Abstract：The frequency domain reflectometry (FDR) method using sweep frequency signals is widely used in cable defect monitoring due to its high frequency components in the incident wave and its ability to quickly monitor weak defects. The broadband impedance spectroscopy (BIS) method and reflection coefficient spectrum (RCS) method, developed based on the FDR method, obtain cable characteristic parameters through scanning signal measurement, and can locate local defects in cables with high sensitivity. However, when using FDR to locate defects, spectrum leakage during Fourier transform can result in many "pseudo peaks" on the final localization spectrum. Due to the influence of these "pseudo peaks", it is difficult to accurately identify the position of defect peaks in the localization spectrum, and due to subjective human factors, it is highly likely to lead to misjudgment. At the same time, during on-site testing, the attenuation of the signal will increase with the increase of cable length, resulting in very inconspicuous cable defects during defect detection for some medium and long cables, causing significant economic losses for subsequent repairs. Therefore, the constant false alarm rate (CFAR) method can be introduced for automatic identification of cable defects. It can automatically extract the position and peak value of defects in the positioning spectrum, greatly reducing misjudgments caused by spectrum leakage and subjective human factors, and improving the fault detection rate. Constant False Alarm Rate is a commonly used method in the field of radar target detection. During the process of detecting targets, radar is subject to interference from clutter. The constant false alarm rate detector adaptively changes the detection threshold with changes in the reference unit to achieve CFAR detection of the target. The ultimate goal is to determine whether the object detected by the radar is a target object, which is consistent with our goal of cable defect recognition. What we need is to determine whether the abnormal peak in the positioning spectrum is a defect. Therefore, the CFAR method has a foundation for application. The most basic form of constant false alarm rate is the cell average constant false alarm rate (CA-CFAR), which has a simple algorithm structure and fast calculation speed, and can be effectively applied in cable defect identification. Firstly, in order to reduce the uncertainty of defect measurement caused by signal attenuation effect, a attenuation compensation method is adopted by approximating the attenuation factor with the test frequency and then deconvoluting it in the frequency domain. This effectively weakens the negative impact of excessive signal attenuation during cable propagation. Secondly, in order to reduce the problem of human subjective experience judgment being prone to misjudgment, the dynamic threshold of CFAR is used to extract the location and normalized amplitude information of defects in cables. The dynamic threshold dynamically selects the threshold for defect judgment based on the changes in test signal amplitude, avoiding the shortcomings of human subjective experience judgment. In order to test the effectiveness of this method, tests were conducted on 30 m, 105 m, and 500 m cables in the laboratory, as well as on 1500 m running cables. The test results showed that this method can not only accurately extract defect locations, but also effectively solve the problem of defect masking during CFAR detection.
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2024, Vol. 39 
