scholarly journals Automated Dimension Measurement System

2021 ◽  
Vol 10 (5) ◽  
pp. 163-169
Author(s):  
Shubham Kakirde ◽  
Shubham Jain ◽  
Swaraj Kaondal ◽  
Reena Kumbhare ◽  
Rita Das
Keyword(s):  
Conveyor Belt ◽  
Detection Algorithm ◽  
Average Error ◽  
Laser Triangulation ◽  
Single Camera ◽  
System Complexity ◽  
Dimension Measurement ◽  
Processing Accuracy ◽  
Laser Module ◽  
The Cost

In this fast-paced world, it is inevitable that the manual labor employed in industries will be replaced by their automated counterparts. There are a number of existing solutions which deal with object dimensions estimation but only a few of them are suitable for deployment in the industry. The reason being the trade-off between the cost, time for processing, accuracy and system complexity. The proposed system aims to automate the mentioned tasks with the help of a single camera and a line laser module for each conveyor belt setup using laser triangulation method to measure the height and edge detection algorithm for measuring the length and breadth of the object. The minimal use of equipment makes the system simple, power and time efficient. The proposed system has an average error of around 3% in the dimension estimation.

scholarly journals Dimension Measurement and Key Point Detection of Boxes through Laser-Triangulation and Deep Learning-Based Techniques

2019 ◽  
Vol 10 (1) ◽  
pp. 26 ◽  
Author(s):  
Tao Peng ◽  
Zhijiang Zhang ◽  
Fansheng Chen ◽  
Dan Zeng
Keyword(s):  
Deep Learning ◽  
Vision System ◽  
Likelihood Estimation ◽  
Optimization Method ◽  
Detection Algorithm ◽  
Laser Triangulation ◽  
Box Dimension ◽  
Logistics Industry ◽  
Dimension Measurement ◽  
Point Detection

Dimension measurement is of utmost importance in the logistics industry. This work studies a hand-held structured light vision system for boxes. This system measures dimension information through laser triangulation and deep learning using only two laser-box images from a camera and a cross-line laser projector. The structured edge maps of the boxes are detected by a novel end-to-end deep learning model based on a trimmed-holistically nested edge detection network. The precise geometry of the box is calculated by the 3D coordinates of the key points in the laser-box image through laser triangulation. An optimization method for effectively calibrating the system through the maximum likelihood estimation is then proposed. Results show that the proposed key point detection algorithm and the designed laser-vision-based visual system can locate and perform dimension measurement of measured boxes with high accuracy and reliability. The experimental outcomes show that the system is suitable for portable automatic box dimension online measurement.

scholarly journals Preventive maintenance of multiple components for hydraulic tension systems

2021 ◽  
Vol 23 (3) ◽  
pp. 489-497
Author(s):  
Hongyan Dui ◽  
Xiaoqian Zheng ◽  
Qian Qian Zhao ◽  
Yining Fang
Keyword(s):  
Working Conditions ◽  
Preventive Maintenance ◽  
Conveyor Belt ◽  
Tension Force ◽  
Maintenance Cost ◽  
Number Of Components ◽  
Multiple Components ◽  
Conveyor Belts ◽  
The Cost

Automatically controlled hydraulic tension systems adjust the tension force of a conveyor belt under different working conditions. Failures of an automatically controlled hydraulic tension system influence the performance of conveyor belts. At present, the maintenance of automatically controlled hydraulic tension systems mainly considers the replacement of components when failures occur. Considering the maintenance cost and downtime, it is impossible to repair all the failed components to improve the hydraulic tension system. One of the key problems is selecting the most valuable components for preventive maintenance. In this paper, preventive maintenance for multiple components in a hydraulic tension system is analyzed. An index is proposed to select more reliable preventive maintenance components to replace the original ones. A case study is given to demonstrate the proposed method. When the cost budget increases, there are three different variations in the number of components for selective preventive maintenance (SPM).

scholarly journals Evaluating the role of community detection in improving influence maximization heuristics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
László Hajdu ◽  
Miklós Krész ◽  
András Bóta
Keyword(s):  
Community Detection ◽  
Real Life ◽  
Detection Algorithm ◽  
Influence Maximization ◽  
Overlapping Community Detection ◽  
Detection Algorithms ◽  
Overlapping Community ◽  
Community Detection Algorithm ◽  
The Cost

