Coriolis mass flow meters provide accurate measurement of single-phase flows, typically to 0.2%. However gas-liquid two-phase flow regimes may cause severe operating difficulties as well as measurement errors in these flow meters. As part of the Sensor Validation (SEVA) research at Oxford University a new fully digital coriolis transmitter has been developed which can operate with highly aerated fluids. This paper describes how a neural network has been used to correct the mass flow measurement for two-phase flow effects, based entirely on internally observed parameters, keeping errors to within 2%. The correction strategy has been successfully implemented on-line in the coriolis transmitter. As required by the SEVA philosophy, the quality of the corrected measurement is indicated by the on-line uncertainty provided with each measurement value.

A multichannel spectral surface plasmon resonance (SPR) sensor module which provides self-referencing capability has been designed to inhibit error influences arising from light source instability. The device timely refreshes the light intensity baseline based on periodical scans over several channels. In particular, the scan operation is achieved by changing optical media on the optical path instead of conventional mechanical scanning. Experiments demonstrate that the sensor module achieves a refractive index resolution level up to ∼ 9.3 × 10 − 7 RIU.