Fault diagnosis based on wavelet package for hydraulic pump

Hou, Wenkui; Chuan, Lu; Liu, Hongmei; Lu, Chen

doi:10.1109/icrms.2009.5269950

Cited by 3 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…proposed a new rough set fault diagnosis algorithm for hydraulic pumps guided by PCA, aiming at the characteristics of fuzzy fault features and low signal-to-noise ratio of hydraulic pumps, using WA for noise reduction processing, extracting effective fault features, using PCA method for dimensionality reduction and decoupling correlation analysis of these features, using rough set theory to establish a knowledge base of diagnosis rules. Hou et al [41] proposed a WPD-based denoising method for hydraulic pump fault feature extraction to solve the problem that the feature signal is weak and covered by noise. Wang et al [42] introduced the idea of WNC denoising in view of the problems of the DCT denoising method, proposed a CNC denoising method, and extracted fault features from the output signal by HHT, effectively solving the problem of missing vibration signal components.…”

Section: Fault Diagnosis Based On Vibration Signalmentioning

confidence: 99%

Current Status and Applications for Hydraulic Pump Fault Diagnosis: A Review

Yang

Liu

Xiao

et al. 2022

Sensors

View full text Add to dashboard Cite

To implement Prognostics Health Management (PHM) for hydraulic pumps, it is very important to study the faults of hydraulic pumps to ensure the stability and reliability of the whole life cycle. The research on fault diagnosis has been very active, but there is a lack of systematic analysis and summary of the developed methods. To make up for this gap, this paper systematically summarizes the relevant methods from the two aspects of fault diagnosis and health management. In addition, in order to further facilitate researchers and practitioners, statistical and comparative analysis of the reviewed methods is carried out, and a future development direction is prospected.

show abstract

Section: Fault Diagnosis Based On Vibration Signalmentioning

confidence: 99%

Current Status and Applications for Hydraulic Pump Fault Diagnosis: A Review

Yang

Liu

Xiao

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…The Wavelet Transform (WT) provides a different approach which can process non-stationary signals in both time and frequency domains [17]- [20]. Unlike the FFT which expands the signal in terms of sine waves, the WT uses wavelets which are generated in the form of translations and dilation of mother wavelets.…”

Section: Takedownmentioning

confidence: 99%