Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation...Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation of equipment. Existing methods for damage perception of planetary gear trains mainly rely on linear vibration analysis. However, these methods based on linear vibration signal analysis face challenges such as rich vibration sources, complex signal coupling and modulation mechanisms, significant influence of transmission paths, and difficulties in separating damage information. This paper proposes a method for separating instantaneous angular speed (IAS) signals for planetary gear fault diagnosis. Firstly, this method obtains encoder pulse signals through a built-in encoder. Based on this, it calculates the IAS signals using the Hilbert transform, and obtains the time-domain synchronous average signal of the IAS of the planetary gear through time-domain synchronous averaging technology, thus realizing the fault diagnosis of the planetary gear train. Experimental results validate the effectiveness of the calculated IAS signals, demonstrating that the time-domain synchronous averaging technology can highlight impact characteristics, effectively separate and extract fault impacts, greatly reduce the testing cost of experiments, and provide an effective tool for the fault diagnosis of planetary gear trains.展开更多
铁道客车轮对上的不平衡质量影响列车运行安全及速度的进一步提升,轮对安装前需要精确检测不平衡质量并进行动平衡处理。本文提出自适应小波消噪、MUSIC(Multiple Signal Classification)谱估计、相关分析法相结合的方法,实现铁道客车...铁道客车轮对上的不平衡质量影响列车运行安全及速度的进一步提升,轮对安装前需要精确检测不平衡质量并进行动平衡处理。本文提出自适应小波消噪、MUSIC(Multiple Signal Classification)谱估计、相关分析法相结合的方法,实现铁道客车轮对动平衡振动信号特征的提取。通过Labview软件与MATLAB混合编程实现软件开发,并搭建铁道客车轮对动平衡测试平台进行实验验证,实验验证结果表明,经过降噪和采样分辨率的控制,可以克服现场噪声及频率干扰问题,提取的信号幅值及相位具有较高的精度,可实现轮对上不平衡质量及位置的准确探测。展开更多
文摘Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation of equipment. Existing methods for damage perception of planetary gear trains mainly rely on linear vibration analysis. However, these methods based on linear vibration signal analysis face challenges such as rich vibration sources, complex signal coupling and modulation mechanisms, significant influence of transmission paths, and difficulties in separating damage information. This paper proposes a method for separating instantaneous angular speed (IAS) signals for planetary gear fault diagnosis. Firstly, this method obtains encoder pulse signals through a built-in encoder. Based on this, it calculates the IAS signals using the Hilbert transform, and obtains the time-domain synchronous average signal of the IAS of the planetary gear through time-domain synchronous averaging technology, thus realizing the fault diagnosis of the planetary gear train. Experimental results validate the effectiveness of the calculated IAS signals, demonstrating that the time-domain synchronous averaging technology can highlight impact characteristics, effectively separate and extract fault impacts, greatly reduce the testing cost of experiments, and provide an effective tool for the fault diagnosis of planetary gear trains.
文摘铁道客车轮对上的不平衡质量影响列车运行安全及速度的进一步提升,轮对安装前需要精确检测不平衡质量并进行动平衡处理。本文提出自适应小波消噪、MUSIC(Multiple Signal Classification)谱估计、相关分析法相结合的方法,实现铁道客车轮对动平衡振动信号特征的提取。通过Labview软件与MATLAB混合编程实现软件开发,并搭建铁道客车轮对动平衡测试平台进行实验验证,实验验证结果表明,经过降噪和采样分辨率的控制,可以克服现场噪声及频率干扰问题,提取的信号幅值及相位具有较高的精度,可实现轮对上不平衡质量及位置的准确探测。
