Kazuhiko Eguchi

Feed forward control of back bead for root gap variation in V-groove welding without backing plate

A stable back bead in the first layer of one-sided multilayer reinforced welding is important to obtain goodquality welds. For this reason, the method of back bead welding with the back root retained in place with a ceramic or other type of backing plate is generally used. During fabrication of box-shaped structures, however, it is in many instances difficult to remove the backing plate after welding. Manual backing plate removal is also incompatible with the needs of automatic welding procedures, so that, for reasons of fabrication costs, it is desirable to weld such structures without the use of a backing plate. In this situation, it is imperative to control the welding conditions, such as the welding current, wire feedrate and welding speed as well as the torch position, including weaving, in response to any external disturbances, such as groove shape or root gap variations. The purpose of this study is to establish a welding procedure with a high degree of adaptability to such external disturbances. This article describes an investigation of the welding conditions being sequentially set in response to the root gap regarded as strongly affecting back bead formation and further outlines a back bead feed forward control system based on root gap detection.

An MOS Digital Network Model on a Modified Thevenin Equivalent for Logic Simulation

A novel analytical model of MOS digital networks, which is based on a modified Thevenin equivalent, is described. The model can handle all the primary circuits inherent in MOS technology, such as transistor logics, wired-ORs, tri-state circuits, charge-share operation, and bidirectional pass transistors etc., with precise estimation of delay time. The model has been implemented in a logic/fault simulator, named HASL-GT. Performance of 4 to 10 k events/sec has been obtained on HITAC M-200H(8MIPS). Fault simulation capability has also been implemented using the concurrent method.

Estimation of arc length and wire extension using neural network

The automatisation of arc welding using robots has progressed in recent years as skilled welding technicians become more and more scarce. For automatic welding, it is essential to implement methods for sensing the welding phenomena; the requirements for weld quality are high so improvement and movement towards highly functional detection accuracy are desirable. It is important to measure the arc length in order to obtain a continuously stable weld quality, regardless of the torch position deviation from the base metal or the molten pool. The objectives for this article are to show how real-time sensing of the arc length and the electrode extension are feasible not only under steady state conditions but also under transient state conditions and to indicate how to construct a highly versatile system by devising a simple model using a neural network. Even for weaving welding within the groove, the detection of arc length and wire extension in the transient state is indispensable for arc length control, torch position control and the weld line tracking control of the weave centre. This article explains the most fundamental examples of the detection of arc length and wire extension when the arc is started on a flat plate.

Fuzzy inference for the initial population of genetic algorithms applied to VLSI floorplanning design

VLSI floorplanning design automation based on soft computing is discussed. A novel approach based on the fusion of genetic algorithms and fuzzy inference for the automation of VLSI floorplanning design is proposed. The fuzzy rules are used to infer the initial position of the on-chip blocks based on analysis of the accumulated knowledge of the expert design engineer. Only the dominant combinations of place and block are inferred. Blocks deemed suitable candidates for placement at the center, relative to the four-corners of the chip, are inferred. These inferences are then reflected in the initial population of the genetic algorithms. The rest of the block placement phase is entrusted to the genetic algorithms. Experimental software to implement the proposed approach was developed. This was in turn used to perform computer-based experiments. The results of the experiments showed a level and quality of placement close to that of the expert design engineer.

Sensing of Arc Length and Wire Extension Using Neural Network in Robotic Welding

It is important to design intelligent welding robots to obtain a good quality of the welding. It is required to detect bead height and deviation from center of gap and to control arc length and back bead by adjusting welding conditions such as welding speed, power source voltage and wire feed rate. Authors propose arc sensor using neural networks to detect arc length and wire extension. By using them and by means of geometric method, the bead height is detected. Moreover, authors propose switch back welding method to get stable back bead. That is, welding torch is not only woven in the groove, but also moved backward and forward.

Application of multilayered fuzzy inference to the tracking of the orbit on a two dimensional plane using industrial robot

This paper deals with the problem concerning the tracking of the orbit on the two dimensional plane with an arm type welding robot. New methods with a multilayered fuzzy controller are proposed for solving this problem. The performance of a fuzzy controller depends on the fuzzy variables and the control rules. Control rules are constructed from the knowledge of the robot operator. The fuzzy variables can be adjusted owing to the shape of the orbit obtained by using a CCD camera.