• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.107-111
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• 2010

The damage of tire by damage material classification method is researched as used ultrasonic wave signal to occur at a tire during vehicle driving. Auto-correlation function after having passed through an envelope detecting preprocess is used for detecting periodicity because of occurring periodic ultrasonic waves signal with tire revolution. One revolution cycle time of a damaged tire and period that calculated auto-correlation function appeared equally in experiment. The result that can classification whether or not there was a tire damage is established.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.113-118
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• 2010

The split spectrum processing algorithm of an ultrasonic wave on the tire was studied for the damage detection of a driving vehicle's tire. The processing results of normal and damaged tire was compared using the split spectrum algorithm to estimate the maximum value. The result that used Auto-correlation in case of damaged tire, the damage feature point is detected during 81ms intervals at a speed of 100km/h and during 162ms periodicity at a speed of 50km/h. This results was meaned the possibility for the tire's damage decision by damaging material with using periodicity feature point of tire damage according to vehicle speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.291-296
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• 2015

The tire damage classification method is researched on the periodicity detection of ramdomness ultrasonic signals to occur at the driving vehicle tire. Setting method of adaptive threshold is proposed in order to valid pulse detection by tire damage in ultrasonic noise on the road and used low pass filter for decrease signal ramdomness as preprocessing. Time interval of detected pulse is setted the density function depend on the vehicle's speed and the method of tire damage detection is proposed that measuring the first peak's time of time density function.The result of time density function in case of one damage material, the first peak's time is measured within the error limit of tire's rotation period, 169.8ms and 97.9ms and 81.8ms, about the speed of 50km/h and 80km/h and 100km/h. In case of more than one damage material, the sum of each peak's time is measured within the error limit of tire's rotation period about the speed.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.21-27
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• 2018

Wearing degree and uneven wearing detection algorithm using horizontal edge information is proposed in this paper. The noise in the input image is removed by bilateral filter, and then edges are extracted from the filtered image by using the proposed mask. As the tire is worn, grooves of tire shoulder or sipes are changed more than the vertical grooves. Therefore the edges from grooves of tire shoulder or sipes have more information about the tire wearing than the edges from vertical grooves. Proposed mask that is reflected this feature is used to extract the horizontal edges. After edge extraction, the edge image is represented in two-level system. The edge pixels of the binarization image are used to decide the wearing degree and uneven wearing. This proposed method can be used easily without any other equipments. The proposed method is conducted with a real vehicle, and the experimental results show the good performance of the proposed method in detecting wearing degree and uneven wearing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.41-46
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• 2011

The tire damage classification method is researched by periodicity detection of ultrasonic envelope signals to occur at the driving vehicle tire. Because periodic signals is generated by rotations of the damaged tire, it should convert to pulse for using the density function. After time intervals of pulses are represented by the density function, the dominant periodicity is detected. The threshold to make a pulse is calculated by moving average of envelope signals. The result of time density function in case of one damage material, the first peak's time is equals to tire's rotation period, 162ms and 102ms, about the speed of 50km/h and 80km/h. In case of more than one damage material, the sum of each peak's time is equals to tire's rotation period about the speed.

• Journal of the Korean Geotechnical Society
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• v.20 no.3
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• pp.119-128
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• 2004

Environmental impact of waste tires as gound-reinforcing material is studied. Analysis for chemical compounds and toxic effect were performed on effluents from twelve lysimeters in which waste tires were mixed with sand and three initially different environmental solutions of acidic, neutral, and basic circulated through the mixture. The test results of effluents collected from the lysimeters provided that the contaminant concentrations were lower than those of Korean drinking water standards for all the selected and tested metal elements. While iron concentration increased slightly with the exposure period, other metal concentrations decreased with the number of circulation times. From the comparison with previous investigations, the contaminant concentration decreased with the increase of tire size, i.e. increases with the increase of the exposed surface of tire metals. From the toxicity tests, no deteriorative effect was observed and it could be concluded that waste tires are not biologically hostile materials.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.47-52
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• 2011

We studied about the damaged tire decision algorithm that measured dominant period of ultrasonic signal due to a foreign material on the friction between tire and road surface. We computed the power spectrum about the envelope of ultrasonic signal acquired from the damaged tire, then proposed the dominant period decision algorithm by statistical power threshold value. As the result of simulation, when driving by the speed of 80km/h, the 100ms of dominant period that measured in the proposed algorithm is more accurate than the 97.6ms of power spectrum peak period referenced on the average period of ultrasonic signal envelope peak, 101.24ms.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.232-232
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• 2023

고속도로 및 편의시설 건설로 불투수층의 면적이 증가하여 강우 시 고속도로 및 편의시설에서 발생하는 오염원에 의한 하천의 수질 영향도 커지고 있다. 특히 휴게소에서는 자동차의 급가속, 급감속으로 더욱 많은 분진과 오염물질이 발생할 수 있으며 타이어 마모 입자, 자동차 배기가스, 중금속 및 오일류 등이 휴게소나 도로 지표에 집적되어 있다. 이렇게 발생한 오염물질은 우기에 강우와 함께 불투수면을 침투하지 못하고 배수로를 통해 유출되어 인근 하천의 수생태 및 토양의 주요 오염원으로 작용하고 있다. 이에 따라 고속도로 및 인근 휴게소의 비점오염 저감대책이 필요하며 효율적인 비점오염원 저감을 위해 장기적인 모니터링, 지속적인 자료 수집 및 분석이 필요하다. 본 연구에서는 강원지역 고속도로 및 인근 휴게소에서 강우 시 강우유출수 모니터링을 통해 강우유출수 유량가중평균농도 (Event Mean Concentration) 산정하고 강우유출수 수문곡선 (hydrograph)을 작성하였다. 또한 강우사상에 따른 분석항목별 초기세척효과(First Flush Effects)와 오염부하량을 산정하였다. 추가적으로 차량 기인 입자를 확인하기 위해 μ-FT-IR 현미경 분석 실험을 하였다. 모니터링 장소는 휴게소 및 고속도로 일원이며, 모니터링은 선행무강우일수 2일 이상, 강우량 10mm 이상일 때 실시하였으며 2022년 6월부터 10월까지 총 4회 실시하였다. 모니터링 결과 타이어 및 브레이크 패드 마모와 관련된 중금속인 Zn, Cu, Pb 등의 중금속이 높게 분석되었으며 이러한 중금속의 오염부하량 역시 높게 산정되었다. 강우유출수 수문곡선에서 강우 초기 오염물질의 세척효과가 나타났다. MFFn 산정 결과 강우 30% 구간에서 초기세척효과를 보였다. μ-FT-IR 현미경 분석 결과 PE (Polyethylene)가 가장 많이 검출되었고 PP (Polypropylene), PS (Polystyrene) 순으로 검출되었다. 이러한 강우유출수 모니터링 데이터는 향후 고속도로 휴게소 및 고속도로 주변 오염저감 시설 설치 및 사회적 동참을 위한 타당한 근거 확보를 위한 기초자료로서 제공될 수 있을 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.124-132
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• 2002

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum Input images, the angle between camera and illumination was found out to be with in 90$^{\circ}$. In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.