@Article{PortoSouz:2020:DiAlHe,
               author = "Porto, Roberta de Cassia Ferreira and Souza, Marcelo Lopes de 
                         Oliveira e",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "A discussion on algorithms for health monitoring, fault prognosis 
                         and RUL prediction of aerospace and automotive equipment",
              journal = "SAE Technical Papers",
                 year = "2020",
               volume = "2020",
             abstract = "Companies are gradually developing: 1) complex and/or highly 
                         integrated systems including vehicles (as satellites, airplanes, 
                         cars, etc.) or equipment (as computers, cell phones, no breaks, 
                         etc.) to use under 2) increasingly varied or inhospitable 
                         environments, and to survive under 3) increasingly long life 
                         cycles and unavoidable changes in staff \& facilities \& 
                         technologies. The overall decision to use (by time, cost, quality, 
                         of functions, services, etc.) such end systems under 2 require 4) 
                         high Dependability (Reliability, Maintainability, Availability, 
                         Correction, Safety, Security, etc.) of them. The overall survival 
                         in use (by health monitoring, housekeeping, retrofit, upgrade, 
                         etc.) of such end systems under 3 require 5) high Suportability 
                         (Maintainability, Adaptability, Availability, Robustness, etc.) of 
                         them coupled with the support systems. To meet the requirements 
                         and expectations 4 and 5, there is a need to even treat a growing 
                         number of faults, arising from 1, 2 and 3 in components, 
                         equipment, subsystems or systems used. In particular, health 
                         monitoring, fault prognosis and Remaining Useful Life (RUL) 
                         prediction have been used to reach 4 and 5 and treat faults in a 
                         priori but informed manner. Currently, electromechanical and 
                         electrochemical equipment are among the faultiest ones in 
                         aerospace and automotive systems. The faults of these equipment 
                         can cause decreased performance, operational damage and/or even 
                         failures, especially in space systems, since these hardly allow 
                         maintenance. So: This paper presents a discussion on algorithms 
                         for health monitoring, fault prognosis and RUL prediction of 
                         aerospace and automotive equipment. To do that, it: 1) reviews the 
                         literature for health monitoring, fault prognosis and RUL 
                         prediction; selects their usual repertoire of faults; 3) 
                         highlights some algorithms to treat them; 4) discuss their pros 
                         and cons; 5) comment on some cases of electromechanical and 
                         electrochemical equipment reported in the literature. Based on all 
                         of this, we expect to show: 1) the adequacy, difficulties and 
                         uncertainties in testing and validating such algorithms; and 2) 
                         the benefits of health monitoring, fault prognosis and RUL 
                         prediction of aerospace and automotive equipment for: a) analysis 
                         and anticipation of faults; b) improved dependability, 
                         supportability of the respective systems and of the overall 
                         decision to use and survival in use of them; c) assistance in 
                         sustainable mobility.",
                  doi = "10.4271/2019-36-0264",
                  url = "http://dx.doi.org/10.4271/2019-36-0264",
                 issn = "0148-7191",
             language = "en",
        urlaccessdate = "28 abr. 2024"
}