AbstractBoth community detection and influence maximization are well-researched fields of network science. Here, we investigate how several popular community detection algorithms can be used as part of a heuristic approach to influence maximization. The heuristic is based on the community value, a node-based metric defined on the outputs of overlapping community detection algorithms. This metric is used to select nodes as high influence candidates for expanding the set of influential nodes. Our aim in this paper is twofold. First, we evaluate the performance of eight frequently used overlapping community detection algorithms on this specific task to show how much improvement can be gained compared to the originally proposed method of Kempe et al. Second, selecting the community detection algorithm(s) with the best performance, we propose a variant of the influence maximization heuristic with significantly reduced runtime, at the cost of slightly reduced quality of the output. We use both artificial benchmarks and real-life networks to evaluate the performance of our approach.

scholarly journals Two-terminal fault detection and location for hybrid transmission circuit

2021 ◽  
Vol 23 (2) ◽  
pp. 639
Author(s):  
Muhd Hafizi Idris ◽  
Mohd Rafi Adzman ◽  
Hazlie Mokhlis ◽  
Mohammad Faridun Naim Tajuddin ◽  
Haziah Hamid ◽  
...  
Keyword(s):  
Fault Detection ◽  
Fault Location ◽  
Detection Algorithm ◽  
Positive Sequence ◽  
Fault Estimation ◽  
Average Error ◽  
Fault Resistance ◽  
Hybrid Transmission ◽  
Check Method ◽  
Location Algorithm

This paper presents the algorithms developed to detect and locate the faults ata hybrid circuit. First, the fault detection algorithm was developed using the comparison of total positive-sequence fault current between pre-fault and fault times to detect the occurrence of a fault. Then, the voltage check method was used to decide whether the fault occurred at overhead line (OHL) or cable section. Finally, the fault location algorithm using the impedance-based method and negative-sequence measurements from both terminals of the circuit were used to estimate the fault point from local terminal. From the tests of various fault conditions including different fault types, fault resistance and fault locations, the proposed method successfully detected all fault cases at around 1 cycle from fault initiation and with correct faulted section identification. Besides that, the fault location algorithm also has very accurate results of fault estimation with average error less than 1 km and 1%.<br /><div> </div>

Sub-Pixel Edge Detection Algorithm Based on Canny–Zernike Moment Method

2020 ◽  
Vol 29 (15) ◽  
pp. 2050238
Author(s):  
Cheng Huang ◽  
Wei Jin ◽  
Qian Xu ◽  
Ziqi Liu ◽  
Zhiliang Xu
Keyword(s):  
Edge Detection ◽  
Moment Method ◽  
Detection Algorithm ◽  
Zernike Moment ◽  
Threshold Method ◽  
Transform Method ◽  
Edge Detection Algorithm ◽  
Running Time ◽  
Dimension Measurement ◽  
Low Efficiency

In order to solve the problems of low efficiency and long running time caused by the traditional Zernike moment method for convolution calculation of the whole image, this paper combines the canny detection algorithm with the Zernike moment method. First, the canny edge detection algorithm, which combined with the Otsu threshold method, is used to extract the pixel edge of the image. Then an improved Hough transform method is used to fit the geometric edge in the image. Based on this, the Zernike moment method is applied to realize sub-pixel positioning of images. The algorithm improves the deficiencies of direct sub-pixel detection, improving accuracy and reducing running time. To verify the effectiveness of the proposed algorithm, the algorithm is applied to the dimension measurement experiment of T-type guide way. The results clearly show that the algorithm is superior to the traditional algorithm in accuracy.

Research of Line-Friction Multi Driving Belt Conveyor

2013 ◽  
Vol 716 ◽  
pp. 638-642
Author(s):  
Yong Sheng Deng ◽  
Yong Zhang ◽  
Tao Zhou ◽  
Yong Sheng Zhou
Keyword(s):  
Driving Forces ◽  
Conveyor Belt ◽  
Transmission Mechanism ◽  
Belt Conveyor ◽  
Lower Intensity ◽  
Conveyor System ◽  
Driving Mode ◽  
Maximum Tension ◽  
Drive Motor ◽  
The Cost

On the basis of analyzing the line friction belt conveyor transmission mechanism of driving forces, the calculation method of driving force, as well as the design essentials of this conveyor system were pointed out. According to the conditons that the line friction drive motor power, the driving belt tensile strength and its minimum tension, the calculation formula of transmission belt length were obtained respectively. Meanwhile according to the maximum tension that supporting belt permitted, the position of the driving belt would be confirmed. Line friction driving mode may reduce the conveyor belt maximum tension, that is, the belt with a lower intensity levels could be selected, thereby the cost of conveying belt would be greatly reduced.

