基于增材制造(即3D打印)技术制作土压力传感器,在增材制造过程中将布拉格光纤光栅(FBG)传感器嵌入到碳纤维模型内部,成功制备了光纤光栅碳纤维土压力传感器,用于不同条件下的压力监测。对增材制造制备的压力传感器进行系统的标定实验与稳定性测试,结果表明FBG土压力传感器的波长与压力的变化具有良好的线性关系,在100次加载卸载循环实验中,传感器具有良好的稳定性。实验发现,增材制造填充密度与压力传感器的关键测量参数有很强的相关性,当增材制造填充密度分别为20%、40%、60%、80%、100%时,FBG土压力传感器的灵敏度分别为0.69,0.45,0.39,0.21,0.19 pm/kPa。现场测试中,7个不同深度(深度间隔为2 m)的FBG土压力传感器(灵敏度依次为15.38,0.61,0.15,0.76,0.3,0.15,0.13 pm/kPa)均可测出相应的土压力值,并且测量值与理论值相吻合,这反映了所提出的新型传感器在实际运用中的良好性能。将FBG土压力传感器封装到增材制造模型内部,制作而成的土压力传感器摆脱了传统传感器的传感参数调节的不灵活性、易受电磁干扰、较差的环境耐腐蚀性、较复杂的制作流程以及不可避免的装配误差、较长的研发与生产周期等缺点。

We successfully designed and fabricated fiber Bragg grating (FBG) earth pressure sensors based on additive manufacturing (i.e., 3D printing) technology by embedding an FBG in a 3D printing model made of carbon fibers for pressure monitoring under different conditions. The systematic calibration experiment and stability test of the pressure sensor prepared by additive manufacturing are carried out. The results indicate a good linear relationship between the wavelength and the change in the pressure loaded on the sensors and show that the sensors show good stability in the 100 loading-unloading cycle tests. The experimental results also show that there is a strong correlation between the infilling density of additive manufacturing and key measurement parameters of the pressure sensors, and that the infilling densities of 20%, 40%, 60%, 80%, and 100% correspond to the sensitivities of FBG earth pressure sensors of 0.69, 0.45, 0.39, 0.21, and 0.19 pm/kPa, respectively. In the field tests, all the seven FBG earth pressure sensors (with a depth interval of 2 m and the sensitivities of 15.38, 0.61, 0.15, 0.76, 0.3, 0.15, and 0.13 pm/kPa) can measure the earth pressure, which is consistent with the theoretical value, indicating good performance of the proposed pressure sensors in actual applications. In conclusion, the proposed earth pressure sensors with an FBG earth pressure sensor encapsulated inside the additive manufacturing model, overcome the shortcomings such as the inflexibility of parameter adjustment for traditional sensors, being susceptible to electromagnetic interference, poor environmental corrosion resistance, complex manufacturing process, inevitable assembly errors, and long R&D and production cycle.