齿轮箱是冶金、能源和化工等行业中复杂装备传递运动和动力的核心部件，低速重载等复杂工况导致其关键部件易于发生故障，振动呈现冲击特征微弱、强背景噪声和低频成分受污染严重等特征。时频分析是齿轮箱故障诊断的有效手段，但现有时频分析方法在处理此类故障信号时有一定的局限。本项目针对低速重载齿轮箱的振动特征，拟提出一套崭新的自适应信号时频分析理论——广义自适应谐波分解（GAHD），并重点对其包含的傅里叶自适应模态分解，广义自适应小波分解和广义自适应傅里叶分解等方法的理论进行研究和完善。在此基础上，以精密诊断低速重载齿轮箱故障为目标，提出基于GAHD的时频分析、时-倒频分析、全息希尔伯特谱分析技术和自适应降噪理论，建立GAHD与复杂性理论结合的非线性故障征兆的自适应表示，进一步形成系统和完整的基于GAHD的低速重载齿轮箱故障诊断与剩余寿命预测的新方法，为齿轮箱健康状态预测水平的提高提供理论和技术支撑。

Gearbox is the core component for motion and power transmission of complex equipment in metallurgy, energy and chemical industries. The working conditions such as low speed and heavy load often lead to its key components being prone to failure, consequently, the generated vibration often presents some special characteristics: weak impact, strong background noise and seriously distorted low frequency components. Time-frequency analysis technique is an effective tool for gearbox fault diagnosis, but the existing methodologies have certain limitations and drawbacks in dealing with these fault signals introduced above. Aiming at revealing the weak vibration characteristics of gearbox under low speed and heavy load working conditions and suppressing the consequences induced by background noise and distorted low frequencies, in this project, a novel adaptive time-frequency analysis theory termed generalized Fourier adaptive harmonic decomposition (GAHD) will be proposed, also, special Fourier-based adaptive mode decomposition, generalized adaptive wavelet decomposition and generalized adaptive Fourier decomposition techniques will be further explored and improved. On this basis, aiming at precise fault diagnosis of low speed and heavy load gearbox, the GAHD-based time-frequency analysis, time-quefrency analysis, Holo-Hilbert spectrum analysis and adaptive denoising theory will be developed, as well as the GAHD and complexity theory-based adaptive representation of nonlinear fault symptoms techniques. Furthermore, a new GAHD-based fault diagnosis and residual life prediction methodology will be formed for low speed and heavy load gearbox. The project will provide theoretical foundation and technical support for improving gearbox health prognostics in technology level.