scholarly journals Mechanical System and Template-Matching-Based Position-Measuring Method for Automatic Spool Positioning and Loading in Welding Wire Winding

2020 ◽  
Vol 10 (11) ◽  
pp. 3762 ◽  
Author(s):  
Jie Xu ◽  
Xin He ◽  
Weixi Ji
Keyword(s):  
Mechanical System ◽  
Template Matching ◽  
Angular Position ◽  
Measuring Method ◽  
Feature Point ◽  
Major Type ◽  
Welding Wire ◽  
Point Distribution ◽  
Matching Process ◽  
Welding Consumable

Welding wire is a major type of welding consumable, which needs to be winded onto spools for sale. Currently, the winding process is accomplished manually due to obstacles such as automatic spool loading and clamping. When loading the spool, the angular position of the spool is a prerequisite for matching the drive rod on the spindle and drive bore on the spool. Therefore, this paper proposes a template-matching method combined with area-based matching and feature-point detection to measure the angular position of the spool, and presents a mechanical system that can rotate the spool to match the drive rod and push the spool onto the spindle. A novel feature-point distribution density (FPDD) method was developed to accelerate the matching process and improve matching reliability by pre-locating the searching area. The robustness and accuracy of the template-matching-based measuring method were validated using a built prototype of the mechanical system. The comparison result shows that the proposed method was superior in robustness, accuracy, and speed, and it was efficient for automatic spool loading in the welding wire winding process.

scholarly journals A Multiscale Constraints Method Localization of 3D Facial Feature Points

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Hong-an Li ◽  
Yongxin Zhang ◽  
Zhanli Li ◽  
Huilin Li
Keyword(s):  
Facial Feature ◽  
Feature Point ◽  
Distribution Model ◽  
Feature Points ◽  
Widespread Application ◽  
Point Distribution ◽  
Localization Accuracy ◽  
Localization Method ◽  
Relative Angle ◽  
Point Distribution Model

It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms.

A rapid seismic data calibration technique using integrated micro-electro-mechanical system inertial sensor groups for a 3C vertical seismic profile

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. P109-P118
Author(s):  
Huailiang Li ◽  
Xianguo Tuo ◽  
Tong Shen ◽  
Mark Julian Henderson ◽  
Jérémie Courtois
Keyword(s):  
Mechanical System ◽  
Seismic Data ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Measuring Method ◽  
Seismic Profile ◽  
Micro Electro Mechanical System ◽  
Vertical Seismic Profile ◽  
Sensor Package

Calibration of 3C vertical seismic profile (VSP) data is an exciting challenge because the orientation of the tool is random when only seismic data are considered. We have augmented the sensor package on the VSP tool with micro-electro-mechanical system (MEMS) inertial sensors and applied a gesture measuring method to determine the tool orientation and calibration. This technique can quickly produce high precision, orientation, and angle information when integrated with the seismometer. The augmented sensor package consists of a low-cost triaxial MEMS gyroscope, an electronic compass, and an accelerometer. The technique to process the gesture information is based on the OpenGL software for 3D modeling. We have tested this approach on a large number of field data sets and it appeared to be faster and more reliable than other approaches.

A Fast and Precise Measuring Method for Large Workpiece Based on Machine Vision

2010 ◽  
Vol 139-141 ◽  
pp. 2076-2081 ◽  
Author(s):  
Hu Zhou ◽  
Jian Guo Yang
Keyword(s):  
Machine Vision ◽  
Template Matching ◽  
Vision System ◽  
Measuring Method ◽  
Search Space ◽  
Field Of View ◽  
Image Mosaic ◽  
Machine Vision System ◽  
Stop Criterion ◽  
Machine Parts

Image measurement based on machine vision is a promising method for the precise measurements of machine parts. As for a large sized workpiece that exceeds the FOV (field of view) of the camera, image mosaic must be performed to implement measurement. While traditional template matching algorithms will lead to long runtime consumption, a combination of algorithms with precise mechanical positioning function using motion control was proposed and applied in the machine vision system. The manufacturing and installing errors have been taken into account to improve the positioning accuracy. This method minimized the search space and thereby reduced the runtime substantially. In addition, a stop criterion of the computation for the algorithms was applied to save a considerable amount of time in the process. Experimental results show that the precision of the image mosaic meets the requirements while speeding up the process significantly.

Methodology to Optimize and Predict the Measurement Point Distribution for Compressor Mapping on the Hot-Gas Test Bench

2019 ◽  
Author(s):  
Holger Mai ◽  
André Kaufmann ◽  
Mathias Vogt
Keyword(s):  
Rotational Speed ◽  
Internal Combustion Engines ◽  
Test Bench ◽  
Logical Consequence ◽  
Test System ◽  
Engine Operation ◽  
Point Distribution ◽  
Hot Gas ◽  
Operation Conditions ◽  
Matching Process