scholarly journals Laser Triangulation in 3-Dimensional Granulometric Analysis

2016 ◽  
Vol 61 (1) ◽  
pp. 15-27 ◽  
Author(s):  
Adam Heyduk
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Particle Surface ◽  
Three Dimensional ◽  
Spatial Arrangement ◽  
Conveyor Belt ◽  
Laser Triangulation ◽  
Depth Maps ◽  
Coal Particles

Abstract The measurement of the particle size distribution plays an important role in mineral processing. Due to the high costs and time-consumption of the screening process, modern machine vision methods based on the acquisition and analysis of recorded photographic images. But the image analysis methods used so far, do not provide information on the three-dimensional shape of the grain. In the coal industry, the application scope of these methods is substantially limited by the low reflectivity of the black coal particle surface. These circumstances hinder proper segmentation of coal stream surface image. The limited information contained in two-dimensional image of the raw mineral stream surface, makes it difficult to identify proper size of grains partially overlapped by other particles and skewed particles. Particle height estimation based on the shadow length measurement becomes very difficult in industrial environment because of the fast movement of the conveyor belt and because of spatial arrangement of these particles, usually touching and overlapping. Method of laser triangulation connected with the movement of the conveyor belt makes it possible to create three-dimensional depth maps. Application of passive triangulation methods (e.g. stereovision) can be impeded because of the low contrast of the black coal on the black conveyor belt. This forces the use of active triangulation methods, directly identifying position of the analyzed image pixel. High contrast of the image can be obtained by a direct pointwise laser lighting. For the simultaneous identification of the entire section of the raw material stream it is useful to apply a linear laser (a planar sheet of the laser light). There have been presented basic formulas for conversion of pixel position on the camera CCD matrix to the real-word coordinates. A laboratory stand has been described. This stand includes a linear laser, two high-definition (2Mpix) cameras and stepper motor driver. The triangulation head moves on the rails along the belt conveyor section. There have been compared acquired depth maps and photographic images. Depth maps much better describe spatial arrangement of coal particles, and have a much lower noise level resulting from the specular light reflections from the shiny fragments of the particle surface. This makes possible an identification of the coal particles partially overlapped by other particles and obliquely arranged particles. It enables a partial elimination or compensation of image disturbances affecting the final result of the estimated particle size distribution. Because of the possibility of the reflected laser beam overriding by other particles it is advantageous to use a system of two cameras. Results of the experimental research confirmed the usefulness of the described method in spite of low reflectance factor of coal surface. The fast detection of changes in particle size distribution makes possible an on-line optimization of complex technological systems - especially those involving coal cleaning in jigs - thus leading to better stabilization of quality parameters of the enrichment output products. An additional application of the described method can be achieved by measuring the total volume of the stream of the transported materials. Together with the measurement signal from the belt conveyor weight it makes possible to estimate the bulk density of the raw mineral stream. The low complexity of the signal processing in the laser triangulation method is associated with the acquisition of high contrast images and analysis based on simple trigonometric dependencies.

scholarly journals Adaptive Multi-View Image Mosaic Method for Conveyor Belt Surface Fault Online Detection

2021 ◽  
Vol 11 (6) ◽  
pp. 2564
Author(s):  
Rui Gao ◽  
Changyun Miao ◽  
Xianguo Li
Keyword(s):  
Conveyor Belt ◽  
Detection Algorithm ◽  
Image Mosaic ◽  
Online Detection ◽  
Estimation Model ◽  
Registration Method ◽  
Speeded Up Robust Features ◽  
Registration Rate ◽  
Feature Based ◽  
Overlapping Region

In order to improve the accuracy and real-time of image mosaic, realize the multi-view conveyor belt surface fault online detection, and solve the problem of longitudinal tear of conveyor belt, we in this paper propose an adaptive multi-view image mosaic (AMIM) method based on the combination of grayscale and feature. Firstly, the overlapping region of two adjacent images is preliminarily estimated by establishing the overlapping region estimation model, and then the grayscale-based method is used to register the overlapping region. Secondly, the image of interest (IOI) detection algorithm is used to divide the IOI and the non-IOI. Thirdly, only for the IOI, the feature-based partition and block registration method is used to register the images more accurately, the overlapping region is adaptively segmented, the speeded up robust features (SURF) algorithm is used to extract the feature points, and the random sample consensus (RANSAC) algorithm is used to achieve accurate registration. Finally, the improved weighted smoothing algorithm is used to fuse the two adjacent images. The experimental results showed that the registration rate reached 97.67%, and the average time of stitching was less than 500 ms. This method is accurate and fast, and is suitable for conveyor belt surface fault online detection.

Sign in / Sign up

Export Citation Format

Share Document