scholarly journals An acoustic emission source localization approach based on time-reversal technology for additive manufacturing

2022 ◽  
Vol 355 ◽  
pp. 01008
Author(s):  
Xiaodi Yang ◽  
Jiazhou Zhou ◽  
Chunming Gao ◽  
Ping Zhang ◽  
Tingting Liu ◽  
...  

The metal additive manufacturing process can inevitably lead to a great temperature gradient in the workpiece. Therefore, the thermal stress deformation and defects seriously affect the processing quality. In this paper, an array acoustic probe is designed on the base plate with the consideration of the time reversal technology. Corresponding simulations is implemented, which are designed to verify the ability of detecting and positioning the workpiece stress release acoustic emission signal. The simulation results demonstrate that the proposed method can position and monitor the random acoustic emission.

2013 ◽  
Vol 380-384 ◽  
pp. 2954-2957
Author(s):  
Xiao Tao Zhang ◽  
Li Wei Tang ◽  
Ping Wang ◽  
Xing Xing Han ◽  
Shi Jie Deng

For the burst-type acoustic emission signal, time delay estimation of two sensors calculated by signal cross-correlation is not accurate, and it leads the source localization results is not also accurate. A new method is proposed to improve accuracy of source localization results based on multi-scale analysis and multi-sensors. Acoustic emission signal multi-scale analysis using wavelet transform, then the most accurate time delay is selected in sub-band of signal multi-scale analysis by multi-sensors time delay vector close rule. Finally, the simulation acoustic emission source localization experiment has high accuracy.


2011 ◽  
Vol 48-49 ◽  
pp. 1395-1400
Author(s):  
Yi Li ◽  
Zhen Kai Wan ◽  
Jia Lu Li

This paper discusses the application and experimental method of acoustic emission for the three-dimensional (3D) braided composite material under flexural testing. It describes the feature of acoustic emission when applied to three-dimensional braided composite material under flexural testing. In order to know the materials damage position precisely, it is very important to collect the signal of acoustic emission source. The results of flexural experiment show that it is precise on the research of acoustic emission source location by the method of wave form analysis .During the collecting signal of acoustic emission , it is compared between parameter analysis and wave form analysis. According to the attenution degree of signal, it is selected signal of acoustic emission source exactly. It is the method to extract the precise acoustic emission signal by the different algorithm of wavelet analysis. We know that humans have been using materials by testing activities support, these tests have developed several centuries. From the traditional rough test to support materials and materials used in all aspects of science and technology, modern, scientific program, at present, there are mutual dependencies between the progress of scientific knowledge and the development of test methods. The 3D braided composite material is a kind of complex structure. Because of the many components and weaving material preparation process characteristic, material mechanics behavior is very complicated. It is characteristics of the 3D braided composite material, that the application on composites is widely more and more. The 3d braided composites have been used widely in aerospace, aviation, transportation, chemical, sports, medical care and other fields, so it is extremely vital significance for research on mechanics performance analysis of 3D braided composite material. Current studies of damage fracture behavior of composite materials are used in homogeneous materials research methods, namely the mechanical test and microscopic observation, but the research cannot distinguish and identify different damage fracture source, due to the combination of mechanical test parameters of the complex fracture micro-mechanism not sensitive. Microscopic observation is in fact observation later, local fracture surface morphology research, so can not observe the interaction of numerous fracture source and micro behavior, and can not study in the character of fracture source of composite materials, therefore the source faults already can not adapt to the traditional methods of composite material damage fracture process. From external or internal force effect material and structure produced deformation or fracture with elastic wave form, the strain energy release phenomenon called acoustic emission or stress wave [1]. Acoustic emission testing method is a kind of material internal defects or potential defects in the dynamic changes in movement, the damage detection method is real-time monitoring and can reflect the characteristics of acoustic emission sources in the load of the dynamic response. The AE information can directly reflect defects and changes [2, 3].


Crystals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 343 ◽  
Author(s):  
Sebastian Weber ◽  
Joaquin Montero ◽  
Christoph Petroll ◽  
Tom Schäfer ◽  
Matthias Bleckmann ◽  
...  

In the laser powder bed fusion processes for metal additive manufacturing, a support structure is needed to fix the part to the base plate and to support overhanging regions. Currently the importance of support structure for a successful build process is often underestimated and some effects are not yet well understood. Therefore, this study investigates the fracture behavior and mechanical properties of thin additive manufactured struts using the titanium alloy Ti-6Al-4V and specific machine parameters for support structures. Tensile tests were performed for different strut diameters and the fracture surfaces were analyzed using a laser microscope and a scanning electron microscope. Additionally, the porosity was examined with micro-CT scans. The results were compared with a different set of parameters used for solid parts. The experiments revealed that struts produced with support parameters had no significantly lower tensile strength than the comparative parts. Despite that, some porosity and around two percent of defects on the fracture surface for parts using the solid parameter set have been found. Parts with support parameters show no porosity, even though the energy density is around 30% lower compared to the solid parameter set.


Author(s):  
Hamed Hosseinzadeh

The powder bed fusion (PBF) metal additive manufacturing (AM) method uses an energy source like a laser to melt the metal powders. The laser can locally melt the metal powders and creates a solid structure as it moves. The complexity of the heat distribution in laser PBF metal AM is one of the main features that need to be accurately addressed and understood to design and manage an optimized printing process. In this research, the dependency of local thermal rates and gradients on print after solidification (in the heat-affected zone) was numerically simulated and studied to provide information for designing the print process. The simulation results were validated by independent experimental results. The simulation shows that the local thermal rates are higher at higher laser power and scan speed. Also, the local thermal gradients increase if the laser power increases. The effect of scan speed on the thermal gradients is opposite during heating versus cooling times. Increasing the scan speed increases the local thermal gradients in the cooling times and decreases the local thermal gradients during the heating. In addition, these simulation results could be used in artificial intelligence (AI) and machine learning for developing digital additive manufacturing.


2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]


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