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In comparison with a traditional planetary gearbox, the split torque gearbox (STG) potentially offers lower weight, increased reliability, and improved efficiency. These benefits have driven helicopter object exchange models (OEMs) to develop products using STG. However, the unique structure of the STG creates a problem on how to locate the gear faults in an STG. As of today, only limited research on STG fault detection using vibration and acoustic emission (AE) sensors has been conducted. In this paper, an effective gear fault location detection methodology using AE sensors for STG is presented. The methodology uses wavelet transform to process AE sensor signals at different locations to determine the arrival time of the AE bursts. By analyzing the arrival time of the AE bursts, the gear fault location can be determined. The parameters of the wavelets are optimized by using an ant colony optimization algorithm. Real seeded gear fault experimental tests on a notional STG are conducted. AE signals at different locations of the gearbox with both healthy and damaged output driving gears are collected simultaneously to determine the location of the damaged gear. Experimental results have shown the effectiveness of the presented methodology.