Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303
With the development of the coal mine industry, the treatment of domestic sewage in coal mines has become an essential topic of environmental protection. Traditional sewage treatment methods have problems such as low efficiency and complicated management, and it is challenging to meet the increasing...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | Environmental Research Communications |
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| Online Access: | https://doi.org/10.1088/2515-7620/adc4b5 |
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| _version_ | 1849698897656545280 |
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| author | Quan Peng Zhenjiang Qiao Genhu Zhang Hui Su Shengfu Mi Xiaoying Lv |
| author_facet | Quan Peng Zhenjiang Qiao Genhu Zhang Hui Su Shengfu Mi Xiaoying Lv |
| author_sort | Quan Peng |
| collection | DOAJ |
| description | With the development of the coal mine industry, the treatment of domestic sewage in coal mines has become an essential topic of environmental protection. Traditional sewage treatment methods have problems such as low efficiency and complicated management, and it is challenging to meet the increasingly strict environmental protection requirements. Therefore, the research of intelligent dosing and control systems becomes necessary. Based on the STM32F303 microcontroller, this study designs and implements an intelligent dosing and control analysis system for coal mine domestic sewage. The system monitors critical parameters such as pH value, turbidity, and dissolved oxygen in sewage in real time and adopts a fuzzy control algorithm and Proportional-Integral-Derivative Control Algorithm (PID) control strategy to realize intelligent adjustment of the dosing process. Through experimental verification, the system can effectively reduce Chemical Oxygen Demand (COD) and Biochemical Oxygen Demand (BOD) in sewage under different pollution load conditions, improve treatment efficiency, and ensure the sewage effluent quality meets the national discharge standard. The experimental data show that the control error of the system is less than ±2%, the dosing accuracy is more than 10% higher than that of the traditional system, the degree of automation is significantly improved, and the operation is convenient. |
| format | Article |
| id | doaj-art-36d6e6582eea4e43b792d53534737d4d |
| institution | DOAJ |
| issn | 2515-7620 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Communications |
| spelling | doaj-art-36d6e6582eea4e43b792d53534737d4d2025-08-20T03:18:46ZengIOP PublishingEnvironmental Research Communications2515-76202025-01-017404502210.1088/2515-7620/adc4b5Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303Quan Peng0Zhenjiang Qiao1Genhu Zhang2Hui Su3Shengfu Mi4Xiaoying Lv5https://orcid.org/0009-0008-5337-0239CHN Energy Shendong Coal Group Co., Ltd, Ordos Inner Mongolia 017209, People’s Republic of ChinaCHN Energy Shendong Coal Group Co., Ltd, Ordos Inner Mongolia 017209, People’s Republic of ChinaCHN Energy Shendong Coal Group Co., Ltd, Ordos Inner Mongolia 017209, People’s Republic of ChinaCHN Energy Shendong Coal Group Co., Ltd, Ordos Inner Mongolia 017209, People’s Republic of ChinaCHN Energy Shendong Coal Group Co., Ltd, Ordos Inner Mongolia 017209, People’s Republic of ChinaZhejiang Dingsheng Environmental Protection Technology Co., Ltd, Hangzhou Zhejiang 310051, People’s Republic of ChinaWith the development of the coal mine industry, the treatment of domestic sewage in coal mines has become an essential topic of environmental protection. Traditional sewage treatment methods have problems such as low efficiency and complicated management, and it is challenging to meet the increasingly strict environmental protection requirements. Therefore, the research of intelligent dosing and control systems becomes necessary. Based on the STM32F303 microcontroller, this study designs and implements an intelligent dosing and control analysis system for coal mine domestic sewage. The system monitors critical parameters such as pH value, turbidity, and dissolved oxygen in sewage in real time and adopts a fuzzy control algorithm and Proportional-Integral-Derivative Control Algorithm (PID) control strategy to realize intelligent adjustment of the dosing process. Through experimental verification, the system can effectively reduce Chemical Oxygen Demand (COD) and Biochemical Oxygen Demand (BOD) in sewage under different pollution load conditions, improve treatment efficiency, and ensure the sewage effluent quality meets the national discharge standard. The experimental data show that the control error of the system is less than ±2%, the dosing accuracy is more than 10% higher than that of the traditional system, the degree of automation is significantly improved, and the operation is convenient.https://doi.org/10.1088/2515-7620/adc4b5coal mine domestic sewagesmart dosingSTM32F303sewage treatment system |
| spellingShingle | Quan Peng Zhenjiang Qiao Genhu Zhang Hui Su Shengfu Mi Xiaoying Lv Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 Environmental Research Communications coal mine domestic sewage smart dosing STM32F303 sewage treatment system |
| title | Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 |
| title_full | Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 |
| title_fullStr | Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 |
| title_full_unstemmed | Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 |
| title_short | Intelligent dosing and control analysis system for coal mine domestic sewage based on STM32F303 |
| title_sort | intelligent dosing and control analysis system for coal mine domestic sewage based on stm32f303 |
| topic | coal mine domestic sewage smart dosing STM32F303 sewage treatment system |
| url | https://doi.org/10.1088/2515-7620/adc4b5 |
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