Study of Oil Starvation in Journal Bearing Using Acoustic Emission and Vibration Measurement Techniques

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Surojit Poddar ◽  
N. Tandon
Keyword(s):  
Acoustic Emission ◽  
Journal Bearing ◽  
Measurement Techniques ◽  
Peak Frequency ◽  
Vibration Measurement ◽  
Frequency Range ◽  
Frequency Shifts ◽  
Deformation And Fracture ◽  
Asperity Contacts ◽  
Ae Signals

Abstract This present article evaluates the state of starvation in a journal bearing using acoustic emission (AE) and vibration measurement techniques. A journal bearing requires a constant supply of oil in an adequate amount to develop a hydrodynamic film, thick enough to separate the surfaces and avoid asperity contacts. On a microscopic level, the surface interaction under starved lubrication results in deformation and fracture of asperities. This causes a proportionate increase in AE and vibration. The AE activities resulting from asperities interaction have significant energy in the frequency range of 100–400 kHz with peak frequencies in the range of 224–283 kHz. Further, the peak frequency shifts from the higher to lower side as the asperity interaction transits from the elastic to plastic contact. This information derived from the spectral analysis of AE signals can be used to develop condition monitoring parameters to proactively control the lubrication and prevent bearing failure.

Classification of journal bearing friction states based on acoustic emission signals

2018 ◽  
Vol 85 (6) ◽  
pp. 434-442 ◽  
Author(s):  
Noushin Mokhtari ◽  
Clemens Gühmann
Keyword(s):  
Acoustic Emission ◽  
Time Domain ◽  
Journal Bearing ◽  
Prediction Method ◽  
Support Vector ◽  
Mechatronic Systems ◽  
Prediction Time ◽  
Ae Signals ◽  
Bearing Friction

Abstract For diagnosis and predictive maintenance of mechatronic systems, monitoring of bearings is essential. An important building block for this is the determination of the bearing friction condition. This paper deals with the possibility of monitoring different journal bearing friction states, such as mixed and fluid friction, and examines a new approach to distinguish between different friction intensities under several speed and load combinations based on feature extraction and feature selection methods applied on acoustic emission (AE) signals. The aim of this work is to identify separation effective features of AE signals to subsequently classify the journal bearing friction states. Furthermore, the acquired features give information about the mixed friction intensity, which is significant for remaining useful lifetime (RUL) prediction. Time domain features as well as features in the frequency domain have been investigated in this work. To increase the sensitivity of the extracted features the AE signals were transformed to the frequency-time-domain using continuous wavelet transform (CWT). Significant frequency bands are determined to separate different friction states more effective. A support vector machine (SVM) is used to classify the signals into three different friction classes. In the end the idea for an RUL prediction method by using the already determined information is given and explained.

scholarly journals Internal Leakage Predicition of Hydraulic Spool valves Based on Acoustic Emission Technology

2021 ◽  
Vol 2113 (1) ◽  
pp. 012016
Author(s):  
Fei Song ◽  
Likun Peng ◽  
Jia Chen ◽  
Benmeng Wang
Keyword(s):  
Acoustic Emission ◽  
High Frequency ◽  
Peak Frequency ◽  
Leakage Rate ◽  
High Frequency Band ◽  
Signal Characteristics ◽  
Spool Valves ◽  
The Relationship ◽  
Ae Signals ◽  
Acoustic Emission Technology

Abstract In order to realize the nondestructive testing (NDT) of the internal leakage fault of hydraulic spool valves, the internal leakage rate must be predicted by AE (acoustic emission) technology. An AE experimental platform of internal leakage of hydraulic spool valves is built to study the characteristics of AE signals of internal leakage and the relationship between AE signals and leakage rates. The research results show the AE signals present a wideband characteristic. The main frequencies are concentrated in 30~50 kHz and the peak frequency is around 40 kHz. When the leakage rate is large, there are significant signal characteristics appearing in the high frequency band of 75~100 kHz. The exponent of the root mean square(RMS) of AE signals is positively correlated with the exponent of the leakage rate only if the leakage rate is greater than 2~3 mL/min. This find could be used to predict the internal leakage rate of hydraulic spool valves.

scholarly journals Friction and Wear Monitoring Methods for Journal Bearings of Geared Turbofans Based on Acoustic Emission Signals and Machine Learning

