TY - JOUR
AU - Volovyk , A. Yu.
AU - Kychak , V. M.
PY - 2021/03/30
Y2 - 2024/05/23
TI - Detection Filter Method in Diagnostic Problems for Linear Dynamic Systems
JF - Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia
JA - RADAP
VL -
IS - 84
SE -
DO - 10.20535/RADAP.2021.84.30-39
UR - https://radap.kpi.ua/radiotechnique/article/view/1646
SP - 30-39
AB - <p>In a presented research paper the problem of synthesis of the fault detection unit and failure occurrence locating in linear discrete dynamic time-invariant systems is considered. The result of synthesis is presented in the form of parallel type structure consisting of two independently functioning Kalman filter. The first of them calculates a system state vector estimation without taking note of faults, and the second - a degenerate type, creates a fault estimations. Linear combination of their exits forms the resulting state vector estimation. Both filters have dimensions smaller dimensions of the tested system and use the split procedure of an error differential signal. Splitting of the error signal is carried out before estimation process unlike Kitanidis filter. It allows to get a certain economy in computing costs, due to introduced restrictions and losses in accuracy. In general the obtained structure is suboptimal. Questions of stability and state vector estimation convergence of a dynamic system are briefly considered. Using of the computing resource of MatLab environment results of a functional methodcheck results are given.The article structure is constructed as follows. At first problem definition is executed and its resolvability from the mathematical point of view is analyzed. The following step is synthesis of the detection unit and localization of multiple faults then the convergence and stability of errors of estimation are analyzed. In final sections results of method operability check are given in the form of illustrative numerical example and the results of the performed research are summed up. In the conceptual plan research makes a generalization the known results for the continuous time systems. </p>
ER -