Input electrical impedance as signature for nondestructive evaluation of weld quality during ultrasonic welding of plastics

Ling, Shih‐Fu; Luan, Jing-en; Li, Xiangchao; Ang, Wendy Lee Yong

doi:10.1016/j.ndteint.2005.05.003

Cited by 21 publications

(12 citation statements)

References 3 publications

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“…They conducted qualitative and quantitative study of arc sound signals 9 and also uses of arc temperature 10 as signature for weld quality monitoring. The scope of electrical impedance 11,12 as parameter for weld quality monitoring was also reported in the literature.…”

Section: Introductionmentioning

confidence: 92%

Use of Machine Learning Algorithms for Weld Quality Monitoring using Acoustic Signature

Sumesh

Rameshkumar

Mohandas

et al. 2015

Procedia Computer Science

104

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Welding is one of the major joining processes employed in fabrication industry, especially one that manufactures boiler, pressure vessels, marine structure etc. Control of weld quality is very important for such industries. In this work an attempt is made to correlate arc sound with the weld quality. The welding is done with various combinations of current, voltage, and travel speed to produce good welds as well as weld with defects. The defects considered in this study are lack of fusion and burn through. Raw data points captured from the arc sound were converted into amplitude signals. The welded specimens were inspected and classified into 3 classes such as good weld and weld with lack of fusion and burn through. Statistical features of raw data were extracted using data mining software. Using classification algorithms the defects are classified. Two algorithms namely, J48 and random forest were used and classification efficiencies of the algorithms were reported.

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Section: Introductionmentioning

confidence: 92%

Use of Machine Learning Algorithms for Weld Quality Monitoring using Acoustic Signature

Sumesh

Rameshkumar

Mohandas

et al. 2015

Procedia Computer Science

104

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“…Recently, the use of input impedance as the monitoring signature for manufacturing processes has been in focus for ultrasonic welding [9], wire bonding [10] and micro drilling [11]. Furthermore, the development of realtime quality monitoring method has been done successfully for RSW based on the input electrical impedance of RSW [12].…”

Section: Introductionmentioning

confidence: 99%

A New Characterization Approach of Weld Nugget Growth by Real-Time Input Electrical Impedance

Wong¹,

Pang²

2014

ENG

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The in-process changes of weld nugget growth during the Resistance Spot Welding were investigated based on the resistance of input electrical impedance. To compute the time varying resistance of input electrical impedance, the welding voltage and current signals are measured simultaneously and then converted into complex-valued signals by using Hilbert transform. Comparing with the dynamic contact resistance as reported in literature, it showed that the time varying resistance of input electrical impedance can be accurately correlated with the physical changes of weld nugget growth. Therefore, it can be used to characterize the in-process changes of weld nugget growth. Several new findings were reported based on the investigation of spot welds under no weld, with and without weld expulsion conditions.

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“…A further study revealed that this method is able to remove the loading effect and therefore increase the measurement accuracy [58]. In 2006, the transduction matrix method was used to monitor the quality of ultrasonic welding of IC wires [61] or thermoplastics [62] driven by piezoelectric actuators (see Figure 2.23). After the identification of the transduction matrix, the welding force and velocity applied to the workpiece can be monitored via the input voltage and current.…”

Section: Transduction Matrix Methodsmentioning

confidence: 99%

Biomimetic whisker transducer for vibrissal tactile sensing

Ju¹

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The unique vibrissal tactile perception possessed by rats allows them to explore the surrounding environment actively with their whiskers, and helps them survive and thrive in hostile environments like underground tunnels, where vision becomes of little use. On the other hand, today most robots lack tactile sensing ability and rely on machine vision heavily. This seriously limits their survival chance and exploration performance in unstructured environments. In this thesis, a novel whisker transducer (WT) aiming to mimic the biological vibrissa system has been proposed, which can endow robots with vibrissal tactile sensing ability. The WT was developed based on a novel transduction matrix model, which characterizes the forward actuation and backward sensing functions of the transducer with a 2×2 matrix. As a result, the WT can perform active whisking and simultaneously sense the mechanical stimuli at its tip, just like what rat's whisker does. And the force, velocity and mechanical impedance at whisker tip are sensed from the input electrical signals, without using any additional sensors. The concept and functions of the WT were validated numerically using a finite element model and experimentally using a prototype. It can accurately measure mechanical impedance, force and velocity at whisker tip with errors of 1.28%, 0.88% and 1.55%, respectively. It also possesses features such as compact structure, good versatility and easy instrumentation, which facilitate its deployment on robots. Vibrissal tactile texture sensing and object locating were first investigated. The texture sensing experiment showed that when the WT sweeps across a surface, the force and velocity sensed at whisker tip both have strong linear relationship with roughness (regression analysis R 2 > 0.99). And the damping property of the surface can be obtained from real part of WT-measured mechanical impedance. The WT was also used to study the mechanism of rat's vibrissal tactile texture perception in a biomimetic perspective. Then the object locating experiment was investigated with a miniaturized WT (50×50×5000 µm). A bio-inspired spatial-temporal-intensity triple-coding scheme was proposed and implemented using digital Abstract ii signal processing and artificial neural networks. The WT can detect horizontal and radial locations of a contacting object with measurement uncertainties of 0.27 µm and 5.4 µm, respectively. And a WT array can enable object locating in the vertical axis. Potential applications of WT were explored experimentally. First, the miniaturized WT can accurately measure geometry of high-aspect-ratio micro trenches and detect invalid tip contact caused by protrusion on the sidewall. Second, a modified WT with a sphere tip can sense both viscosity and density of a fluid online. The extracted viscosity and density were separated from each other, rather than in the form of product (ηρ) or quotient (η/ρ) as detected by existing viscosity sensors. The low working frequency (104 Hz) and large vibration amplitude (0.43 mm) of WT made ...

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Input electrical impedance as signature for nondestructive evaluation of weld quality during ultrasonic welding of plastics

Cited by 21 publications

References 3 publications

Use of Machine Learning Algorithms for Weld Quality Monitoring using Acoustic Signature

Use of Machine Learning Algorithms for Weld Quality Monitoring using Acoustic Signature

A New Characterization Approach of Weld Nugget Growth by Real-Time Input Electrical Impedance

Biomimetic whisker transducer for vibrissal tactile sensing

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