Acoustic Emission Signal Parameters Research Articles

Identification of the concrete damage degree based on the principal component analysis of acoustic emission signals and neural networks

Abstract This paper aims to improve the calculation efficiency and accuracy of concrete damage degree identification, and then to analyze the damage mechanism of concrete damage. First, the correlation analysis and principal component analysis of 15 characteristic parameters of acoustic emission signals accompanying concrete uniaxial compression and splitting damage process are performed through which the dimension is reduced into 5 non-correlated principal components. Then, based on the analysis of the relationship between each principal component and the damage and cracking mechanism of concrete, the damage degree of concrete is identified as an input variable of the BP neural network. The results show that the 5 principal components effectively eliminate redundant information and carry information on the failure mechanism of concrete damage and the damage process. Principal component analysis and the neural network are used to achieve the accurate recognition of acoustic emission parameters and the degree of concrete damage.

Damage monitoring of carbon fiber reinforced silicon carbide composites under random vibration environment by acoustic emission technology

Carbon fiber-reinforced silicon carbide (C/SiC) composites are widely used in high-temperature thermo-structural applications. They are subjected to extreme loading conditions, such as random vibrations, which are likely to damage the structure. Structural micro-damage identification during vibration is very difficult, owing to the randomness of the environmental vibration and the complicated response it causes in structures. This study aims to determine a method for monitoring the damage properties of a C/SiC structure under a random vibration environment using acoustic emission (AE) technology. First, a pencil break experiment is conducted to verify the feasibility of the AE technology. Then, an AE monitoring experiment of the structural damage in a vibration environment is systematically conducted. Two types of experiments are designed for simulating the damage formation process inside the structure. In addition, the parameter characteristics of typical AE signals in the random vibration test are analyzed, and the relationships between the AE signal parameters and vibration loading are obtained. Lastly, the different stages of material damage development and damage types in each stage are provided to reveal the damage evolution processes of C/SiC composites. The results indicate that AE technology can be effectively applied to investigate the damage behaviors of C/SiC composites in random vibration environments.

Acoustic properties of fracture of dental restorative materials and endocrown restorations under quasi-static loading

Objectives(1) To investigate the properties of acoustic emission (AE) signals from fracture of dental materials and endocrown restorations during quasi-static compression using the continuous wavelet transform analysis. (2) To determine by the parameters of AE signals in which structural element of tooth-endocrown system the fracture starts. MethodsFive restorative materials (zirconium dioxide (Prettau zirconia), ceramics (IPS e.max Press), metal ceramics (GC Initial MC+Nicrallium N2 BCS), composite resin (Nano Q), luting cement (Relyx™ U200)) were manufactured into discs, 13mm diameter, 5mm thick, which were divided into 5 groups (Group B, C, D, E, F, respectively) and included into Type 1. Twenty-five extracted human molars were divided into 5 groups and included into Type 2: Group A (control, no restoration); BE (tooth restored by zirconium dioxide endocrowns); CE (restored by ceramic endocrowns); DE (restored by metal ceramic endocrowns); EE (restored by composite resin endocrowns). An increasing load was applied to the center of the samples with a hard steel ball until a fracture occurred. The loading rate was 0.12mm/min. Two-channel AE detection system was used to record the AE activity during testing. The parameters including the peak frequency, bandwidth, duration time and energy of AE signals were analyzed. ResultsThe restorative materials (Type 1) differ from each other by acoustic properties such as the peak frequency main bands and energy of AE signals. The detected AE signals correspond to the different fracture types. The dominant fracture mechanism of Group C, E and F specimens was the macrocracking (brittle fracture), and of Group D specimens was the microcracking, which alternated with the plastic deformation and macrocracking. For the number of events corresponding to the brittle fracture, statistically significant differences (p<0.05) were found between all group pairs. AE signals were not released during compression test of the zirconium dioxide samples, thus the fracture was not detected.All the AE signals detected during compression test of the different endocrown systems (Type 2) had two peak frequency bands. The fracture of Groups A, BE, CE and DE samples characterized by alternating the micro- and macrocracking with plastic deformation, and the brittle fracture was the dominant fracture mechanism. The restorations of Group EE fractured without plastic deformation. For the number of events corresponding to the brittle fracture, statistically insignificant differences (p>0.05) were found between Groups A vs CE and A vs EE, and statistically significant differences (p<0.05) were found between Groups A vs BE and A vs DE. SignificanceThe initiation of fracture in the restorations with endocrowns made from different materials begins with the tooth damage. The metal ceramic endocrown restoration showed the highest fracture resistance, what is especially important for clinical use.