Lubricants ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 29 ◽  
Author(s):  
Noushin Mokhtari ◽  
Jonathan Gerald Pelham ◽  
Sebastian Nowoisky ◽  
José-Luis Bote-Garcia ◽  
Clemens Gühmann
Keyword(s):  
Machine Learning ◽  
Acoustic Emission ◽  
Friction And Wear ◽  
Journal Bearing ◽  
Journal Bearings ◽  
Wear Volume ◽  
Time Frequency ◽  
Ae Signal ◽  
Ae Signals

In this work, effective methods for monitoring friction and wear of journal bearings integrated in future UltraFan® jet engines containing a gearbox are presented. These methods are based on machine learning algorithms applied to Acoustic Emission (AE) signals. The three friction states: dry (boundary), mixed, and fluid friction of journal bearings are classified by pre-processing the AE signals with windowing and high-pass filtering, extracting separation effective features from time, frequency, and time-frequency domain using continuous wavelet transform (CWT) and a Support Vector Machine (SVM) as the classifier. Furthermore, it is shown that journal bearing friction classification is not only possible under variable rotational speed and load, but also under different oil viscosities generated by varying oil inlet temperatures. A method used to identify the location of occurring mixed friction events over the journal bearing circumference is shown in this paper. The time-based AE signal is fused with the phase shift information of an incremental encoder to achieve an AE signal based on the angle domain. The possibility of monitoring the run-in wear of journal bearings is investigated by using the extracted separation effective AE features. Validation was done by tactile roughness measurements of the surface. There is an obvious AE feature change visible with increasing run-in wear. Furthermore, these investigations show also the opportunity to determine the friction intensity. Long-term wear investigations were done by carrying out long-term wear tests under constant rotational speeds, loads, and oil inlet temperatures. Roughness and roundness measurements were done in order to calculate the wear volume for validation. The integrated AE Root Mean Square (RMS) shows a good correlation with the journal bearing wear volume.

Identification of Damage Modes in Twill-Weave Composite Based on EMD of AE Event

2012 ◽  
Vol 198-199 ◽  
pp. 60-63
Author(s):  
Wen Qin Han ◽  
Jin Yu Zhou
Keyword(s):  
Acoustic Emission ◽  
Fourier Transform ◽  
Composite Materials ◽  
Acoustic Emissions ◽  
Peak Frequency ◽  
Intrinsic Mode Functions ◽  
Mode Decomposition ◽  
Different Types ◽  
Twill Weave ◽  
Ae Signals

Acoustic emission (AE) monitoring is the primary technology used for the identification of different types of failure in composite materials. Tensile test were carried out on twill-weave composite specimens, and acoustic emissions were recorded from these tests. AE signals were decomposed into a set of Intrinsic Mode Functions(IMF) components by means of Empirical Mode Decomposition(EMD) , the Fast Fourier Transform (FFT) of each IMF component was performed, it was shown that the event peak frequency of each IMF component could be directly related to the materials damage modes.

scholarly journals Identification of Deformation Stage and Crack Initiation in TC11 Alloys Using Acoustic Emission

2020 ◽  
Vol 10 (11) ◽  
pp. 3674
Author(s):  
Jiaoyan Huang ◽  
Zhiheng Zhang ◽  
Cong Han ◽  
Guoan Yang
Keyword(s):  
Acoustic Emission ◽  
Titanium Alloy ◽  
Crack Initiation ◽  
Peak Frequency ◽  
Identification Accuracy ◽  
Energy Ratio ◽  
Frequency Bands ◽  
Mode Decomposition ◽  
Tc11 Titanium Alloy ◽  
Ae Signals

The Acoustic Emission (AE) is a widely used real-time monitoring technique for the deformation damage and crack initiation of areo-engine blades. In this work, a tensile test for TC11 titanium alloy, one of the main materials of aero-engine, was performed. The AE signals from different stages of this test were collected. Then, the AE signals were decomposed by the Variational Mode Decomposition (VMD) method, in which the signals were divided into two different frequency bands. We calculated the engery ratio by dividing the two different frequency bands to characterize TC11′s degree of deformation. The results showed that when the energy ratio was −0.5 dB, four stages of deformation damage of the TC11 titanium alloy could be clearly identified. We further combined the calculated Partial Energy Ratio (PER) and Weighted Peak Frequency (WPF) to identify the crack initiation of the TC11 titanium alloy. The results showed that the identification accuracy was 96.33%.

scholarly journals Study on the Acoustic Emission Characteristics of Different Rock Types and Its Fracture Mechanism in Brazilian Splitting Test

