scholarly journals Using a vision sensor system for performance testing of satellite-based tractor auto-guidance

2010 ◽  
Vol 72 (2) ◽  
pp. 107-118 ◽  
Author(s):  
Dwight R. Easterly ◽  
Viacheslav I. Adamchuk ◽  
Michael F. Kocher ◽  
Roger M. Hoy
Keyword(s):  
Performance Testing ◽  
Sensor System ◽  
Vision Sensor

Welding seam recognition and tracking for a novel mobile welding robot based on multi-layer sensing strategy

2021 ◽  
Author(s):  
Chao Liu ◽  
Hui Wang ◽  
Yu Huang ◽  
Youmin Rong ◽  
Jie Meng ◽  
...  
Keyword(s):  
Seam Tracking ◽  
Sensor System ◽  
Vision Sensor ◽  
Welding Robot ◽  
Welding Seam ◽  
Localization And Mapping ◽  
Laser Vision Sensor ◽  
Tracking Ability ◽  
Mobile Welding Robot ◽  
Laser Vision

Abstract Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.

Visual Sensing System for Thin Plate Welding Based on Rotund Facular Laser

2012 ◽  
Vol 538-541 ◽  
pp. 1498-1501
Author(s):  
Wang Ping Gu ◽  
Zhen Yu Xiong ◽  
Pin Liu
Keyword(s):  
Thin Plate ◽  
Visual Image ◽  
Sensor System ◽  
Vision Sensor ◽  
Butt Welding ◽  
Vision Sensing ◽  
Sensing System ◽  
Visual Sensing ◽  
Processing Software ◽  
Image Processing Software

In order to solve the problem of thin plate butt-welded tracking, a welding vision sensing system with a rotund facular laser has been designed. In the vision sense system, each parameter of the interior part has been designed by a variety of experiments. The designed image processing software can precisely identify the position of the joint, based on the optimal designed vision sensor system. The thin plate butt welding experiments have been taken with the designed sensing device. The experimental results show that the vision sensor system with a suitable auxiliary illuminant can obtain satisfying visual image information in stainless thin plate butt-welded.

Vision sensor system for the environment of disaster

1991 ◽  
Author(s):  
Yoshikazu Kawauchi ◽  
Koichi Kawata
Keyword(s):  
Sensor System ◽  
Vision Sensor

An on-board vision sensor system for small unmanned vehicle applications

2012 ◽  
Vol 23 (3) ◽  
pp. 403-415 ◽  
Author(s):  
Beau J. Tippetts ◽  
Dah-Jye Lee ◽  
James K. Archibald
Keyword(s):  
Sensor System ◽  
Vision Sensor ◽  
Unmanned Vehicle

scholarly journals SENSOR SYSTEM DESIGN FOR PROPELLER TEST BENCH

Vortex ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 37
Author(s):  
Nurul Ihsan ◽  
Denny Dermawan ◽  
Lazuardy Rahendra P
Keyword(s):  
System Design ◽  
Test Bench ◽  
Performance Testing ◽  
Sensor System ◽  
Average Error ◽  
Test Results ◽  
Wood Type ◽  
Error Factor ◽  
Measurement Results ◽  
Sensor System Design

