A novel optical fiber displacement sensor of wider measurement range based on neural network

Abstract

By studying on the output characteristics of random type optical fiber sensor and semicircular type optical fiber sensor, the ratio of the two output signals was used as the output signal of the whole system. Then the measurement range was enlarged, the linearity was improved, and the errors of reflective and absorbent changing of target surface are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network(ANN) is set up. So the intrinsic errors such as effects of fluctuations in the light, circuit excursion, the intensity losses in the fiber lines and the additional losses in the receiving fiber caused by bends are eliminated. By discussing in theory and experiment, the error of nonlinear is 2.9%, the measuring range reaches to 5-6mm and the relative accuracy is 2%.And this sensor has such characteristics as no electromagnetic interference, simple construction, high sensitivity, good accuracy and stability. Also the multi-point sensor system can be used to on-line and non-touch monitor in working locales.