2021 ◽  
Vol 9 ◽  
Author(s):  
Li Shengxiang ◽  
Xie Qin ◽  
Liu Xiling ◽  
Li Xibing ◽  
Luo Yu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Rock Fracture ◽  
Peak Frequency ◽  
Test System ◽  
Mineral Particle ◽  
Splitting Test ◽  
Ae Signal ◽  
The Relationship ◽  
Ae Signals ◽  
Internal Fracture

In order to investigate the relationship between rock microfracture mechanism and acoustic emission (AE) signal characteristic parameters under split loads, the MTS322 servo-controlled rock mechanical test system was employed to carry out the Brazilian split tests on granite, marble, sandstone, and limestone, while FEI Quanta-200 scanning electron microscope system was employed to carry out the analysis of fracture morphology. The results indicate that different scales of mineral particle, mineral composition, and discontinuity have influence on the fracture characteristics of rock, as well as the b-value. The peak frequency distribution of the AE signal has obvious zonal features, and these distinct peak frequencies of four types of rock fall mostly in ranges of 0–100 kHz, 100–300 kHz, and above 300 kHz. Due to the different rock properties and mineral compositions, the proportions of peak frequencies in these intervals are also different among the four rocks, which are also acting on the b-value. In addition, for granite, the peak frequencies of AE signals are mostly distributed above 300 kHz for granite, marble, and limestone, which mainly derive from the internal fracture of k-feldspar minerals; for marble, the AE signals with peak frequency are mostly distributed in over 300 kHz, which mainly derive from the internal fracture of dolomite minerals and calcite minerals; AE signals for sandstone are mostly distributed in the range of 0–100 kHz, which mainly derive from the internal fracture of quartz minerals; for limestone, the AE signals with peak frequency are mostly distributed in over 300 kHz, which mainly derive from the internal fracture of granular-calcite minerals. The relationship between acoustic emission signal frequency of rock fracture and the fracture scale is constructed through experiments, which is of great help for in-depth understanding of the scaling relationship of rock fracture.

Differentiation of journal bearing friction states and friction intensities based on feature extraction methods applied on acoustic emission signals

2017 ◽  
Vol 84 (s1) ◽  
Author(s):  
Noushin Mokhtari ◽  
Farid Rahbar ◽  
Clemens Gühmann
Keyword(s):  
Acoustic Emission ◽  
Feature Extraction ◽  
Journal Bearing ◽  
Extraction Methods ◽  
Mechatronic Systems ◽  
Mixed Friction ◽  
Feature Spaces ◽  
Prediction Time ◽  
Ae Signals ◽  
Bearing Friction

AbstractFor diagnosis and predictive maintenance of mechatronic systems, monitoring of bearings is essential. An important building block for this is the determination of the bearing friction condition. This paper deals with the possibility of monitoring different journal bearing friction states, such as mixed and fluid friction, and examines a new approach to distinguish between different friction intensities under several speed and load combinations based on feature extraction and feature selection methods applied on acoustic emission (AE) signals. The aim of this work is to identify separation effective features of AE signals to subsequently classify the journal bearing friction states. Furthermore, the acquired features give information about the mixed friction intensity, which is significant for remaining useful lifetime (RUL) prediction. Time domain features as well as features in the frequency domain have been investigated in this work. The combination of several features generates feature spaces. The position of the objects within these spaces has proved that it is possible to differentiate between journal bearing friction states with the use of AE signals and suitable feature extraction methods. In addition, features that indicate different mixed friction intensities have been found.

scholarly journals Investigation of Ib-Values for Determining Fracture Modes in Fiber-Reinforced Composite Materials by Acoustic Emission

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3641
Author(s):  
Doyun Jung ◽  
Woong-Ryeol Yu ◽  
Wonjin Na
Keyword(s):  
Acoustic Emission ◽  
Failure Modes ◽  
Peak Frequency ◽  
Matrix Cracking ◽  
Failure Behavior ◽  
B Values ◽  
Fracture Modes ◽  
Reinforced Composite ◽  
Carbon Fiber Epoxy ◽  
Ae Signals

