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

AbstractFluid 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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Acoustic emission based condition monitoring study of piston rod seals by varying speed and pressure parameters

Annual Conference of the PHM Society ◽

10.36001/phmconf.2020.v12i1.1133 ◽

2020 ◽

Vol 12 (1) ◽

pp. 9

Author(s):

Vignesh Vishnudas Shanbhag ◽

Thomas Meyer ◽

Leo Caspers ◽

Rune Schlanbusch

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Median Frequency ◽

Test Rig ◽

Mean Frequency ◽

Emission Signal ◽

Seal Failure ◽

Power Spectral ◽

Hydraulic Cylinders ◽

Rod Seals

Hydraulic cylinders are used in a wide range of applications such as oil drilling equipment, construction vehicles and manufacturing machines. Seal failure is one of the primitive causes of failure in hydraulic cylinders, possibly leading to fluid spill, unscheduled maintenance, reduced availability and thus leading to lower productivity. Regular visual inspection of seals without affecting the productivity is difficult as the seals are placed internally in the hydraulic cylinder requiring disassembly of the piston. Therefore, condition monitoring is required to assess the current health of the seals. There have been successful attempts made in literature for the assessment of seal quality using acoustic emission-based condition monitoring. However, there have been very few studies performed to diagnose the seal failure under varying speed and pressure parameters. Therefore, this study aims at increasing the understanding of seal failure under varying speed and pressure conditions through correlation with the acoustic emission signal. Experiments were performed on a hydraulic test rig using unworn, semi-worn and worn piston rod seals. For each seal wear condition, experiments were performed for five strokes at pressure conditions of 10, 20, 30 and 40 bar and speeds of 50 mm/s and 100 mm/s. Continuous acoustic emission data were acquired during all the tests. The acoustic emission signal of each piston rod stroke was analyzed using different acoustic emission features such as power spectral density, root mean square, peak, mean frequency, median frequency and band power. From the acoustic emission analysis, by using power spectral density, mean frequency and median frequency feature it is possible to identify and segregate unworn seal, leakage due to semi-worn seal and leakage due to worn seal in the test rig. The acoustic emission-based condition monitoring methodology developed in this study lays a strong foundation for further research to develop real-time monitoring of the piston rod seal in hydraulic cylinders that are used in the offshore industry.

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

Sensors ◽

10.3390/s21186012 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6012

Author(s):

Jørgen F. Pedersen ◽

Rune Schlanbusch ◽

Thomas J. J. Meyer ◽

Leo W. Caspers ◽

Vignesh V. Shanbhag

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Hydraulic Cylinder ◽

Remaining Useful Life ◽

Test Rig ◽

Operational Conditions ◽

Hydraulic Cylinders ◽

Ae Signal ◽

Useful Life ◽

The Impact

The foremost reason for unscheduled maintenance of hydraulic cylinders in industry is caused by wear of the hydraulic seals. Therefore, condition monitoring and subsequent estimation of remaining useful life (RUL) methods are highly sought after by the maintenance professionals. This study aimed at investigating the use of acoustic emission (AE) sensors to identify the early stages of external leakage initiation in hydraulic cylinders through run to failure studies (RTF) in a test rig. In this study, the impact of sensor location and rod speeds on the AE signal were investigated using both time- and frequency-based features. Furthermore, a frequency domain analysis was conducted to investigate the power spectral density (PSD) of the AE signal. An accelerated leakage initiation process was performed by creating longitudinal scratches on the piston rod. In addition, the effect on the AE signal from pausing the test rig for a prolonged duration during the RTF tests was investigated. From the extracted features of the AE signal, the root mean square (RMS) feature was observed to be a potent condition indicator (CI) to understand the leakage initiation. In this study, the AE signal showed a large drop in the RMS value caused by the pause in the RTF test operations. However, the RMS value at leakage initiation is seen to be a promising CI because it appears to be linearly scalable to operational conditions such as pressure and speed, with good accuracy, for predicting the leakage threshold.

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Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission

Journal of Vibration and Control ◽

10.1177/10775463211016130 ◽

2021 ◽

pp. 107754632110161

Author(s):

Aref Aasi ◽

Ramtin Tabatabaei ◽

Erfan Aasi ◽

Seyed Mohammad Jafari

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Time Domain ◽

Central Moment ◽

Rolling Element Bearings ◽

Test Rig ◽

Acoustic Emission Sensor ◽

Outer Race ◽

Common Time ◽

Rolling Element

Inspired by previous achievements, different time-domain features for diagnosis of rolling element bearings are investigated in this study. An experimental test rig is prepared for condition monitoring of angular contact bearing by using an acoustic emission sensor for this purpose. The acoustic emission signals are acquired from defective bearing, and the sensor takes signals from defects on the inner or outer race of the bearing. By studying the literature works, different domains of features are classified, and the most common time-domain features are selected for condition monitoring. The considered features are calculated for obtained signals with different loadings, speeds, and sizes of defects on the inner and outer race of the bearing. Our results indicate that the clearance, sixth central moment, impulse, kurtosis, and crest factors are appropriate features for diagnosis purposes. Moreover, our results show that the clearance factor for small defects and sixth central moment for large defects are promising for defect diagnosis on rolling element bearings.

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Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration Sensors

Processes ◽

10.3390/pr9071108 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1108

Author(s):

Oliver Mey ◽

André Schneider ◽

Olaf Enge-Rosenblatt ◽

Dirk Mayer ◽

Christian Schmidt ◽

...

