The Choice of Sampling Frequency and Optimal Method of Signals Digital Processing in Problems of a Random Loading Process Treating to Assess Durability

• Published in: Inorganic materials Vol. 56; no. 15; pp. 1551 - 1558
• Main Authors: Gadolina, I. V., Lisachenko, N. G., Svirskiy, Y. A., Dubin, D. A.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.12.2020; Springer Nature B.V
• Subjects: Algorithms; Chemistry; Chemistry and Materials Science; Data processing; Durability; Extremum values; Hardware; Industrial Chemistry/Chemical Engineering; Inorganic Chemistry; Level crossings; Materials Science; Mathematical Methods of Investigation; Optimization; Random processes; Reliability analysis; Signal processing; integer arithmetic; Random process of loading; durability; the fatigue of materials; sampling frequency; extrema; quantization of the crossing levels; rain-flow method
• ISSN: 0020-1685; 1608-3172
• DOI: 10.1134/S0020168520150054

Theoretical and practical issues of digital information processing in the problems of load assessment in the evaluation of durability are considered. Due to the specifics of the problem under consideration, in which the precise definition of the extremum values and their sequence is of paramount importance, a number of generally accepted recommendations are unacceptable. For example, the Kotelnikov theorem, which was originally proposed in relation to the problems of estimating the frequency composition of the process, can lead to significant errors. It is shown that the requirements for the analysis of random loading processes for the further purpose of assessing the durability, due to their specificity, are in contradiction with this indication, namely, when choosing a frequency according to this rule, it is very likely to make an error, and not into the safe side. It was also considered the digital filtering of hardware data. Alternative approaches to the selection of extrema of the random process are analyzed: (1) direct hardware selection of extrema and (2) discretization by the method of level crossings. The latter approach has an optimal algorithm for selecting extrema allowing selecting the extremes of the random process with less cost and greater accuracy. The natural transition to integer arithmetic allows to optimize this algorithm even more. The model and real examples demonstrate the gain in terms of speed and memory, which ultimately will help to increase the reliability of the information necessary to assess the durability. The savings in memory and performance will allow longer implementations to be processed, which ultimately allows for a more accurate estimate of the durability at the production stage and for the estimation of the residual life.