Online nugget diameter control system for resistance spot welding

The aim of this paper is to provide an integrated real-time control system for resistance spot welding (RSW), which is capable of producing welds with predetermined nugget diameters. Nugget diameter is a commonly used criterion for estimating the weld quality; thus, the system can be used for online quality control of RSW. The proposed system consists of two parts: a constant current controller and an online nugget diameter estimator. The constant current controller is used to guarantee the consistency of the nugget formation and growth during the welding process, while the online nugget diameter estimator can be used as a sensor for online estimation of the nugget diameter. The proposed online nugget diameter estimator is a mathematical function of the heat energy absorbed by the weld, which is taken into account only after the time when the first melting point of a weld appears. This time can be obtained by means of the dynamic resistance curve with a high resolution. A mathematical model of the online nugget diameter estimator is proposed and realized based on the experiment results and mathematical analysis. The welding process would be terminated when the difference between the actual nugget diameter and the predetermined desired value is within a given tolerance. According to a series of experiments, the welds used in the experiments had nugget diameters, which were well within the limits and the errors were within the given tolerance.     

Quality monitoring based on dynamic resistance and principal component analysis in small scale resistance spot welding process

The present study aims at solving weld quality monitoring problem in small scale resistance spot welding of titanium alloy. Typical dynamic resistance curves were divided into several stages based on the weld nugget formation process. A smaller electrode force or lower welding current was found to promote the initial resistance peak. The bulk material heating stage could not be detected under very high welding current condition. Electrode force effect on dynamic resistance and failure load was much smaller than that of welding current. Principal component analysis was made on discrete dynamic resistance values. The first principal component was selected as independent variable in regression analysis for quality estimation. A back propagation neural network model was then proposed to simultaneously predict the nugget size and failure load. The electrode force, welding current, welding time, and first five principal components were designed as network inputs. Effectiveness of the developed model was validated through data training, testing, and validation. The realtime and online quality monitoring purpose could be realized.     

An algorithm for the estimation of the quality of the spot welds

Spot welds are widely used in industry, especially in automotive, so welds must be reliable. One of the approaches to estimate the quality of spot welds is to use ultrasonic testing. Spot welding is used in the automotive repair industry as well. However, a spot weld testing device, dedicated for the automotive repair industry, is not available. The objective of this work was to develop an algorithm for estimation of the quality of spot welds, to be used in a simple device in the automotive repair industry. The algorithm developed identifies the peaks in the acquired signal and separates the main peaks (ultrasonic signal reflected from the backwall of the weld) from intermediate peaks (which identify the defects in the weld or undersized weld). Then, according to the peak distribution and peak amplitude variations in the signal, the quality of the weld is determined and an automatic pass or fail indication given. The algorithm was verified using a finite element model of a good weld, an undersized weld and a weld with a pore.     

Quality evaluation in resistance spot welding by analysing the weld fingerprint on metal bands by computer vision

This paper introduces a novel method for the quality evaluation of resistance spot welds. The evaluation is based on computer vision methods, which allow non-destructive on-line real-time processing. The input of the system is the image of a weld imprint on a metal band which covers the electrodes against wear and soiling. The shape and size of the structures within the imprint correlate with the nugget area and, therefore, allow an accurate estimation of the quality of the spot weld. The system segments the electrode imprint and computes the nugget area from the minimum and maximum axis of a fitted ellipse. This method does not need training samples to perform reliable quality estimation. Additionally, the used algorithms are easy to implement and efficient, which guarantees real-time ability. Since there is only a single low-cost camera needed, the hardware can be placed directly on the gun arm, which makes a fast evaluation possible.     

