The Experts below are selected from a list of 16587 Experts worldwide ranked by ideXlab platform
Fukuhisa Matsuda - One of the best experts on this subject based on the ideXlab platform.
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effect of shielding conditions of local dry cavity on Weld Quality in underwater nd yag laser Welding
Journal of Materials Processing Technology, 2006Co-Authors: Xudong Zhang, Eiji Ashida, Susumu Shono, Fukuhisa MatsudaAbstract:Abstract During underwater laser beam Welding (LBW), the Welding Quality is severely influenced by the shielding condition of the local dry cavity. In this paper, the stability of the local dry cavity and the effect of shielding condition on the Weld Quality during laser Welding of Type 304 stainless steel were investigated. Firstly, Welding experiments under various water depths without any way to exclude water from the Welding zone were performed. It was found that one kind of laser-induced plasma having strong shielding effect to the incident laser beam forms when the laser irradiates the water directly if the water depth is larger than 3 mm. This shielding effect will lead to the impossibility of deep penetration Welding in water. So in the Welding, a water curtain nozzle was used to form a local dry cavity. The effect of the shielding conditions, e.g. water flow rate, gas flow rate and water flow angle, on the stability of the local dry cavity was studied. The Welding results under various shielding conditions show the relationship between the shielding condition and the Quality of the Weld bead.
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relationship between Weld Quality and optical emissions in underwater nd yag laser Welding
Optics and Lasers in Engineering, 2004Co-Authors: Xudong Zhang, Wuzhu Chen, Eiji Ashida, Fukuhisa MatsudaAbstract:In underwater laser Welding (LBW), the Weld Quality is very dependent on the shielding conditions of the local dry cavity when other Welding parameters are fixed. Thus, diagnosing the stability of the local dry cavity is the key to monitoring of underwater LBW. In this work, a sensing system containing two optical sensors was set up to detect the infrared and ultraviolet waveband of the optical emissions induced in the Welding. The effect of water on the laser Welding was studied first by conducting direct underwater Welding, which was performed without any method to exclude the water from the Welding zone. A kind of plasma that has strong ultraviolet emission formed if the water depth was more than several millimeters, which considerably reduced the penetration depth. Then a gas-shielding nozzle was used to form a local dry cavity for underwater LBW. The relationship between the optical signals and the Weld Quality with various shielding conditions were investigated. The results show that the detected signal well reflects the shielding condition variations of the local dry cavity. The optimal shielding condition could be determined by signal stability.
Mihaela Banu - One of the best experts on this subject based on the ideXlab platform.
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online Quality inspection of ultrasonic composite Welding by combining artificial intelligence technologies with Welding process signatures
Materials & Design, 2020Co-Authors: Baicun Wang, Tae Hwa Lee, Mihaela BanuAbstract:Abstract Ultrasonic Welding is a joining technology suitable for carbon-fiber-reinforced thermoplastic (CFRTP) components because of its high throughput, and ease of automation. An effective online Weld-Quality inspection technology can promote the industrial application of ultrasonic composite Welding. Literature focused on the Quality inspection of ultrasonic composite Welding is scarce. To address this, the present study proposes an online Weld-Quality inspection method for ultrasonic composite Welding by combining artificial intelligence (AI) technologies with Welding process signatures. The failure load in a tensile-shear test and the Weld Quality level (i.e., under Weld, normal Weld, and over Weld) are predicted simultaneously using artificial neural network (ANN) and random forest (RF) models. Eight features consisting of the duration and energy at each Welding stage are extracted from the process signatures as independent variables. The results indicate that both the ANN and RF models exhibit high prediction accuracies. The Weld Quality can be assessed comprehensively and reasonably by considering both the failure load and Weld Quality level. The findings of this study demonstrate the feasibility of online Weld-Quality inspection for ultrasonic composite Welding.
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Weld Quality Prediction in Ultrasonic Welding of Carbon Fiber Composite Based on an Ultrasonic Wave Transmission Model
Journal of Manufacturing Science and Engineering, 2019Co-Authors: Zhiwei Liu, Tae Hwa Lee, Junqi Shen, Mihaela BanuAbstract:Ultrasonic Welding has been widely used in joining plastic parts since it is fast, economical, and suitable for automation. It also has great potential for joining thermoplastic composite structures in the aerospace and automotive industries. For a successful industrial application of ultrasonic composite Welding, it is necessary to have effective Weld Quality prediction technology. This paper proposes a model for Weld Quality prediction by establishing a correlation between ultrasonic wave transmission and Welding process signatures. The signatures, Welding power, and force are directly related to the Weld Quality. This model is used to predict the Weld Quality with three contact conditions and validated by experiments. The results show that the Quality model performs well when a centralized and consistent contact condition is achieved. The model provides a process physics-based solution for the online Weld Quality prediction in ultrasonic Welding of carbon fiber composite.
