A tacholess order tracking method based on the STFTSC algorithm for rotor unbalance fault diagnosis under variable-speed conditions

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Binyun Wu, Liang Hou, Shaojie Wang, Xiaozhen Lian
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引用次数: 0

Abstract

Abstract Due to the fact that rotors usually operate in a non-stationary mode with changing speeds, the conventional rotor unbalance detection method based on the stationary signal will produce a major “spectrum ambiguity issue” and affect the accuracy of rotor unbalance detection. To this end, a tacholess order tracking method based on the STFTSC algorithm is suggested in this study, where the STFTSC algorithm is developed by combining the short-time Fourier transform and the seam carving algorithm. Firstly, the STFTSC algorithm is utilized to accurately extract the instantaneous frequency (IF) of the rotor and calculate the instantaneous phase under variable-speed conditions. Subsequently, the original signal is resampled in the angular domain to transform the non-stationary time domain signal into a stable angle domain signal, eliminating the effect of the speed variations. Finally, the angular domain signal is transformed into the order domain signal, which uses the discrete Fourier transform and the discrete spectrum correction method to identify the amplitude and phase corresponding to the fundamental frequency component of the signal. The simulation results show that the IF extracted by the STFTSC algorithm has higher extraction accuracy compared with the traditional STFT spectral peak detection method and effectively eliminates the effect of speed fluctuations. A rotor dynamic-balancing experiment shows that the unbalance correction effect based on the STFTSC algorithm is remarkable, with the average unbalance amount decrease rate on the left and right sides being 90.02% and 92.56%, respectively, after a single correction.
基于STFTSC算法的无转速阶次跟踪方法用于变转速条件下转子不平衡故障诊断
摘要由于转子通常处于变速的非平稳状态,传统的基于平稳信号的转子不平衡检测方法会产生较大的“频谱模糊问题”,影响转子不平衡检测的准确性。为此,本研究提出了一种基于STFTSC算法的无盲点阶次跟踪方法,其中STFTSC算法将短时傅里叶变换与切缝算法相结合,开发了STFTSC算法。首先,利用STFTSC算法精确提取转子的瞬时频率(IF),并计算出变速条件下的瞬时相位;随后,在角域对原始信号进行重采样,将非平稳时域信号转化为稳定的角域信号,消除了速度变化的影响。最后,将角域信号变换为阶域信号,利用离散傅里叶变换和离散频谱校正方法识别信号基频分量对应的幅值和相位。仿真结果表明,与传统的STFT谱峰检测方法相比,STFTSC算法提取的中频具有更高的提取精度,并且有效地消除了速度波动的影响。转子动平衡实验表明,基于STFTSC算法的不平衡校正效果显著,单次校正后左右两侧的平均不平衡量下降率分别为90.02%和92.56%。
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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
期刊介绍: The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications. Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping
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