Satoshi Yamane

Digital control of torch position and weld pool in MIG welding using image processing device

A digital computer control system for improving the stability of the torch position and weld pool shape in metal inert gas (MIG) welding is proposed. It is shown how the characteristic of the digital controller may be selected for yielding a desired transient behavior. >

Neural network and fuzzy control of weld pool with welding robot

The sensing and control of weld pool depth in robotic welding are discussed. A neural network-based method for measuring the depth is proposed, since the depth cannot be directly measured in real time. The weld pool depth is estimated by using the information obtained from the welding side. The surface shape of the weld pool and the width of the groove gap can be measured during the welding. The weld pool depth can also be measured after the welding. Training data were constructed from these numerical data. When the width of the groove gap changes, the weld pool depth changes too. The feedforward control system for the variation of the groove gap width just under the electrode can be constructed by observing the groove gap width before the electrode. The feedback control system was constructed in order to keep the output of the neural network constant. The fuzzy control system was constructed from the feedback control part and the feedforward control part. The validity of a neuro-fuzzy controller was verified by welding experiments.<<ETX>>

Adaptive control of back bead in V groove welding without backing plate

Abstract The formation of stable back beads in the first layer weld during one side multilayer welding is important to achieve high quality welded metal joints. The authors thus employed the switch back welding method for welding V groove joints without using backing plates. Moreover, in the field work, there is misalignment of both metal plates during set-up. The suitability of the welding conditions for each root gap and the misalignment were verified by observation of the arc, molten pool and external appearance of back beads. Welding conditions, namely, welding current, wire feedrate, weaving width, forward/backward stroke of switch back motion and welding speed, were controlled continuously according to root gap variations. Stable back beads were obtained for root gaps between 4.9 and 2.3 mm and misalignments between 0.1 and 2.8 mm.

Sensing and control of weld pool by fuzzy-neural network in robotic welding system

It is important to control the penetration depth of the weld pool during welding, so as to obtain a good-quality weld, but it may be difficult to detect the penetration depth directly by using a visual sensor. In order to detect the penetration depth, the authors propose a penetration depth model based on a neural network. During welding, a fuzzy controller adjusts the welding current so as to obtain the desired penetration depth. Since the performance of the fuzzy controller depends on fuzzy variables, its tuning can be performed by using the neural network model. The validity of the fuzzy neural network is verified by some welding experiments.

Controlling of torch attitude and seam tracking using neuro arc sensor

It is important to realize intelligent welding robots to obtain a good quality of weld. For this purpose, it is required to detect the deviation from the center of the groove, the torch height, and the torch attitude. In order to simultaneously detect these, the authors propose a neuro arc sensor as the sensor fusion by using a neural network. First, the authors deal with the welding phenomena as the melting phenomena in the electrode wire of the MIG welding. Next, the training data of the neural networks are made from the numerical simulations. A neuro arc sensor is trained so as to get the desired performance by the backpropagation method. The welding experiments are carried out to examine the performance of the neuro arc sensor. A good performance of the neuro arc sensor is obtained. By using it, the seam tracking can be performed in the T-joint welding.

Effect of power source characteristic on CO2 short circuiting arc welding

Abstract Some problems are reported concerning the observation of the weld pool and effects of the power source characteristic on arc stability in CO2 short circuiting arc welding. First, the effect of a power source with a constant voltage characteristic on CO2 short circuiting arc welding is investigated by analysing the behaviour of the voltage and the current. From the results of this analysis, the cause of spatter generation is identified. A new power source characteristic is then proposed to improve the stability and the self-regulation of the arc. By adjusting the power source characteristic, the metal transfer can be stabilised in the CO2 short circuiting arc welding process, i.e. the present authors have developed a power source having a non-linear characteristic. Its performance is verified by carrying out experiments.

Sensing and seam tracking of welding line in backingless V groove welding

Abstract The formation of stable back beads in the first layer weld during one side multilayer welding is important to achieve high quality welded metal joints. The authors tried to apply the switch back welding method to butt welding to join discs with flat metal plates without backing plates. During the welding, the gap was detected by processing the weld pool image taken with a CCD camera. Moreover, the tip of the electrode wire is changing owing to a curve of its wire extension in accordance with a rotation of the torch axis. Even though teaching is achieved before the welding, the weaving centre is shifted from the gap centre. The controller of the seam tracking was designed to prevent any steady state error.

Intelligent cooperative control system in visual welding robot

The quality of multi-layer welding depends on the welding in the first layer. In order to get high-quality welding, it is necessary to make a stable back-bead and to melt the base metals. In narrow-gap welding, it is difficult to control the bead height (deposited metal) and the back-bead (the melted area of the back side) simultaneously by using conventional welding. To improve this situation, the authors propose a cooperative control of the welding equipment, including the welding power source, the electrode wire feeder and the welding robot, i.e. the welding torch is not only oscillating on the groove but also moving back and forth. To control the heat input, the power source is controlled according to the torch motion (robot motion) too. In the forward process, the arc (the heat) is given to the root edges to get a wide back-bead. In backward process, a suitable bead height is obtained. The idea of this robot motion comes from the knowledge of skilled welding workers. The arc length must be kept short during the welding regardless of unexpected disturbances. Therefore, the weld pool and the arc position are observed by using a CCD camera. A personal computer processes image and adjusts the welding current and the torch motion. Welding experiments are carried out to verify the validity of the cooperative control method.

Neural control of weld pool in the robotic welding

This paper deals with some problems concerning the controlling of the weld pool shape. The model of the weld pool is represented by using the RC circuit, where the resistance R corresponds to the thermal resistance. The authors try to keep the voltage across the capacitor C constant, regardless of the variation of R, by controlling the applied voltage to the RC circuit. If the knowledge about the variation of the parameter of the plant is known, the performance of the controller may be improved. A neural network controller (NNC) with learning ability is applied to the control of the plant. A performance of NNC depends on the training data, the number of the unit in the hidden layers, and the input variables. A new method based on the experts knowledge is proposed to construct the network. That is, the authors determine the input variables from the pole assignment method. The validity of the NNC is verified by using numerical experiments.<<ETX>>

Feed forward control of back bead and bead height in narrow gap robotic welding

Abstract For high quality welding, it is necessary to form a stable back bead and to melt metal plates. In narrow gap welding, it is difficult to control the bead height and the back bead simultaneously using conventional welding. In order to solve this problem, a switch back welding method is proposed in which the welding torch is moved back and forth along the welding line. In the forward movement of the torch, the arc heat is given to the root edges to obtain a wide back bead. In the backward movement, suitable bead height is formed. From the fundamental experimental results, a numerical model was prepared for this type of welding. Using this model, the optimum stroke length was found. Its validity was verified by carrying out welding experiments.