An intelligent diagnosis model of accidents in nuclear power plant

This essay focus on the situation when the operator of the main control room can not handle the accident in time or make wrong judgment under accident condition in nuclear power plant, which may lead to the occurrence of major accidents or even more accidents concurrently. An intelligent fuzzy diagnosis model based on Grey Relational degree is constructed in this paper, by establishing accident-state correlation matrix and accident-state probability matrix, defining the vector of information weights for accident characteristic vector and monitoring result vector with linear transform, using Grey Relation to measure the relevance degree between monitoring result vector and accident characteristic vector, Searching for suspected accidents approaching to real solutions in iterative recursive algorithms, realizing automatic fuzzy diagnosis of multiple accidents. The results of simulation experiments of LOCA accidents indicate that the model and algorithm can diagnose various common accidents accurately and rapidly in complex nuclear power systems, providing strategy for operator’s diagnosis decision.

Il concetto di “diagnosi fuzzy”: una applicazione alla malattia di Anderson-Fabry* / The concept of “fuzzy diagnosis”: an application to the Anderson-Fabry disease

Per garantire un’elevata affidabilità diagnostica, la classificazione tradizionale delle malattie si basa su due criteri fondamentali: la presenza di caratteristiche peculiari che identificano una malattia distinguendola dalle altre e l’individuazione delle cause o della correlazione multifattoriale. Questa concezione si basa su regole che rimandano ai principi della logica classica, la quale, tuttavia, non può considerarsi uno strumento adeguato in medicina. Essa potrebbe rivelarsi uno strumento utile di fronte a quelle manifestazioni della malattia “prototipiche”, ma non per molte patologie che si presentano come fenomeni complessi e incoerenti, ovvero caratterizzati, sul piano eziologico, da un insieme interrelato di possibili cause e fattori scatenanti e, sul piano clinico, da una elevata variabilità individuale. La diagnosi di tali malattie richiede una logica tramite la quale sia possibile categorizzare il mondo degli oggetti reali. L’articolo prende in esame la logica fuzzy come strumento per il ragionamento diagnostico, e in particolar modo i concetti di “fuzzy set” e “diagnosi fuzzy”, anche al fine di verificarne il possibile impiego nella diagnosi di una patologia rara ad eziologia complessa: la malattia di Anderson-Fabry. L’analisi svolta porta a soffermarsi sulla finalità pratica (e non conoscitiva) della diagnosi, che le conferisce una valenza etica. Muovendo da questa prospettiva, l’articolo propone, nell’ultima parte, alcuni criteri etici di orientamento nel complesso bilanciamento che il clinico effettua tra il rischio inerente alla formulazione di una ipotesi diagnostica di “tipo fuzzy” e i benefici per il paziente di una diagnosi precoce, soprattutto in considerazione della disponibilità di trattamenti farmacologici innovativi. ---------- To ensure high diagnostic reliability, the traditional classification of the diseases is based on two fundamental criteria: the presence of peculiar characteristics that identify a disease distinguishing it from the others; and the detection of causes or multifactorial correlation. This idea is based on rules that refer to the principles of classical logic, which however cannot be considered an appropriate tool in medicine. It may prove to be a useful tool in case of “prototypical” manifestations of a disease, but not for a lot of pathologies that appear as complex and inconsistent cases, or characterized (on the etiological plane) by an interrelation between possible causes and trigger factors, and (on the clinical plane) by an high individual variability. The diagnosis of such diseases requires a logic through which it is possible to categorize the world of real objects. The article examines the fuzzy logic as a tool for the diagnostic reasoning, and particularly the “fuzzy set” and “fuzzy diagnosis” concepts, in order to verify its possible use in the diagnosis of a rare disease with complex etiology: the Anderson-Fabry disease. Our analysis underlines the practical (and not theoretical) purpose of the diagnosis, which gives it an ethical value. From this point of view, the article suggests, in the last part, some ethical criteria in the balance carried out by the clinician between the risk concerning the formulation of a “fuzzy” diagnostic hypothesis and the advantages of an early diagnosis for the patients, especially considering the availability of innovative pharmacological treatments.