Friction stir processing (FSP) has emerged as an effective secondary processing technique to improve the microstructure and properties of aluminum matrix composites (AMCs). Al/(0–15 wt%) Al3Fe AMCs ...were prepared by adding pure iron powder to molten aluminum and subjected to FSP. The microstructural changes before and after FSP were studied using OM, SEM, EBSD and TEM. Cast composites exhibited coarse grains, segregation, pores and sharp-edged particles. The distribution of particles was rearranged into a homogeneous distribution after FSP. Casting defects such as pores were eliminated. The sharp edges of Al3Fe particles were removed and rounded into near spherical shape. The grain size reduced remarkably due to severe plastic deformation and the pinning effect of reinforced particles. The density of dislocations increased considerably after FSP. The microstructural changes resulted in an improvement of tensile strength and ductility. The possible strengthening mechanisms were reported.
•Friction stir processing of Al/(0–15 wt%) Al3Fe composites.•Total rearrangement of particles into a homogenous distribution occurred.•Polygonal shape Al3Fe particles were broken down into fine sized particles.•Grain size of cast composites were reduced to extremely fine size.•Tensile strength was improved considerably after processing.
•Polypyrrole coatings were successfully deposited on rheo-cast Al- 4.5% Si alloy.•Eutectic silicon and intermetallic particles increase the electrodeposition rate.•Polypyrrole coatings can relatively ...protect the Al-Si alloy in 0.6 M NaCl solution.•Barrier effect and passivation protection mechanism can be suggested.•Casting related defects on the coating’s surface affect the corrosion protection.
Electropolymerization of polypyrrole coatings in the presence and absence of sodium nitrate was applied on rheo-cast Al-4.5% Si alloy and pure aluminum. The results showed that the eutectic silicon phase and intermetallic particles in the alloy’s microstructure increase the electrodeposition rate in comparison to the pure aluminum substrate.
The electrochemical and microstructural studies show that the polypyrrole coatings are able to protect the surface due to the barrier properties and the passivation protection provided by the reduction of the conductive polymer. The coating electrodeposited from sodium nitrate-containing electrolyte presented improved protection for longer immersion time.
Localized formation of a thick oxide layer as a result of the drastic galvanic coupling at the polypyrrole/aluminum interface leads to blister formation and failure of the coating. It was revealed that the coating could be deposited into the porosities produced by the casting related defects, but in most cases, this affects the corrosion protection leading to imminent failure.
Although die-casting is one of the most popular mass production processes of precise metal parts, the manufacturing environment of the die-casting factory remains at the traditional level. In this ...study, we developed three core technologies to realize a smart-factory platform for die-casting industry: 1) a novel cost-effective product-tracking technology to obtain high-quality process data providing individual product information, 2) an advanced process data acquisition system that considers process failure, and 3) a fault detection module based on an artificial neural network. Our newly developed systems for the die-casting process were verified using 1500 test production. Based on the pilot production data, we developed a fault detection module with the pre-processing of time series temperature and pressure measurement data. The developed fault detection module shows 96.9 % accuracy for untrained data. The technologies developed in this study are expected to be a promising smart-factory platform to reduce the defect rate and production cost in die-casting industry.
