Abstract

In practical applications, some special working scenarios need to take into account both narrow space and extreme temperature, which puts more strict requirements on the size and temperature adaptability of the laser triangulation displacement sensor (LTDS). In this paper, a small-size LTDS was developed and the measurement error caused by temperature drift of the sensor was corrected. Firstly, based on direct projection laser triangulation imaging with a reflector unit, a mathematical model of the compact geometry optical structure was established; then, an optimization process of the optical parameters was formulated, and the sensor was assembled. Secondly, a temperature drift error database was built by an extreme temperature experiment, and a general regression neural network model was constructed for error compensation. In addition, root mean square error and execution time were used to evaluate and compare different regression methods. Finally, the experimental results showed that the repeatability accuracy of the proposed sensor was ±2.3 µm, and the temperature linearity was 0.001% F.S. °C−1.

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