기계학습을 이용한 의료폐기물 소각로의 COVID-19 전-후 운전특성 분석

• 영문명: Analysis of operation characteristics before and after COVID-19 of medical waste incinerator using machine learning
• 발행기관: 한국환경에너지공학회
• 저자명: 손권 윤진한 이정규 홍원석
• 간행물 정보: 『환경에너지공학』제19권 제1호, 27~38쪽, 전체 12쪽
• 주제분류: 공학 > 환경공학
• 파일형태: PDF
• 발행일자: 2024.07.31

국문 초록

In Korea, medical waste is placed in special containers and disposed of separately, and it is impossible to open it or analyze its calorific value before incineration. Due to these characteristics, difficulties are arising in the operation of incinerators exclusively for medical waste due to the characteristics of incinerators whose operating conditions are determined based on the calorific value of the waste. In addition, since incinerators require continuous optimization of operating conditions as equipment ages, operation optimization through prediction of operating conditions is necessary. In this study, the incinerator operation characteristics were analyzed using a Neural Network machine learning model using TMS data from a 20-ton/day commercial medical waste incinerator. In order to exclude abnormal operation conditions such as during the overhaul period, operation data was acquired at points where the combustion chamber temperature was above 850℃, and after learning this, correlation analysis between variables and accuracy of prediction data were analyzed. As a result of this study, it was confirmed that after COVID-19, a strong correlation occurred between variables related to combustion conditions (O2, exhaust gas flow rate, combustion chamber temperature, and combustion exhaust gas flow rate) that were not observed before COVID-19. In the before and after COVID-19 variable prediction results, it was confirmed that the exhaust gas flowrate prediction interval was expanded and the O2 concentration cluster formation trend changed significantly. In summary, it was confirmed that significant changes in incinerator operation characteristics occurred before and after the COVID-19 pandemic due to the high calorific value of COVID-19 medical waste and the same-day-discharge same-day incineration principle.

목차

1. 서론

2. 기계학습 알고리즘 설계

3. 의료폐기물 소각로의 COVID-19 전-후 운전특성 변화

4. 결론

키워드

Medical Waste Incinerator COVID-19 Machine Learning