Application Cases

【Overview】
In this study, the Aigtek ATA-1220E broadband amplifier was used to build an experimental platform for a multi-branch cable fault location system. This method enables precise fault location in multi-branch cables, significantly improving both positioning accuracy and defect fault sensitivity.

Experiment Name: Experiment on Multi-Branch Cable Fault Location System

Research Directions:

• Verification of detection signals with different modulation ratios and pseudo-blind zones

• Preprocessing verification of multi-branch positioning signals

• Verification of multi-branch fault location strategies

• Verification of optimized time-delay estimation algorithms

• Verification of adaptive threshold curve-based localization

• Verification of multi-physics field wave velocity fitting and super-frequency estimation accuracy improvement

Experiment Objective:
This paper uses spread spectrum time-domain reflectometry based on pseudo-random sequences generated by the Mersenne Twister method as the core technology. To address the difficulties and low accuracy of fault location in submarine multi-branch cables, a multi-branch fault detection strategy combining controllable wave-blocking magnetic rings and wireless switches is proposed. Localization accuracy is further improved through reflected signal preprocessing, optimized time-delay estimation algorithms, construction of a multi-physics field wave velocity fitting model, and adaptive threshold curves. Experimental results show that this method achieves precise fault location in multi-branch cables, with significant improvements in both positioning accuracy and defect fault sensitivity.

Testing Equipment:
Power amplifier (Aigtek ATA-1220E), Y-branch cable, host computer, oscilloscope, wireless switch, shielding magnetic ring, signal source, FPGA chip, digital-to-analog conversion module.

Experimental Procedure:
An experimental platform was first built with an FPGA as the main controller, integrating ADC/DAC, power amplifier, and wireless magnetic rings to simulate a Y-shaped multi-branch cable and seawater environment. Subsequently, the detection performance of signals with different modulation ratios was tested for a 200 m open circuit and a 6 m blind-zone fault. The blind-zone localization capability of optimization algorithms such as the PHAT-weighted coherence suppression method was verified. Reflected signals from a 50 m branch and a 100 m defect fault were preprocessed to improve defect fault sensitivity. Faulty branches were accurately distinguished by controlling the magnetic rings on and off. The single-branch and multi-branch fault detection performance of two optimized time-delay algorithms was tested. Finally, the ability of the adaptive threshold curve to identify long-distance faults was verified, along with the improvement in positioning accuracy achieved by multi-physics field wave velocity fitting and super-frequency estimation.

Figure 1: System Control Block Diagram

Figure 2: Experimental Platform

Experimental Results:

1. Different modulation ratios and pseudo-blind zone experiments showed that the optimal detection performance was achieved at a modulation ratio of 0.4. The PHAT-weighted coherence suppression method and the improved SCOT weighting function method enabled direct fault localization within a 3–8 m blind zone, with smaller positioning errors for longer fault distances.

2. Multi-branch positioning signal preprocessing experiments confirmed that the preprocessing method combining mean ratio de-stacking with adaptive threshold-corrected wavelet denoising significantly improved sensitivity to defect faults with changes in characteristic impedance. Defects such as a 50 m branch node and a 99.424 m defect fault were successfully identified.

3. Adaptive threshold curve localization experiments revealed that the adaptive threshold curve could adapt to signal attenuation at different distances, effectively identifying long-distance attenuated faults. Its detection performance was superior to traditional fixed-threshold methods.

4. Multi-physics field wave velocity fitting and super-frequency estimation accuracy improvement experiments demonstrated that multi-physics field wave velocity fitting improved positioning accuracy by approximately 6%. The super-frequency estimation method with 10 samplings further improved positioning accuracy by about 0.3%, with greater improvement observed when more sampling groups were used.

   
   

Figure 3: Multi-Branch Fault Detection Results

Advantages of Aigtek Amplifiers in This Application:

1. Wide bandwidth – Covers the core frequency bands, ensuring signal fidelity.

2. Voltage output – Increases detection range and improves defect sensitivity.

3. Flexible output and fine control – Supports precise fault location in complex multi-branch topologies.

Recommended Product: ATA-1220E Broadband Amplifier

Figure: ATA-1220E Broadband Amplifier Specifications and Parameters