基于人工神经网络的反硝化滤池外碳源投加控制
中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第36卷 期数: 2020年第7期 页码: 19-25 栏目: 出版日期: 2020-04-01
- Title:
- External Carbon Source Dosage Control in Denitrification Biofilter Based on Artificial Neural Network
Keywords:- denitrification biofilter; advanced nitrogen removal; external carbon source; artificial neural network
摘要:- 针对反硝化滤池外碳源过量投加导致的出水总碳超标与碳源浪费问题，利用实际污水与小试装置研究了最适外碳源投加量的影响因素，并应用人工神经网络建立了外碳源投加模型与脱氮效果预测模型。结果表明，基于进水总氮负荷与碳氮生化反应计量守恒而进行的外碳源投加可缓解碳源浪费与污染问题，但脱氮效果缺乏稳定性，可考虑通过进水ORP、pH值、DO与温度的综合影响来进行改进。应用自适应学习速率动量梯度下降法建立了输入为5项进水指标、输出为最适投加量的外碳源投加模型，相关系数为0.964 8，表明模型中进水参数与最适投加量具有很好的相关性，外碳源投加模型的改进具有可行性。应用贝叶斯正则化法建立了输入为5项进水指标、输出为NO3- -N与NO2- -N浓度的脱氮效果预测模型，相关系数为0.908 5，表明预测反硝化滤池的脱氮效果具有一定可行性。外碳源投加模型可配合脱氮效果预测模型构建反硝化滤池外碳源投加控制系统，完善污水厂的自动化控制。
Abstract:- Excessive dosage of carbon source in the denitrification biofilter will result in total carbon over set standard in the effluent and waste of carbon source.Therefore, factors influencing the optimal dosage of external carbon source were explored in the laboratory test device feeding actual sewage, and the models of external carbon source dosage and denitrification performance prediction were built by applying artificial neural network.The problem of waste and pollution of carbon source could be alleviated by adding external carbon sources based on the total nitrogen load of influent and the conservation of carbon nitrogen biochemical reaction. However, the denitrification performance was not stable, and it could be improved by the combined effects of ORP, pH, DO and temperature. The adaptive learning rate momentum gradient descent algorithm was used to establish a carbon source dosage model with input of five influent indexes and output of an optimal dosage of external carbon source. The correlation coefficient was 0.964 8,indicating that there was a good correlation between the influent parameters and the optimal carbon dosage and the improvement of the model was feasible. The Bayesian-regularization algorithm was used to establish the denitrification performance prediction model with input of five influent indexes and output of NO3- -N and NO2- -N concentration.The correlation coefficient was 0.908 5, indicating that it was feasible to predict the performance of the denitrification biofilter. The external carbon source dosage control system of denitrification biofilter could be established by cooperation of the carbon source dosage model and the denitrification performance prediction model, in order to improve the automatic control of the sewage treatment plant.
关键词：包括碳源投加的文章如下：
高排放标准下城市污水深度脱氮技术研究 [27－31]1
