Theory and application of parameter self-optimizing intelligent sampling method

Parameter self-optimizing sampling is a method of software synchronization. This paper further investigates correcting parameter self-optimizing on the basis of sampling parameter self-optimizing, analyzes its application in harmonic measuring. Using mountain-climb searching and the algorithms of traversal frequency points, it finds the sampling number N, the alternation T_s. The optimizing sampling parameters make it over 67% within power periods that the synchronous error is zero, and the asynchronous at the remainder are less than 3 T_d (timer resolution of MPU), the sampling precision is to 10^-5 magnitude order. The measurement error of self-optimizing sampling method approaches zero after correcting by k,. (correction parameter), only need consider the calculate error of 10^-6 magnitude order by the quantification effect of k_c word length. In self-optimizing, because no calculation exists during each sampling, the function of auto reloading initial value of microprocessor timer can be used, so it is proper equal interval sampling. In the last part of this paper, an application example in engineering is given, and takes ideas of “softer hardening” to meet real-time requirements.