Wavelet Leaders Based Vibration Signals Multifractal Features of Plunger Pump in Truck Crane

Abstract

Vibration signal of plunger pump in truck crane is a typical nonlinear, nonstationary signal, and the multifractal features are a powerful tool for depicting the geometry features of such signals. The wavelet-leaders based multifractal features extraction method is an attractive tool, which has solid theoretical mathematical support and a simplified calculation procedure. The waveletleaders based multifractal features extraction method is compared for the original signal and the denoised signal, and the statistical performance of the obtained features is also introduced based on block bootstrap technology. The effectiveness of the wavelet leaders based method is first verified for a traditional multifractal signal. Then, the application of the proposed method to the pump vibration signals of three working conditions of truck crane: lifting, rotating, and luffing is discussed. The result shows that the geometry features of vibration signals can be obtained with wavelet leaders multifractal analysis method, and the denoising process improves the multifractal features.

A Vibration Signal-Based Method for Fault Identification and Classification in Hydraulic Axial Piston Pumps

“…The characteristic mark of such a critical operating condition has been identified in the acceleration signals by Buono et al [19] for a lubricating gerotor pump. Even the vibrations of hydraulic pumps can convey a lot of information about different faults; for this reason, many researchers have proposed diagnostics solutions based on an accelerometer installed on the case of the machine [20][21][22][23][24]. The methodology presented in Reference [25] is applied to experimental signals measured by two accelerometers mounted on the pump housing; the outcomes show that features highlighting the presence of the considered fault can be extracted by the proposed method for the analysis of the acceleration signals.…”

A Methodology Based on Cyclostationary Analysis for Fault Detection of Hydraulic Axial Piston Pumps

“…The vibration of hydraulic pumps, which can be measured using accelerometers installed on the pump case, is affected by the majority of the faults, and therefore it is considered in many works which propose diagnostics solutions for hydraulic pumps [12][13][14][15][16]. Other works about condition monitoring exploit vibration signals to train neural networks and compute the diagnosis [17][18][19].…”