discrete event dynamic systems." Journal of Computational Science 44, no. : 101162.
Difficult-to-obtain variables in industrial applications have led to the rise of soft sensors, which use prior system information and measurements to estimate these difficult-to-obtain variables. In real systems, the measurements that need to be estimated by a soft sensor are often infrequently measured or delayed. Sometimes, these delays and sampling time are variable in time. Though there are papers considering soft sensors in the presence of time delays and different sampling times, the variation of those parameters has not been considered when evaluating the adequacy of the soft sensors. Therefore, this paper will evaluate the impact of such variations for a data-driven soft sensor and propose modifications of the soft sensor that increase its robustness. The reliability of its estimate will be shown using the Bauer-Premaratne-Durán Theorem. Furthermore, the soft sensor will be simulated applying it to a continuous stirred tank reactor. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate.
Fritjof Griesing-Scheiwe; Yuri A.W. Shardt; Gustavo Pérez-Zuñiga; Xu Yang. Soft Sensor Design for Restricted Variable Sampling Time. IFAC-PapersOnLine 2020, 53, 80 -85.
AMA StyleFritjof Griesing-Scheiwe, Yuri A.W. Shardt, Gustavo Pérez-Zuñiga, Xu Yang. Soft Sensor Design for Restricted Variable Sampling Time. IFAC-PapersOnLine. 2020; 53 (2):80-85.
Chicago/Turabian StyleFritjof Griesing-Scheiwe; Yuri A.W. Shardt; Gustavo Pérez-Zuñiga; Xu Yang. 2020. "Soft Sensor Design for Restricted Variable Sampling Time." IFAC-PapersOnLine 53, no. 2: 80-85.
Fault detection and isolation (FDI) systems play a key role to provide efficiency, reliability and safety in today’s industrial processes. The teaching of FDI systems is facilitated if it is carried out not only with theoretical lectures but also with practical experiences. This paper proposes a virtual laboratory environment (VLE) to carry out online practical experiences with FDI systems for a benchmark process. Thanks to this VLE, students can set up faults in sensors, actuators or in the process itself, program model-based FDI algorithms and test FDI system performance. The use of this environment is illustrated by testing the performance of FDI systems for the quadruple-tank process (4TP) under different fault scenarios. Finally, the procedure of using this proposal for practical experience with two model-based FDI design methods is shown.
Javier Sotomayor-Moriano; Gustavo Pérez-Zúñiga; Mario Soto; Luis Enciso. Teaching Model-based Fault Detection and Isolation using a Virtual Laboratory Environment. IFAC-PapersOnLine 2020, 53, 17350 -17355.
AMA StyleJavier Sotomayor-Moriano, Gustavo Pérez-Zúñiga, Mario Soto, Luis Enciso. Teaching Model-based Fault Detection and Isolation using a Virtual Laboratory Environment. IFAC-PapersOnLine. 2020; 53 (2):17350-17355.
Chicago/Turabian StyleJavier Sotomayor-Moriano; Gustavo Pérez-Zúñiga; Mario Soto; Luis Enciso. 2020. "Teaching Model-based Fault Detection and Isolation using a Virtual Laboratory Environment." IFAC-PapersOnLine 53, no. 2: 17350-17355.
For the improvement of safety and efficiency, fault diagnosis becomes increasingly important in mining industry. The expansion of flotation processes with high-tonnage cooper concentrators demands the use of large flotation circuits in which the large amount of instrumentation and interconnected subsystems (with coupled measured and non-measured variables) makes this process complex. Moreover, in a flotation process, any equipment failure can lead to a fault condition, which will affect the operation of this process. This paper proposes an approach for on-line fault diagnosis useful for a large flotation circuit based on a distributed architecture. In this approach, structural analysis is used for the design of the distributed fault diagnosis system. Finally, a procedure for the implementation of local diagnosers for on-line operation is presented and illustrated with an application to a flotation process.
C.G. Pérez-Zuñiga; J. Sotomayor-Moriano; E. Chanthery; L. Travé-Massuyès; M. Soto. Flotation Process Fault Diagnosis Via Structural Analysis. IFAC-PapersOnLine 2019, 52, 225 -230.
AMA StyleC.G. Pérez-Zuñiga, J. Sotomayor-Moriano, E. Chanthery, L. Travé-Massuyès, M. Soto. Flotation Process Fault Diagnosis Via Structural Analysis. IFAC-PapersOnLine. 2019; 52 (14):225-230.
