Acoustic Emission-Based Condition Monitoring and Remaining Useful Life Prediction of Hydraulic Cylinder Rod Seals

Pedersen, Jørgen F.; Schlanbusch, Rune; Meyer, Thomas

doi:10.3390/s21186012

Cited by 11 publications

(7 citation statements)

References 20 publications

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“…Pedersen et al [31] conducted a study to determine the early stages of external leakage initiation in hydraulic cylinders through Run-To-Failure (RTF) studies of PolyTetraFluoroEthylene (PTFE) seals in a test rig. An accelerated leakage initiation process was conducted by generating longitudinal scratches on the piston rod.…”

Section: Mechanical Accelerated Testing Of Hydraulic Sealsmentioning

confidence: 99%

A Review of State of the Art for Accelerated Testing in Fluid Power Pitch Systems

Ruz,

Pedersen,

Liniger

et al. 2024

Preprint

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Failures in hydraulic systems in offshore wind turbines represent an enormous challenge for manufacturers and operators, as the pitch system statistically is one of the subsystems contributing the most to the downtime of the turbines, which is the case for both electrical and hydraulic pitch systems. However, the complex failure mechanisms of the various different hydraulic components mean that, typically, the critical components of hydraulic systems must be tested to better understand the failure mechanisms. Nonetheless, conventional testing procedures are lengthy and costly. Accelerated testing plays a critical role as it can mimic hydraulic system failure mechanisms in a shorter period. However, the lack of standardized test methods and detailed knowledge about the failure-accelerating effects complicates the process. Therefore, this paper offers a comprehensive examination of approaches applicable to conducting accelerated tests on hydraulic systems. It identifies and discusses five primary component types or sub-components related to the acceleration of testing in hydraulic systems being: pumps, cylinders, seals, valves, and hoses. Each section references studies that delve into accelerated testing methodologies for these individual components. Furthermore, within each component, a concise overview of the current techniques is provided, followed by a discussion and summary based on the state of the art.

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Section: Mechanical Accelerated Testing Of Hydraulic Sealsmentioning

confidence: 99%

A Review of State of the Art for Accelerated Testing in Fluid Power Pitch Systems

Ruz,

Pedersen,

Liniger

et al. 2024

Preprint

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“…From the RTF tests conducted a comparison of the time and frequency domain features were conducted, and it was observed that the RMS feature was the most suited for use as condition monitoring indicators to identify wear of piston rod seals (Pedersen et al 2021). Therefore, in this study, the RMS feature was used to develop the ARIMA model.…”

Section: Arima Model Using the Rms Featurementioning

confidence: 99%

“…To classify the severity of fluid leakage, an optimization deep belief network (DBN) combined with the Complete Ensemble Empirical Model Decomposition with Adaptive Noise (CEEMDAN) was used and classification accuracy up to 93 % was achieved. (Pedersen et al 2021), performed run-to-failure tests at different pressure and speed conditions on a hydraulic test rig to understand the AE features that can be evaluated to determine fluid leakage initiation. RMS features were proposed as potential condition monitoring indicators to understand fluid leakage initiation.…”

Section: Introductionmentioning

confidence: 99%

“…As the ARIMA technique has successfully been used with the AE features for forecasting the process change or failure of components, the ARIMA technique in this research is used with AE features for forecasting the seal degradation. In this paper, the AE data from our previous experimental study conducted by (Pedersen et al 2021) is used for forecasting analysis.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting Piston Rod Seal Failure Based on Acoustic Emission Features in ARIMA Model

2022

Self Cite

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Fluid leakage due to piston rod seal failure in hydraulic cylinders results in unscheduled maintenance, machine downtime and loss of productivity. Therefore, it is vital to understand the piston rod seal failure at initial stages. In literature, very few attempts have been made to implement forecasting techniques for piston rod seal failure in hydraulic cylinders using acoustic emission (AE) features. Therefore, in this study, we aim to forecast piston rod seal failure using AE features in the auto regressive integrated moving average (ARIMA) model. AE features like root mean square (RMS) and mean absolute percentage error (MAPE) were collected from run-to-failure (RTF) tests that were conducted on a hydraulic test rig. The hydraulic test rig replicates the piston rod movement and fluid leakage conditions similar to what is normally observed in hydraulic cylinders. To assess reliability of our study, two RTF tests were conducted at 15 mm/s and 25 mm/s rod speed each. The process of seal wear from unworn to worn state in the hydraulic test rig was accelerated by creating longitudinal scratches on the piston rod. An ARIMA model was developed based on the RMS features that were calculated from four RTF tests. The ARIMA model can forecast the RMS values ahead in time as long as the original series does not experience any large shifts in variance or deviates heavily from the normal increasing trend. The ARIMA model provided good accuracy in forecasting the seal failure in at least two of four RTF tests that were conducted. The ARIMA model that was fitted with 15 pre-samples was used to forecast 10 out of sequence samples, and it showed a maximum moving absolute percentage error (MAPE value) of 28.99 % and a minimum of 4.950 %. The forecasting technique based on ARIMA model and AE features proposed in this study lays a strong basis to be used in industries to schedule the seal change in hydraulic cylinders.

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“…The features are selected to characterize the system dynamics during transient and steady-state operation and then combined to produce a condition indicator. In (Pedersen, Schlanbusch, Meyer, Caspers, & Shanbhag, 2021), acoustic emission (AE) sensors are used to identify the early stages of external leakage initiation in hydraulic cylinders. The impact of sensor location and rod speeds on the AE signal were investigated using both time-and frequency-based features.…”

Section: Introductionmentioning

confidence: 99%

Data Driven Condition Monitoring Based on a Digital Twin for a Linear Actuator Realized As a Closed Hydraulic System

Pichler¹,

Foschum

Haas³

et al. 2022

PHM_CONF

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Linear actuators, implemented as closed hydraulic systems, without external piping, are a state of the art drive concept, see (Gannon, 2017). Collecting data, used to train a condition monitoring (CM) for such drives, running 24/7, is cumbersome or even not possible. To gain training data, containing valid and invalid system states, we developed a simulation model, consisting of the most relevant physical effects. The simulated data are evaluated by a one-step feature approach and additionally with a two-step approach using two less complex fault state separation methods. In the end, the two-step method showed to be slightly better. The condition monitoring is not only used to recognize, but also to distinguish between accumulator and pump faults.

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Acoustic Emission-Based Condition Monitoring and Remaining Useful Life Prediction of Hydraulic Cylinder Rod Seals

Cited by 11 publications

References 20 publications

A Review of State of the Art for Accelerated Testing in Fluid Power Pitch Systems

A Review of State of the Art for Accelerated Testing in Fluid Power Pitch Systems

Forecasting Piston Rod Seal Failure Based on Acoustic Emission Features in ARIMA Model

Data Driven Condition Monitoring Based on a Digital Twin for a Linear Actuator Realized As a Closed Hydraulic System

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