X-ray flaw detection is a key link in the detection of internal defects in titanium alloy castings which are used for most important components in aeroengines. However, the existing manual defect ...detection methods from the X-ray images have common drawbacks such as unstable artificial recognition, misdetection, misjudgment, fails of quantitative analysis, huge workload, and low-quality inspection efficiency. To avoid these drawbacks, this paper proposes a new artificial intelligent (AI) method to detect and recognize the aerospace titanium casting defects from the X-ray images. It includes the target defect positioning method named as filtered selective search algorithm (FSS) and the defect classification method named as evenly distributed convolutional neural network (ED-CNN). In the target positioning step, through statistical analysis of defect characteristics, a filtered selective search algorithm is built with two filters (size and edge curvature). In this way, the FSS algorithm can position the defects with almost 100 % of accuracy, hence avoid missed detection and false detection. In the target classification step, an ED-CNN is constructed with a similar structure of the same number of layers in each feature extraction stage, and its entire architecture is evenly distributed. Compared with other three classic high-performance convolutional neural network models (AlexNet, VGG16 and VGG19), the ED-CNN model has the best performance. The ED-CNN model was tested with 324 targets from 50 original images, a classification accuracy of nearly 90 % was obtained for low density holes, porosity, linear defects, high density inclusions and casting structure. The FSS/ED-CNN method of two phases defect detection proposed in this paper can achieve accurate positioning and high accurate classification of typical defect targets, and is expected to solve the common drawbacks of "manual defect detection". The newly-proposed FSS/ED-CNN method has important research significance and engineering value.
Abstract
Centrifugal casting magnesium alloy pipe has been widely used. Still, because of its poor mechanical properties, it isn’t to meet the needs of the working environment, which limits its ...development in civil and industrial fields. Therefore, it is necessary to study the centrifugal casting process of magnesium alloy. In this paper, AZ80 magnesium alloy is used as the research material, and the numerical simulation of the centrifugal casting process is carried out by ANSYS Fluent software. The influence of different variable conditions on the solidification rate is analyzed, and a concept of defect ratio is proposed. The post-processing software is used to write an expression for macroscopic analysis of pore defect ratio on the outer surface of the casting, using which the influence of defect ratio under different variables is given. The research aims to guide the centrifugal casting experiment and predict the defects, greatly saving resources and costs.
•Solid feeding for the shrinkage accommodation caused the deterioration on the ductility.•The elimination of the intergranular eutectic network by heat treatment is important to mechanical ...properties.•Solidification location sequence dominates the uniformity of microstructures and properties of the asymmetric parts.
In this work, 7075 Al alloy, a high-strength wrought aluminum alloy with high hot tearing sensibility, was used in the squeeze casting of an asymmetric part. The solidification defects, microstructures and mechanical properties of the part solidified under different forming pressures were studied. Furthermore, the uniformities of the microstructures, mechanical properties and the solidification mechanisms were investigated. Results show that increasing the forming pressure is helpful to improve the liquid/solid feeding for counteracting the particularly serious shrinkage during the wide mushy zone of 7075 Al alloy. Therefore, the solidification defect can be avoided. Moreover, increasing the forming pressure is helpful to not only obtaining fine equiaxed grains, but also diminishing the intergranular segregation of alloying elements. With the increasement of forming pressures, the strengths of the part increased, along with the decreases in the ductile due to the work hardening resulted from the serious solid feeding. The microstructures and mechanical properties are impacted by the solidification rate of the melt at different regions. When the forming pressure was 150 MPa, fine microstructures and excellent mechanical properties were obtained. The uniformity of the microstructures and mechanical properties are dominated by the solidification location sequence of the melt. Further on, it is determined by the thermal gradient of the melt at different locations. For 7xxx series alloys, more solid feeding is needed for counteracting the serious shrinkage at the first solidified regions, causing a work hardening and associated strengths increasements. A near uniform part thickness and direct feeding loads are appreciated to improve the uniformities. In this work, the optimal tensile properties tested in the part were tested to be as follows: the yield strength (YS), ultimate tensile strength (UTS), and elongation (EL) are 345.5 MPa, 483.2 MPa, and 7.6%, respectively. The UTS uniformity is tested to be 86.4%.
