Gear Fault Location Detection for Split Torque Gearbox Using AE Sensors
Gear Fault Location Detection for Split Torque Gearbox Using AE Sensors
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DOI：
10.1109/tsmcc.2011.2182609
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
Ruoyu Li;S. Seçkiner;D. He;Eric Bechhoefer;P. Menon
中科院分区：
文献类型：
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作者：
Ruoyu Li;S. Seçkiner;D. He;Eric Bechhoefer;P. Menon
与传统的行星变速箱相比，分力矩变速箱(STG)有可能提供更轻的重量、更高的可靠性和更高的效率。这些好处促使直升机对象交换模型(OEM)开发使用STG的产品。然而，STG的独特结构给如何定位STG中的齿轮故障带来了难题。到目前为止，利用振动和声发射(AE)传感器进行STG故障检测的研究还很有限。本文提出了一种利用声发射传感器进行齿轮故障定位的有效方法。该方法使用小波变换对不同位置的声发射传感器信号进行处理，以确定声发射爆发的到达时间。通过分析声发射爆发的到达时间，可以确定齿轮的故障位置。利用蚁群优化算法对小波的参数进行优化。对一台概念STG进行了实际的播种齿轮故障试验。同时采集齿轮箱不同位置的声发射信号，以确定受损齿轮的位置。实验结果表明了该方法的有效性。
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.