Optimisation of sensor locations for measurement of flue gas flow in industrial ducts and stacks using neural networks

This paper presents a novel application of neural network modelling in the optimisation of sensor locations for measurement of flue gas flow in industrial ducts and stacks. The neural network model has been validated with experiment based upon a case-study power plant. The results have shown that the optimised sensor location can be determined using this model. The measurement accuracy of the flue gas flow can be significantly improved in the optimised sensor location, resulting in a possible reduction in the manual operation.