Abstract Current and future legal requirements for internal combustion engines (ICE) are increasing the complexity of modern charging systems. Test system manufacturers are facing high demands in terms of hardware specifications and methods for turbocharger testing on a hot-gas test bench. Innovative test systems and methodologies help to improve the quality of the turbocharger and engine matching process and significantly optimize the operating strategy in engine process simulation, especially in the early development and design phase. The compressor and turbine characteristic maps are the most important sources of information in order to quantify the performance of the turbocharger. This is achieved in practice by thermodynamically evaluating turbochargers on the hot-gas test bench under test conditions that are as close as possible to real engine operation conditions. Turbocharger compressor mapping relies on the measurement of pressure and temperature upstream and downstream of the compressor at designated operating points. For use in the turbocharger matching process, mostly equidistant points on the operation line between surge and choke are required. Comparison to Computational Fluid Dynamics (CFD) requires a higher density of measurement points, especially in the vicinity of maximum compressor efficiency to analyze different geometries. The requirement to measure different point distributions at fixed rotational speed is the logical consequence. The primary objective of this paper is to develop and evaluate a methodology that allows different operating point distributions of compressor speed lines for the compressor mapping on the hot-gas test bench. The secondary objective deals with the prediction of the measurement points with respect to pressure ratio and volume flow rate at a fixed rotational speed. This facilitates the pre-selection of settings on the hot-gas test bench.

scholarly journals Image recognition in online monitoring of power equipment

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141990083
Author(s):  
Guifeng Wu ◽  
Miao Yu ◽  
Wangwang Shi ◽  
Shengquan Li ◽  
Jiatong Bao
Keyword(s):  
Image Recognition ◽  
Template Matching ◽  
Online Monitoring ◽  
Source Image ◽  
Power Equipment ◽  
Target Image ◽  
Matching Algorithm ◽  
Matching Process ◽  
Abnormal State ◽  
Fast Recognition

The application of remote digital video surveillance and image recognition technology in online monitoring of power equipment is conducive to timely equipment maintenance and troubleshooting. In order to solve the problem of slow speed and large amount of computation of traditional template matching algorithm for power image recognition, a second template matching algorithm for fast recognition of target image is proposed in this article. Firstly, a quarter of the template data is taken and matched within a quarter of the source image, and a reasonable error threshold is given in the matching process. Then, the neighborhood of the minimum error point in rough matching is matched to get the final result. Finally, the algorithm is applied to identify the power equipment and detect the abnormal state of the power equipment. The experimental results show that the matching algorithm can not only accurately locate and identify power equipment and detect equipment faults, but also greatly improve the matching speed compared with other commonly used template matching algorithms.

A Fast Underwater Image Stitching Algorithm with Adaptive Adjustment of Attitude Angle

2021 ◽  
Author(s):  
Lizhou Jiang ◽  
Zhijie Tang ◽  
Zhihang Luo ◽  
Chi Wang
Keyword(s):  
Feature Point ◽  
Reference Image ◽  
Image Stitching ◽  
Panoramic Image ◽  
Feature Points ◽  
Image Capture ◽  
Matching Process ◽  
Underwater Image ◽  
Adaptive Adjustment ◽  
The Impact

In underwater image acquisition process, due to the impact of water currents and other disturbances, the movement posture of the underwater machine will be unstable, which could lead to unusual problems such as twisting of underwater image capture. These factors will increase the error rate of feature point matching and lead to the failure of panoramic image mosaic. In this regard, we propose a new, highly applicable underwater image stitching algorithm. Firstly, the posture angle adjustment link is added to the underwater image processing, and the angle deflection problem of the underwater image is effectively improved by using the posture angle information. Secondly, the feature points of underwater images are extracted based on the accelerated robust feature (SURF) algorithm. Then, the reference image is matched with the feature points of the image to be registered, and effective feature point pairs are obtained by screening. Finally, the images are stitched based on OpenCV to obtain a good panoramic image. Afterexperimental analysis and comparison, our method can increase the number of matching feature point pairs between images. In addition, the Euclidean distance is significantly shortened during the matching process, which further makes the matching of feature points more accurate. Our method satisfactorily overcomes the adverse effects of actual underwater operations and has a better application prospect.

Realtime arbitrary-shaped template matching process

2012 ◽  
Author(s):  
Dai-Duong Truong ◽  
Vinh-Tiep Nguyen ◽  
Anh-Duc Duong ◽  
Chau-Sang Nguyen Ngoc ◽  
Minh-Triet Tran
Keyword(s):  
Template Matching ◽  
Matching Process

FACE RECOGNITION IN COLOUR IMAGES USING NEURAL NETWORKS AND GENETIC ALGORITHMS

2005 ◽  
Vol 05 (01) ◽  
pp. 55-67 ◽  
Author(s):  
STEPHEN KARUNGARU ◽  
MINORU FUKUMI ◽  
NORIO AKAMATSU
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Template Matching ◽  
Distance Measure ◽  
Facial Feature ◽  
Training Data ◽  
Segmentation Method ◽  
Facial Feature Extraction ◽  
Matching Process ◽  
The Face

In this paper, a system that can automatically detect and recognise frontal faces is proposed. Three methods are used for face recognition; neural network, template matching and distance measure. One of the main problems encountered when using neural networks for face recognition is insufficient training data. This problem arises because, in most cases, only one image per subject is available. Therefore, amongst the objectives is to solve this problem by "increasing" the data available from the original image using several preprocesses, for example, image mirroring, colour and edges information, etc. Moreover, template matching is not trivial because of differences in the template shapes and sizes. In this work, template matching is aided by a genetic algorithm to automatically test several positions around the target and automatically adjust the size of the template as the matching process progresses. Distance measure method depends heavily on good facial feature extraction results. The image segmentation method applied matches such demand. The face colour information is represented using YIQ and the XYZ colour spaces. The effectiveness of the proposed method is verified by performing computer simulations. Two sets of databases were used. Database1 consists of 267 faces from the Oulu university database and database2 (for comparision purposes) consists of 250 faces from the ORL database.

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