Detection of Misfire in a Six-Cylinder Diesel Engine Using Acoustic Emission Signals

2018 ◽  
Author(s):  
Mohammad Jafari ◽  
Pietro Borghesani ◽  
Puneet Verma ◽  
Ashkan Eslaminejad ◽  
Zoran Ristovski ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Diesel Engine ◽  
Sensor Technology ◽  
Angular Domain ◽  
Acoustic Emission Sensor ◽  
Emission Signal ◽  
Crank Angle ◽  
Ae Signal ◽  
Envelope Spectrum ◽  
Short Time

This study will focus on the detection of misfire using Acoustic emission sensor in a multi-cylinder diesel engine. Detection of misfire is important since this malfunction can cause the engine to stall in a short time. In order to investigate the misfire, an experimental engine was run with and without injection of the fuel in the first cylinder. The acoustic emission signal was acquired synchronously with the crank angle signal, in order to have a reference for the transformation from time to angular domain. The AE signal was then processed using the squared envelope spectrum to highlight angle-periodic modulations in the signal’s power (cyclic bursts). This study will present the effectiveness of this combination of sensor technology and signal processing to detect misfire in a six-cylinder diesel engine connected to a hydraulic dynamometer.

Experiment on Surface Roughness and Acoustic Emission Signal in Infeed Period of Cylindrical Plunge Grinding

2013 ◽  
Vol 690-693 ◽  
pp. 2442-2445 ◽  
Author(s):  
Hao Lin Li ◽  
Hao Yang Cao ◽  
Chen Jiang
Keyword(s):  
Surface Roughness ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Feed Rate ◽  
Grinding Process ◽  
Experiment Research ◽  
Plunge Grinding ◽  
Emission Signal ◽  
Ae Signal ◽  
Ae Signals

This work presents an experiment research on Acoustic emission (AE) signal and the surface roughness of cylindrical plunge grinding with the different infeed time. The changed infeed time of grinding process is researched as an important parameter to compare AE signals and surface roughnesses with the different infeed time in the grinding process. The experiment results show the AE signal is increased by the increased feed rate. In the infeed period of the grinding process, the surface roughness is increased at first, and then is decreased.

On-Line Monitoring the Hard Turning Using Distribution Parameters of Acoustic Emission Signal

2015 ◽  
Vol 787 ◽  
pp. 907-911
Author(s):  
J. Bhaskaran
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Hard Turning ◽  
Metal Cutting ◽  
Cubic Boron Nitride ◽  
Emission Signal ◽  
Distribution Parameters ◽  
On Line ◽  
Ae Signal ◽  
Wear Monitoring

In hard turning, tool wear of cutting tool crossing the limit is highly undesirable because it adversely affects the surface finish. Hence continuous, online tool wear monitoring during the process is essential. The analysis of Acoustic Emission (AE) signal generated during conventional machining has been studied by many investigators for understanding the process of metal cutting and tool wear phenomena. In this experimental study on hard turning, the skew and kurtosis parameters of root mean square values of AE signal (AERMS) have been used for online monitoring of a Cubic Boron Nitride (CBN) tool wear.

Acoustic Emission (AE) Propagation Attenuation Theory and Rule in Non-Perfect Elastic Coal and Rock

2013 ◽  
Vol 477-478 ◽  
pp. 620-623
Author(s):  
Guo Wei Dong
Keyword(s):  
Numerical Simulation ◽  
Acoustic Emission ◽  
Quality Factor ◽  
Field Test ◽  
Propagation Distance ◽  
Signal Propagation ◽  
Emission Signal ◽  
Ae Signal ◽  
Propagation Rule ◽  
Quality Factor Q

Propagation rule of acoustic emission (AE) signal in coal and rock is an important basis when AE technique forecasts coal and rock dynamical disasters. Based on correlative theory of quality factor Q, Acoustic emission signal propagation attenuation formula in non-perfect elastic coal and rock are analyzed, Based on the theoretic formula, Effects of different quality factor and propagation distance on AE propagation attenuation are theoretically analyzed ;Based on theoretic analysis results, AE signal propagation numerical simulation and field test programs are designed, AE signal propagation rules in elastoplastic coal and rock are obtained. Field test and numerical simulation experimentation results validate rationality of theoretic forumla. Study production can guide AE technique that forecasts mine and rock dynamical disasters.

