Multifractals in technical diagnostics general concept

In general there are three basic tasks of technical diagnostics, i.e. we want to know in what technical state a considered object was in the past (1st), we want to find out what is the state of the object right now (2nd), and finally what it will be in the future, especially a far one (3rd). The paper presents general concept of using multifractals theory to solving the third task mention earlier. The idea of multifractals was introduced by Benoit Mandelbrot who claimed that multifractal model was more reliable type of financial theory than conventional financial models. According to Mandelbrot and other researchers the advantage of multifractal theory consists in better prediction of occurrence of low predictability and large impact phenomenons. And to know beforehand about rising possibility of occurrence of these phenomenons is crucial just because of their large impact to the whole system. Nowadays we can make pretty accurate diagnosis of the technical state of the considered object. However it is based on the assumption that variation of features of diagnostics signals can be modelled by random processes that follow rather “mild” or “slow” pattern of randomness and to be fair this is almost always true. But such approach completely neglects the presence of “wild” randomness and this can lead to the serious failures. In Author’s opinion the idea of a fractal or a multifractal view of risk, ruin and reward in financial theory can be used successfully in the context of technical diagnostics. Perhaps thanks to it will be possible to prevent or to prepare for unknown unknowns, i.e. for occurrence of low predictability and simultaneously very serious failures.