Quality indices prediction of onboard radio-electronic devices

DOI: 10.34759/trd-2021-116-05


Bykov A. P.*, Piganov M. N.**

Samara National Research University named after Academician S.P. Korolev, 34, Moskovskoye shosse, Samara, 443086, Russia

*e-mail: bykal@yandex.ru
**e-mail: kipres@ssau.ru


The article presents a technique for developing predictive mathematical models and quality indicators individual forecasting of the spacecraft onboard radio-electronic devices by the results of autonomous tests. For forecasting, Extrapolation method, based on the quasi-deterministic models application, was selected. Transient resistance between electrical circuits of the microprocessor based temperature controller, which installed on the honeycomb panels in the spacecraft unpressurized compartments, was selected as the predictable parameter. The training experiment data, obtained after the second cycle of the testing impacts, served as initial data for the prediction.

The second cycle of tests included checking the device functioning in normal climatic conditions, a low pressure effect test, and a higher humidity effect test. Linear, parabolic, logarithmic, and exponential models were proposed. When these models developing the predictable parameter normalizing by the mathematical expectation was used. The forecast models selection was based on minimum average dispersion criteria, computed at the reference temporal points of tests and minimum values of the erroneous solutions probability and consumer’s risk. The study of the above said models was performed.

Probabilistic characteristics of their efficiency were obtained. It was established that the logarithmic model ensured minimum average dispersion values and the manufacturer’s risk, as well as acceptable erroneous solution probability value, i.e. consumer’s risk minimum value. The parabolic model allows obtaining zero value of the manufacturers risk and acceptable level of erroneous solutions probability.


prediction, quality, radio-electronic device, tests, mathematical model, research, extrapolation


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