scholarly journals Investigation on recognition method of acoustic emission signal of the compressor valve based on CNN and LSTM network

2021 ◽  
Vol 252 ◽  
pp. 02023
Author(s):  
Yanfeng Wang ◽  
Jin Wang ◽  
Junwei Sun ◽  
Enhao Liang ◽  
Tao Wang
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Dynamic Characteristics ◽  
Short Term Memory ◽  
Reciprocating Compressor ◽  
Short Term ◽  
Emission Signal ◽  
Ae Signal ◽  
Long Short Term Memory ◽  
Lstm Network

The valve is one of the important parts of the reciprocating compressor, which directly affects the thermodynamic process and reliability of the compressor. In this paper, acoustic emission (AE) technology is used to predict the dynamic characteristics of valves. The AE signal of the compressor valve is analyzed based on the deep learning method, and the mapping relation between the AE signal and the dynamic characteristics of the valve is obtained. The results show that the prediction accuracy of the models trained by Long Short-Term Memory (LSTM) artificial neural network and Convolutional Neural Network (CNN) is 97% and 95%, respectively, which can accurately predict the dynamic characteristics of the valve. Although the prediction results of CNN are slightly lower than that of LSTM network, the calculation speed of CNN is relatively faster.

scholarly journals Electrical discharge phenomenon of electrode gaps in oil insulation

2018 ◽  
Vol 197 ◽  
pp. 11005
Author(s):  
Jannus Maurits Nainggolan ◽  
MK Iwa Ganiwa ◽  
Chairul Hudaya ◽  
Amien Rahardjo
Keyword(s):  
Acoustic Emission ◽  
Signal Analysis ◽  
Electrical Discharge ◽  
Frequency Component ◽  
Solid Layer ◽  
Insulating Material ◽  
Emission Signal ◽  
Plane Electrode ◽  
Maximum Value ◽  
Ae Signal

An electrical discharge is a phenomenon of ionization of an insulating material. Ionization can occur when the stress applied to the insulating material begins to close to the maximum value of stress can be restrained. In this study, a high voltage was given on a point-plane electrode that would produce ionization (discharge) on the gap of the electrode. The point-plane electrode was placed in an iron tank containing oil insulation. The distance of a gap between the electrodes varies from 2 mm to 4 mm. Then, the signal from the occurrence of electrical discharge was capture using an acoustic emission (AE) sensor placed on the outside of the tank wall. The detected acoustic emission signal was amplified with a 40 dB amplifier, so the signal would be easier to analyze. At the other condition, a solid layer of insulation with a thickness of 4 mm would also be placed on the gap the electrode. The result of the signal analysis showed small differences in the intensity of the detected AE signal at all the distance of electrode gaps. The main frequency component of the detected AE signal at all electrode gaps was several hundred kilohertz.

Investigation of the Peculiarities of Deformation and Fracture of Metals Obtained on the Basis of 3D Printing with Registration of an Acoustic Emission Signal

2021 ◽  
Vol 1037 ◽  
pp. 71-76
Author(s):  
Maksim S. Anosov ◽  
Yury G. Kabaldin ◽  
Dmitrii A. Shatagin ◽  
Dmitry A. Ryabov ◽  
Pavel Kolchin
Keyword(s):  
Acoustic Emission ◽  
3D Printing ◽  
Test Temperature ◽  
Acoustic Emission Signal ◽  
Fracture Mechanisms ◽  
Characteristic Parameters ◽  
Diagnostic Features ◽  
Emission Signal ◽  
Deformation And Fracture ◽  
Ae Signal

The paper investigates the features of deformation and fracture of steels obtained using the technology of 3D printing by electric arc surfacing based on the registration of the acoustic emission signal. With a decrease in the test temperature of 07Cr25Ni13 steel, a decrease in the work expended in stretching the specimen is observed, both at the stage of elastic deformation and at the stage of strain hardening. It was found that the most informative characteristic parameters of the AE signal include: the pulse count rate N, the total count NΣ, and the AE signal entropy. With a decrease in the test temperature, there is a significant increase in the intensity of the AE signal, the total number of pulses at all stages of deformation and destruction of steel. The obtained regularities of changes in the characteristic parameters of the AE signal can be used as diagnostic features, both in assessing the stage of deformation and destruction of the material, and the structural state of the material. Fractographic studies have shown a significant decrease in the tough component of 08Mn2Si steel with a decrease in the test temperature. The fracture mechanisms of 07Cr25Ni13 steel change insignificantly with decreasing temperature, however, a significant decrease in the ductility of the metal is observed, as evidenced by a decrease in the size of ductile fracture cups.

