Tesis
Desarrollo de un prototipo electrónico para analizar la demanda bioquímica de oxígeno en aguas residuales con carga orgánica conocida.
Fecha
2018-03Registro en:
Taday Morocho, Erika Elizabeth; Telenchano Toalombo, Gladys Yolanda. (2018). Desarrollo de un prototipo electrónico para analizar la demanda bioquímica de oxígeno en aguas residuales con carga orgánica conocida. Escuela Superior Politécnica de Chimborazo. Riobamba.
Autor
Taday Morocho, Erika Elizabeth
Telenchano Toalombo, Gladys Yolanda
Resumen
The present work had as an objetive to develop an electronic prototype to analyze the oxygen biochemical demand in residual water with known organic load. Two single microbial fuel cells of simple camera were implemented. Each cell was formed by an anodic and cathodic camera of acrylic in which pre-treated carbon fiber was installed as electrodes separated by cellophane paper as a proton exchange membrane. The enrichment and adaptation phase of the electrochemically active bacteria was carried out in batch mode under a fixed external load of 1000(ohms). Residual water from the overflow of the primary clarifier of the Ucubamba- Cuenca Residual Water Treatment Plant was used as well as mud activated as a bacterial inoculum.Once the biofilm was formed , the cells were fed at a concentration of specific biochemical demand of oxygen (DBO) (60, 100,150 and 200 ppm) up to generation of a stable current followed by inanition up to a current of approximately 0,010 mA. The electric signal generated the fuel oxidation on the anode surface and the reduction of the oxidant in the cathode was processed through an electronic system based on the arduino platform which permitted to determine the organic charge of a residual artificial water (AW). The measurements recorded by the biosensor showed a variation coefficient (CV) of 1,05% to 7,63% much lower than the biosensor DBO above which reached a CV of up to a 12% , it was determined with a reliability of 95% that both methods (device and conventional ) are comparable. These results are hopeful and open the posibility of creating a simple, rapid and reliable system to monitor the water quality, innovating the analysis techniques of the DBO. It is recommended to use sophisticated characterization techniques such as artificial neuron networks to improve the current DBO model.