Rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement method and device

Rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement method and device

The invention discloses a rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement method and a rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement device. According to the method, the pH value of inlet water,...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: YUAN PING, LIANG ZHIWEI, CHEN XUANCAI, LUO ANCHENG, CHEN ANYAO, LIN QIANG
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES
MEASURING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
TESTING
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Beschreibung
Zusammenfassung:The invention discloses a rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement method and a rural domestic sewage A2O treatment terminal effluent total nitrogen concentration soft measurement device. According to the method, the pH value of inlet water, the pH value of outlet water, the conductivity of inlet water, the conductivity of outlet water, the turbidity of inlet water, the turbidity of outlet water, the concentration of ammonia nitrogen in inlet water and the concentration of ammonia nitrogen in outlet water are used as input indexes forpredicting the total nitrogen concentration of outlet water, and a BP neural network is used for constructing a correlation model between the input indexes and the total nitrogen concentration of outlet water. Through simulation and verification of the BP neural network model, the result shows that the neural network model established by the invention can quickly and accurately predict the total nitrogen concentration of