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STFT spectrogram based hybrid evaluation method for rotating machine transient vibration analysis

机译：基于STFT谱图的旋转机瞬态振动分析的混合式评价方法

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摘要

The main purpose of this paper is to represent a methodenabling vibration components to be extracted from a high-resolution Short-Time Fourier-Transformation (STFT) based spectrogram assessed as an image to support transient analysis on rotating machines. Therefore, an improved STFT algorithm was developed to allocate and utilize computational memory more efficiently. The resulting spectrogram was compressed into a grey-scale image without any kind of information loss and was used for further image processing methods to obtain details about the vibration components. Furthermore, differential and moving average predictive tracking algorithms were developed for frequency ridge evaluation in the spectrogram image. For further analysis, the obtained results were transformed back with an inverse transformation method from image-space to time-frequency plane. Moreover, these results are able to be used to estimate the speed of rotation of the machine and to observe the frequency components. The methods were tested and validated with simulated signals and transient measurements on rotating machines. With the combination of vibration signal- and image processing techniques the evaluation time and computational resource requirements are decreased enhancing more efficient and accurate analysis, nevertheless opens the possibility of a real-time condition monitoring based on a basic vibration measurement.
机译：本文的主要目的是表示从高分辨率短时傅里叶变换（STFT）基于高分辨率的傅里叶变换（STFT）的谱图中提取的备用振动分量，评估为图像，以支持旋转机器的瞬态分析。因此，开发了一种改进的STFT算法以更有效地分配和利用计算存储器。将得到的频谱图被压缩成灰度图像，而无需任何类型的信息丢失，并且用于进一步的图像处理方法，以获得有关振动分量的细节。此外，开发了差分和移动平均预测跟踪算法用于频谱图图像中的频率脊评估。为了进一步分析，将获得的结果用从图像空间到时频平面的逆变换方法转换回来。此外，这些结果能够用于估计机器的旋转速度并观察频率分量。测试并验证了旋转机器上的模拟信号和瞬态测量方法。利用振动信号和图像处理技术的组合，评估时间和计算资源要求降低了提高更有效和准确的分析，因此基于基本振动测量开辟了实时条件监控的可能性。

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