一种采用B样条插值的改进能量算子在电梯电机轴承故障诊断中的应用

摘要:

在电梯系统中，电机是维持电梯运行不可或缺的核心组成部分，它通过将电能转换为机械能来驱动电梯的运行。而轴承作为电梯电机的重要传动件起到了重要的传递作用，但由于其工作环境较为恶劣导致容易损坏，因此对轴承的早期故障检测非常重要。Teager能量算子是一种经典的能量解调方法，专门用于检测损伤轴承振动信号的幅值和频率调制。通过固有幅值解调，从而在频谱中识别故障特征频率。然而，Teager能量算子容易对强烈的噪声和振动干扰敏感。针对传统能量解调算法对强背景噪声较为敏感的不足，本文提出一种改进的能量解调算法。该算法的思想是将B样条理论与传统Teager能量算子方法进行结合，首先B样条对信号进行插值起到滤波作用，然后再利用基于Teager能量算子对插值信号进行转换，最后利用傅里叶变换得到转换信号的能量谱从而揭示故障特征。这种基于B样条插值的能量解调方法不仅保留了传统能量解调算法的优点，如较高的解调精度和优秀的时间分辨率等，并且在强噪声存在的情况下表现更加优秀。仿真和实验结果表明，该方法提高了轴承故障检测的性能，能够在故障退化的早期检测故障。

Abstract:

In the elevator system, the motor is a crucial component, which drives the elevator by converting electrical energy into mechanical energy. Bearings, as vital transmission parts of the motor, are susceptible to damage. Therefore, early detection of bearing faults is imperative. Teager energy operator, as a classic energy demodulation method, is specially employed to detect both the amplitude and frequency modulations of the vibration signals recorded from damaged elements. The fault characteristic frequency is identified in the spectrum of energy-transformed signal through the inherent amplitude demodulation.Aiming at the deficiency of conventional energy demodulation algorithms sensitive to strong background noise, an improved energy demodulation method is proposed in this paper. The main principle of the proposed energy demodulation method is to combine the B-spline theory with the traditional Teager energy operator. First, the proposed method interpolates the signal using the B-spline that acts as a filter and then transforms the interpolated signal using the Teager energy operator. Finally, the Fourier transform is used to obtain the energy spectrum of the transformed signal to reveal the fault characteristics. This improved energy demodulation method based on B-spline interpolation not only retains the advantages of the Teager energy demodulation algorithm, such as high demodulation accuracy and excellent time resolution but also performs better in the presence of strong noise. Simulation and experimental results show that this proposed method improves the performance of bearing fault detection and can detect faults at an early stage of degradation.