Resistance Spot Welding System Research Articles

Resistance Spot Welding Gun System Development Based on C# and Solidworks

In this paper, the type selection of resistance spot welding guns and 3D part drawings library are developed based on the C# programming software and Solidworks environment. It is called rswg-swc software system. The selection method of resistance spot welding guns is analyzed, 3D graphic library about the general parts and series parts of welding gun is established .Utilizing the user interface, input the necessary parameters to choose corresponding product model, product assembly drawings and part drawing are created in Solidworks.

Performance Analysis of ANN Training Algorithms to Detect the Magnetization Level in the Magnetic Core of a Welding Transformer

The aim of this study is to perform an analysis of the different ANN methods employed to detect the saturation level in the magnetic core of a welding transformer. The magnetization level detector is a substantial component of a middle-frequency direct current (MFDC) resistance spot welding system (RSWS). The basic circuit of a resistance spot welding system consists of an input rectifier, an inverter, a welding transformer, and a full-wave rectifier which is mounted on the output of the welding transformer. The presence of unbalanced resistances of the transformer secondary windings and the difference in characteristics of output rectifier diodes can cause the transformers magnetic core to become saturated. This produces spikes in the primary current and finally leads to the over-current protection switch-off of the entire system. To prevent the occurrence of such a phenomena, the welding system control must detect and maintain the magnetic core saturation within certain limits. Previously, an Artificial Neural Network based detector was proposed to detect the saturation level. In this paper, we will take an in depth look at the different ANN methods that can be employed, analyze them and then decide which is the best method based on factors such as computational time, algorithm complexity, root mean square error and the gradient obtained. Three algorithms in total are evaluated including Resilient-Back propagation, Levenberg-Marquardt, Gradient-Descent. Based on the results obtained, the Levenberg- Marquardt and the Resilient Back propagation were found to be the best algorithms but the Resilient Back propagation is preferred due to reasons such as computational time and algorithm complexity. In terms of RMSE both gave almost the same values. It is also shown that the Gradient Descent algorithm cannot be

The Impact of the Voltage Generation Method on Acoustic Noise Emissions Caused by a Welding Transformer

This paper deals with the acoustic noise emissions caused by a welding transformer (WT) operating as part of a middle-frequency direct current resistance spot welding system (RSWS). The WT consists of an iron core, one primary winding, and two secondary windings. The primary winding is supplied by the voltage from the input converter while the full-wave diode output rectifier is connected to the two secondary windings in order to generate a direct welding current. In the case study, the alternating current primary voltage is generated in two different ways, by applying a pulse width modulation and two hysteresis controllers. The aim of this paper is to analyze how the voltage generation method influences the acoustic noise emissions caused by the WT. The analysis is based on the values of the supply current, the welding current, and the iron core flux density measured on a 160 kW industrial WT operating as a part of laboratory RSWS where the supply voltage is generated in two different ways. The results presented in the paper show that proper voltage generation method can substantially reduce the acoustic noise emissions caused by a WT.

Evaluation of Iron Core Quality for Resistance Spot Welding Transformers Using Current Controlled Supply

This paper reflects a newly developed method for evaluation of iron core quality for resistance spot welding (RSW) transformers. The classical methods for determination of the iron core quality are mostly based on a sinusoidal excitation. The proposed method is based on corresponding excitation by hysteresis controlled current in primary winding under no load operation, whereas consequently the primary current changes between its maximum and minimum value. Therefore, the operation point during the test is defined by the maximum magneto motive force (mmf) of the magnetic circuit. The tested iron core that reaches higher value of the magnetic flux density with the same maximum mmf, has lower average magnetic resistance and it is categorized as a better one, for the discussed RSW application. Furthermore, the value of the input reactive power is considered as an additional indicator for evaluation of the iron core quality. The proposed method is fully verified with numerical computations and laboratory measurements. The main advantage of the proposed method is that no extra equipment is required when testing the RSW systems.