Chicago/Turabian StyleC.G. Pérez-Zuñiga; J. Sotomayor-Moriano; E. Chanthery; L. Travé-Massuyès; M. Soto. 2019. "Flotation Process Fault Diagnosis Via Structural Analysis." IFAC-PapersOnLine 52, no. 14: 225-230.
Industrial plants, especially on mining, metal processing, energy and chemical/petrochemical processes require integrated management of all the events that may cause accidents and translate into alarms. Process alarm management can be formulated as an event-based pattern recognition problem in which temporal patterns are used to characterize different typical situations, particularly at startup and shutdown stages. In this paper, a new layer based on a diagnosis process is proposed over the typical layers of protection in industrial processes. Considering the alarms and the actions of the standard operating procedure as discrete events, the diagnosis step relies on situation recognition to provide the operators with relevant information about the failures inducing the alarm flow. The new concept of super alarms is based on a methodology with a diagnosis step that permits generate these types of superior alarms. For example, the Chronicle Based Alarm Management (CBAM) methodology involves different techniques to take the hybrid aspect and the standard operational procedures of the concerned processes into account.
J.W. Vásquez; G. Pérez-Zuñiga; J. Sotomayor-Moriano; Y. Muñoz; A. Ospino. New concept of safeprocess based on a fault detection methodology: Super Alarms. IFAC-PapersOnLine 2019, 52, 231 -236.
AMA StyleJ.W. Vásquez, G. Pérez-Zuñiga, J. Sotomayor-Moriano, Y. Muñoz, A. Ospino. New concept of safeprocess based on a fault detection methodology: Super Alarms. IFAC-PapersOnLine. 2019; 52 (14):231-236.
Chicago/Turabian StyleJ.W. Vásquez; G. Pérez-Zuñiga; J. Sotomayor-Moriano; Y. Muñoz; A. Ospino. 2019. "New concept of safeprocess based on a fault detection methodology: Super Alarms." IFAC-PapersOnLine 52, no. 14: 231-236.
This paper describes the development of a virtual laboratory environment (VLE) that allows students to perform control design practice in a virtual plant from remote locations through a web browser. The proposed VLE facilitates to learn concepts; such as, design of controllers and system identification of multivariable processes using a simulation environment, and an industrial device with a reliable model of a benchmark plant. Architecture of the VLE is explained and evidence of its use is showed. The proposed VLE represents an education tool that is user friendly, wide availability, with graphical interface capabilities and low cost maintenance, that allows to improve student skills by connecting the theory and practice.
Javier Sotomayor-Moriano; Gustavo Pérez-Zúñiga; Mario Soto. A Virtual Laboratory Environment for Control Design of a Multivariable Process. IFAC-PapersOnLine 2019, 52, 15 -20.
AMA StyleJavier Sotomayor-Moriano, Gustavo Pérez-Zúñiga, Mario Soto. A Virtual Laboratory Environment for Control Design of a Multivariable Process. IFAC-PapersOnLine. 2019; 52 (9):15-20.
Chicago/Turabian StyleJavier Sotomayor-Moriano; Gustavo Pérez-Zúñiga; Mario Soto. 2019. "A Virtual Laboratory Environment for Control Design of a Multivariable Process." IFAC-PapersOnLine 52, no. 9: 15-20.
Alex Smith Huaman Loayza; Carlos Gustavo Perez Zuniga. Design of a Fuzzy Sliding Mode Controller for the Autonomous Path-Following of a Quadrotor. IEEE Latin America Transactions 2019, 17, 962 -971.
AMA StyleAlex Smith Huaman Loayza, Carlos Gustavo Perez Zuniga. Design of a Fuzzy Sliding Mode Controller for the Autonomous Path-Following of a Quadrotor. IEEE Latin America Transactions. 2019; 17 (06):962-971.
Chicago/Turabian StyleAlex Smith Huaman Loayza; Carlos Gustavo Perez Zuniga. 2019. "Design of a Fuzzy Sliding Mode Controller for the Autonomous Path-Following of a Quadrotor." IEEE Latin America Transactions 17, no. 06: 962-971.
Centralized fault diagnosis architectures are sometimes prohibitive for large-scale interconnected systems such as distribution systems, telecommunication networks, water distribution networks, fluid power systems. This paper presents a decentralized fault diagnosis method for continuous systems that only requires the knowledge of local models and limited knowledge of their neighboring subsystems. The notion of Fault-Driven Minimal Structurally Overdetermined (FMSO) set is used as the corner stone of the design of residual generators for the design of decentralized fault diagnosis for systems that have constraints of confidentiality, distance or limited access to some information. Binary integer linear programming (BILP) is used to optimize the choice of FMSO sets in each local subsystem.
