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A vibration-based approach for diesel engine fault diagnosis

机译:基于振动的柴油发动机故障诊断方法

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As diesel engines play a critical role in various applications, the ability for a health monitoring system to perform early fault diagnosis is of vital importance for the reliable functioning of a diesel engine throughout its service. In regard to the criticality of diesel engine fault diagnosis, an abundance of research efforts have been conducted by adopting injection-based, vibration-based, or instantaneous speed-based methods. The study presented in this paper discusses an integrated approach of diagnosing combustion faults and valve leakage, by combining vibration signal with cylinder pressure and revolution speed signals. Signal processing methods, including time frequency domain analysis such as wavelet decomposition are applied to extract features from data collected under different health conditions. The dimension of the feature set is further reduced based on discriminant analysis. Classification techniques are subsequently evaluated as fault diagnosis tools. The proposed approach is validated on a small-scale diesel engine test bed, and is to be applied in a real world health monitoring system.
机译:由于柴油发动机在各种应用中发挥着关键作用,因此对健康监测系统进行早期故障诊断的能力对于柴油发动机在整个服务中的可靠运作至关重要。关于柴油发动机故障诊断的关键性,通过采用基于注射的,振动的或基于瞬时速度的方法,进行了丰富的研究工作。本文提出的研究讨论了通过将振动信号与汽缸压力和旋转速度信号组合的振动信号进行振动信号诊断燃烧断层和阀泄漏的综合方法。信号处理方法,包括诸如小波分解的时间频域分析,用于从不同健康状况下收集的数据提取特征。基于判别分析,进一步减少了特征集的尺寸。随后评估分类技术作为故障诊断工具。所提出的方法在小型柴油发动机试验台上验证,可应用于现实世界健康监测系统。

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