Abstract: In the process of intelligent construction of coal mine fully mechanized mining face, there are problems with difficult perception of straightness and low measurement accuracy of scraper conveyor. To solve these problems, this paper designs a non twisted uniform multi-point dual core curvature sensor based on fiber optic grating sensing theory. A dynamic model of the scraper conveyor was established, and the angle recursive algorithm was used to establish the relationship between the various middle grooves of the scraper conveyor. Secondly, calibration experiments were conducted on the non twisted multi-point dual core curvature sensor, and the mathematical equation between the wavelength drift and angle change of the fiber optic grating was derived. Finally, a straightness perception experiment was conducted based on the actual working state of the scraper conveyor. The experimental results show that the fitted data of the sensor is highly consistent with the measured data, with a maximum error of no more than 3mm. It can achieve intelligent perception of the curvature of the scraper conveyor in the fully mechanized mining face, providing a new solution for monitoring the straightness of the scraper conveyor.