Research on the Signal Characteristics of Internal Gas Leakage in Safety Valve

Based on the acoustic emission theory, this paper explores the signal characteristics of internal gas leakage in safety valve. In this paper, a simulation test-bed and an acoustic emission signal detection system for internal leakage in safety valve are designed and built. Through theoretical analysis and experimental research, the influence of factors such as inlet pressure of safety valve, size of leakage hole of sealing surface are explored, and the quantitative relationship between the gas volume leakage rate and the average signal level ASL of the characteristic parameters of acoustic emission signal is established.

Вплив швидкості різання на параметри сигналів акустичної емісії, які генеруються

Вплив швидкості різання на параметри сигналів акустичної емісії, які генеруються

A fault identification method for marine auxiliary machinery

A large number of auxiliary equipment is set up on the shipping system, most of them is rotating machinery and in working state for most of the time, it is very important to identify health condition of equipment to find early damage and avoid fatal failure. Acoustic emission is based on rapid release of energy in case of material deformation or cracking. Auxiliary equipment will continue to emit acoustic signals, which is collected by means of a protable detection device in this paper, parameters like RMS, Peak Factor are calculated to identify health condition in time domain. Through laboratory simulation test and real ship test, the result shows that by comparing the parameters of acoustic emission signal, health condition or its change trend can be obtained, early failure of equipment can be prevented.

Study of Limestone Deformation Stages on The Basis of Acoustic Emission and Thermomechanical Effects

The data of the uniaxial compression tests of limestone samples with the registration of the strain gauge data and parameters of acoustic emission and thermoradiation signals are presented. A joint analysis of the experimental time dependencies of the variations of mechanical and physical parameters is performed. The identification methods of the deformation stages of the test samples are considered, and the possibility of the integrated use of acoustic and thermal measurements in monitoring systems for geomechanical events in rock masses is presented.

METHOD OF REJECTION OF DEFECTS IN CARBON FIBER SAMPLES BY PARAMETERS OF ACOUSTIC EMISSION SIGNALS UNDER STATIC AND THERMAL LOADING

A method for rejecting defects in T 800 carbon fiber samples loaded with a static tensile load at an interval of ΔP = 10 kN until complete destruction is proposed. One part of the samples was loaded at a temperature of 20 °C, and the other part was subjected to simultaneous static loading and heating to a temperature of 100 °C. Samples made of carbon fiber with a size of 600×100×0.9 mm were made using autoclave and vacuum technologies at temperatures of 80; 135; 180 °C. the process of destruction of samples was controlled by acoustic emission (AE). To perform defect rejection, informative parameters of AE signals (structural coefficient and median signal amplitude) were used. The critical damage associated with the breaking of the fibers in the composite corresponded to AE signals with a structural coefficient less than a threshold and a median of amplitudes greater than a threshold.

MUTUAL CHANGE OF ACOUSTIC EMISSION STATISTICAL ENERGY PARAMETERS AT TREATING TOOL WEAR

The results of experimental studies of acoustic radiation energy during processing tool wear are considered. The regularities of acoustic emission signal statistical energy parameters changes at normal and catastrophic processing tool wear are determined. It is revealed that the regularities of change in the statistical energetic parameters of acoustic emission signals do not observe a characteristic features of the change which are associated with the appearance of a certain type of tool wear. The regularities of experimental acoustic emission signal statistical energy parameters mutual change during normal and catastrophic processing tool wear are determined. It is shown that the ratio of the acoustic emission signal average energy level to the average energy level standard deviation at a given analysis interval is a sensing parameters to the mechanisms and stages of cutting tool wear during materials machining.