유전알고리즘을 이용한 인버터 DC 저항점용접에서의 정전류퍼지제어기 최적화

Inverter DC resistance spot welding process has been very widely used for joining such as automotive body sheet metal. Because the lobe area of DC welding is larger than AC welding and DC welding has low electrode wear. So the use of Inverter DC resistance spot welding process has been further increased. And the application of high tensile steel is growing for light weight vehicle. To improve the weldability of high strength steel, the development of Inverter DC resistance spot welding system is more conducted. However, Inverter DC resistance spot welding system has a few problems. Current waveform is unstable and the expulsion has been occurred by characteristics of steel. In this study, inverter DC resistance spot welding system was made. And Fuzzy control algorithm was applied for constant current. The genetic algorithm was applied to optimize the fuzzy scaling factors, in order to optimize the fuzzy control.

Evaluation of workers exposure to magnetic fields

Following ICNIRP Guidelines of 1998, European Parliament in 2004 has stated the reference levels for workers exposure to electromagnetic fields. In low frequency regime, due to the nature of the basic mechanism of short term interaction, the exposure limits are based on the values of induced eddy currents inside human body, thus electromagnetic simulation is an important tool for the assessment of electromagnetic field exposure. This paper presents a method for computing eddy currents inside human body and applies the method to the evaluation of eddy currents induced by a resistance spot welding system. A comparison between results obtained with two different models of human body and with different discretization levels is performed and results are discussed.

Exposure of Working Population to Pulsed Magnetic Fields

Reference values of exposure for working population at extremely low frequency electromagnetic fields have been stated in ICNIRP Guidelines of 1998, and accepted by European Parliament in 2004. Nevertheless, quantification of coupling mechanism under pulsed field conditions is still an open question. The effect of complex non-sinusoidal or non-periodic waveforms is not univocally defined and several ways of estimating it have been proposed. This paper compares different ways of assessing effects of pulsed electromagnetic fields with frequency spectrum below 100 kHz and compare them to the eddy currents induced in one realistic model of human body by a resistance spot welding system supplied by in pulsed medium frequency direct current mode.

Artificial Neural Network Applied for Detection of Magnetization Level in the Magnetic Core of a Welding Transformer

This paper deals with the detection of saturation in the magnetic core of a welding transformer which is a part of a middle-frequency direct current (MFDC) resistance spot welding system (RSWS). It consists of an input rectifier, which produces dc bus voltage, an inverter, a welding transformer, and a full-wave rectifier that is mounted on the output of a transformer. During normal RSWS operation welding transformer's magnetic core can become saturated due to the unbalanced resistances of both transformer secondary windings and different characteristics of output rectifier diodes, which causes current spikes and over-current protection switch-off of the entire system. In order to prevent saturation of the transformer magnetic core, the RSWS control must detect that the magnetic core is approaching the saturated region. The aim of this paper is to present a reliable method for detection of magnetic core saturation that does not require an additional sensor. It is based on the artificial neural network (ANN). Its input is the measured primary current of the welding transformer. The applied ANN is trained to recognize the waveform of the current spikes in the primary current caused by the magnetic core saturation, which is used for magnetization level detection.

Prevention of Iron Core Saturation in Multi-Winding Transformers for DC-DC Converters

This paper deals with prevention of saturation in the iron core of a multi-winding transformer. It is a substantial part of dc-dc converters used in resistance spot welding systems. The discussed resistance spot welding system consists of a semiconductor input converter, a single-phase welding transformer with one primary coil and two secondary coils, and a full-wave output rectifier connected to the transformer's secondary coils. The paper shows that the interaction among magnetically nonlinear behavior of the iron core combined with unbalanced parameters of the circuits with the two transformer's secondary coils can cause iron core saturation even when elements connected to coils are passive elements. The first part of the paper focuses on analysis of saturation phenomena in multi-winding transformers. It is performed on specially designed laboratory transformer composed of the iron core in the form of two C-shaped segments and modular coils used to form the single-coil primary winding and two-coil secondary winding. Knowledge acquired on the laboratory transformer is applied to develop two different solutions for active prevention of the iron core saturation in multi-winding welding transformers. Both solutions are presented in the second part of the paper.