Quality monitoring of resistance spot welding based on electrode displacement characteristics analysis

A new method is developed to monitor joint quality based on the information collection and process in spot welding. First, twelve parameters related to weld quality are mined from electrode displacement signal on the basis of different phases of nugget formation marked by simultaneous dynamic resistance signal. Second, through correlation analysis of the parameters and taking tensile-shear strength of the spot-welded joint as evaluation target, different characteristic parameters are reasonably selected. At the same time, linear regression, nonlinear regression and radial basis function (RBF) neural network models are set up to evaluate weld quality between the selected parameters and tensile-shear strength. Finally, the validity of the proposed models is certified. Results show that all of the models can be used to monitor joint quality. For the RBF neural network model, which is more effective for monitoring weld quality than the others, the average error validated is 2.88% and the maximal error validated is under 10%. __________ Translated from Chinese Journal of Mechanical Engineering, 2006, 42(10): 176–181 [译自: 机械工程学报]     

Research on Microelectromagnetic Relays

A new microelectromagnetic relay is presented and fabricated based on micromachining technology, aiming at the miniaturization and high manufacturing efficiency of electromagnetic relays. This microrelay is composed of a lower magnetic circuit, a planar exciting coil, and an upper magnetic armature. A complete magnetic circuit is composed, and the “ON” and “OFF” states are controlled by the current of the exciting coil. The dimension of this microrelay is 5 mm × 5 mm × 0.4–mm. The fabrication process mainly includes lithography, sputtering, electroplating, etching, sacrifice-layer technology, etc. Electromagnetic force is calculated theoretically. The calculation results are used for the optimization design of the armature and the number of turns of the exciting coil. A microelectromagnetic relay is fabricated and the initial test results are given. The resistance of the exciting coil is about 300 Ω. The switch-on state resistance is about 1.7 Ω at an exciting current of about 50–mA. Translated from Journal of Beijing University of Technology, 2004, 30(2) (in Chinese)     

Power control of dual-motor electric drive for tracked vehicles

The fundamental problem of the power control for the driving of a dual-motor drive electric tracked vehicle is analyzed. The tracked vehicle and its electric drive system are mathematically modeled. Power control schemes of the dual-motor drive system is put forward, designed, and analyzed, including the distributed control system and the two control schemes speed-regulation and torque-regulation. The field experiment shows that the two types of drive control schemes realize the driving function of the vehicle feasibly and effectively. Obviously the comprehensive controller and two motors’ controllers are closely coupled in the “speed-regulation” control scheme, in which they must coordinate very well to guarantee the control. Contrastingly, in the “torque-regulation” control scheme, the comprehensive controller and two motors’ controller are not dependent closely when the accuracy and response of the torque controlling is guaranteed. The latter is simpler and more practical than the former.     

Evaluation of material degradation on the basis of ultrasonic tomography during the detection of scattered signals

Evaluation of the operational degradation of materials using nondestructive methods is an urgent problem of materials science. The nucleation and accumulation of dispersed flaws in structural materials occur from the very beginning of their exploitation and lead to changes in material properties, nucleation of macrocracks, and finally damage. Phenomenological approaches, using both direct and indirect methods are used to study and evaluate flaws [1]. Fractography is a direct method. The measurement of “flaws” (as relative deviations from a standard value) in various physicomechanical characteristics (density, modulus of elasticity, or microhardness) and electrical resistance are classified as indirect methods.     

Design and static performance of high speed machining centre with “direct drive”

“Direct drive” is an ideal method for speeding machine tools. In the structure of a CNC machining centre with “direct drive”, the linear motor’s primary and secondary parts are assembled into the worktable and machine bed respectively to directly drive the worktable. The built-in rotary motor is assembled in the spindle to realize the main transmission system of the machine tool “direct drive”. All mechanical transmission elements in machine tools are eliminated. High speed, efficiency, and accuracy are easily obtained. However, in this type of “direct drive” machining centre, the magnetic attraction force between the primary and the secondary linear motors and the dynamic impact at acceleration and deceleration are directly imposed on the machine tool, and influence the performance of the machining centre. This paper analyzes the special demands of “direct drive” on the machine centre, and introduces a new structure of the machining tool. The worktable and machine bed are optimized to meet the special demands of “direct drive”. Static performance simulation on the machining centre is done to reveal an ideal result.     

