طرحی جديد برای طبقه‌بندی خودکار اغتشاشات کيفيت توان بر اساس ابزار پردازش سیگنال و یادگیری ماشین
الموضوعات :مهدي حاجيان 1 , اصغر اکبری فرود 2
1 - دانشگاه سمنان
2 - دانشگاه سمنان
الکلمات المفتاحية: مونيتورينگ کیفیت توان تشخیص الگو انتخاب ویژگی تحلیل زمان- فرکانسی تبدیل موجک گسسته تبدیل S هذلولی,
ملخص المقالة :
تشخیص و دسته‌بندی اغتشاشات کیفیت توان یکی از وظایف مهم در حفاظت و نظارت سیستم‌های قدرت امروزی است. در حال حاضر اهمیت اصلی، بهبود روش‌های تشخيص و طبقه‌بندي خودکار شكل موج‌ها به کمک يك الگوريتم مؤثر مي‌باشد. در این مقاله روشی مؤثر برای استخراج ویژگی بر اساس ترکیب تبدیل S هذلولی و موجک ارائه شده است. انتخاب و كاهش ويژگي، موجب كاهش زمان آموزش مي‌گردد و در بیشتر موارد افزايش ميزان دقت در طبقه‌بندي داده‌ها را به همراه دارد. در این مقاله، روشی جديد به نام گرام- اشمیت براي انتخاب ويژگي به کار گرفته شده و همچنین از ساختار طبقه‌بندی کننده مشهور ماشین بردار پشتیبان چندکلاسه استفاده شده است. همچنین پارامتر‌های متغیر این طبقه‌بندی کننده با استفاده از الگوریتم ابتکاری بهينه‌سازي گروهي ذرات، بهینه شده است. 6 اغتشاش منفرد و 2 اغتشاش ترکیبی و همچنین حالت نرمال برای طبقه‌بندی در نظر گرفته شده‌اند. حساسیت روش پیشنهادی تحت شرایط مختلف نویزی با سطوح مختلف سیگنال همراه با نویز بررسی شده است. همچنین با مقایسه نتایج این مقاله با نتایج مقالات دیگر، کارامدی روش پیشنهادی مورد بررسی قرار گرفته است.
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