• Journal of Information Processing Systems
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• v.19 no.6
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• pp.745-755
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• 2023

The wire rope is an indispensable production machinery in coal mines. It is the main force-bearing equipment of the underground traction system. Accurate detection of wire rope defects and positions exerts an exceedingly crucial role in safe production. The existing defect detection solutions exhibit some deficiencies pertaining to the flexibility, accuracy and real-time performance of wire rope defect detection. To solve the aforementioned problems, this study utilizes the camera to sample the wire rope before the well entry, and proposes an object based on YOLOv5. The surface small-defect detection model realizes the accurate detection of small defects outside the wire rope. The transfer learning method is also introduced to enhance the model accuracy of small sample training. Herein, the enhanced YOLOv5 algorithm effectively enhances the accuracy of target detection and solves the defect detection problem of wire rope utilized in mine, and somewhat avoids accidents occasioned by wire rope damage. After a large number of experiments, it is revealed that in the task of wire rope defect detection, the average correctness rate and the average accuracy rate of the model are significantly enhanced with those before the modification, and that the detection speed can be maintained at a real-time level.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1758-1764
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• 2012

A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.418-424
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• 2014

A large number of wire rope has been used in various industries such as cranes and elevators. When wire used for a long time, wire defects occur such as disconnection and wear. It leads to an accident and damage to life and property. To prevent this accident, we proposed a wire rope fault detection system in this paper. We constructed the whole system choosing the leakage fault detection method using hall sensors and the method is simple and easy maintenance characteristics. Fault diagnosis and analysis were available through analog filter and amplification process. The amplified signal is transmitted to the computer through the data acquisition system. This signal could be obtained improved results through the digital filter process.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.53-60
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• 2005

The wire rope of container crane is a important component to container transfer system and is used in a myriad of various applications such as elevator, mine hoist, construction machinery, and so on. If it happen wire rope failures in operating, it may lead to the safety accident and economic loss, which is productivity decline, competitive decline of container terminal, etc. To solve this problem, we developed the active and portable wire rope fault detecting system. The developed system consists of three parts that are the fault detecting, signal processing, and remote monitoring part. All detected signal has external noise or disturbance according to circumstances. Therefore we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. As experimental result, we can reduce the expense for container terminal because of extension of exchange period of wire rope for container crane and this system is possible to apply in several fields to use wire rope.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.417-423
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• 2015

In this study, Magnetic Flux Leakage(MFL)-based inspection system was applied to detect the local fault of wire rope. To verify the feasibility of the proposed damage detection technique, an 4-channel MFL sensor head prototype was designed and fabricated. A wire rope with several types of cross-sectional damages were fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the wire rope specimen. To interpret the condition of the wire rope, magnetic flux signals were used to determine the locations of the flaws. To improve the resolution of signal, the instantaneous variation value of magnetic flux was utilized. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

• Journal of Navigation and Port Research
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• v.27 no.1
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• pp.97-102
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• 2003

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, the wire rope of crane is important component to container transfer. If it happens wire rope failures during the operation, it may lead to safety accident, economic loss by productivity decline and so on. To solve this problem, we developed remote wire rope fault detecting system, and this system is consisted of 3 parts that portable fault detecting part, signal processing part and remote monitoring part. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data. It is verified that the detecting system by de-noising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension fo wire ropes exchange period and could competitive power. Also, this system is possible to apply in several field such as elevator, lift and so on.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1547-1548
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• 2015

본 연구에서는 홀센서를 이용하여 크레인 와이어로프의 결함 탐지를 위하여 제작된 결함탐지 시스템의 성능 개선을 위한 방안에 대하여 연구하였다. 기존의 센서 보드 대신 플렉시블 보드를 제작하고 홀센서를 6개에서 10개로 늘려 장착하여 센서헤더부를 보완 제작하였다. 또한, 검사자가 한 눈에 알아보기 쉽도록 하기 위하여 결함 신호 측정 구간을 6개 구간에서 2개 구간으로 바꾸었으며, 정밀한 실험과 정확한 검증을 위하여 테스트베드를 제작하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.63-70
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• 2017

In this paper, a magnetic flux leakage(MFL) based steel bar damage detection was first researched to quantify the signals from damages on the wire rope. Though many researches inspecting damages using a MFL method was proceeded until the present, the researches are at the level that diagnose whether damages are or not. This has limitation to take measures in accordance with the damage level. Thus, a MFL inspection system was modeled using a finite element analysis(FEM) program dealing with electromagnetism problems, and a steel bar specimen was adopted as a ferromagnetic object. Then, an experimental study was also carried out to verify the simulation results with a steel bar which has same damage conditions as the simulation. The MFL signals was nearly not affected by the increase of the inspection velocity, and the magnitudes of the signals are not identical according to the change of the defect width even the defects have same depth. On the basis of the analysis, the signal properties from the damages were extracted to classify the type of damages, and it could be confirmed that classification of damages using extracted signal properties is feasible.