Detecting saturation level in the iron core of a welding transformer in a resistance spot-welding system

This paper deals with saturation level detection in the iron core of a welding transformer (WT), which is a part of the resistance direct current spot-welding system. The saturation level in the iron core must be detected and controlled in order to utilize the iron core. This work evaluates four different methods appropriate for detecting the saturation level in the transformer's iron core. These methods actually detect the instant the iron core starts to become saturated and generate those signals used during control, in order to prevent saturation. In method I a flux linkage value is used to detect the saturation level. In method II the partial derivative of the flux linkage versus magnetomotive force characteristic is applied. Method III uses the ratio between the induced voltages measured by the probe coil wound around the iron core and the probe coil placed on the surface of the iron core. Method IV is similar to method III. The flux measurement with a surface mounted probe coil as applied in method III is replaced in method IV by flux density measurement using a Hall sensor placed close to the iron core's surface. All the methods presented are evaluated by measurements performed on the iron core of an industrial 120 kVA spot WT.

Advanced Control of a Resistance Spot Welding System

This paper deals with a middle-frequency resistance spot welding system. It consists of an input converter, welding transformer, and a full-wave rectifier mounted at the transformer secondary. The welding current at the full-wave rectifier output is normally controlled by the pulse width modulated primary voltage of the transformer supplied by the input converter. The unequal ohmic resistances of the two transformer's secondary circuits and the different characteristics of the diodes of output rectifier certainly lead to the magnetic saturation which, consequently, causes the unwanted spikes in the transformer's primary current and over-current protection switch-off. This disadvantage of classical spot welding systems is completely eliminated by the proposed advanced hysteresis controller (AHC), which keeps transformer iron core saturation within prescribed bounds regardless of how unequal the ohmic resistances and diodes' characteristics in the transformer's secondary circuits are. This is achieved by a combined closed-loop control of the welding current and closed-loop control of the iron core saturation level. The proposed AHC assures a very short rise time of the welding current and the best possible utilization of the transformer iron core.

Opportunistic electrode replacement in a robotic spot welding system

This paper addresses the electrode replacement and general maintenance optimization problems for a robotic resistance spot welding system consisting of k non-identical guns. The electrode tip wear compensation methodology is introduced. Using the modelling results based on field data, a tip wear trend as well as high and low limits for tip usage are established. The expected failure time or replacement time for a specific tip is then predicted. Three kinds of replacement policies (corrective replacement, preventive replacement and opportunistic replacement) are described. Through a careful cost investigation, a simulation model for electrode opportunistic replacement in a 17-robot resistance welding system has been developed. An optimum electrode opportunistic replacement interval is then predicted, which achieves a maximum cost saving based on some simple operational assumptions. The total expected cost, number of tips replaced, production line stoppage times and the next replacement time can also be obtained.

Quality evaluation by classification of electrode force patterns in the resistance spot welding process using neural networks

Since resistance spot welding (RSW) has become one of the safest and most reliable processes for fabricating sheet metals, many quality estimation methods have been developed to ensure the welding qualities. In this paper, two kinds of quality evaluation method by classification of electrode force patterns using neural networks are proposed in a servo-controlled RSW system. Firstly, experiments were conducted under different welding conditions with various process parameters such as welding currents and electrode forces in order to determine the relations between force patterns and qualities. Secondly, experiments were conducted in order to generate basic data to train the proposed neural networks and finally to evaluate welding qualities through the classification into standard patterns. The proposed learning vector quantization (LVQ) net indicates the fast classification, showing a total success rate of 90 per cent for test data with five standard patterns. The proposed back-propagation (BP) net shows the precise classification with a total success rate of 95 per cent, considering a slightly longer time for classification due to the additional data process time. The results evaluated with the standard welding quality classes show the practical feasibility of the proposed classification methods.

A prototype fuzzy resistance spot welding system

In assembly automation, the need to perform on-line quality monitoring and to provide near real-lime inspection of resistance spot welds, has attained unsurpassed importance in industries. This paper describes the development of a prototype fuzzy control system for a two-stage resistance spot welding machine with potential of being incorporated into an automation line. It encompasses a new approach aimed at providing simultaneous control of more than two major welding parameters for achieving consistent quality spot welds by assessing the condition of the heat affected zone created. The prototype system, developed in C language, comes with a decision making mechanism and a quick search mechanism. Its rule-base contains a total of 125 heuristic control rules derived from literature reviews and interviews with experts and through experiments. The various factors affecting the quality of spot welds are outlined in the paper. The correlation between spot weld quality and welding parameters were examined using...