Unsupervised learning approach to automation of hammering test using topological information

Kasahara, Jun Younes Louhi; Fujii, Hiromitsu; Yamashita, Atsushi; Asama, Hajime

doi:10.1186/s40648-017-0081-7

Cited by 11 publications

(3 citation statements)

References 12 publications

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“…However, it is sometimes used when using serial equipment for spectral signal analysis. The [18] describes the use of a perforator as an oscillation exciter.…”

Section: Fig 2 Fragment Of Support With Reinforced Concrete Slabsmentioning

confidence: 99%

Science and Practice for Assessing the State of Underground Structures Support by Vibroacoustic Method

Krukovskyi¹,

Skipochka²,

Serhiienko³

et al. 2023

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In this work, subject of the research is a method of non-destructive vibroacoustic control of underground structures support. The purpose of the research was to create a methodology and apparatus for vibroacoustic control of the state of the system "support – rock massif" with a wide range of use. The main types of objects where the use of this method is appropriate are determined. Negative influence of external factors on performance characteristics of support is shown. A basic type of support for underground objects is reinforced concrete. It is established that the most characteristic defects are formation of cavities in geological environment behind the support and broken connection of separate segments of the support. The influence of these defects on character of free oscillations of support elements at single shock action was studied theoretically. It is established that the following parameters can be informative for detecting these defects: amplitude characteristic of package of vibration, its duration and spectral composition. Information about the means of vibroacoustic control designed by the Institute with participation of the authors is provided. The methodical features of using vibroacoustic control for assessing technical state of different types of support are considered. The limitations for using the method are explained. Some results of the use of vibroacoustic control of support in underground objects of the various purposes are given.

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“…However, it is sometimes used when using serial equipment for spectral signal analysis. The [18] describes the use of a perforator as an oscillation exciter.…”

Section: Fig 2 Fragment Of Support With Reinforced Concrete Slabsmentioning

confidence: 99%

Science and Practice for Assessing the State of Underground Structures Support by Vibroacoustic Method

Krukovskyi¹,

Skipochka²,

Serhiienko³

et al. 2023

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show abstract

“…Tests on two commonly found defects were conducted on experimental test blocks and yielded satisfying results. [16] In Japan, engineers that manage them are insufficient due to aging. Therefore, the authors developed a hammering robot that can imitate the hammering sounds of inspection workers.…”

Section: Related Workmentioning

confidence: 99%

Improvement of Sound Classification Method on Smartphone for Hammering Test Using 5G Network

Fukumura

Aratame

Ito

et al. 2022

IJNC

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The demand for inspections has increased due to the aging of concrete structures and tile wall surfaces. The hammering test is a simple inspection method, but the inspector needs much experience distinguishing the hammering sounds. Therefore, we developed a device that automatically classifies the hammering sounds using deep learning. However, the hardware with GPU for deep learning is the one-board microcomputer, which has no display, a battery, or an input device, so the inspector cannot change the settings or check the status during the hammering test. Therefore, we used a smartphone instead of a one-board microcomputer. We also used a cloud GPU since a smartphone does not have GPU. The results showed that communication time was the bottleneck. So we considered using a 5G network and compared the classification time, training time, and battery life of the smartphone. As a result, although the training time remained the same, we found that the classification speed was 1.46 times faster than the conventional method, and the smartphone's battery life was sufficient.

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“…In [2,3] research is conducted to automate the hammering with a robotic unit and measure the sound with a microphone. To analyse the data supervised and unsupervised learning algorithms are applied.…”

Section: Introductionmentioning

confidence: 99%

Laser Sensing System for Contactless Detection of Subsurface Defects in Concrete Tunnel Lining

Weiher¹,

Heinze²,

Pankrath³

et al. 2022

eJNDT

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Regular inspections of underground infrastructure are mandatory to maintain structural integrity and traffic safety. Standard procedures rely on visual inspection, complemented by testing for internal defects of the tunnel lining with the hammering method. This testing method uses manual excitation with a hammer and interpretation of the perceived sound by an engineer or technician. Result quality is based on the experience of the executing personal and thus highly subjective. The presented project aims at the automation of this procedure to enable a fast and objective inspection covering the whole tunnel lining. To achieve this, a new laser-based measurement system for detecting near surface defects in large concrete structures is developed. Surface vibrations are induced with plasma ignition and measured with a Doppler Vibrometer. The system has motorized mirror adjustment and can thus obtain fast-paced measurements on a grid. We present the experimental setup, the measurements performed on a concrete test block with artificial defects and the algorithms for automated defect detection. From the measured eigenfrequencies, we derive the size and location of defects. Computer vision techniques are adapted to make the system resilient against variable environmental conditions, like noise and temperature, or changes in construction material and age. These sophisticated signal processing methods are applied to extract relevant information from the measurements and are combined with topological data to provide service personnel with detailed maps for maintenance work.

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Unsupervised learning approach to automation of hammering test using topological information

Cited by 11 publications

References 12 publications

Science and Practice for Assessing the State of Underground Structures Support by Vibroacoustic Method

Science and Practice for Assessing the State of Underground Structures Support by Vibroacoustic Method

Improvement of Sound Classification Method on Smartphone for Hammering Test Using 5G Network

Laser Sensing System for Contactless Detection of Subsurface Defects in Concrete Tunnel Lining

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