تعیین محل اصابت صاعقه به کمک روش معکوس زمانی الکترومغناطیسی(EMTR) و یادگیری ماشین
الموضوعات :
عباس همدونی اصلی
1
(دانشكده مهندسی برق دانشگاه بوعلی سینا)
محمدحسن مرادی
2
(دانشكده مهندسی برق، دانشگاه بوعلی سینا)
الکلمات المفتاحية: تعیین محل اصابت صاعقه, تفاضل محدود حوزه زمان, روش معکوس زمانی الکترومغناطیسی, یادگیری ماشین,
ملخص المقالة :
تعیین محل اصابت صاعقه (LLS) از چالش‌های امروزی در حوزه‌های مختلف و به‌ویژه حوزه برق و الکترونیک است. برای تعیین محل اصابت صاعقه، استفاده از روش‌های کلاسیک مرسوم بود؛ ولی اخیراً استفاده از روش معکوس زمانی الکترومغناطیسی (EMTR) نیز رواج یافته است. با توجه به محاسبه شکل موج کامل میدان با استفاده از روش EMTR، دقت در تعیین محل اصابت صاعقه به‌طور قابل توجهی نسبت به روش‌های پیشین افزایش یافته است. در روش معکوس زمانی الکترومغناطیسی به کمک تفاضل محدود حوزه زمان (FDTD)، ابتدا میدان الکترومغناطیسی گذرای تولیدشده توسط کانال صاعقه محاسبه شده و پس از معکوس‌کردن زمانی موج، از محل حسگر یا حسگرها به منبع خود بازانتشار می‌گردد و مجدداً با کمک FDTD، میدان الکترومغناطیسی بازانتشاری در محیط مورد نظر محاسبه می‌شود. با داشتن میدان الکترومغناطیسی محیط با استفاده از معیارهایی مانند حداکثر دامنه میدان، حداکثر انرژی و آنتروپی و ...، محل اصابت صاعقه تعیین می‌گردد. در این مقاله روشی بر اساس ترکیب یادگیری ماشین و EMTR برای تعیین محل اصابت صاعقه پیشنهاد شده است. ابتدا روش تفاضل محدود حوزه زمان سه‌بعدی(D-FDTD3) در محاسبه میدان الکترومغناطیسی محیط به‌کار گرفته شد و با استفاده از EMTR میدان الکترومغناطیسی بازانتشاری مجدداً با کمک (D-FDTD3) در کل محیط محاسبه گردید. بدین طریق داده‌های لازم برای تولید پروفایل‌های سه‌بعدی تصاویر RGB آماده گردید. سپس برای یادگیری ماشین از VGG19، یک شبکه عصبی کانولوشنی (CNN) از پیش آموزش‌دیده، برای استخراج ویژگی‌های تصاویر استفاده شد. در آخر برای تعیین محل اصابت صاعقه، لایه برازش‌کننده‌ای به بالای 19VGG اضافه شد. روش پیشنهادی در MATLAB و Python شبیه‌سازی و اجرا گردید که نتایج، کارایی آن را برای تعیین محل اصابت صاعقه در محیط سه‌بعدی نشان می‌دهند.
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