Extending the range of a fibre-optic relative-humidity sensor

A new signal-processing method to extend the linear operational range of an optical-fibre humidity sensor is presented in this study. The sensor is based on a Nafion-crystal violet complex immobilized on a glass substrate. Low-cost plastic optical fibres are employed as light guides to direct light from a tungsten halogen source to the sensor and from the sensor to a CCD-based spectrometer. Generated spectra for varying relative-humidity levels are analysed using artificial neural networks. Sensor measurements at wavelengths corresponding to the red, orange, yellow and NIR LEDs are used for the artificial neural network input. This study has shown that the artificial neural networks successfully extend the linear response range of the fibre-optic relative-humidity sensor from the 40-55% humidity range previously recorded to a nominal range of 40-82%. The use of LED-compatible wavelengths shows that the sensor can be readily adapted for use with low-cost solid-state instrumentation.