Post-Processing of Phased-Array Ultrasonic Inspection Data with Parallel Computing for Nondestructive Evaluation

Guan, Xuefei; Zhang, Jingdan; Zhou, S. Kevin; Rasselkorde, El Mahjoub; Abbasi, Waheed A.

doi:10.1007/s10921-013-0219-3

Cited by 14 publications

(4 citation statements)

References 15 publications

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“…Although the results indicate the fused image achieves better localization performance than the individual images, the fused image may fail to detect the damage under the employed fusion scheme if there is no damage shown in the individual images. In Guan et al, 181 the maximum and the average data fusion strategy are used to postprocess the phased-array ultrasonic inspection data. Results indicate that the average fusion scheme produces a clearer visualization for the ultrasonic data.…”

Section: Data Fusion Techniques In Shmmentioning

confidence: 99%

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

Jahanshahi

2018

Structural Health Monitoring

159

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During the past decades, significant efforts have been dedicated to develop reliable methods in structural health monitoring. The health assessment for the target structure of interest is achieved through the interpretation of collected data. At the beginning of the 21st century, the rapid advances in sensor technologies and data acquisition platforms have led to the new era of Big Data, where a huge amount of heterogeneous data are collected by a variety of sensors. The increasing accessibility and diversity of the data resources provide new opportunities for structural health monitoring, while the aggregation of information obtained from multiple sensors to make robust decisions remains a challenging problem. This article presents a comprehensive review of the recent data fusion applications in structural health monitoring. State-of-the-art theoretical concepts and applications of data fusion in structural health monitoring are presented. Challenges for data fusion in structural health monitoring are discussed, and a roadmap is provided for future research in this area.

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Section: Data Fusion Techniques In Shmmentioning

confidence: 99%

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

Jahanshahi

2018

Structural Health Monitoring

159

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“…For example, it can sweep a sectorial domain at one time, and by moving the probe, the same internal location can be interrogated from multiple directions and locations [16][17][18]. Consequently, the reliability of damage detections can greatly be improved [19,20]. In addition, the efficiency and flexibility of the ultrasound phased array also allow for rapid inspections of material blocks, reducing the overall inspection time [18,21].…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic Flaw Recognition by Multi-Angle Phased Array Data Integration

Zhang

Wang

Guan

2020

Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

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Abstract This study presents a method of ultrasonic flaw identification using phased array ultrasonic inspection data. Raw data from each individual channel of the phased array ultrasonic inspection are obtained. The data trimming and de-noising are employed to retain the data within the boundary of the inspected object and remove the speckle noise components from the raw data, respectively. The resulting data are passed into a sequence of signal processing operations to identify embedded flaws. A shape-based filtering method is proposed to reduce the intensity of geometric noise components due to the non-uniform microstructures introduced in the manufacturing process. The resulting data matrices are integrated to obtain the intensity matrix of the possible flaw regions. Thresholding is applied to the intensity matrix to obtain the potential flaw regions, followed by a connected component analysis to identify the flaws. The overall method is demonstrated and validated using realistic phased array experimental data.

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“…At present, the main methods of nondestructive testing are the X-ray methods, magnetic and electromagnetic ones, the metal magnetic memory method, and the acoustic methods. The most efficient methods to control defects located at large distances from the surface are the acoustic ones [1][2][3][4][5][6]. Analysis of acoustic methods showed that the most satisfactory method to assess the quality of a roll and to control the presence of defects (for example, cracks) in the surface layer of work rolls for cold-rolling mills is the echo method in jet variant.…”

Section: Introductionmentioning

confidence: 99%

Diagnostics and Forecasting of Defects in Rotation Details

Egorova

Вдовин

Логунова

2018

Proceedings of the 4th International Conference on Industrial Engineering

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In the given paper, ultrasonic installation which allows to carry out automatic diagnostics of quality of details of rotation by a method of ultrasonic scanning is offered and described. The machine makes it possible to automatically control the quality of work rolls, to identify the rolls liable to spalling and delamination of the hardened layer using the ultrasonic scanning method. The application of the proposed machine makes it possible to detect the defects in a mill roll at all production stages. The paper offers a description of the software product, which controls the ultrasonic card, and using an ultrasonic sensor automatically generates and receives ultrasonic signals. The obtained results confirm the guaranteed defect detection in the near-surface layer of the mill roll. The application of the proposed machine makes it possible to detect the defects in a mill roll at all production stages.

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Post-Processing of Phased-Array Ultrasonic Inspection Data with Parallel Computing for Nondestructive Evaluation

Cited by 14 publications

References 15 publications

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

Ultrasonic Flaw Recognition by Multi-Angle Phased Array Data Integration

Diagnostics and Forecasting of Defects in Rotation Details

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