以熱影像機器視覺為基礎之太陽能光電模組回收分選系統;Solar photovoltaic module recycling and sorting system based on thermal imaging machine vision

NCUIR > Engineering College > Graduate Institute of opto-Mechatronics > Electronic Thesis & Dissertation > Item 987654321/92241

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/92241

Title:	以熱影像機器視覺為基礎之太陽能光電模組回收分選系統;Solar photovoltaic module recycling and sorting system based on thermal imaging machine vision
Authors:	卓憲和;Cho, Hsien-Ho
Contributors:	光機電工程研究所
Keywords:	熱影像機器視覺;太陽能光電模組回收;分選系統;thermal image machine vision technology;solar photovoltaic module recycling;sorting system
Date:	2022-12-28
Issue Date:	2024-09-19 15:26:35 (UTC+8)
Publisher:	國立中央大學
Abstract:	由於全球環保節能減碳的思維逐漸備受重視，使得太陽能光電產業之興起。近幾年政府當局以綠能及非核家園作為施政重點，推動能源轉型計畫，並積極投入太陽能發電之相關基礎建設，因此太陽能光電產業的永續經營及未來發展被各界重視。隨著太陽能光電產業市場需求漸增，勢必產生大量太陽能光電模組廢棄物，而這些廢棄物若不妥善處理並加以回收，將對環境造成影響。因此，多數廠商除了開發回收模組的技術，也研究如何提升這些廢棄材料回收後的應用價值，形成商業模式的可行性。本研究設計了一套以熱影像機器視覺為基礎的太陽能光電模組回收分選系統，將熱裂解處理後之太陽能板透過熱影像與機構控制的系統整合進行分選處理，其主要分選的材料為玻璃與矽基板。回收後的矽基板可以作為在太陽能行業中半導體重複使用，若能有效回收此材料，將會創造出很大的循環經濟利益，而玻璃及其他金屬透過分選技術分別出來，能夠再利用精煉等方式將這些廢棄物有效回收再利用，透過此分選系統達到回收再利用之最佳化。本文所設計之系統是透過機構設計、篩選外力、控制系統及辨識系統的相互整合所完成，並利用硬體及軟體的相互配合以達分選目的。整體實驗步驟為將待分選之晶圓矽基板及玻璃加熱，依據彼此熱傳導係數的不同，吸收熱量速度也不一樣，導致在熱影像畫面中顯示其溫差變化，進而得以分辨。再以影像處理方式，將熱影像儀上玻璃材料進行標註，透過實驗室座標將相關待分選物鎖定並辨識此材料。最後經過機器視覺成功辨識後，得知待分選物位置，再透過檔板的外力作用，將待分選物從所有材料中將其分選出，經過這些程序可將分選回收率達到90%的優良分選回收率。 ;In recent years, all around the world have attached great importance to sustainable development and environmental protection. Therefore, the subject of waste recycling is extremely important. The waste to be recycled in this study is solar photovoltaic modules. According to the International Renewable Energy Agency′s forecast model, the global waste solar panel will reach 910 million metric tons from now to 2050. In this study, a solar photovoltaic module recycling and sorting system based on thermal image machine vision was designed. Integrate the difference of heat absorption and exotherm of the materials to be sorted with thermal imaging technology, complete the identification of solar module materials after thermal cracking, and develop the external force of sorting technology to effectively select and classify silicon substrates and glass, so as to achieve the purpose of sorting. Based on thermal image machine vision technology, a solar photovoltaic module recycling and sorting system was developed. After adjusting the parameters for several times, the measured sorting accuracy can reach up to 90%. In terms of vision, the device can more clearly determine the glass position through machine vision, which is more convenient and more accurate than human eye recognition. In the future, it is hoped that this prototype can be enlarged, and the optical sorting method can be used in practice.
Appears in Collections:	[Graduate Institute of opto-Mechatronics] Electronic Thesis & Dissertation

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