Detection of micro gap weld joint by using magneto-optical imaging and Kalman filtering compensated with RBF neural network

Gao, Xiangdong; Chen, Yuquan; You, Deyong; Zhenlin, Xiao; Chen, Xiaohui

doi:10.1016/j.ymssp.2016.07.041

Cited by 40 publications

(7 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, safety is maintained by detecting defects in a structure at an early stage with various non-destructive testing methods. Non-destructive testing using a magneto-optical (MO) effect is a high-resolution non-destructive inspection technique for a metallic structure [ 1 , 2 , 3 , 4 , 5 , 6 ]. The MO effect is a phenomenon where a polarization plane of light rotates when a linearly polarized light passes through the magnetized magnetic materials [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Properties of Magnetic Garnet Films for Flexible Magneto-Optical Indicators Fabricated by Spin-Coating Method

et al. 2022

View full text Add to dashboard Cite

Non-destructive testing using a magneto-optical effect is a high-resolution non-destructive inspection technique for a metallic structure. It is able to provide high-spatial resolution images of defects. Previously, it has been difficult to fabricate flexible magneto-optical sensors because thermal treatment is necessary to crystallize the magnetic garnet. Therefore, it was not possible to apply magneto-optical imaging to complicated shapes in a test subject, such as a curved surface. In this study, we developed a new process for deposition of the magnetic garnet on the flexible substrate by applying the magnetic garnet powders that have already undergone crystallization. In this new process, as it does not require thermal treatment after deposition, flexible substrates with low heat resistance can be used. In this paper, we report our observations of the optical properties, magnetic hysteresis loop, crystallizability and density of the particles on the flexible substrate deposited by the spin-coating method.

show abstract

Section: Introductionmentioning

confidence: 99%

Properties of Magnetic Garnet Films for Flexible Magneto-Optical Indicators Fabricated by Spin-Coating Method

et al. 2022

View full text Add to dashboard Cite

show abstract

“…As the Kalman filter (KF) can use the real-time state estimation and the measurement from sensors to predict the optimized estimation state of the observation object, it is an effective technology for object tracking in machine vision [20][21][22]. Some researchers apply the KF to seam tracking based on visual sensing.…”

Section: Introductionmentioning

confidence: 99%

“…In [10], through embedding an Elman neural network into an adaptive KF, the error estimator was used to compensate for the filtering errors during the high-power fiber laser welding process with the stainless steel plate. In [23], a KF and a radial basis function neural network were applied to tracking the weld center position by a magneto optical sensor. In [24], the WSP in images was searched in a small area that was estimated by a KF to avoid some disturbance.…”

Section: Introductionmentioning

confidence: 99%

Stable 3D seam tracking for thick plate GMAW manufacturing with T-joints using Kalman filter and machine learning

He¹,

Zhang²,

Xiao³

et al. 2021

Preprint

View full text Add to dashboard Cite

In this paper, a robust stable three-dimensional (3D) seam tracking method is investigate based on the Kalman filter (KF) and machine learning during the multipass gas metal arc welding process with a T-joint of 60 mm thickness. The laser vision sensor is used to profile the weld seam, and with the reference image captured before arcing a scheme is proposed to extract the variable weld seam profiles (WSPs) using scale-invariant feature transform and the clustering algorithm. An effective slope mutation detection method is presented to identify the feature points of the extracted WSP, namely the candidate welding positions. In order to lower the impact of fake welding positions on seam tracking, a Bayesian Network model is first built to implement fault detection and diagnosis for the visual feature measurement process using the involved process parameters and the trigger rule. A KF, as an estimator, is then established to further stabilize the tracking process combing with a self determination algorithm of the measurement result. With the visual calibration technology, 3D seam tracking is realized. Seam tracking results show that the proposed method overcomes the tremor of the tracking position and multiple fake candidate welding positions on tracking accuracy, and the tracking accuracy is 0.6 mm. This method provides potential industrial application value for industrial manufacturing with large-scale components.

show abstract

“…Neural networks can be used to approximate any nonlinear function with generalization. Thus, a Radial Basis Function (RBF) neural network is adopted to address this problem; see [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Neural Terminal Sliding‐Mode Control for Uncertain Systems with Building Structure Vibration

Wang

Chen

et al. 2019

Complexity

View full text Add to dashboard Cite

Building structures occasionally suffer from unpredictable earthquakes, which can cause severe damage and can threaten human lives. Thus, effective control methods are needed to protect against structural vibration in buildings, and rapid finite-time convergence is a key performance indicator for vibration control systems. Rapid convergence can be ensured by applying a sliding-mode control method. However, this method would result in chattering issue, which would weaken the feasibility of the physical implementation. To address this problem, a neural terminal sliding-mode control method is proposed. The proposed method is combined with a terminal sliding-mode and a hyperbolic tangent function to ensure that the considered system can be stabilized in finite-time without chattering. Finally, the control effect of the proposed method is compared with that of LQR (linear quadratic regulator) control and switching function control. The simulation results showed that the proposed method can ensure rapid convergence while the chattering issue can be eliminated effectively. And the structural building vibration can be suppressed effectively too.

show abstract

Detection of micro gap weld joint by using magneto-optical imaging and Kalman filtering compensated with RBF neural network

Cited by 40 publications

References 22 publications

Properties of Magnetic Garnet Films for Flexible Magneto-Optical Indicators Fabricated by Spin-Coating Method

Properties of Magnetic Garnet Films for Flexible Magneto-Optical Indicators Fabricated by Spin-Coating Method

Stable 3D seam tracking for thick plate GMAW manufacturing with T-joints using Kalman filter and machine learning

Neural Terminal Sliding‐Mode Control for Uncertain Systems with Building Structure Vibration

Contact Info

Product

Resources

About