Injector waveform analysis and engine fault diagnosis based on frequency space subdivision in wavelet transform

Shuxia Jiang, Yuanyuan Liu
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引用次数: 4

Abstract

Although traditional waveform analysis in time domain plays an important role in realizing engine non-disintegration fault diagnosis, this method fails to make an accurate fault diagnosis when fault waveform and normal waveform are very close. To solve this problem, a new method based on frequency space subdivision (FSS) in wavelet transform (WT) is proposed and applied in this paper. Meanwhile, a processing approach of engine data stream is introduced, which makes further waveform analysis possible. This method is applied to an injector-pulse-width waveform analysis. As for the No. 12 fault analysis, firstly a biorthogonal wavelet base with good characteristics is selected, then three-layer wavelet decomposition is used to analyze injector-pulse-width in both time domain and frequency domain, and finally the accurate fault band is located through calculation of the sum of the difference between fault and normal wavelet coefficients. The result obtains that the fault comes from the oxygen sensor, which is completely coincident with the experimental fault hypothesis. Injector-pulse-width waveform of No.1, 8, 11 and 19 faults are also analyzed similarly. The results show that the proposed waveform analysis method improves the accuracy of the engine fault diagnosis. This method provides a supplement for the known non-disintegration engine fault diagnosis and supplies a good reference for fault diagnosis of the other large machines.
基于小波变换频率空间细分的喷油器波形分析与发动机故障诊断
传统的时域波形分析在实现发动机不解体故障诊断中发挥了重要作用,但当故障波形与正常波形非常接近时,该方法无法准确诊断故障。为了解决这一问题,本文提出了一种基于小波变换的频率空间细分(FSS)方法。同时,介绍了一种发动机数据流的处理方法,使进一步的波形分析成为可能。将该方法应用于喷油器脉宽波形分析。对12号故障进行分析,首先选取具有良好特征的双正交小波基,然后采用三层小波分解对注入器脉宽进行时域和频域分析,最后通过计算故障与正常小波系数之差之和确定准确的故障带。结果表明,故障来源于氧传感器,与实验假设完全吻合。对1号、8号、11号、19号断层的喷油脉宽波形也进行了类似的分析。结果表明,所提出的波形分析方法提高了发动机故障诊断的准确性。该方法为已知的非解体发动机故障诊断提供了补充,并为其他大型机械的故障诊断提供了很好的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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