基于高精度温度传感器的多股碳纤维导线潜伏性缺陷检测方法

为提升多股碳纤维导线的质量，研究基于高精度温度传感器的多股碳纤维导线潜伏性缺陷检测方法。利用布里渊光时域反射技术设计高精度温度传感器，并将单根光纤植入多股碳纤维导线中，通过注入窄谱光源来实现温度采集。采用外差检测法对窄谱光源进行处理，获取多股碳纤维导线的温度采集结果。采用平均处理方法滤除温度数据内部的噪声。基于滤波后的温度数据，建立多股碳纤维导线的温度场逆问题模型，并利用牛顿迭代法对模型进行求解，从而得到多股碳纤维导线的热导率。实验证明，该方法能够有效地采集多股碳纤维导线的温度，并成功滤除99%的内部噪声。检测无缺陷多股碳纤维导线的热导率是235 W/m·k,基于此，该方法也能够根据与无缺陷导线的热导率的差异有效地检测导线的潜伏性缺陷。值得注意的是，当导线的负荷电流增加时，该方法的潜伏性缺陷检测效果更佳。

Method for detecting latent defects in multi strand carbon fiber conductors based on high precision temperature sensors

To improve the quality of multi-strand carbon fiber wires, a method for detecting latent defects in multi strand carbon fiber wires based on high-precision temperature sensors is studied. Design a high-precision temperature sensor using Brillouin optical time-domain reflection technology, and implant a single fiber into multiple carbon fiber wires to achieve temperature collection by injecting a narrow spectral light source. Using heterodyne detection method to process narrow-spectrum light sources and obtain temperature collection results of multi-strand carbon fiber wires. Using an average processing method to filter out internal noise in temperature data. Based on the filtered temperature data, the inverse problem model of the temperature field of the multi strand carbon fiber conductor is established, and the Newton Iterative method is used to solve the model, so as to obtain the thermal conductivity of the multi strand carbon fiber conductor. Experiments have shown that this method can effectively collect the temperature of multiple carbon fiber wires and successfully filter out 99% of internal noise. The thermal conductivity of detecting defect free multi stranded carbon fiber wires is 235 W/m·k. Based on this, this method can also effectively detect latent defects in wires based on the difference in thermal conductivity compared to defect free wires. It is worth noting that the method performs better in detecting latent defects when the load current of the wire increases.