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

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.

2021 ◽  
Vol 9 ◽  
Author(s):  
Li Shengxiang ◽  
Xie Qin ◽  
Liu Xiling ◽  
Li Xibing ◽  
Luo Yu ◽  
...  

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.


1990 ◽  
Vol 112 (1) ◽  
pp. 84-91 ◽  
Author(s):  
Xiangying Liu ◽  
Elijah Kannatey-Asibu

A relationship developed earlier between acoustic emission signals and the process of athermal martensitic transformation based on the free energy associated with the process is extended and verified experimentally. The relationship is found to model the process characteristics very well. The intensity of AE signal generated during transformation was found to be proportional to the temperature derivative of the fraction of martensite, the cooling rate, and volume of specimen. The AE signal was also found to be related to the carbon content of the steel. During transformation, the signal intensity was found to increase to a peak, and then tail off near the end of the transformation. Values of the martensite start temperature obtained from plots of the total RMS squared AE signals were also found to correlate well with values from the literature.


2012 ◽  
Vol 198-199 ◽  
pp. 60-63
Author(s):  
Wen Qin Han ◽  
Jin Yu Zhou

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.


2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Surojit Poddar ◽  
N. Tandon

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.


Author(s):  
Zhongzheng Zhang ◽  
Hua Liang ◽  
Cheng Ye ◽  
Wensheng Cai ◽  
Jun Jiang ◽  
...  

In order to study acoustic emission (AE) signals waveform characteristics of pitting corrosion on 304 stainless steel under higher temperature than lower one, Pitting corrosion process on 304 stainless steel in 6% ferric chloride solution at 70°C was monitored by AE technology. Wavelet transform and mode acoustic emission technology were combined to deal with recorded AE signals, and micromorphologic observation was performed for further verification. The results showed that signal waveform was mainly composed of low-frequency (<100KHz) flexural wave with larger amplitude & energy and high-frequency (>100KHz) expansion wave with lesser amplitude & energy. The research results have some certain significance for AE monitoring of pitting corrosion on 304 stainless steel.


2013 ◽  
Vol 66 (1) ◽  
Author(s):  
M. Mohammad ◽  
S. Abdullah ◽  
N. Jamaludin ◽  
O. Innayatullah

This study was carried out to investigate the relationship between the strain and acoustic emission (AE) signals, thus, to confirm the capability of AE technique to monitor the fatigue failure mechanism of a steel component. To achieve this goal, strain and AE signals were captured on the steel specimen during the cyclic fatigue test.  Both signals were collected using specific data acquisition system by attaching the strain gauge and AE piezoelectric transducer simultaneously at the specimen during the test. The stress loading used for the test was set at 600 MPa, and the specimens were fabricated using the SAE 1045 carbon steel.  The related parameters for both signals were determined at every 2000 seconds until the specimen failed.  It was found that a meaningful correlation of all parameters, i.e. amplitude, kurtosis and energy, was established. Finally, all AE parameters are correlated with the damage values, which have been estimated using the Coffin-Manson model.  Hence, it was suggested that the AE technique can be used as a monitoring tool for fatigue failure mechanism in a steel component.


2020 ◽  
Vol 10 (11) ◽  
pp. 3674
Author(s):  
Jiaoyan Huang ◽  
Zhiheng Zhang ◽  
Cong Han ◽  
Guoan Yang

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%.


2020 ◽  
Vol 1009 ◽  
pp. 25-30
Author(s):  
Yoshiaki Akematsu ◽  
Hiromitsu Gotho ◽  
Takayuki Tani ◽  
Hideaki Murayama ◽  
Tsuyoshi Matsuo ◽  
...  

In this study, the potential to monitor the high-technology nailing of carbon fiber reinforced thermoplastic material (CFRTP) under ultrasonic vibration was investigated by acoustic emission (AE) method. AE signals were detected by a piezoelectric AE sensor during high-technology nailing under ultrasonic vibration. This paper describes some experimental results on AE signal characteristics and observation of the high-technology nailing. In order to investigate the effects of machining condition, we focused on RMS voltage, which is dependent on the energy parameter of the AE signal. It was found that the AE method is a useful method of monitoring high-technology nailing.


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