scholarly journals Real-Time Tunnel Deformation Monitoring Technology Based on Laser and Machine Vision

2018 ◽  
Vol 8 (12) ◽  
pp. 2579 ◽  
Author(s):  
Zurong Qiu ◽  
Haopeng Li ◽  
Wenchuan Hu ◽  
Chenglin Wang ◽  
Jiachen Liu ◽  
...  
Keyword(s):  
Machine Vision ◽  
Laser Beam ◽  
Real Time ◽  
Measurement Errors ◽  
Detection System ◽  
Deformation Monitoring ◽  
Interest Points ◽  
Real Time System ◽  
Deformation Velocity ◽  
Low Visibility

Structural health monitoring is a topic of great concern in the world, and tunnel deformation monitoring is one of the important tasks. With the rapid developments in tunnel traffic infrastructure construction, engineers need a portable and real-time system to obtain the tunnel deformation during construction. This paper reports a novel method based on laser and machine vision to automatically measure tunnel deformation of multiple interest points in real time and effectively compensate for the environment vibration, and moreover it can overcome the influence of a dusty and dark tunnel environment in low visibility. An automatic and wireless real-time tunnel deformation monitoring system, which is based on laser and machine vision and can give early warnings for tunnel collapse accidents, is proposed. The proposed system uses a fixed laser beam as a monitoring reference. The image acquisition modules mounted on the measured points receive the laser spots and measure the tunnel accumulative deformation and instantaneous deformation velocity. Compensation methods are proposed to reduce measurement errors caused by laser beam feasibility, temperature, air refraction index, and wireless antenna attitude. The feasibility of the system is verified through tunnel tests. The accuracy of the detection system is better than 0.12 mm, the repeatability is less than 0.11 mm, and the minimum resolution is 10 μm; therefore, the proposed system is very suitable for real-time and automatic detection of tunnel deformation in low visibility during construction.

Development of a real-time machine vision system for functional textile fabric defect detection using a deep YOLOv4 model

2021 ◽  
pp. 004051752110342
Author(s):  
Sifundvolesihle Dlamini ◽  
Chih-Yuan Kao ◽  
Shun-Lian Su ◽  
Chung-Feng Jeffrey Kuo
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Defect Detection ◽  
Data Augmentation ◽  
Detection System ◽  
Vision System ◽  
Good Precision ◽  
Machine Vision System ◽  
Time Machine ◽  
Textile Fabric

We introduce a real-time machine vision system we developed with the aim of detecting defects in functional textile fabrics with good precision at relatively fast detection speeds to assist in textile industry quality control. The system consists of image acquisition hardware and image processing software. The software we developed uses data preprocessing techniques to break down raw images to smaller suitable sizes. Filtering is employed to denoise and enhance some features. To generalize and multiply the data to create robustness, we use data augmentation, which is followed by labeling where the defects in the images are labeled and tagged. Lastly, we utilize YOLOv4 for localization where the system is trained with weights of a pretrained model. Our software is deployed with the hardware that we designed to implement the detection system. The designed system shows strong performance in defect detection with precision of [Formula: see text], and recall and [Formula: see text] scores of [Formula: see text] and [Formula: see text], respectively. The detection speed is relatively fast at [Formula: see text] fps with a prediction speed of [Formula: see text] ms. Our system can automatically locate functional textile fabric defects with high confidence in real time.

