کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1891468 1533648 2015 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Reduced fractal model for quantitative analysis of averaged micromotions in mesoscale: Characterization of blow-like signals
ترجمه فارسی عنوان
مدل فراکتال کاهش یافته برای تجزیه کمی میکروموتورهای میانگین در مقیاس مسی: مشخص کردن سیگنال های مشابه
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم فیزیک آماری و غیرخطی
چکیده انگلیسی


• A new approach describes fractal-branched systems with long-range fluctuations.
• A reduced fractal model is proposed.
• The approach is used to characterize blow-like signals.
• The approach is tested on data from different fields.

It has been shown that many micromotions in the mesoscale region are averaged in accordance with their self-similar (geometrical/dynamical) structure. This distinctive feature helps to reduce a wide set of different micromotions describing relaxation/exchange processes to an averaged collective motion, expressed mathematically in a rather general form. This reduction opens new perspectives in description of different blow-like signals (BLS) in many complex systems. The main characteristic of these signals is a finite duration also when the generalized reduced function is used for their quantitative fitting. As an example, we describe quantitatively available signals that are generated by bronchial asthmatic people, songs by queen bees, and car engine valves operating in the idling regime.We develop a special treatment procedure based on the eigen-coordinates (ECs) method that allows to justify the generalized reduced fractal model (RFM) for description of BLS that can propagate in different complex systems. The obtained describing function is based on the self-similar properties of the different considered micromotions. This kind of cooperative model is proposed here for the first time. In spite of the fact that the nature of the dynamic processes that take place in fractal structure on a mesoscale level is not well understood, the parameters of the RFM fitting function can be used for construction of calibration curves, affected by various external/random factors. Then, the calculated set of the fitting parameters of these calibration curves can characterize BLS of different complex systems affected by those factors. Though the method to construct and analyze the calibration curves goes beyond the scope of this paper, this result could benefit future studies that will employ the developed reduced models in diagnosis, prevention, and control of unpredicted and undesired phenomena of some engineering applications that possibly exhibit such BLS.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chaos, Solitons & Fractals - Volume 76, July 2015, Pages 166–181
نویسندگان
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