Ensuring the compliance of the finished product with the project during the manufacturing of cutting heads/drums of the mining machines, largely determines the efficiency of rock mining, especially hard-to-cut rocks. The manufacturing process of these crucial elements of cutting machines is being robotized in order to ensure high accuracy and repeatability. This determines, among others the need to assess in real-time the degree of the approach of pick holders positioned by the industrial robot to the side surface of the working unit of the cutting machine in their target position. This problem is particularly important when in the manufacturing process are used the bodies of decommissioned cutting heads/drums, from which old pick holders have been removed. The shape and external dimensions of these hulls, unless they are subjected to regeneration, may differ quite significantly from the nominal ones. The publication, on the example of a road header cutting head, presents the procedure for automatically identifying and indexing markers displayed on its side surface, recorded on measuring photos by two digital cameras of a 3D vision system. Experimental research of the developed method was carried out using the KUKA VisionTech vision system installed on the test stand in the robotics laboratory of the Department of Mining Mechanization and Robotization at the Faculty of Mining, Safety Engineering and Industrial Automation of the Silesian University of Technology. Data processing was carried out in the Matlab environment using the libraries of the Image Processing Toolbox. The functions provided in this library were used in the developed algorithm, implemented in the software. This algorithm allows automatic identification of markers located in the images of the side surface of the cutting head. This is the basis for determining their location in space. The publication presents a method of segmenting images recorded by cameras into homogeneous areas. The method of separating interesting areas from the image by comparison to the pattern was presented. Also shown is the method of the automatic numbering of mutually matching pairs of markers on photos from two cameras included in the vision system depending on the spatial orientation of the marker grid in the measuring images.
For effective mining, it is essential to ensure that the picks are positioned correctly on the working unit of a mining machine. This is due to the fact that the design of roadheader cutting heads/drums using computer-aided tools is based on the operating conditions of the roadheader/shearer/milling machine. The geometry of the cutting head is optimized for selected criteria by simulating the mining process using a computer. The reclaimed cutting head bodies that are utilized in production are manufactured again in the overhaul process. Ensuring that the dimensions of the cutting head bodies match the rated dimensions is labor-intensive and involves high production costs. For dimensional deviations of the cutting head bodies, it is necessary to control the position of the pick holders relative to the cutting head side surface in real time during robotic-assisted assembly. This article discusses the possibility of utilizing a stereovision system for calculating the distance between the pick holder base and the roadheader cutting head side surface at the point where the pick holder is mounted. The proposed measurement method was tested on a robotic measurement station constructed for the purpose of the study. A mathematical measurement model and procedures that allow automatic positioning of the camera system to the photographed objects, as well as acquisition and analysis of the measurement images, were developed. The proposed method was validated by using it for measuring the position of the pick holders relative to the side surface of the working unit of a mining excavating machine, focusing on its application in robotic technology. The article also includes the results observed in laboratory tests performed on the developed measurement method with an aim of determining its suitability for the metrology task under consideration.
The efficiency of rock cutting with mining machines is largely determined by the arrangement of picks, i.e. the number and their arrangement on the working unit of the mining machine. Not only the correct selection of the pick system for given conditions at the design stage is important, but also ensuring compliance with the design of the finished product. Strives, among others therefore, for robotisation of the process of manufacturing cutting heads/drums. From the point of view of the robotisation of the pick holders welding process, it is necessary to assess in real time the position of the pick holders relative to the side surface of the cutting head body. A convenient way is to use contactless measurement methods based on vision systems. The article presents a method of determining the position of pick holders relative to the side surface of the cutting head body of a roadheader, during their positioning, using a 3D vision system. Data processing was carried out in the Matlab software using the libraries of the Computer Vision Toolbox. A mathematical model describing the transformation of images recorded by cameras has been presented. On the basis of this model, the distribution of distances between the pick holder base points and the side surface of the cutting head was determined for a given pick holder setting. The developed measurement method was tested on an experimental stand built in the Laboratory of robotics of the Department of Mining Mechanization and Robotisation at the Silesian University of Technology.
The stereometry of the working units of mining machines is optimized at the design stage, in terms of selected criteria based on computer simulations of the mining process. The recovered bodies of cutting heads or drums used in manufacturing are regenerated in the overhaul process. Ensuring that their dimensions comply with the nominal ones is labor-intensive and raises production costs. However, deviations of these components from the nominal shape can make it difficult to position the pick holders (which can cause collisions) or make welding them impossible (which results from too large a distance between the pick holders’ base and the side surface of the working unit). This applies especially to robotic technologies. By utilizing automatic (online) measurements of the distribution of the actual distances of the pick holders’ bases from the side surface of the working unit (taken during their positioning using a robot), it is possible to correct their positions without changing the setting of the pick itself. This measurement can be carried out using the non-contact stereovision method. This paper presents a method of matching raster images obtained from a stereovision system installed on an experimental robotic station. The results are presented of the numerical research carried out to select a mathematical model of the geometric transformation of images, for ensuring the effectiveness of the developed method.
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