Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Bose, Payel; Sasikumar, T.; Jose, Prince; Philip, Jeby

doi:10.20855/ijav.2018.23.21447

Cited by 3 publications

(1 citation statement)

References 18 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While Figs. 22 and 24 indicate that the IH-PSO is able to escape from the local optimal solutions, which makes up for the deficiencies of the original PSO algorithm and increases the final diagnosis accuracy.…”

Section: ) Comparison Of Experimental Resultsmentioning

confidence: 99%

Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine

et al. 2019

View full text Add to dashboard Cite

Because of its excellent small sample learning abilities and simple network structure, support vector machine (SVM) is widely applied in various pattern recognition fields, e.g., face recognition, scene classification, fault diagnosis, etc. Due to the complexity and diversity of analog circuit faults, the diagnosis accuracy and stability of SVM classifier optimized by traditional particle swarm optimization (PSO) are unsatisfactory. Therefore, this paper proposes an improved hybrid particle swarm optimization (IH-PSO) algorithm to optimize SVM, which is applied in the fault diagnosis of analog circuits. Compared with the traditional PSO algorithm, the proposed IH-PSO mainly has three improvements, namely, the oppositionbased learning population initialization, the nonlinear time-varying inertia weight, and the new position updating strategy with a spiral convergence mechanism. The performance of the proposed IH-PSO algorithm is verified by 12 commonly used benchmark functions and experimental results show that the proposed IH-PSO algorithm overcomes the deficiencies of the traditional PSO algorithm, such as slow convergence speed and trapping into local optimums. In addition, to further verify the performance of IH-PSO algorithm, the IH-PSO optimized SVM is applied to solve analog circuits fault diagnosis problems. Extensive experiments are carried out and results indicate that the proposed method has better performances both in diagnosis accuracy and stability compared with that of the traditional method.

show abstract

Section: ) Comparison Of Experimental Resultsmentioning

confidence: 99%

Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine

et al. 2019

View full text Add to dashboard Cite

show abstract

Discriminative feature analysis based on the crossing level for leakage classification in water pipelines

Luong

Kim

2019

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

Selection algorithm based on Kullback–Leibler distance is one of the simplest, fastest, and most effective methods suitable for feature selection of real applications like leak detection systems. However, this method has problems when the training dataset is not large enough. This paper proposes a crossing level value that evaluates the level of overlap between the conditional probability space and the degree of dispersion of each probability to choose the best features before classifying. The evaluation results indicate the proposed method is more stable, more reliable, and has a higher accuracy than the Kullback–Leibler method.

show abstract

The Influence of H<sub>2</sub>SO<sub>4</sub>- NaCl Electrolyte Composition to the Electrochemical Noise Behaviour of a High-Alloy Cast Steel

Mandel

Kietov

Wendler

et al. 2020

DDF

View full text Add to dashboard Cite

In this study, the influence of varying sulphuric acid – sodium chloride electrolyte composition to the electrochemical noise behaviour of a high-alloy cast steel was analysed. The noise analysis was carried out in a bare 0.1 M sulphuric acid solution, in a pure 5 wt.% sodium chloride solution and three solutions with defined ratios of both. The electrochemical current noise signal was recorded with a sampling rate of 100 Hz for 1 hour in each test solution. For the identification of the frequency content of notified characteristic transients, the current-time records were analysed by the continuous wavelet transform (CWT). The characteristic transients were extracted from the noise signal for a further analysis of their frequency and amplitude characteristics. The results show high-frequency transients in the bare sulphuric acid and low-frequency transients in the pure sodium chloride solution. In the combined electrolyte solutions the portion of low-frequency components increases when the NaCl content increases and indicates the enhancing influence of localised damage evolution processes at the steel surface.

show abstract

Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Cited by 3 publications

References 18 publications

Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine

Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine

Discriminative feature analysis based on the crossing level for leakage classification in water pipelines

The Influence of H<sub>2</sub>SO<sub>4</sub>- NaCl Electrolyte Composition to the Electrochemical Noise Behaviour of a High-Alloy Cast Steel

Contact Info

Product

Resources

About