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Manufacturing Systems ◽

Acoustic Emissions ◽

Machine Learning Algorithms ◽

Damage Classification ◽

Industrial Facilities ◽

Vibration Sensors ◽

Drive Trains ◽

Condition Monitoring Systems

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. Data analysis can be improved by applying machine learning algorithms and fusion of data from heterogenous sensors. This paper presents an approach for a step-wise integration of classifications gained from vibration and acoustic emission sensors in order to combine the information from signals acquired in the low and high frequency ranges. A test rig comprising a drive train and bearings with small artificial damages is used for acquisition of experimental data. The results indicate that an improvement of damage classification can be obtained using the proposed algorithm of combining classifiers for vibrations and acoustic emissions.

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Condition monitoring of internal leakage in modern water hydraulic cylinders using acoustic emission

10.32657/10356/18848 ◽

2008 ◽

Author(s):

Ping Chen

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Hydraulic Cylinders ◽

Water Hydraulic

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Measurement and Analysis of Inadequate Friction Mechanisms in Liquid-Buffered Mechanical Seals Utilizing Acoustic Emission Technique

Vibration ◽

10.3390/vibration4010018 ◽

2021 ◽

Vol 4 (1) ◽

pp. 263-283

Author(s):

Manuel Medina-Arenas ◽

Fabian Sopp ◽

Johannes Stolle ◽

Matthias Schley ◽

René Kamieth ◽

...

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

High Frequency ◽

Friction Mechanisms ◽

Acoustic Emissions ◽

Mechanical Seal ◽

Mechanical Seals ◽

Monitoring Methods ◽

Acoustic Emission Technique ◽

Condition Monitoring System

Mechanical seals play an important role in the reliability of a process. Currently, the condition monitoring of mechanical seals is restricted due to the limitations of the traditional monitoring methods, including classical vibration analysis. For this reason, the objective of the present work is the detection and analysis of friction mechanisms inside a mechanical seal that are unfavorable and induce fault conditions using the acoustic emission technique, which allows the measurement of high-frequency vibrations that arise due to material fatigue processes on a microscopic scale. For this purpose, several fault condition modes were induced on a test rig of an agitator vessel system with a double-acting mechanical seal and its buffer fluid system. It was possible to detect the presence of inadequate friction mechanisms due to the absence and limited use of lubrication, as well as the presence of abrasive wear, by measuring a change in the properties of the acoustic emissions. Operation under fault condition modes was analyzed using the acoustic emission technique before an increase in the leakage rate was evaluated using traditional monitoring methods. The high friction due to the deficient lubrication was characterized by a pattern in the high-frequency range that consisted of the harmonics of a fundamental frequency of about 33 kHz. These results demonstrate the feasibility of a condition monitoring system for mechanical seals using the acoustic emission technique.

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Gas Turbine Condition Monitoring Using Acoustic Emission Signals

Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems ◽

10.1115/1.4044232 ◽

2019 ◽

Vol 2 (3) ◽

Author(s):

S. Shahkar ◽

K. Khorasani

Keyword(s):

Acoustic Emission ◽

Gas Turbine ◽

Condition Monitoring ◽

Gas Turbines ◽

Acoustic Emissions ◽

Time Instant ◽

Rotary Machinery ◽

Ae Signal ◽

Reliable Classification ◽

Ae Signals

Acoustic emission (AE) signals are recognized as complementary measures for detecting incipient faults and condition monitoring in rotary machinery due to their containment of sources of potential fault energy. However, determining the potential sources of faults cannot be easily realized due to the non-stationarity of AE signals. Available techniques that are capable of evoking instantaneous characteristics of a particular AE signal cannot optimally perform in a sense that there is no guarantee that these characteristics (hereinafter referred to as the “features”) remain constant when another AE signal is obtained from the system, albeit operating under the same machine condition at a different time instant. This paper provides a theoretical framework for developing a highly reliable classification and detection methodology for gas turbine condition monitoring based on AE signals. Mathematical results obtained in this paper are evaluated and validated by using actual gas turbines that are operating in power generating plants, to demonstrate the practicality and simplicity of our methodologies. Emphasis is given to acoustic emissions of similar brand and sized gas turbine turbomachinery under different health conditions and/or aging characteristics.

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Condition monitoring of hydraulic cylinder seals using acoustic emissions

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-020-05738-4 ◽

2020 ◽

Vol 109 (5-6) ◽

pp. 1727-1739

Author(s):

Vignesh V. Shanbhag ◽

Thomas J. J. Meyer ◽

Leo W. Caspers ◽

Rune Schlanbusch

Keyword(s):

Condition Monitoring ◽

Acoustic Emissions ◽

Hydraulic Cylinder ◽

Cylinder Seals

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Expansion of the Metrological Visualization Capability by the Implementation of Acoustic Emission Analysis

Advances in Tribology ◽

10.1155/2017/3718924 ◽

2017 ◽

Vol 2017 ◽

pp. 1-17 ◽

Cited By ~ 11

Author(s):

Philipp Bergmann ◽

Florian Grün ◽

Florian Summer ◽

István Gódor ◽

Gabriel Stadler

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Journal Bearing ◽

Acoustic Emissions ◽

Close Correlation ◽

Emission Analysis ◽

Evaluation Parameters ◽

Acoustic Emission Analysis

The acquisition and evaluation of acoustic emissions (AE) in tribology have proven to be a meaningful tool for condition monitoring and offer possibilities to deepen the understanding of tribological processes. The authors used this technology with the aim of expanding existing test methodologies towards increased visualization capability of tribological processes and investigated the correlation between tribological processes and acoustic emissions on a Ring-on-Disc and a close-to-component journal bearing test setting. The results of this study include the description of friction as well as wear processes and prove the usability of several AE evaluation parameters whereby a close correlation between AE and tribological processes can be shown. Consequently, it was possible to expand the visualization and evaluation capabilities of the test settings offering additional insights by making use of AE.

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