一种基于机器学习调控的磷石膏固化处理方法
By using machine learning models to predict the formulation of reagents in phosphogypsum treatment, calcium fluorophosphate is generated, which solves the problems of time-consuming, labor-intensive and unstable phosphogypsum treatment in traditional methods. It achieves efficient and stable phosphogypsum solidification and reduces the release of phosphorus and fluoride ions and pH fluctuations.
CN119680996BActive Publication Date: 2026-07-17WENGFU (GRP) CO LTD +2
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WENGFU (GRP) CO LTD
- Filing Date
- 2024-12-04
- Publication Date
- 2026-07-17
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Figure CN119680996B_ABST
Abstract
本发明公开了一种基于机器学习调控的磷石膏固化处理方法，包括将氧化钙、有机分散剂与水添加到磷石膏中，实现磷石膏固化；其中，氧化钙添加量、有机分散剂添加量与水添加量通过以下过程确定：采集磷石膏浸出液样本的参数，包括可溶磷浓度、可溶氟浓度、pH与含水率；将磷石膏浸出液样本的参数输入到磷石膏的参数与投加参数的机器学习模型中，输出投加参数，投加参数包括氧化钙添加量、有机分散剂添加量与水添加量。本发明通过机器学习模型，可以根据不同原料的具体成分，快速调整氧化钙添加量、有机分散剂添加量与水添加量，适应性更强。这种方法不仅提高了处理效果，减少了实验次数和人力投入，通过精确的药剂配方，避免了药剂的过量使用，从而节省了药剂成本。
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