Acoustic-Emission Procedure for Rejecting Defects in Multiple-Pass Girth Welds

A procedure is proposed for rejecting girth welds based on an analysis of the main parameters of acoustic emission (AE) signals recorded during multiple-pass welding. The accuracy of locating AE signals recorded from defects and their filtering from noise and interference were ensured by the use of a modified tabular method and rejection grid. Normalized coefficients were calculated from the energy and amplitude of localized AE signals and used for in-process assessment of weld quality. Threshold values were determined for the normalized coefficients above which the weld is rejected. Defects in girth welds were identified using this procedure, and the possibility of determining defect hazardousness in real time was demonstrated.

A study to determine the onset of catastrophic wear of a processing tool by statistical parameters of acoustic emission

In the present study, experimental research was carried out to determine the effect of the processing tool wear on the mutual change in the average statistical amplitude parameters of acoustic emission signals. Acoustic emission signals were recorded when turning silumin. The research was aimed at finding parameters to determine the occurrence of critical wear of the processing tool. It is shown that the recorded signals are continuous. The statistical amplitude parameters of the acoustic emission signals were processed under normal and catastrophic wear of the processing tool. It has been determined that the development of normal and catastrophic wear of the tool leads to a decrease in the values of the statistical amplitude parameters of the recorded signals. However, no peculiarities were found in their change to determine the developing type of wear. Meanwhile, at different time intervals, there was an anticipating increase or decrease in one of the statistical amplitude parameters of the acoustic emission signals. The processed parameter was a coefficient characterising a mutual change in the statistical amplitude values of the recorded signals. It has been determined that absence of the tool wear is characterised by stable values of the calculated coefficient in time. The occurrence and development of catastrophic wear leads to an outburst of the value of the calculated coefficient with its subsequent accelerated decrease to the destruction of the tool. The emergence and development of normal wear leads to an increase in the value of the calculated coefficient with a subsequent transition to a sawtooth change and a gradual decrease of its size. The obtained regularities can be used when devising methods for controlling and monitoring the condition of the tool during the mechanical processing of materials, including monitoring the state of the processing tool in robotic industries

Estimation and Comparison of Electrode Wear and Ae Parameters of Titanium Material in Wire Electric Discharge Machining Using ANN

Wire Electrical Discharge Machining (WEDM) is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. Selection of process parameters for obtaining higher cutting efficiency or accuracy in WEDM is still not fully solved, even with most up-to-date CNC wire EDM machine. It is widely recognised that Acoustic Emission (AE) is gaining ground as a monitoring method for health diagnosis on rotating machinery. The advantage of AE monitoring over vibration monitoring is that the AE monitoring can detect the growth of subsurface cracks whereas the vibration monitoring can detect defects only when they appear on the surface. This study outlines the optimization of titanium material using L16design of experiment. Each experiment has been performed varying the process parameters like pulse-on time, pulse-off time, current and bed speed. Among different process parameters voltage and flush rate were kept constant. Molybdenum wire having diameter of 0.18 mm was used as an electrode. Simple functional relationships between the parameters were plotted to arrive at possible information on Electrode Wear (EW) and AE signals. But these simpler methods of analysis did not provide any information about the status of the electrode. Thus, there is a requirement for more sophisticated methods that are capable of integrating information from the multiple sensors. Hence, method like Artificial Neural Network (ANN) has been applied for the estimation of EW, AE signal strength, AE count and AE RMS. The ANN algorithm is designed to learn the process by training the algorithm with the experimental data. The experimental observations are divided into three sets: the training set, validation set and testing set. The training set is used to make the ANN learn the process and the testing set will check the performance of ANN. Different models can be obtained by varying the percentage of data in the training set and the best model can be selected from these, viz., 50%, 60% and 70%. The best model is selected from the said percentages of data. Estimation of the EW and AE signals parameters by ANN at 70% of data training set showed the best correlation with the measured value.