The sensor system is a system that functions to detect signals that come from changes in energy such as electrical energy, physical energy, chemical energy, biological energy, mechanical energy, and so on. The propeller test bench is an propeller performance testing platform prior to propeller installation on an aircraft to ensure engine suitability. The purpose of this design is to test the performance capability of the engine with the right sensor system measurement tool so that it can generate the value of thrust, rpm speed, and the temperature of an engine which will be designed to be used in the learning process to support propulsion practicum activities. The method used in this research is an experimental method of sensor system design. The design of the sensor system consists of a tachometer as a rpm measurement sensor, a thermostat as a sensor to measure the temperature of the propeller spool and temperature of the engine fin, and also a load cell as a sensor to measure the thrust value.The sensor system test results were then validated using the measurement results by the sensor manufacturer. The test was carried out on a wood-type propeller measuring 22 x 8 chords 4,5 cm and 5 cm. Based on the test results, it is known that the chord wood type propeller is 4,5 cm, at the maximum rpm is 7021.7, the resulting thrust value is 6.75. In testing the 5cm chord wood type propeller shows the maximum speed of 6977.5 produces a thrust of 6.95. Validation was carried out on the measurement results of rpm and thrust, the average error factor obtained for 4,5 cm chord wood type propeller was 0.783%, while for 5 cm chord wood type propeller the average error factor obtained was 1.0582%. From the resulting average error, it can be concluded that the measuring instrument for this sensor system has good accuracy

A bio-inspired apposition compound eye machine vision sensor system

2009 ◽  
Vol 4 (4) ◽  
pp. 046002 ◽  
Author(s):  
J D Davis ◽  
S F Barrett ◽  
C H G Wright ◽  
M Wilcox
Keyword(s):  
Machine Vision ◽  
Compound Eye ◽  
Sensor System ◽  
Vision Sensor

scholarly journals An Advanced Edge-Detection Method for Noncontact Structural Displacement Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4941
Author(s):  
Xin Bai ◽  
Mijia Yang ◽  
Beena Ajmera
Keyword(s):  
Edge Detection ◽  
Natural Frequencies ◽  
Vision System ◽  
Cost Effective ◽  
Sensor System ◽  
Mode Shapes ◽  
Testing System ◽  
Vision Sensor ◽  
Street Sign ◽  
Edge Detection Method

A non-contact vision sensor system for monitoring structural displacements with advanced Zernike subpixel edge detection technique is suggested in this paper. Edge detection can detect features of objects effectively without using templates. Subpixel techniques provide more accurate and cost-effective results when compared to integer pixel methods. Built on these two techniques, a new version sensor method was developed to detect the vibrations of structures in this study. Satisfactory agreements were found between the displacements measured by the vision sensor system and those recorded by the Multipurpose Testing System (MTS). A field test was then carried out on a street sign using the proposed vision system. Satisfactory results were obtained using the new version of the sensor system at many points simultaneously without any manually marked targets. Moreover, the system was able to provide natural frequencies and mode shapes of the target instantaneously, which could be used to accurately locate damage.

scholarly journals Reliable Template Matching for Image Detection in Vision Sensor Systems

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8176
Author(s):  
Youngmo Han
Keyword(s):  
Template Matching ◽  
Closed Form Solution ◽  
Detection Algorithm ◽  
Ease Of Use ◽  
Sensor System ◽  
Size Difference ◽  
Vision Sensor ◽  
Projection Model ◽  
Image Detection ◽  
Additional Information

Template matching is a simple image detection algorithm that can easily detect different types of objects just by changing the template without tedious training procedures. Despite these advantages, template matching is not currently widely used. This is because traditional template matching is not very reliable for images that differ from the template. The reliability of template matching can be improved by using additional information (depths for the template) available from the vision sensor system. Methods of obtaining the depth of a template using stereo vision or a few (two or more) template images or a short template video via mono vision are well known in the vision literature and have been commercialized. In this strategy, this paper proposes a template matching vision sensor system that can easily detect various types of objects without prior training. To this end, by using the additional information provided by the vision sensor system, we study a method to increase the reliability of template matching, even when there is a difference in the 3D direction and size between the template and the image. Template images obtained through the vision sensor provide a depth template. Using this depth template, it is possible to predict the change of the image according to the difference in the 3D direction and the size of the object. Using the predicted changes in these images, the template is calibrated close to the given image, and then template matching is performed. For ease of use, the algorithm is proposed as a closed form solution that avoids tedious recursion or training processes. For wider application and more accurate results, the proposed method considers the 3D direction and size difference in the perspective projection model and the general 3D rotation model.

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