Xudong Zhang - One of the best experts on this subject based on the ideXlab platform.
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effect of shielding conditions of local dry cavity on Weld Quality in underwater nd yag laser Welding
Journal of Materials Processing Technology, 2006Co-Authors: Xudong Zhang, Eiji Ashida, Susumu Shono, Fukuhisa MatsudaAbstract:Abstract During underwater laser beam Welding (LBW), the Welding Quality is severely influenced by the shielding condition of the local dry cavity. In this paper, the stability of the local dry cavity and the effect of shielding condition on the Weld Quality during laser Welding of Type 304 stainless steel were investigated. Firstly, Welding experiments under various water depths without any way to exclude water from the Welding zone were performed. It was found that one kind of laser-induced plasma having strong shielding effect to the incident laser beam forms when the laser irradiates the water directly if the water depth is larger than 3 mm. This shielding effect will lead to the impossibility of deep penetration Welding in water. So in the Welding, a water curtain nozzle was used to form a local dry cavity. The effect of the shielding conditions, e.g. water flow rate, gas flow rate and water flow angle, on the stability of the local dry cavity was studied. The Welding results under various shielding conditions show the relationship between the shielding condition and the Quality of the Weld bead.
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relationship between Weld Quality and optical emissions in underwater nd yag laser Welding
Optics and Lasers in Engineering, 2004Co-Authors: Xudong Zhang, Wuzhu Chen, Eiji Ashida, Fukuhisa MatsudaAbstract:In underwater laser Welding (LBW), the Weld Quality is very dependent on the shielding conditions of the local dry cavity when other Welding parameters are fixed. Thus, diagnosing the stability of the local dry cavity is the key to monitoring of underwater LBW. In this work, a sensing system containing two optical sensors was set up to detect the infrared and ultraviolet waveband of the optical emissions induced in the Welding. The effect of water on the laser Welding was studied first by conducting direct underwater Welding, which was performed without any method to exclude the water from the Welding zone. A kind of plasma that has strong ultraviolet emission formed if the water depth was more than several millimeters, which considerably reduced the penetration depth. Then a gas-shielding nozzle was used to form a local dry cavity for underwater LBW. The relationship between the optical signals and the Weld Quality with various shielding conditions were investigated. The results show that the detected signal well reflects the shielding condition variations of the local dry cavity. The optimal shielding condition could be determined by signal stability.
Dipten Misra - One of the best experts on this subject based on the ideXlab platform.
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A sequentially integrated multi-criteria optimization approach applied to laser transmission Weld Quality enhancement—a case study
The International Journal of Advanced Manufacturing Technology, 2013Co-Authors: Bappa Acherjee, Arunanshu S. Kuar, Souren Mitra, Dipten MisraAbstract:In the present research, a sequentially integrated optimization approach, based on Taguchi method, response surface methodology, and desirability function analysis, is proposed for evaluating the optimal set of laser transmission Welding parameters. Two Quality characteristics namely, Weld strength and Weld width, and three Welding parameters namely laser power, Welding speed, and focal position are selected for experimental work. Taguchi Quality loss function is first used to find the optimum level of control factors. The outputs of Taguchi analysis is further used in central composite design for developing response surface models. Desirability function analysis is performed next using the developed response surface models, to evaluate the optimal parameters setting by considering multiple objectives. The Weld Quality is improved markedly at the optimal process condition, as verified by additional confirmation tests. The performance of the proposed optimization approach is also compared with the Taguchi method and grey–Taguchi method and found that the proposed optimization approach gives better results than the other two techniques.
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application of artificial neural network for predicting Weld Quality in laser transmission Welding of thermoplastics
Applied Soft Computing, 2011Co-Authors: Bappa Acherjee, Subrata Mondal, Bipan Tudu, Dipten MisraAbstract:The present work establishes a correlation between the laser transmission Welding parameters and output variables though a nonlinear model, developed by applying artificial neural network (ANN). The process parameters of the model include laser power, Welding speed, stand-off distance and clamping pressure; whereas, the output parameters of the model include lap-shear strength and Weld-seam width. Experimental data is used to train and test the network. The present neural network model is used to predict the experimental outcome as a function of input parameters within a specified range. Linear regression analyses are performed to compute the correlation coefficients, to measure the relationship between the actual and predicted output values, for checking the adequacy of the ANN model. Further, a sensitivity analysis is performed to determine the parametric influence on the model outputs. Finally, a comparison is made between the ANN and multiple regression models for predicting laser transmission Weld Quality. The same data set, which are used to develop the ANN model, are also used to develop the multiple regression models. The simulation data obtained from the neural network confirms the feasibility of this model in terms of applicability and shows better agreement with the experimental data, compared to those from the regression models.