This study analyzed failure behavior using Ib-values obtained from acoustic emission (AE) signals. Carbon fiber/epoxy specimens were fabricated and tested under tensile loads, during which AE signals were collected. The dominant peak frequency exhibited a specific range according to fracture mode, depending on the fiber structures. Cross-ply specimens, with all fracture modes, were used and analyzed using b- and Ib-values. The b-values decreased over the specimens’ entire lifetime. In contrast, the Ib-values decreased to 60% of the lifetime, and then increased because of the different fracture behaviors of matrix cracking and fiber fracture, demonstrating the usefulness of Ib-values over b-values. Finally, it was confirmed that abnormal conditions could be analyzed more quickly using failure modes classified by Ib-values, rather than using full AE data.

scholarly journals Identification of Fracturing Behavior In Thermally Cracked Granite Using The Frequency Characteristics of Acoustic Emission

2021 ◽  
Author(s):  
Kazumasa Sueyoshi ◽  
Manami Kitamura ◽  
Xinglin Lei ◽  
Ikuo Katayama
Keyword(s):  
Acoustic Emission ◽  
Stress Drop ◽  
Triaxial Compression ◽  
Low Frequency ◽  
Peak Frequency ◽  
Frequency Characteristics ◽  
Peak Amplitude ◽  
Cracking Behavior ◽  
Thermal Cracks ◽  
Ae Signals

Abstract The frequency characteristics of acoustic emission (AE) during triaxial compression of thermally cracked and unheated (“fresh”) granite samples were investigated with the aim of understanding the influence of pre-existing cracks on precursor information regarding macroscopic failure. The peak frequency during the damage process was the same for thermally cracked and fresh granites. Analysis of AE signals showed that signals with low peak frequency appeared before failure of the sample, implying the initiation of microfractures with progressive growth of cracks. The peak amplitude of the frequency spectrum recorded in the thermally cracked samples was much lower than that in the fresh samples. This result suggests two reasons for the difference in peak amplitude: reduction in shear modulus and the attenuation filtering phenomenon caused by thermal cracks. In particular, the maximum value of peak amplitude in the low-frequency band for the thermally cracked samples was smaller than that for fresh samples. This characteristic can be related to the stress drop and crack size. Assuming that pre-existing thermal cracks grow during the pre-failure stage, the events with low peak frequency and low peak amplitude in the heat-treated samples are interpreted as exhibiting a low stress drop because of the small rupturing area for individual events. Therefore, although AE signals with low frequency can be considered as precursors to rock failure, cracking behavior suggested by events with low frequency depends on the initial damage condition of the rock sample.

DETERMINATION OF THE CONNECTION BETWEEN THE STRUCTURE OF CARBON FIBER SAMPLES AND THE PARAMETERS OF ACOUSTIC EMISSION SIGNALS DURING SIMULTANEOUS STATIC AND THERMAL LOADING

2019 ◽  
pp. 4-13 ◽  
Author(s):  
L. N. Stepanova ◽  
V. A. Bataev ◽  
V. V. Chernova
Keyword(s):  
Acoustic Emission ◽  
Carbon Fiber ◽  
Thermal Loading ◽  
Static Load ◽  
Carbon Plastic ◽  
Frequency Range ◽  
Simultaneous Exposure ◽  
Informative Parameters ◽  
Partial Energy ◽  
Ae Signals

The effects of positive and negative temperature and static load on the main informative parameters (structure coefficient, partial energy, location) of acoustic emission (AE) signals, which determined the mechanism for changing the structure of carbon fiber and the beginning of its destruction, are investigated. Tests of specimens of carbon fiber T800, made of nine monolayers with laying [±45/90/О3/90/±45], size 600x100x0.9 mm. Each sample was subjected to static loading and the effects of positive (+20, +40, +60, +80, +100 °С) or negative (–20, –40, –60, –80 °C) temperatures in the area of the concentrator in the form of a 12 mm diameter hole. Using fractography, changes in the structure of carbon plastic from the applied static load and temperature and changes informative parameters were analyzed. It was shown that the lamination of the material with simultaneous exposure to static load and temperatures from –80 to –20 °C and from +60 to +100 °C corresponded to an increase in the structural coefficient and partial energy, which caused an energy shift in the frequency range 125…250 kHz. Under the same static loads, but temperatures of +20 and +40 °C, informative parameters took on minimal values, that meant the energy was shifted to the frequency range 250…500 kHz, characterized the crumbling of the matrix and breaking of the fibers without lamination of the CFRP. Under all temperature conditions, the location of the signals began in the hole area and spread in the direction of the static load. The detection the disturbance of the CFRP structure by the informative parameters of AE signals makes it possible to reduce the risk of emergency situations during working of the composite construction.

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