Welding of Ti-6Al-4V alloy using dynamically controlled plasma arc welding process

A novel dynamically controlled plasma arc welding process was introduced,which is able tominimize heat input into the workpiece materials while maintaining desired full penetration,and it was used to weld Ti-6Al-4V alloy sheets.The microstructures,facture surfaces and microhardness of the welded joints were characterized by using optical microscope,scanning electron microscope （SEM） and Vickers microhardness tester.Comparing with welds such as gas tungsten arc and conventional plasma arc processes,the experimental results revealed the improvements when using the present process including：1） reducing prior-beta （β） grain size and prohibiting formation of hard martensite phases in the fusion zone due to the decreased heat input;and 2） better toughness and higher hardness.

Structural considerations in friction welding of hybrid Al_2O_3-reinforced aluminum composites

Comparative studies on the relationship between the welding parameters and joining efficiency in the friction welding of hybrid Al203-reinforced aluminum composites were conducted. Metal matrix composites （MMCs） with 37% （volume fraction） aluminum particle were joined by friction welding. The results show that the effects of the rotation speed on the reduction rate of particle size are greater than those of the upset pressure, and the area of the MMC weld zone decreases as the joining efficiency increases, while it is considered that the joining efficiency does not increase as the reduction rate of particle size decreases. During the macro-examination of the bonding interlace, a gray discolored region was observed on the bonding interface, and the center of the region was dark gray. After the micro-examination of the bonding interface, base metal made some second particulate formed by condensed alumina particulate but discoloration part distributed minute alumina particulate without second particulate. Consequently, it was also observed that rotational speed of 3 000 r/min and upset pressure of 63.6 MPa showed a very good.joint.

Relationship between interfacial structure and property of steel-mushy Al-28Pb bonding pate

The interfacial properties of steel-mushy Al-28Pb bonding plate with different interfacial structures, and the influence of ratio of Fe-Al compound at the interface on interfacial shear strength were investigated. The results show that there is a nonlinear relationship between the ratio of Fe-Al compound at the interface and the interfacial shear strength. When the ratio of Fe-Al compound at the interface is smaller than 71.4%, with the increase of the ratio of Fe-Al compound at the interface, the interfacial shear strength increases gradually; when the ratio of Fe-Al compound at the interface is larger than 71.4%, with the increase of the ratio of Fe-Al compound at the interface, the interfacial shear strength decreases continuously; when the ratio of Fe-Al compound at the interface is 71.4%, the largest interfacial shear strength 70.2MPa is obtained.

Research on numerical welding experiment of a thick spherical shell structure

In this paper, in order to predict the residual deformation of thick spherical structure, a welding program is compiled in APDL language based on Ansys and a numerical welding experiment of a welding example is carried out. The temperature field of welding was simulated firstly, then a thermal-structure coupling analysis was carried out, and at last the residual stress and deformation after welding were got. After that, the numerical experiment result was compared with physical experiment one. The comparative analysis shows that the numerical simulation fits well with physical experiment. On the basis of that, a three-dimensional numerical experiment of a thick spherical shell structure was carried out to get the changing rule of stress and deformation of a thick spherical shell structure during welding. The research is of great value to the prediction of residual deformation and high precision machining.

Correlation between microstructural features and tensile strength for friction welded joints of AA-7005 aluminum alloy

Similar friction welded joints of AA-7005 aluminum rods were fabricated using different combinations of process parameters such as friction pressure(1.0, 1.5 and 2.0 MPa) and friction time(10, 15 and 20 s). Interfacial microstructure and formation of intermetallic compounds at the joint interface were evaluated via scanning electron microscopy(SEM) equipped with energy dispersive spectrum(EDS), and optical microscopy(OM). Microstructural observations reveal the formation of intermetallic phases during the welding process which cannot be extruded from the interface. Theses phases influence the tensile strength of the resultant joints. From the tensile characteristics viewpoint, the greatest tensile strength value of 365 MPa is obtained at 1.5 MPa and 15 s. Finally, the role of microstructural features on tensile strength of resultant joints is discussed.

Classification of Ultrasonic Signs Pre-processed by Fourier Transform through Artificial Neural Network Using the Echo Pulse Technique for the Identification of Defects in Welded Joints of Structural Steel

It is due to the need to ensure the security and integrity of equipment, that the non-destructive tests have been increasingly used in the industrial sector. Among these, the ultrasonic pulse echo technique is the most used in industry, mainly for its simplicity and efficiency. With one transducer only, it is possible to emit the ultrasonic and receive the echo pulse. The ANNs （artificial neural networks） are artificial intelligence techniques that, when properly trained, align themselves to inspection tests becoming a powerful tool in the detection and fault identification. In this work, the echo pulse technique was used to detect discontinuities in welds, where ANNs were fed from the information obtained by digital signal processing techniques （Fourier transform）, to identify and classify three distinct classes of defects. Results showed that with the combination of feature extraction by Fourier transformation and classification with neural networks, it is possible to obtain an automatic defect detection system in welded joints with average efficiency.