Vibration identification of the roadheader cutting head using high-speed cameras

Cheluszka, Piotr; Mann, Rajmund

doi:10.1051/matecconf/201925203018

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Similarly, [48] [96] presented a method for detecting the side surface shape of the cutting head. They also determined the boom [97] and cutting head [98] vibrations of the roadheader during cutting based on an analysis of the time-lapse pictures of the recorded footage obtained from high-speed cameras using dedicated TEMA 3D software. The aforementioned studies significantly contribute to enhancing the intelligence level of tunneling equipment and enabling automatic mining of underground roadways.…”

Section: ) Cutting Head Visual Detectionmentioning

confidence: 99%

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Du,

Zhang,

Liang

et al. 2023

IEEE Access

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The realization of intelligent mining is the only method for realizing high-quality development in the coal industry. As the forefront working link in mine production, achieving automatic roadway tunneling control is key to improving production efficiency, enhancing intelligence, and reducing accident rates at fully mechanized tunneling working faces. Among various detection techniques, machine vision technology stands out with advantages of non-contact measurement, rich information acquisition, and high detection accuracy. The detection and control of tunneling equipment groups based on machine vision has become a research hotspot in the intelligence process of coal mines. This study first introduces the key technologies of a visual detection system, including camera calibration, image preprocessing, feature extraction, visual matching, target segmentation and recognition, visual measurement, and 3D reconstruction. It then elaborates on detection principles, workflows, limitations, precautions, and development status of various vision detection systems in practical application scenarios at tunneling faces, such as tunneling equipments, anchoring systems, transportation systems, and safety auxiliary systems, which significantly improve production safety and efficiency. Finally, considering challenging work conditions and strong interference in mines, the successful adaptation of machine vision to excavation sites relies on addressing technical challenges related to poor environment adaptability, limited imaging field of view, and low intelligence level. Furthermore, according to existing research results and the current technical status, this paper forecasts key technologies that need to be developed in the future for coal mine intelligent equipment systems based on machine vision, including multi-sensor information fusion, equipment group collaborative control, and digital twin-driven remote monitoring.INDEX TERMS Machine vision, coal machinery equipment, detection and measurement, roadway fully mechanized tunneling faces, unmanned coal mine.

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Section: ) Cutting Head Visual Detectionmentioning

confidence: 99%

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Du,

Zhang,

Liang

et al. 2023

IEEE Access

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“…During the discussed measurements it was 2⋅10-5 s. With such a short exposure time, an important factor affecting the quality of the recorded film material was adequate lighting, without which it would have not been possible to obtain the required contrast necessary for the digital image analysis (Cheluszka & Mann, 2019). Despite the high optical sensitivity of cameras, the ultra-short recording times of individual film frames required the use of very strong light.…”

Section: Measuring Systemmentioning

confidence: 99%

Determination of boom vibrations of the road header during cutting based on the analysis of images from high-speed cameras

Cheluszka

Mann

2019

New Trends in Production Engineering

Self Cite

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Excavation, especially of hard rocks, using boom-type road headers is a source of strong vibrations of the boom in which they are equipped. These vibrations are transferred through construction nodes further to the turntable and the body of the road header. On the one hand, they are of great importance from the point of view of the durability and the reliability of the mining machine. On the other hand, they affect the variability of the parameters at which the process of cutting the heading face surface of a drilled roadway or tunnel is carried out. For the purpose of determining the vibration intensity of the boom of the road header a photogrammetry system based on two high-speed cameras Phantom Miro LC 120 was used. During the experimental investigations of the cutting process of a cement-sand block using the R-130 road header, the boom and turntable movements were recorded. The analysis of the time-lapse pictures of the recorded footage obtained from the high-speed cameras using dedicated TEMA 3D software allowed to determine the spatial trajectory of movement of the boom and the turntable during the cutting of the massive with specified mechanical properties with set values of the parameters of this process. Basing on the time courses of the coordinates of the boom and turntable characteristic points, the courses of the actual boom swinging speed and acceleration components of its vibrations were determined. The intensity of these vibrations was related to the conditions of the cutting process.

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“…Acaroglu compared and analyzed the vibration characteristics and stability of the cutting head of the roadheader under different cutting modes. According to stability analysis for the roadheader with point attack cutters, there might be a stability problem at turning around the vertical axis stability state in arcing the cutting mode [6]. Huang established a nonlinear dynamic model and carried out vibration analysis of the bearing under time-varying loads in order to study the dynamic characteristics of the cutting head and the cantilever beam system [7].…”

Section: Introductionmentioning

confidence: 99%

Health Diagnosis of Roadheader Based on Reference Manifold Learning and Improved K‐Means

Yang²,

et al. 2021

Shock and Vibration

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The safe and stable operation of roadheader is of great significance to the efficient and rapid production of a coal mine. Health diagnosis based on vibration signals has been studied in bearings and motors. Complex geological conditions and bad working environment lead to the characteristics of nonlinear and time-varying vibration signals of a roadheader. In this paper, a health state analysis method based on reference manifold (RM) learning and improved K-means clustering analysis was proposed; the method was verified by using the real-time collected roadheader cutting reducer fault signal. Firstly, the comparison signal and analysis signal were extracted from the actual collected vibration data of the roadheader, and the referential analysis samples were constructed through time domain and wavelet packet energy analysis. Then, the characteristic structure of the low-dimensional space of the referential analysis samples is obtained by Locally Linear Embedding (LLE), which is a method of manifold learning. Through the improved K-means clustering analysis method, the low-dimensional structure parameters were analyzed and the clustering effect index was obtained, which was used as the health evaluation index (HEI). Finally, the normal distribution model of the health evaluation index is established, and the confidence interval of the health evaluation index is determined, so as to realize the health state analysis of the roadheader and realize the fault warning function. Through the analysis of data of three sensors, the results show that the roadheader failed on the 15th day, which is consistent with the actual working condition. Through practical analysis, the effectiveness of the method was verified and provided a kind of fault analysis idea and method for equipment working under complex working conditions and the theoretical basis for fault type analysis.

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Vibration identification of the roadheader cutting head using high-speed cameras

Cited by 5 publications

References 4 publications

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Determination of boom vibrations of the road header during cutting based on the analysis of images from high-speed cameras

Health Diagnosis of Roadheader Based on Reference Manifold Learning and Improved K‐Means

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