Abstract
This paper describes the results of work in the field of failure self-diagnostics for automated systems in real time to increase the efficiency of their operation. We describe the method developed of a diagnosis search formation space by applying to the Expert System Knowledge Base to diagnose failures in automated systems. The input data for the Expert Diagnostic System is a conflicting set of diagnostic codes generated by the automated system over the time interval ∆t during its operation. We proposed mathematical methods to work with a data structure “m-tuples based on ordinary sets of arbitrary cardinality n” to process the input data. We conducted a comparative analysis to estimate the execution time of algorithms for the diagnosis search formation space using sequential access to the Boolean of input data and using the method developed. The analysis showed that the application of the proposed method changes the functional dependency of the execution time estimation of the algorithm in accordance with the number of its input data n from exponential to cubic. The application of the method developed allows us to minimize the time needed to establish the diagnosis to real time. The method presented to diagnose automated systems allows creating methods and algorithms for automatic self-recovery of their operability after reversible failures in real time
Highlights
In recent years, the way people control various kinds of technology has radically changed
Formation of the diagnosis search space using the rules from the Expert System Knowledge Base with partially defined parameters is carried out by finding a complement to the Boolean element 2 X(Dt) for a subset of an ordered basis set of arbitrary cardinality
Discussion of the research results to investigate the effectiveness of the diagnostic method developed by the criterion of the diagnostic time duration
Summary
Dmytra Yavornytskoho ave., 19, Dnipro, Ukraine, 49600 process is taken by automated systems, SCADA (Supervisory Control and Data Acquisition) systems included. The given crucial application fields show that these systems should meet strict requirements to ensure their fault-tolerance and reliability in the process of their work at mission-critical facilities. It is known that most of the failures in the system operation occur due to errors of operational and maintenance personnel who have insufficient qualifications (and/or limited time resources with increased information flow) for supervisory control, quality assistance, and restoration of system operability. The pressing problem is to develop highly reliable and fault-tolerant SCADA systems by improving the methods of their automatic self-diagnostics in real time with the possibility of auto-recovery of their operability after reversible failures
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