Abstract: Aiming at the defect that the low cost Mini Unmanned Helicopter（MUH） sensors easily fail due to poor stability, a method of fault diagnosis based on phase difference and wavelet packet analysis is proposed. A model of fault diagnosis based on phase difference according to the signal characteristic of MUH sensors is introduced. The estimated phase difference is used to detect faults by correlation analysis. The wavelet threshold denoising method is adopted to process the sampled signals to improve the estimate accuracy of phase difference, and the wavelet packet analysis is applied to isolating the faults. A simulation based on the experimental data is conducted, and the result shows that the method is feasible and effective for MUH sensors fault diagnosis, and the proposed method has been successfully applied in the MUH flight experiments.

Key words: Mini Unmanned Helicopter（MUH）, wavelet threshold denoising, correlation analysis, phase difference, wavelet packet analysis, fault diagnosis

摘要： 针对低成本的微小型无人直升机（MUH）传感器性能不稳定，容易出现故障的缺陷，提出了一种基于相位差和小波包分析相结合的故障诊断方法。根据MUH传感器输出信号的特点，建立了基于相位差的故障诊断模型，利用相关分析法估计相位差进行故障检测，采用小波阈值法对采样信号进行预处理，以提高相位差的估计精度，运用小波包分析进行故障分离。结合实验数据进行仿真，结果表明该方法是一种行之有效的MUH传感器故障诊断方法，已成功应用在某微小型无人直升机的飞行实验中。

关键词: 微小型无人直升机, 小波阈值去噪, 相关分析法, 相位差, 小波包分析, 故障诊断