An intelligent algorithm based on evolutionary strategy and clustering algorithm for Lamb wave defect location

Imaging algorithms for visualization of defects play a significant role in Lamb wave–based research of nondestructive testing and structural health monitoring. In classical algorithms, the position or distribution of defects is located by mapping the amplitude or phase information of signals from the time domain to every discrete spatial grid of the structure. It is time-consuming. In this study, the diversity, statistical, and fuzzy characteristics of the elliptic imaging algorithm are analyzed first; then, an intelligent defect location algorithm is proposed based on the evolutionary strategy and the K-means algorithm. The position of defects can be identified by observing the distribution of individuals. There are six parts in the proposed algorithm, including the data structure design, adaptive population screening, adaptive population reproduction, diversity maintenance mechanism, and cutoff criterion. Considering the statistical and fuzzy characteristics in the detection, several specific input parameters are defined in our algorithm, such as the distance-dependent screening threshold, path-dependent residual vector, and path-independent residual. To maintain the diversity of individuals in the analysis, we have made two adjustments to the evolutionary strategy: one is to optimize the population screening and reproduction steps with the K-means algorithm, and the other is to add a diversity maintenance method into the evolutionary strategy. The effectiveness of the proposed intelligent defect location algorithm is verified by numerical simulations and experiments. Numerical studies indicate that the proposed algorithm has a reliable performance in the detection of defects with different shapes and sizes. In the experimental research, we demonstrate that the efficiency of the proposed algorithm is about 200 times faster than the elliptic imaging algorithm. And the optimum parameter setting of the algorithm is investigated by analyzing the influence of parameter setting on the detection.

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Evolutionary strategy–based location algorithm for high-resolution Lamb wave defect detection with sparse array

IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control ◽

10.1109/tuffc.2021.3060094 ◽

2021 ◽

pp. 1-1

Author(s):

Honglei Chen ◽

Zenghua Liu ◽

Yu Gong ◽

Bin Wu ◽

Cunfu He

Keyword(s):

High Resolution ◽

Defect Detection ◽

Lamb Wave ◽

Evolutionary Strategy ◽

Sparse Array ◽

Location Algorithm

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An automatic welding defect location algorithm based on deep learning

NDT & E International ◽

10.1016/j.ndteint.2021.102435 ◽

2021 ◽

Vol 120 ◽

pp. 102435

Author(s):

Lei Yang ◽

Huaixin Wang ◽

Benyan Huo ◽

Fangyuan Li ◽

Yanhong Liu

Keyword(s):

Deep Learning ◽

Automatic Welding ◽

Defect Location ◽

Location Algorithm ◽

Welding Defect

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An improved OPTICS clustering algorithm for discovering clusters with uneven densities

Intelligent Data Analysis ◽

10.3233/ida-205497 ◽

2021 ◽

Vol 25 (6) ◽

pp. 1453-1471

Author(s):

Chunhua Tang ◽

Han Wang ◽

Zhiwen Wang ◽

Xiangkun Zeng ◽

Huaran Yan ◽

...

Keyword(s):

Time Complexity ◽

Clustering Algorithm ◽

Nearest Neighbor ◽

Clustering Algorithms ◽

Substantial Improvement ◽

Experimental Results ◽

High Time ◽

Parameter Setting ◽

K Nearest Neighbor ◽

Density Based Clustering

Most density-based clustering algorithms have the problems of difficult parameter setting, high time complexity, poor noise recognition, and weak clustering for datasets with uneven density. To solve these problems, this paper proposes FOP-OPTICS algorithm (Finding of the Ordering Peaks Based on OPTICS), which is a substantial improvement of OPTICS (Ordering Points To Identify the Clustering Structure). The proposed algorithm finds the demarcation point (DP) from the Augmented Cluster-Ordering generated by OPTICS and uses the reachability-distance of DP as the radius of neighborhood eps of its corresponding cluster. It overcomes the weakness of most algorithms in clustering datasets with uneven densities. By computing the distance of the k-nearest neighbor of each point, it reduces the time complexity of OPTICS; by calculating density-mutation points within the clusters, it can efficiently recognize noise. The experimental results show that FOP-OPTICS has the lowest time complexity, and outperforms other algorithms in parameter setting and noise recognition.

