Flaw Detection in Highly Scattering Materials Using a Simple Ultrasonic Sensor Employing Adaptive Template Matching

Wu, Biao; Huang, Yong

doi:10.3390/s22010268

Cited by 4 publications

(3 citation statements)

References 37 publications

(46 reference statements)

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“…However, the absorption term is usually insignificant and negligible when compared to the scattering term; therefore, the attenuation model can be expressed as:

where

is the velocity of the sound in stainless steel and

is the time delay of the pulse. In practice, the attenuation coefficient

can be estimated beforehand [ 27 ]. Generally, the spectrum of the transmitted pulse

possesses a Gaussian shape with the following form:

where

is the center frequency of the transmitted pulse,

is a parameter that describes the frequency bandwidth of the transmitted pulse.…”

Section: Modeling Of Ultrasonic Ndt Signalmentioning

confidence: 99%

A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures

Yang²,

Huang³

et al. 2023

Sensors

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Ultrasonic nondestructive testing (NDT) provides a valuable insight into the integrity of stainless steel structures, but the noise caused by the scattering of stainless steel microstructure often limits the effectiveness of inspection. This work presents a novel adaptive filtering approach to enhance the signal-to-noise ratio (SNR) of a measured ultrasonic signal from the inspection of a stainless steel component, enabling the detection of hidden flaws under strong noise. After the spectral modeling of the noisy ultrasonic NDT signal, the difference between the spectral characteristics of a flaw echo and that of grain noise is highlighted, and a reference spectrum model to estimate the frequency spectrum of the echo reflected by any possible flaw is developed. Then, the signal is segmented and the similarity between the spectra of data segments and the reference spectra is evaluated quantitatively by the spectral similarity index (SSI). Based on this index, an adaptive time-frequency filtering scheme is proposed. Each data segment is processed by the filtering to suppress the energy of noise. The processed data segments are recombined to generate the de-noised signal after multiplying weighting coefficients, which again is determined by the SSI. The performance of the proposed method for SNR enhancement is evaluated by both the simulated and experimental signal and the effectiveness has been successfully demonstrated.

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“…However, the absorption term is usually insignificant and negligible when compared to the scattering term; therefore, the attenuation model can be expressed as:

where

is the velocity of the sound in stainless steel and

is the time delay of the pulse. In practice, the attenuation coefficient

can be estimated beforehand [ 27 ]. Generally, the spectrum of the transmitted pulse

possesses a Gaussian shape with the following form:

where

is the center frequency of the transmitted pulse,

is a parameter that describes the frequency bandwidth of the transmitted pulse.…”

Section: Modeling Of Ultrasonic Ndt Signalmentioning

confidence: 99%

A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures

Yang²,

Huang³

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…The traditional chip defect detection technology is usually used to detect and identify the defect information such as cracks, white spots, defects, and internal defects contained in the target chip sample by inspection methods such as magnetic particle inspection method, penetrant inspection method, eddy current inspection method, ultrasonic inspection method, and X-ray inspection [4][5][6][7][8][9][10]. Despite the achievements of traditional chip defect detection methods, there are some drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Application of machine vision technology in defect detection of high-performance phase noise measurement chips

Zhou

2023

3C Tecnología

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The problem of chip defects has always existed in industrial production, and since there are more and more environmental problems caused by chip defects, people have attached greater importance to the identification and detection of chip defects. Pursuant to the ecological environmental problems caused by chip defects in the process of chip production, this paper uses machine vision technology to detect the defects of high-performance phase noise measurement chips. The results suggest that the accuracy of machine vision technology for the identification of chip defects reaches up to 98%. The production volume of organic waste gas decreases from 5968.0t/a to 4000t/a. The yield of organic wastewater decreases from 5496m3/d to 4600m3/d. The production amount of solid waste reduces from 8000t/a to 6500t/a. The aforementioned data all confirm that machine vision technology has the advantages of automation, high detection efficiency, and high accuracy of defect identification for the defect detection of high-performance phase noise measurement chips. And also, by improving the chip defects, the discharge volume of waste gas, wastewater, and solid waste in the chip production process is reduced, and thereupon the ecological environment is ameliorated.

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“…The early identification of flaws allows for timely corrective actions, reducing the likelihood of unexpected failures and potential safety hazards. It also helps extend the service life of components and structures, optimize maintenance schedules, and minimize downtime, leading to enhanced operational efficiency and cost savings (Wu & Huang, 2021).…”

Section: Introductionmentioning

confidence: 99%

Review on Non-Destructive Techniques for Early Flaw Detection in Inspections

Egbokhaebho,

Olalere,

Gidiagba

et al. 2023

Mate.corr.eng.manag.

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Non-destructive testing (NDT) is critical in ensuring various materials’ and structures’ integrity and safety by detecting flaws without causing damage. Early flaw detection is essential for preventing catastrophic failures, reducing maintenance costs, and enhancing operational efficiency. This research paper comprehensively reviews non-destructive techniques for early flaw detection in inspections. The paper begins with an introduction to the significance of flaw detection and the motivation behind employing non-destructive techniques. It proceeds with a thorough literature review, summarizing existing research and highlighting the strengths and limitations of different methods. The main section of the paper delves into the description and principles of common non-destructive techniques, including Ultrasonic Testing (UT), Radiographic Testing (RT), Magnetic Particle Testing (MPT), Liquid Penetrant Testing (LPT), Eddy Current Testing (ECT), Thermography, Acoustic Emission Testing (AET), and others. The efficacy of each technique is explored through various case studies and real-world applications across diverse industries. Advantages, limitations, and factors influencing technique selection in specific scenarios are critically analyzed. Furthermore, the paper discusses recent advancements and emerging technologies in non-destructive testing that offer potential improvements for early flaw detection. It also covers relevant international and industry-specific standards and regulations governing NDT, emphasizing their significance in enhancing inspection reliability. The conclusion reaffirms the importance of non-destructive techniques for early flaw detection. It proposes future research directions to overcome existing challenges. This review aims to provide engineers, researchers, and practitioners with valuable insights into the state-of-the-art NDT methods, fostering continuous improvement in early flaw detection and ensuring the safety and reliability of critical infrastructures and materials.

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Flaw Detection in Highly Scattering Materials Using a Simple Ultrasonic Sensor Employing Adaptive Template Matching

Cited by 4 publications

References 37 publications

A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures

A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures

Application of machine vision technology in defect detection of high-performance phase noise measurement chips

Review on Non-Destructive Techniques for Early Flaw Detection in Inspections

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