Antiretroviral Therapy Interruption and Clinical Outcomes in HIV-infected Adults

Acoustic Emission (AE) method for material state monitoring during fatigue tests was attested for turbine blade durability estimation for different types of superalloys. Average value of summarized AE signals, N̄ae, registered during the beginning of tests and summarized AE-signals, (Nae)01, in the second semi-cycle of blade bending both have good correlation with durability that blades reached at the moment of fracture. The discovered relations between summarized AE signals and durability demonstrated the high value of the correlation factor. For the moment of crack origination, the number of cycles, (Nf)α, can be simulated also by the AE signals, (Nae)t, registered during time interval in several minutes. In all discussed cases, relations between parameters of AE signals and critical values of the cycle’s number for estimating durability introduced with discovered factors.

Comparison of the effect of different additives on acoustic emission parameters obtained during three-point bending tests of alkali-activated slag composites

The development of failure in quazi-brittle materials is associated with the formation of microcracks, which is followed by the release of energy in the form of elastic ultrasonic waves. The acoustic emission method is an effective non-destructive method for the detection and determination of different damage mechanisms not only in composite materials. This experimental work presents results from the acoustic emission measurements obtained during three-point bending tests without the central notch on alkali-activated materials with various additives. The acoustic emission activity was monitored using piezoelectric sensors, and the way of damage based on parameters of acoustic emission signals was investigated. The preliminary results showed that the addition of carbon black significantly reduced the maximal stress, whereas the addition of graphite increased the brittleness of the alkali-activated material. The higher brittleness is determined by the lower number of overshoots of acoustic emission signals before the fracture of the specimens.

The Use of the Acoustic Emission Method to Identify Crack Growth in 40CrMo Steel.

The article presents the application of the acoustic emission (AE) technique for detecting crack initiation and examining the crack growth process in steel used in engineering structures. The tests were carried out on 40CrMo steel specimens with a single edge notch in bending (SENB). In the tests crack opening displacement, force parameter, and potential drop signal were measured. The fracture mechanism under loading was classified as brittle. Accurate AE investigations of the cracking process and SEM observations of the fracture surfaces helped to determine that the cracking process is a more complex phenomenon than the commonly understood brittle fracture. The AE signals showed that the frequency range in the initial stage of crack development and in the further crack growth stages vary. Based on the analysis of parameters and frequencies of AE signals, it was found that the process of apparently brittle fracture begins and ends according to the mechanisms characteristic of ductile crack growth. The work focuses on the comparison of selected parameters of AE signals recorded in the pre-initiation phase and during the growth of brittle fracture cracking.

Flexural Characteristics Evaluation for Reinforced Concrete Affected by Steel Corrosion Based on an Acoustic Emission Technique

The purpose of this research is to utilize a more advanced test method for investigating the effect of steel corrosion on the flexural characteristics of a reinforced concrete (RC) beam on a microscopic cracking level. Firstly, over-reinforced RC beam specimens were prepared and corroded using an electrical accelerated steel corrosion setup in different ratios. Subsequently, bending and acoustic emission (AE) tests were performed on all the specimens to obtain their ultimate flexural loads, failure modes and AE signals. Furthermore, rise time/peak amplitude (R/A), ringing counts/duration (AF) and improved b (Ib) values, as the statistical parameters of AE signals, were calculated for indicating the transformation of RC specimens’ crack modes and failure modes under the effect of steel corrosion. Finally, the locations of AE events were obtained by localization technology and compared with the locations of concrete cracks (cracks map). The results revealed that the ultimate flexural load decreases with steel corrosion. The crack tends to transform from shear- to tensile-type along with the increase of the steel corrosion ratio. The trend of the Ib-value curve can reflect the formation and development of cracks; and the larger the duration of violent fluctuations in the Ib-value curve is, the larger the ultimate flexural load of the RC beam is. The region where the crack is located can be judged by the position where the relatively dense distribution of the AE events is.

