基于神经网络模型的污水处理过程故障检测方法

2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE) Pub Date : 2017-10-01 DOI:10.1109/ISEEE.2017.8170684

M. Miron, L. Frangu, S. Caraman

{"title":"基于神经网络模型的污水处理过程故障检测方法","authors":"M. Miron, L. Frangu, S. Caraman","doi":"10.1109/ISEEE.2017.8170684","DOIUrl":null,"url":null,"abstract":"In this paper is presented a fault detection method for a biological wastewater treatment process (WWTP) based on residual generation. The residuals were determined by comparing the process model affected by different faults with its neural model. The simulation results demonstrate that this approach is efficient for detecting faults which occurs in biotechnological processes.","PeriodicalId":276733,"journal":{"name":"2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fault detection method for a wastewater treatment process based on a neural model\",\"authors\":\"M. Miron, L. Frangu, S. Caraman\",\"doi\":\"10.1109/ISEEE.2017.8170684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper is presented a fault detection method for a biological wastewater treatment process (WWTP) based on residual generation. The residuals were determined by comparing the process model affected by different faults with its neural model. The simulation results demonstrate that this approach is efficient for detecting faults which occurs in biotechnological processes.\",\"PeriodicalId\":276733,\"journal\":{\"name\":\"2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISEEE.2017.8170684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISEEE.2017.8170684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

提出了一种基于残余生成的生物污水处理过程故障检测方法。通过比较受不同故障影响的过程模型及其神经模型，确定残差。仿真结果表明，该方法对生物工艺过程中的故障检测是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Fault detection method for a wastewater treatment process based on a neural model

In this paper is presented a fault detection method for a biological wastewater treatment process (WWTP) based on residual generation. The residuals were determined by comparing the process model affected by different faults with its neural model. The simulation results demonstrate that this approach is efficient for detecting faults which occurs in biotechnological processes.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)

自引率

0.00%

发文量