Internal Leakage Diagnosis of a Hydraulic Cylinder Based on Optimization DBN Using the CEEMDAN Technique

Zhang, Peng; Chen, Xinyuan

doi:10.1155/2021/8856835

Cited by 9 publications

(6 citation statements)

References 38 publications

(36 reference statements)

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“…RMS, peak, bandpower, mean frequency and median frequency showed capability in identifying unworn and worn piston rod seal conditions at different speeds and pressures. Zhang et al [26] monitored internal leakage in gashydraulic pressurised cylinders using AE at different loads. The optimization deep belief network (DBN) combined with the complete ensemble empirical mode decomposition with adaptive noise (CEEMAN) technique was used to analyse the AE signals.…”

Section: Introductionmentioning

confidence: 99%

Defining acoustic emission-based condition monitoring indicators for monitoring piston rod seal and bearing wear in hydraulic cylinders

Meyer

Schlanbusch

2021

Int J Adv Manuf Technol

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Fluid leakage from hydraulic cylinders is a major concern for the offshore industries as it directly affects hydraulic cylinder energy efficiency and causes environmental contamination. There have been attempts made in literature to develop robust condition monitoring techniques for hydraulic cylinders. However, most of these studies were performed to identify degradation of single components. Therefore, in this study, the aim is to monitor degradation of multiple components simultaneously in hydraulic cylinders using acoustic emissions. Experiments performed consist of three test phases and were performed using a hydraulic test rig. In the first test phase, the study is performed to identify acoustic emission features that can be used to monitor piston rod seal wear. In the second test phase, acoustic emission features are identified that can be used to understand bearing wear when unworn, semi-worn or worn piston rod seals are used in hydraulic test rig. In the third test phase, a run-to-failure test is conducted to identify acoustic emission features that can indicate fluid leakage initiation due to piston rod seal wear. The median frequency feature showed good repeatability in all the three test phases to identify piston rod seal wear, bearing wear and fluid leakage initiation during the initial stages in the hydraulic test rig. The proposed acoustic emission-based condition monitoring technique is robust and can be used for the hydraulic cylinders in the industries, as it identifies acoustic emission features based on particular frequency bands associated to specific components, making it less susceptible to noise from other components.

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Section: Introductionmentioning

confidence: 99%

Defining acoustic emission-based condition monitoring indicators for monitoring piston rod seal and bearing wear in hydraulic cylinders

Meyer

Schlanbusch

2021

Int J Adv Manuf Technol

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“…It is far more difficult to diagnose an internal leakage under low loads. That is why the authors of [31] proposed a method for automatic diagnosis of internal leakage under low loads based on optimizing a deep belief network (DBN).…”

Section: Introductionmentioning

confidence: 99%

Modelling Internal Leakage in the Automatic Transmission Electro-Hydraulic Controller, Taking into Account Operating Conditions

Dziubak,

Szczepaniak

2023

Energies

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The basic malfunction of automatic transmissions (ATs) is oil flow through hydraulic precision pair clearances called an “internal leakage”, leading to difficulties in controlling the AT. There are no sufficiently accurate methods for assessing the impact of “internal leakage” on the AT technical condition in the course of operation. A proprietary hydraulic precision pair internal leak flow model has been proposed in the paper. The novelty of the model is applying electro-hydraulic controller precision pair clearance values as data that was determined through measurements involving an actual object with a specific AT operation period. The authors conduct variant tests of the model to determine the total AT hydraulic system controller leakage. Reduced oil viscosity (approx. 20%) results in internal leakage increasing by 25%. Significant wear of the controller’s precision pair and increased oil temperature (above 80 °C) lead to internal leakage increasing by more than 50% and oil pressure decreasing below the permissible value.

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“…For example, Wang et al [17] proposed a combination of sliding-window spectrum feature extraction and a deep belief network (DBN) for fault diagnosis in hydraulic systems. Zhang and Chen [18] developed a fault diagnosis method based on an optimized DBN combined with complete ensemble empirical mode decomposition with adaptive noise techniques. Guo et al [19] compared the performance of different regression algorithms in predicting internal leakage, including convolutional neural network (CNN), BPNN, radial basis function network, support vector regression, T-S neural network, and Elman neural network.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Fault Diagnostics of Hydraulic Cylinder Using Particle Filter

Zhang,

Vacca,

Gong

et al. 2023

Machines

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Condition-based hydraulic cylinder maintenance necessitates quantitative fault diagnostics. However, existing methods are characterized by either qualitative or limited quantitative capabilities. In this paper, a quantitative fault diagnostic method using a particle filter for hydraulic cylinders is proposed. The problem of quantitative fault diagnostics is formally formulated in a stochastic framework to assess the health/fault state, and an architecture based on joint state-parameter estimation is proposed. Through the establishment and analysis of a nonlinear dynamic model of the hydraulic cylinder, the impact of time-varying parameters on the state variables is revealed. Three fault modes of the cylinder, including friction, internal leakage, and external leakage, are theoretically identified. The proposed method allows for a simultaneous quantitative diagnosis of these three fault modes. The performance of the proposed method is evaluated using meticulously designed experiments. The results demonstrate that the mean absolute percentage errors in the parameter estimations are below 9% (accuracy exceeding 91%), thus validating its feasibility and effectiveness.

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Internal Leakage Diagnosis of a Hydraulic Cylinder Based on Optimization DBN Using the CEEMDAN Technique

Cited by 9 publications

References 38 publications

Defining acoustic emission-based condition monitoring indicators for monitoring piston rod seal and bearing wear in hydraulic cylinders

Defining acoustic emission-based condition monitoring indicators for monitoring piston rod seal and bearing wear in hydraulic cylinders

Modelling Internal Leakage in the Automatic Transmission Electro-Hydraulic Controller, Taking into Account Operating Conditions

Quantitative Fault Diagnostics of Hydraulic Cylinder Using Particle Filter

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