Correlation analysis between acoustic emission signal parameters and fracture stress of wool fiber

In order to optimize the tensile performance measurement of wool and other fiber materials, the present paper proposes a novel characterization method based on acoustic emission detection of fiber fracture acoustic signals, which can characterize the tensile properties of materials. When the fiber material is stretched and fractured, part of the elastic potential energy accumulated during the stretching process will propagate into the air in the form of oscillating sound waves, which will carry the tensile property information of the fiber material. Firstly, the signal is de-noised by wavelet transform and the waveform parameters are extracted. Secondly, the amplitudes in the characteristic frequency interval (As-CFI) of the spectrum are extracted by fast Fourier transform, and principal component analysis is utilized to reduce the parameter dimension. Finally, the waveform parameters and the spectral parameters are respectively regression analyzed with tensile parameters. The result shows that there is a clear linear correlation between the tensile parameters of wool fibers and the acoustic signal parameters. In the multiple linear regression analysis of waveform parameters and As-CFI versus fracture stress, the correlation coefficients are all above 0.90.

Investigation of X80 Line Pipe Steel Fracture during Tensile Testing Using Acoustic Emission Monitoring

The acoustic emission (AE) monitoring technique is widely used in mechanical and materials research for detection of plastic deformation, fracture initiation and crack growth. However, the quantitative dependences of the AE signal parameters on material fracture parametersare not completely understood. This paper presents recent research results on AE monitoring of the fracture behavior of X80 line pipe steel, a critically important material for the oil and gas transportation industry.Fracture of this steel was studied using tensile testing of small scale specimens coupled with AE monitoring and high speed video camera. The dependence of fracture behavior and AE parameters on loading conditions (strain rate and presence or absence of a notch) was investigated. The AE parameters were analyzed using the “Average Hit” features and “Wave Form and Power Spectrum” methodologies. The fracture surface was characterized using scanning electron microscopy and a dependence of the AE parameters on the average void size has been obtained.

Observations of changes in acoustic emission parameters for varying corrosion defect in reciprocating compressor valves

Abstract Acoustic Emission (AE) technology is probably one of the most recent entries in the field of machinery condition monitoring. This paper investigates the application of AE parameters for valve faults detection in reciprocating compressor. The defective valves were designed by emulating the actual valve corrosion with varying sizes such that defects could be applied onto the reciprocating compressor. A set of experiments was performed to acquire the AE signal. The primary source of AE signal was verified using waveform analysis. The AE parameters versus different operational and valve condition were illustrated individually. In addition, the significance of the change and sensitivity of AE parameters versus different experimental conditions was verified using MANOVA and coefficient of variance analysis. It is concluded that the AE signal parameters can be used to detect the valve faults in the reciprocating compressor with the consideration of the variation in the AE parameters sensitivity.

Wear, vibration and acoustic emission characterization of sliding friction processes of coarse-grained and ultrafine-grained copper

Microstructural evolution of copper samples after equal channel angular pressing (ECAP) have been studied. The equiaxed ultrafine-grains first appeared after 4 ECAP passes and then occupied the bulk of the sample after 8 and 12 passes thus forming more homogeneous grain-subgrain structures. High values of ultimate tensile strength 653 MPa and microhardness (180 HV) have been achieved. Tribological testing under unlubricated sliding friction of as-annealed and ECAPed copper samples against a steel counterbody have been carried out with simultaneous registration of vibration acceleration (VA) and acoustic emission (AE) signals. Wear reduced with the ECAP pass number changed from 0 to 12. Structural evolution of metal in different structural states after sliding tests has been studied and its effect on wear and friction has been revealed. The ECAPed samples formed thick oxidized layers on their worn surfaces which then deteriorated by subsurface fracture. This subsurface cracking changed the sliding friction dynamics as well as the AE signal parameters. Correlations between the tribological system vibrations and AE signal parameters have been established.