A computer-integrated framework for global quality chain management

Facing increasing pressure from customers to achieve greater responsiveness and reliability, as well as the current trend of globalization, many companies are considering global supply chain management as the core of their business strategy. This global tendency brings new challenges to traditional quality management approaches. It requires moving from the past focus of “my quality” to an emphasis on “our quality.” A new concept called global quality chain management (GQCM) is raised in this paper to figure out the principles, approaches, mechanisms, and processes involved in global quality management. In order to support GQCM, a computer-integrated and Internet-based system called the global quality chain management system (GQCMS) is proposed, with which the distributed partners in a global quality chain can cooperate as a whole. This paper outlines the overall framework of the GQCMS and presents the result of the Phase 1 development, known as the QQ-Enterprise system.     

Effects of tool–workpiece interface temperature on weld quality and quality improvements through temperature control in friction stir welding

A real-time wireless temperature measurement system has been developed and successfully implemented for closed-loop control of tool shoulder–workpiece interface temperature. The system employs two thermocouples in through holes and measures the shoulder and pin interface temperatures with an angular resolution as small as 10°. Both temperatures correlate with weld quality (mechanical testing and weld cross sections), e.g., all welds in 4.76-mm-thick 6061-T6 with an average shoulder interface temperature below 520 °C and an average pin interface temperature below 460 °C fail in the weld zone instead of the heat-affected zone, have unacceptable tensile strengths and in some cases voids. Similarly, welds with shoulder temperatures above the solidus temperature result in a degradation of the weld quality. It was found that a shoulder interface temperature of 533 °C results in the highest weld quality; hence, this temperature should be used as the setpoint temperature in the control system with a constant travel speed of 400 mm/min. The temperature measurement strategy was shown to be able to indicate welds with insufficient shoulder–workpiece contact, thus potentially identifying and preventing welds with detrimental weld quality due to lack of penetration. It was shown that backing plates of different thermal diffusivity change the heat flow out of the weld zone, hence weld temperature, and caused a measurable impact on the weld strength. By changing other process parameters, e.g., through a temperature control system, weld quality can be maintained in the presence of such changing thermal boundary conditions.     

Power control of dual-motor electric drive for tracked vehicles

The fundamental problem of the power control for the driving of a dual-motor drive electric tracked vehicle is analyzed. The tracked vehicle and its electric drive system are mathematically modeled. Power control schemes of the dual-motor drive system is put forward, designed, and analyzed, including the distributed control system and the two control schemes speed-regulation and torque-regulation. The field experiment shows that the two types of drive control schemes realize the driving function of the vehicle feasibly and effectively. Obviously the comprehensive controller and two motors’ controllers are closely coupled in the “speed-regulation” control scheme, in which they must coordinate very well to guarantee the control. Contrastingly, in the “torque-regulation” control scheme, the comprehensive controller and two motors’ controller are not dependent closely when the accuracy and response of the torque controlling is guaranteed. The latter is simpler and more practical than the former.     

A study on using scanning acoustic microscopy and neural network techniques to evaluate the quality of resistance spot welding

This paper shows that the quality of resistance spot welds can be evaluated using scanning acoustic microscopy (SAM). Two-layered coated spot-welded samples are investigated utilising a wide-field short-pulse scanning acoustic microscope with operation frequencies of 25, 50 and 100 MHz. Geometrical parameters, e.g. nugget area, maximum axis of nugget, and minimum axis of nugget, are acquired from C-scan images of weld nuggets using mathematical morphology techniques. These parameters serve as inputs for an artificial neural network (ANN) model to evaluate the quality of spot welds. The output of the model during the training process comprises the results of nugget peeling tests and expert opinions. The ANN can provide suggestions on weld quality with a higher than 95% correctness. A JAVA computer program is developed for image processing, ANN training, and ANN testing. With this model, the computer program can render the quality of spot welds that are close to those achieved using off-line destructive method.     