Yansong Zhang - One of the best experts on this subject based on the ideXlab platform.
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characterization of multilayer ultrasonic Welding based on the online monitoring of sonotrode displacement
Journal of Manufacturing Processes, 2020Co-Authors: Yansong ZhangAbstract:Abstract Ultrasonic spot Welding (USW) of multilayer metal sheets is a critical process of lithium battery manufacturing. However, inconsistent Weld Quality is still an issue in multilayer USW which makes the online Quality monitoring very necessary to provide rapid and reliable feedbacks of each workpiece’s Weld Quality. In this work, the displacement of the sonotrode in the clamping direction was monitored by a high-frequency displacement sensor in order to establish the relationship with the Weld Quality. Features of displacement signals were analyzed combined with changes in the plastic deformation and Welding qualities which were characterized by the laser scanning confocal microscopy, the optical microscopy and the electron backscattered diffraction (EBSD). Besides, effects of Welding parameters on the displacement signal were studied. Finally, the relationship between the displacement signal, the plastic deformation and the Weld Quality was established which can be used for the online Quality monitoring of the multilayer USW.
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On-line inspection of Weld Quality based on dynamic resistance curve in resistance spot Welding and Weldbonding
Fourth International Symposium on Precision Mechanical Measurements, 2008Co-Authors: Haitao Sun, Yansong Zhang, Xinmin Lai, Guanlong ChenAbstract:In order to reduce destructive testing of car sub-assemblies, on-line inspection of Weld Quality has gained more and more concern in terms of both resistance spot Welding (RSW) and Weldbonding. Dynamic resistance directly determines the amount of heat generated by current flow and consequently reflects nugget formation and growth, which is one of the most effective technologies for Quality inspection. Under the measurements of voltage and current at the secondary circuit of a Welding transformer, this paper proposes a method for on-line inspection of Weld Quality based on two indicators from dynamic resistance curve: time to nugget initiation and durable time to nugget expansion. Firstly, during the Welding process of RSW and Weldbonding, the proper range of time to nugget initiation and durable time to nugget expansion for good Welds is set up. Then on-line inspection of Weld Quality on the basis of the developed proper range of these two indicators is carried out. The experimental results show the following conclusions: it is clearly able to separate accepted Welds without expulsion from the Welds of unaccepted nugget size in both RSW and Weldbonding; the proper range for good Welds, independent of electrode wear, is obtained only for a new electrode.
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effect of variable electrode force on Weld Quality in resistance spot Welding
Science and Technology of Welding and Joining, 2007Co-Authors: Yansong Zhang, J ShenAbstract:AbstractResistance spot Weldability is defined as the acceptable Welding current ranges as determined by the Weld lobe in resistance spot Welding. Nowadays many studies have focused on the effect of Welding current and Welding time under constant electrode force on the Weld Quality and Weldability. There is little research on the influence of variable electrode force on the Weld Quality and Weldability because of the difficulty in controlling variable electrode force using pneumatic gun. In the present study, first, the influence of three stages of electrode force, including squeeze force, Welding force and forging force, on the Quality of Welds is analysed. Then a design of experiment approach is applied to analyse the influence of the three stages of electrode force on Welding Quality and thus to obtain optimum parameter of variable electrode force by controlling the electrode force with servo gun. The comparisons of tensile shear strength, nugget size, Weld lobe width and wear rate of electrode tip bet...
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Study on Weld Quality Control of Resistance Spot Welding Using a Neuro-Fuzzy Algorithm
Lecture Notes in Computer Science, 2004Co-Authors: Yansong Zhang, Guanlong Chen, Zhongqin LinAbstract:Resistance spot Welding (RSW) is widely utilized as a joining technique for automobile industry. However, good Weld Quality evaluation method has not yet been developed in plant environment. It is necessary to achieve real-time inspection of RSW. This paper proposed a neuro-fuzzy algorithm to predict Weld Quality online. An experimental system was developed to measure electrode displacement curve. Accordingly based on electrode displacement curve nugget diameter will be inferred. Inference results showed that proposed neuro-fuzzy algorithm is suitable as a Weld Quality monitoring for resistance spot Welding.
