Rapid Detection of BOD Based on PSO-ELM in Complex Water Quality Environment

CHEN Ying; CUI Xing-ning; XIAO chun-yan; ZHANG Jie; ZHANG Can; YANG Hui; LI Shao-hua

doi:10.3969/j.issn.1000-1158.2021.01.17

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Acta Metrologica Sinica ›› 2021, Vol. 42 ›› Issue (1) : 105-110. DOI: 10.3969/j.issn.1000-1158.2021.01.17

Rapid Detection of BOD Based on PSO-ELM in Complex Water Quality Environment

CHEN Ying¹,CUI Xing-ning¹,XIAO chun-yan²,ZHANG Jie¹,ZHANG Can¹,YANG Hui¹,LI Shao-hua³

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Abstract

In order to overcome the shortcoming of complex operation, poor time-efficiency of traditional five-day culture method (BOD5), and the influence of complex environmental factors on the detection process in actual water quality, a detection method of BOD combining the rapid detection system and the extreme learning machine (ELM) algorithm optimized by particle swarm optimization (PSO) was proposed. The detection system was centered on a dissolved oxygen sensor and a microbial membrane reactor, which can perform the test within 35 minutes. The microbial reactor was made of functionalized spiral glass tubes, but the microbial membrane was affected by the environment of water quality. For this reason, PSO-ELM algorithm was used to eliminate the influence of turbidity (SS), pH and REDOX potential (ORP). Compared with BP neural network and ELM algorithm, the running time is shortened by 0.92 s and 0.24 s respectively, and the test error is reduced by 5.3% and 4.0% respectively. In the test of actual seawater samples, the relative error varies from 2.69% to 3.86%.

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metrology / biochemical oxygen demand / rapid measurement / PSO / ELM

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CHEN Ying,CUI Xing-ning,XIAO chun-yan,ZHANG Jie,ZHANG Can,YANG Hui,LI Shao-hua. Rapid Detection of BOD Based on PSO-ELM in Complex Water Quality Environment[J]. Acta Metrologica Sinica. 2021, 42(1): 105-110 https://doi.org/10.3969/j.issn.1000-1158.2021.01.17

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