Fabrication of Acoustic Emission Sensor Integrated with Cantilever Array for Detection of Signals Divided into Frequency Domain

2012 ◽  
Vol 523-524 ◽  
pp. 575-580 ◽  
Author(s):  
Takahiro Kawashima ◽  
Atsushi Matsui ◽  
Kazuo Muto ◽  
Moeto Nagai ◽  
Takayuki Shibata
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
Frequency Domain Analysis ◽  
Acoustic Emission Sensor ◽  
Batch Fabrication ◽  
Ae Signal ◽  
Cantilever Array ◽  
Detection Of Signals ◽  
Ae Signals

In order to detect acoustic emission (AE) signals which are transient elastic waves generated by rapid release of strain energy derived from deformation in materials etc., general AE sensors were fabricated by using a piezoelectric film for detection of AE signals. However, these sensors required frequency domain analysis after recording AE signal. Therefore, this research has been developing an AE sensor integrated with cantilever array with different resonant frequencies for detection of AE signals divided into frequency domain by using MEMS techniques. In this paper, a design of cantilever structures was executed. Theoretical analysis and simulation using ANSYS software revealed that a resonant frequency of a cantilever was increased with decrease of its length in the range from 100 k to 1 MHz. Therefore, fabrication and frequency characterization of a cantilever array fabricated in our batch fabrication process were executed.

Spectrum Analysis of Acoustic Emission Signal Obtained during Breakaway Oxidation of 2.25Cr-1Mo Steel

2009 ◽  
Vol 293 ◽  
pp. 27-39 ◽  
Author(s):  
B.B. Jha ◽  
Barada Kanta Mishra ◽  
S.N. Ojha
Keyword(s):  
Acoustic Emission ◽  
Spectrum Analysis ◽  
Oxide Scales ◽  
Frequency Pattern ◽  
Frequency Spectra ◽  
Breakaway Oxidation ◽  
Emission Signal ◽  
Ae Signal ◽  
Characteristic Features ◽  
Physical Phenomena

Frequency spectrum analysis of acoustic emission (AE) signal has been carried out during breakaway oxidation and internal cracking of oxide scales formed on 2.25Cr-1Mo steel. Three regions viz pre-breakaway, post-breakaway and internal cracking of scales have been distinguished based upon thermogravimetric analysis and SEM/EPMA observations. The frequency pattern of the AE signal obtained in three different regions shows three different characteristic features. Frequency spectra based upon the predominant frequencies have been correlated with the physical phenomena occurring during the course of oxidation.

Study on Porcelain Acoustic Emission Signal Based on All Phase Spectrum Analysis

2011 ◽  
Vol 391-392 ◽  
pp. 569-574
Author(s):  
Ding Ye ◽  
Wei Jin ◽  
Chen Xi Liu
Keyword(s):  
Acoustic Emission ◽  
Spectrum Analysis ◽  
Weighted Average ◽  
Phase Spectrum ◽  
Truncation Method ◽  
Emission Signal ◽  
Energy Leakage ◽  
Phase Signal ◽  
Ae Signal

In order to differentiate the porcelain quality, the paper introduces the All Phase spectrum analysis technology and studies on analyzing porcelain acoustic emission (AE) signal. As for the energy leakage by traditional signal truncation method in processing the signal, the all phase truncation method somewhat reduce the leakage which affects the follow-up porcelain quality discrimination. All instances consisting sample point are considered and weighted average technology is introduced to make amplitude-frequency clearer. According to the simulation, the energy leakage based on all phase signal processing is weakened and the spectrum is able to be accurate. It is more beneficial to the follow-up porcelain quality discrimination.

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