Tube walls are an essential part of the thermal power plant boiler. During the operation of the boiler, the heating surface of the tube walls are exposed to furnace particles, intense heat, and chemical components resulting from the combustion reaction. These cause corrosion and wear, which permanently collapse the tubes, and affect the reliability and performance of the boiler. Therefore, a protection layer of heat and corrosion-resistant material is typically welded on the surface of the tube walls. In this study, a dedicated weld overlay automatic system is proposed. The downward welding technique with the pulse gas metal arc welding (GMAW) process is used to accomplish the proposed approach. The system generates and plans beads sequence based on the analysis of the tube walls geometry. The inverse kinematic theory was used to calculate the coordinates and transformations of the welding torch. Then, a mathematical model for the welding torch trajectory was established. A SIMOTION controller was adapted for motion control. A weld-tracking system based on the adaptive neuro-fuzzy inference system (ANFIS) was used to solve the welding distortion and the assembly error. The experiment results show that the proposed design is efficient and reliable compared to previous methods. The degree of automation and the weld overlay quality of the boiler tube walls have been notably improved.

Hybrid systems of the fuzzy logic and neural networks, are widely spread in real world problems with high effectiveness and versatility for different kinds of applications. The state description of unknown plant by using mathematical models, sometimes, is difficult to obtain. The fuzzy logic systems with their ability of tackling imprecise knowledges, and neural networks with their advantages of establishing a relationship between the inputs and the outputs of the system, are represented as qualified tools for systems of unknown plant. Furthermore, the hybrid systems which utilize the features of the fuzzy logic and Neural networks has been employed for better characteristics. Whilst, there are several different architectures of the neuro-fuzzy system proposed in literature, this article come out to highlight the common known architectures of how these techniques fuse together to build an enhanced system that can complement the lack of each method individually and improve the system performance over all.

The membrane wall is one of the important parts in the boiler industry. It is a pipe-plate structure; The length of the pipe is much longer than it is outer diameter. The chemical reactions of the liquid inside the boilers lead to corrosion problem of the membrane wall. In order to protect the membrane wall from corrosion, overlaying weld should be applied. The structure of the membrane wall has low stiffness and can be easily deformed. Therefore, for automatic overlaying weld, a sensor is required to ensure the distance between the welding torch and the membrane wall. In this paper, a tracking contact sensor based on the potentiometer is introduced for membrane wall pipes. The proposed sensor is composed of three displacement detectors. The left and right ones detect the position deviation between the welding torch and the pipe in the left and right sides, respectively. The middle one detects the deviation between the torch and the pipe in the middle point. Hence, based on the negative feedback from the sensor, the torch position will be adjusted. Finally, the real-time tracking of the torch to the membrane wall is realized and the problem of welding position deviation due to the membrane wall deformation is determined.