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A feature weighted FCM clustering algorithm based on evolutionary strategy

Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527) ◽

10.1109/wcica.2002.1020845 ◽

2003 ◽

Author(s):

Jie Li ◽

Xinbo Gao ◽

Hongbing Ji

Keyword(s):

Clustering Algorithm ◽

Evolutionary Strategy ◽

Fcm Clustering

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Impact of Changing Temperature on Lamb Wave Propagation for Damage Detection

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.588.140 ◽

2013 ◽

Vol 588 ◽

pp. 140-148 ◽

Cited By ~ 2

Author(s):

Rafal Radecki ◽

Wieslaw Jerzy Staszewski ◽

Tadeusz Uhl

Keyword(s):

Wave Propagation ◽

Damage Detection ◽

Lamb Wave ◽

Structural Damage ◽

Clustering Algorithm ◽

Lamb Waves ◽

Ultrasonic Waves ◽

Effect Of Temperature ◽

Propagation Parameters ◽

Lamb Wave Propagation

Lamb waves are the most widely used guided ultrasonic waves for structural damage detection. One of the major problems associate with Lamb wave propagation is the effect of temperature on wave propagation parameters. It is important that these parameters are more sensitive to damage than to varying temperature. The paper demonstrates how amplitude and arrival time of Lamb waves are affected by temperature. The analysis is performed for the experimental data gathered from Lamb wave propagation in a damaged aluminium plate. A simple clustering algorithm is used to distinguish between "undamaged" and "damaged" conditions in the presence of changing temperature.

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Finite Element Analysis of the Swing-Rod Constraint Reciprocating Piston-Type Oil-Free Air Compressor

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.2130 ◽

2013 ◽

Vol 333-335 ◽

pp. 2130-2135

Author(s):

Kui Hua Geng ◽

Jing Guo ◽

Wen Gui Su ◽

Shi Guang Du

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Performance Improvement ◽

Structure Design ◽

Parameter Setting ◽

Element Analysis ◽

Air Compressor ◽

Free Air ◽

Simulation Results ◽

And Performance

Based on finite element analysis technology, a static simulation model of the swing-rod constraint reciprocating piston-type oil-free air compressor was established for stress analysis of the compressor. Simulation results show that the stress in the main parts of the new compressor is within the permitted range, so structure design and parameter setting of the compressor are reasonable. Moreover, the force condition of seal rings is improved by adding swinging-rod constraint mechanism, which will prolong the service life of seal rings. With this study, these simulation results will guide further modification and performance improvement of the compressor.

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The Estimation Of The Lamb Wave Phase Velocity Dispersion Curves Base On K-Means Clustering Algorithm

2020 15th Symposium on Piezoelectrcity, Acoustic Waves and Device Applications (SPAWDA) ◽

10.1109/spawda51471.2021.9445484 ◽

2021 ◽

Author(s):

Xiang Gao ◽

Chen-xu Li ◽

Jing-pin Jiao ◽

Ze-wen Feng

Keyword(s):

Phase Velocity ◽

Lamb Wave ◽

Clustering Algorithm ◽

Velocity Dispersion ◽

Dispersion Curves ◽

Wave Phase ◽

Phase Velocity Dispersion ◽

Wave Phase Velocity

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Research on product innovation design of modularization based on theory of TRIZ and axiomatic design

Advances in Mechanical Engineering ◽

10.1177/1687814018814087 ◽

2018 ◽

Vol 10 (12) ◽

pp. 168781401881408 ◽

Cited By ~ 3

Author(s):

Zhong-hang Bai ◽

Shan Zhang ◽

Man Ding ◽

Jian-guang Sun

Keyword(s):

Problem Solving ◽

Design Theory ◽

Clustering Algorithm ◽

Modular Design ◽

Design Method ◽

Axiomatic Design ◽

Structure Design ◽

Design Matrix ◽

Development Cycle ◽

Axiomatic Design Theory

Modular design can shorten the product development cycle and enhance the product research and development capability of enterprises. To better solve the problem of module interface coupling after module partition, the present modular product design method has been improved based on the theory of inventive problem solving and axiomatic design theory. This article summarizes the engineering parameters commonly used in modular design based on the requirement analysis and conflict problems of modular structure design. And in the process of dividing the functional modules by fuzzy clustering algorithm, we propose defining and classifying the principle (technical) correlation between parts by these parameters. Then the coupling relation of each module interface is analyzed by the design matrix of axiomatic design and the conflict solving tool of the theory of inventive problem solving is utilized for decoupling. Finally, the high chair is taken as the design object and the design process is used to verify the feasibility of this method.

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