Robust design of spot welds in automotive structures: A decision-making methodology

Automotive structures include thousands of spot welds whose design must allow the assembled vehicle to satisfy a wide variety of performance constraints including static, dynamic and crash criteria. The objective of a standard optimization strategy is to reduce the number of spot welds as much as possible while satisfying all the design objectives. However, a classical optimization of the spot weld distribution using an exhaustive search approach is simply not feasible due to the very high order of the design space and the subsequently prohibitive calculation costs. Moreover, even if this calculation could be done, the result would not necessarily be very informative with respect to the design robustness to manufacturing uncertainties (location of welds and defective welds) and to the degradation of spot welds due to fatigue effects over the lifetime of the vehicle. In this paper, a decision-making methodology is presented which allows some aspects of the robustness issues to be integrated into the spot weld design process. The starting point is a given distribution of spot welds on the structure, which is based on both engineering know-how and preliminary critical numerical results, in particular criteria such as crash behavior. An over-populated spot weld distribution is then built in order to satisfy the remaining design criteria, such as static torsion angle and modal behavior. Then, an efficient optimization procedure based on energy considerations is used to eliminate redundant spot welds while preserving as far as possible the nominal structural behavior. The resulting sub-optimal solution is then used to provide a decision indicator for defining effective quality control procedures (e.g. visual post-assembly inspection of a small number of critical spot welds) as well as designing redundancy into critical zones. The final part of the paper is related to comparing the robustness of competing designs. Some decision-making indicators are presented to help the analyst to plan robust resistance spot welds designs along with quality controls in order to insure a specified level of structural performance. All examples are presented on a full body-in-white structure (one million dofs and thousands spot welds).     

Modelling knowledge related to the allocation of modular jigs for part fixturing using fuzzy reasoning

One the problems a workholder designer faces in attempting to gain knowledge about the modelling of the “wear” in a positioning system by means of allocating positioning devices to each “virtual”locating point is that this knowledge is often verbalized by experts in an imprecise and uncertain way. Knowledge comes from technological know-how, and is developed through experience, personal habits and production-specific requirements. Nevertheless, current modelling of “expert knowledge” does not allow us to represent the different semantics (such as imprecision and uncertainty) that are related to it. In this paper, we present a method based on fuzzy reasoning that is able to support the modelling of these different knowledge semantics .     

A Further Discussion on Trends in the Development of Advanced Manufacturing Technology

This paper is a supplement to “Trends in the Development of Advanced Manufacturing Technology” (Yang and Wu in Chin. J. Mech. Eng., 39: 73, 2003) but delves deeper into it. It first points out the strategic status of manufacturing industry in state development. Then, a detailed analysis is given on the features and trends in the development of advanced manufacturing technology in a total of 12 points from three aspects: “precision,” “extreme,” and “culture” from the aspect of the product itself; “green,” “rapidness,” “saving,” and “efficiency” during the manufacturing process; and “digit,” “auto,” “integration,” “networking,” and “intelligence” in view of the manufacturing method. In addition, it emphasizes that all the above aspects should be based on two base points: “manufacture” and “machinery.” Finally, it puts forth the guiding ideologies for the development of advanced manufacturing technology and the aspects China should give priority to in development, while stressing on the principles of independence, innovation and “human orientation.”     

Road profile estimation using neural network algorithm

This paper more specifically focuses on the estimation of a road profile (i.e., along the “wheel track”). Road profile measurements have been performed to evaluate the ride quality of a newly constructed pavement, to monitor the condition of road networks in road management systems, as an input to vehicle dynamic systems, etc. The measurement may be conducted by a slow-moving apparatus directly measuring the elevation of the road or using a means that measures surface roughness at highway speeds by means of accelerometers coupled with high speed distance sensors, such as laser sensors or using a vehicle equipped with a response-type road roughness measuring system that indirectly indicate the user’s feelings of the ride quality. This paper proposes a solution to the road profile estimation using an artificial neural network (ANN) approach. The method incorporates an ANN which is trained using the data obtained from a validated vehicle model in the ADAMS software to approximate road profiles via the accelerations picked up from the vehicle. The study investigates the estimation capability of neural networks through comparison between some estimated and real road profiles in the form of actual road roughness and power spectral density.     