High-Zn aluminum casting alloys usually contain coarse dendrites, network eutectoid structure and casting defects which deteriorate the mechanical properties seriously. In order to overcome these ...problems, the combination of melt spinning and extrusion was explored for microstructure modification in this work. A high-Zn aluminum alloy (Al–27Zn-1.5Mg-1.2Cu-0.08Zr) was prepared by melt spinning and extrusion. The results show that the melt spun alloy mainly consists of micro-sized network-like grain boundary (GB) η-MgZn2 structure (η phase) and disc-like precipitates (GP-zone, η′-phase and η-precursor) embedded into fine α-Al grains with high solute atomic concentration. After extrusion, the grain size of α-Al is further refined due to the recrystallization, and primary network GB η-phase structures are transformed to granular η particles. Moreover, the extrusion induces the precipitation of nano-sized η′-phase, η-precursor and Zn phases. As a result, the alloy exhibits a high tensile strength of 485 MPa and a reasonable elongation of 5.2%. The contributions of grain boundary, dislocation, solid solution and precipitate strengthening to the yield strength are calculated according to the microstructure analysis, and it is found that precipitation strengthening is the main strengthening mechanism in this alloy. Fracture analysis shows that micro-cracks preferentially occur at α-Al/η phase interfaces due to interfacial de-cohesion, and propagate along the GBs.
•A high-Zn Al alloy was designed and prepared by melt spinning and extrusion.•Melt spinning obtains fine grain size and high solute solubility of matrix.•Extrusion induces the precipitations of η′-phase/η-precursor and Zn, and refine network structure.•Precipitate strengthening is the main strengthening mechanism.
Aluminum alloy castings have a high utilization rate in the automotive industry, and its quality directly affects the safety performance of the mechanical components. Hence, casting quality ...management is vital during the casting production process. This paper presents a weakly-supervised Convolutional Neural Network model to recognize defects based on casting X-ray images. These images are divided into two classes including defective and non-defective. Firstly, attention maps are generated to represent the defective parts by weakly-supervised learning for each image. Then mutual-channel loss combined with the cross-entropy loss function encourage the network to focus on discriminative features. Simultaneously, a novel data-augmentation methods guided by these attention maps is proposed to enlarge the dataset. The test accuracy achieves 95.5%, and the recall is 96.0%, which means our model is accurate and robust. The efficiency of the proposed approach is verified by comparing the state-of-art approaches and the ablation experiments.
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•A weakly supervised convolutional neural network for classification is proposed.•The defective castings with the X-ray casting images are classified automatically.•The attention-guided data augmentation enlarges the dataset effectively.•The mutual-channel loss focuses on subtle discriminative details in two classes.
•Effects of porosity on size effect and scatter of fatigue strength are investigated.•Two alloys with different degrees of porosity are used.•Magnitude of size effect and scatter are linked to the ...population defects.•High density and large size defects lead to minor size effect and less scatter.•Low density and small size defects induce large size effect and high scatter.
Cast Al-Si alloys have been widely used in automotive applications with regard to their low density and excellent thermal conductivity. Many components made of these alloys are subjected to cyclic loads which can lead to fatigue failure. Furthermore, for these materials the well know size effect in fatigue, whereby the fatigue strength is reduced when the size is increased, can be significant and need to be properly evaluated. This paper analyses the role of casting defects on the fatigue strength’s size effect sensitivity. A uniaxial fatigue testing campaign (R = 0.1) has been conducted using two cast aluminium alloys, fabricated by different casting processes (gravity die casting and lost foam casting), associated with the T7 heat treatment, and with different degrees of porosity. The fatigue response of different specimens (smooth and notched) with different stressed volumes has been investigated. The first part of this article is dedicated to the experimental characterization of the size effect in both alloys via the concept of the Highly Stressed Volume. The second part investigates the effect of the Highly Stressed Volume on the critical defect size via Kitagawa-Takahashi diagrams. The results show that the magnitude of the size effect and the experimental scatter are strongly linked to the characteristics of the defect population present in the alloy. It is revealed that the alloy B, with a high density of pore and a population of defects with relatively large size, shows non-significant size effect and less scatter in fatigue strength. In comparison, alloy A that exhibits a low density of pore and a population of defects of relatively small size manifests significant size effect and high scatter in fatigue strength.
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