Journal
MEASUREMENT
Volume 124, Issue -, Pages 436-446Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2018.01.001
Keywords
Wastewater treatment process; Soft sensor; Chemical Oxygen Demand; Stable learning
Funding
- National Science Foundation of Liaoning Provincial Education Department of China [L2015297]
- National Science Foundation of China [61673199, 61573364]
- Scientific Research Cultivation Fund of Liaoning Shihua University [2016PY-017]
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It is difficult to estimate the water quality of the wastewater treatment process, because the operating conditions are frequently changed. This paper gives an effective adaptive estimation method, which uses Hammerstein with wavelet neural networks, adaptive weighted fusion, and approximate linear dependence (ALD) analysis. Adaptive stable learning algorithm for the local Hammerstein with wavelet neural networks is proposed. A novel synchronous learning of fusion weighs is discussed. On-line calibration of operating centers with ALD improves the estimation accuracy. The experimental results show that the proposed estimation method for the water quality COD (Chemical Oxygen Demand) is satisfied compared with the laboratory results even when the operating conditions are changed frequently.
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