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将动态信号处理与模糊数学方法结合起来,正是解决不确定性(随机性和模糊性)并精确认识事物的有效途径。本文介绍了如何对一些信号处理的结果进行转换而得到模糊隶属函数。用实例说明了运用由动态信号处理得到的模糊隶属函数,有效地解决了精密机床杂音质量检验、大型压缩机组和汽轮发电机组运行状态的识别和评价问题,更深刻地反映了事物的属性.
The combination of dynamic signal processing and fuzzy mathematics is an effective way to solve uncertainties (randomness and ambiguity) and accurately recognize things. This article describes how to convert the result of some signal processing to get the fuzzy membership function. An example is given to illustrate the application of fuzzy membership function obtained from dynamic signal processing, which effectively solves the problem of noise quality inspection of precision machine tools, identification and evaluation of operational status of large compressors and steam turbine generators, and more profoundly reflects the properties of things.