Juanjuan Shi

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Effective fault diagnosis of rotating machinery helps prevent unexpected machine breakdowns resulting from the failure of essential components. Traditional artificial intelligence methods, such as artificial neural networks and support vector machine, have been proved to be effective in fault identification. However, extracting features manually requires a(More)
The design of joints between purrs is one of the most critical issues in the desipn of sheet meral assemblies. This paper presents a new pan-to-pan joinr desipn e~aluanon index developed for dimensional control of sheer meral assemblies. The proposed index provides a newr analytical roo1 to address the dimensional capabiliries of an assembly process in the(More)
As a breakthrough in the field of machine fault diagnosis, deep learning has great potential to extract more abstract and discriminative features automatically without much prior knowledge compared with other methods, such as the signal processing and analysis-based methods and machine learning methods with shallow architectures. One of the most important(More)
Localized faults on gears tend to result in periodic transient components under a constant speed operation. Extraction of such transient components is crucially important for gear fault diagnosis. Sparse decomposition based on matching pursuit (MP) is one of the effective methods to extract the weak feature contaminated by strong background noise and has(More)
Order tracking is one of the most widely used techniques for machine condition monitoring under variable speed. This method requires the shaft rotating speed beforehand. However, a tacho is not always allowed to be installed in the industry and furthermore the signal components associated to shaft rotating speed cannot be directly extracted from vibration(More)
Bearing fault diagnosis under variable speed usually have confronted two obstacles: a) blurry time frequency representation (TFR) and thus unavailable instantaneous frequency (IF) for resampling, and b) errorprone resampling process. To address such problems, this paper proposes a method which consists of two main steps: a) a regional peak search algorithm(More)
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