Dynamic modeling and cooperative control of a redundant manipulator based on decomposition

This paper demonstrates the use of a redundant manipulator to execute multiple tasks specified at different points on the manipulator. This is accomplished by decomposing a redundant arm at an intermediate arm location, called “elbow”, into two non-redundant local arms, referred to as the “bascarm” and the forearm. This decomposition transforms a redundant arm into a “serially linked dual-arm system,” where the cooperation between the basearm and the forearm is carried out through the task distribution and the elbow control. To distribute a given task to individual local arms according to their dynamic capabilities, the Cartesian space model of a serially linked dual-arm system is derived using Lagrangian mechanics. The Cartesian space dynamic model enables us to quantify the dynamic capbilities of individual arms based on two hyper ellipsoids: the Cartesian Force Ellipsoid (C. F. E.) representing the range of Cartesian forces due to the unit norm of joint torques, and Cartesian Acceleration Ellipsoid (C. A. E.) representing the range of Cartesian accelerations due to the unit norm of Cartesian forces. In addition to the local dynamic characteristics, the global task requirements such as singularity avoidance, joint torque limit avoidance, motion generation efficiency, and accurate motion control, are improved by elbow control. Elbow control can also be used to execute a subtask at the elbow, for example, obstacle avoidance.     

Internal defect and process parameter analysis during friction stir welding of Al 6061 sheets

Welding parameters like welding speed, rotation speed, plunge depth, shoulder diameter etc., influence the weld zone properties, microstructure of friction stir welds, and forming behavior of welded sheets in a synergistic fashion. The main aims of the present work are to (1) analyze the effect of welding speed, rotation speed, plunge depth, and shoulder diameter on the formation of internal defects during friction stir welding (FSW), (2) study the effect on axial force and torque during welding, (c) optimize the welding parameters for producing internal defect-free welds, and (d) propose and validate a simple criterion to identify defect-free weld formation. The base material used for FSW throughout the work is Al 6061T6 having a thickness value of 2.1 mm. Only butt welding of sheets is aimed in the present work. It is observed from the present analysis that higher welding speed, higher rotation speed, and higher plunge depth are preferred for producing a weld without internal defects. All the shoulder diameters used for FSW in the present work produced defect-free welds. The axial force and torque are not constant and a large variation is seen with respect to FSW parameters that produced defective welds. In the case of defect-free weld formation, the axial force and torque are relatively constant. A simple criterion, (?τ/?p)_defective?>?(?τ/?p)_{defect free} and (?F/?p)_defective?>?(?F/?p)_{defect free}, is proposed with this observation for identifying the onset of defect-free weld formation. Here F is axial force, τ is torque, and p is welding speed or tool rotation speed or plunge depth. The same criterion is validated with respect to Al 5xxx base material. Even in this case, the axial force and torque remained constant while producing defect-free welds.     

SPOT WELDING QUALITY FUZZY CONTROL SYSTEM BASED ON MULTISENSOR INFORMATION FUSION

The multisensor information fusion technology is adopted for real time measuring the four parameters which are connected closely with the weld nugget size(welding current,electrode displacement,dynamic resistance,welding time),thus much more original information is obtained.In this way,the difficulty caused by measuring indirectly weld nugget size can be decreased in spot welding quality control,and the stability of spot welding quality can be improved.According to this method,two-dimensional fuzzy controllers are designed with the information fusion result as input and the thyristor control signal as output.The spot welding experimental results indicate that the spot welding quality intelligent control method based on multisensor information fusion technology can compensate the influence caused by variable factors in welding process and ensure the stability of welding quality.