Volumetric Tooth Wear Measurement of Scraper Conveyor Sprocket Using Shape from Focus-Based Method

Abstract

Volumetric tooth wear measurement is important to assess the life of scraper conveyor sprocket. A shape from focus-based method is used to measure scraper conveyor sprocket tooth wear. This method reduces the complexity of the process and improves the accuracy and efficiency of existing methods. A prototype set of sequence images taken by the camera facing the sprocket teeth is collected by controlling the fabricated track movement. In this method, a normal distribution operator image filtering is employed to improve the accuracy of an evaluation function value calculation. In order to detect noisy pixels, a normal operator is used, which involves with using a median filter to retain as much of the original image information as possible. In addition, an adaptive evaluation window selection method is proposed to address the difficulty associated with identifying an appropriate evaluation window to calculate the focused evaluation value. The shape and size of the evaluation window are autonomously determined using the correlation value of the grey scale co-occurrence matrix generated from the measured pixels' neighbourhood pixels. A reverse engineering technique is used to quantitatively verify the shape volume recovery accuracy of different evaluation windows. The test results demonstrate that the proposed method can effectively measure sprocket teeth wear volume with an accuracy up to 97.23%. discussed the wear condition of a driving sprocket and the influence of wear on the sliding distance by taking the sliding speed and sliding distance of the meshing process as the index. Wang et al. [8] also analyzed the relationship between the deformation of a ring chain and driving sprocket wear by combining numerical analysis with experiments. However, these methods are not only tedious and time-consuming, they are also not sufficiently accurate or efficient.The research of computer vision in industry field has attracted more and more attention of many researchers. Alverdi et al. [9] proposed a new way of using images to model the kerf profile in abrasive water jet milling. Qian et al. [10] presented an algorithm to compute the axis and generatrix focus on complex surfaces or irregular surfaces. A new monitoring technique for burr detection was proposed for the optimization of drill geometry and process parameters [11]. In addition, as a relatively simple and practical 3D reconstruction technology, shape from focus (SFF) has been applied to tool wear measurements [12,13], LCD/TFT (Liquid Crystal Display/Thin-Film Technology) display manufacturing [14] and grinding wheel surface morphology [15], etc.To realize 3D surface topography restoration, in 1988, Darrell et al. [16] proposed using a Laplace operator-Gauss fitting method to search the clear frame of pixels in the sequence partial focus image according to image focusing information. In the 1990s, Nayar et al. [17,18] proposed an SFF-based method and obtained the height information of the corresponding surface of the window image by searching the image position cor...

Special Features on Intelligent Imaging and Analysis

“…To measure volumetric tooth wear, a set of sequence images over sprocket teeth in a scraper conveyer can be collected. A focused morphology restoration algorithm has been applied to the image set by Ding et al [3]. The method uses image filtering with a normal distribution operator to improve the accuracy of an evaluation function.…”

Dynamic Properties of Chain Drive in a Scraper Conveyor under Various Working Conditions

“…The longwall fully mechanized mining face comprises hydraulic support, a scraper conveyor, a shearer, and other auxiliary equipment [5]. The scraper conveyor is the only coal transportation equipment and the running track of the shearer and the fulcrum of the hydraulic support [6][7][8].…”