C.G. Pérez-Zuñiga; E. Chanthery; L. Travé-Massuyès; J. Sotomayor; C. Artigues. Decentralized Diagnosis via Structural Analysis and Integer Programming. IFAC-PapersOnLine 2018, 51, 168 -175.
AMA StyleC.G. Pérez-Zuñiga, E. Chanthery, L. Travé-Massuyès, J. Sotomayor, C. Artigues. Decentralized Diagnosis via Structural Analysis and Integer Programming. IFAC-PapersOnLine. 2018; 51 (24):168-175.
Chicago/Turabian StyleC.G. Pérez-Zuñiga; E. Chanthery; L. Travé-Massuyès; J. Sotomayor; C. Artigues. 2018. "Decentralized Diagnosis via Structural Analysis and Integer Programming." IFAC-PapersOnLine 51, no. 24: 168-175.
Raul Rivas-Perez; J. Sotomayor-Moriano; Gustavo Perez-Zuñiga. Adaptive Expert Generalized Predictive Multivariable Control of Seawater RO Desalination Plant for a Mineral Processing Facility. IFAC-PapersOnLine 2017, 50, 10244 -10249.
AMA StyleRaul Rivas-Perez, J. Sotomayor-Moriano, Gustavo Perez-Zuñiga. Adaptive Expert Generalized Predictive Multivariable Control of Seawater RO Desalination Plant for a Mineral Processing Facility. IFAC-PapersOnLine. 2017; 50 (1):10244-10249.
Chicago/Turabian StyleRaul Rivas-Perez; J. Sotomayor-Moriano; Gustavo Perez-Zuñiga. 2017. "Adaptive Expert Generalized Predictive Multivariable Control of Seawater RO Desalination Plant for a Mineral Processing Facility." IFAC-PapersOnLine 50, no. 1: 10244-10249.
Gustavo Perez-Zuñiga; E. Chanthery; L. Travé-Massuyès; J. Sotomayor. Fault-Driven Structural Diagnosis Approach in a Distributed Context. IFAC-PapersOnLine 2017, 50, 14254 -14259.
AMA StyleGustavo Perez-Zuñiga, E. Chanthery, L. Travé-Massuyès, J. Sotomayor. Fault-Driven Structural Diagnosis Approach in a Distributed Context. IFAC-PapersOnLine. 2017; 50 (1):14254-14259.
Chicago/Turabian StyleGustavo Perez-Zuñiga; E. Chanthery; L. Travé-Massuyès; J. Sotomayor. 2017. "Fault-Driven Structural Diagnosis Approach in a Distributed Context." IFAC-PapersOnLine 50, no. 1: 14254-14259.
In model-based diagnosis (MBD), structural models can provide useful information for fault diagnosis and fault-tolerant control design. In particular, they are known for supporting the design of analytical redundancy relations (ARRs) which are widely used to generate residuals for diagnosis. On the other hand, systems are increasingly complex whereby it is necessary to develop decentralized architectures to perform the diagnosis task. Decentralized diagnosis is of interest for on-board systems as a way to reduce computational costs or for large geographically distributed systems that require to minimizing data transfer. Decentralized solutions allow proper separation of industrial knowledge, provided that inputs and outputs are clearly defined. This paper builds on the results of [1] and proposes an optimized approach for decentralized fault-focused residual generation. It also introduce the concept of Fault-Driven Minimal Structurally-Overdetermined set (FMSO) ensuring minimal redundancy. The method decreases communication cost involved in decentralization with respect to the algorithm proposed in [1] while still maintaining the same isolation properties as the centralized approach as well as the isolation on request capability.
C G Pérez; L Travé-Massuyès; E Chanthery; J Sotomayor. Decentralized diagnosis in a spacecraft attitude determination and control system. Journal of Physics: Conference Series 2015, 659, 012054 .
AMA StyleC G Pérez, L Travé-Massuyès, E Chanthery, J Sotomayor. Decentralized diagnosis in a spacecraft attitude determination and control system. Journal of Physics: Conference Series. 2015; 659 (1):012054.
Chicago/Turabian StyleC G Pérez; L Travé-Massuyès; E Chanthery; J Sotomayor. 2015. "Decentralized diagnosis in a spacecraft attitude determination and control system." Journal of Physics: Conference Series 659, no. 1: 012054.