Pipeline Diagnostics With Ultrasonic Meters

2016 ◽  
Author(s):  
Nicole Gailey ◽  
Noman Rasool
Keyword(s):  
Real Time ◽  
Measurement Errors ◽  
Flow Measurement ◽  
Detection System ◽  
Leak Detection ◽  
The United States ◽  
Time Data ◽  
Critical System ◽  
Detection Systems ◽  
Transient Models

Canada and the United States have vast energy resources, supported by thousands of kilometers (miles) of pipeline infrastructure built and maintained each year. Whether the pipeline runs through remote territory or passing through local city centers, keeping commodities flowing safely is a critical part of day-to-day operation for any pipeline. Real-time leak detection systems have become a critical system that companies require in order to provide safe operations, protection of the environment and compliance with regulations. The function of a leak detection system is the ability to identify and confirm a leak event in a timely and precise manner. Flow measurement devices are a critical input into many leak detection systems and in order to ensure flow measurement accuracy, custody transfer grade liquid ultrasonic meters (as defined in API MPMS chapter 5.8) can be utilized to provide superior accuracy, performance and diagnostics. This paper presents a sample of real-time data collected from a field install base of over 245 custody transfer grade liquid ultrasonic meters currently being utilized in pipeline leak detection applications. The data helps to identify upstream instrumentation anomalies and illustrate the abilities of the utilization of diagnostics within the liquid ultrasonic meters to further improve current leak detection real time transient models (RTTM) and pipeline operational procedures. The paper discusses considerations addressed while evaluating data and understanding the importance of accuracy within the metering equipment utilized. It also elaborates on significant benefits associated with the utilization of the ultrasonic meter’s capabilities and the importance of diagnosing other pipeline issues and uncertainties outside of measurement errors.

scholarly journals Automated programming robot component transfer system utilizing machine vision as detection interface

2018 ◽  
Vol 221 ◽  
pp. 03004
Author(s):  
H J Vermaak ◽  
L Rogers
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
New Product Introduction ◽  
Real Time Control ◽  
Product Introduction ◽  
Real Time System ◽  
Flexible System ◽  
Time Control ◽  
Automation Systems ◽  
Automated Programming

Modern day automation systems rely on fixed programming routines to carry out their operations. If an automated flexible system is introduced onto such a production line, the complete reprogramming process required for new products needs could be automated with limited loss in production time. Therefore, instead of reprogramming each new position for the robot system the system takes over real-time control of the robot and carries out the required steps autonomously. The benefit with such a system would be that the robot would not need to be reprogrammed for every new routines but is controlled in a real-time environment to carry out new procedures based on external vision sensors. Using a real-time system could remove the need for a fixed programming environment and replace it with an automated changing programming setup. This could result in a system automatically adapting to a new product introduction through real-time machine vision processing techniques.

Real-Time Monitoring Method for Five-Degrees-of-Freedom of the Extruder’s Moving Parts

2011 ◽  
Vol 105-107 ◽  
pp. 630-634 ◽  
Author(s):  
Xian Wang ◽  
Jian Ping Tan ◽  
Ling Yun Quan ◽  
Xiao Le Cheng
Keyword(s):  
Machine Vision ◽  
Laser Beam ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Real Time Monitoring ◽  
Long Distance ◽  
Monitoring Method ◽  
Moving Parts

On the basis of systematic study on the existing measurement methods of multi-degrees-of-freedom, A real-time monitoring method for five-degrees-of-freedom of the extruder’s moving parts was proposed based on laser beam measurement reference and machine vision. Simultaneously measuring multi-degrees-of-freedom is implemented by two-collimated laser beam and three-point measurement in this method, laser dispersion technology is used for several measuring points using the same basis simultaneously, the baseline errors are initial adjusted and real-time monitored, the method of machine vision is used for precise extraction of the position signals. Position signals are collected and selected by a Charge Coupled Device (CCD) sensor and a high speed Digital Signal Processor (DSP), long-distance propagation and reconciliation of multi-channel data is implemented by an industrial Ethernet. Experiments indicated the method is effective and steady.

scholarly journals Real time detection system for rail surface defects based on machine vision

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Yongzhi Min ◽  
Benyu Xiao ◽  
Jianwu Dang ◽  
Biao Yue ◽  
Tiandong Cheng
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Surface Defects ◽  
Detection System ◽  
Real Time Detection

An FPGA-Based Real-Time Human Eye Pupil Detection System Using E2V Smart Camera

2019 ◽  
Vol 16 (2) ◽  
pp. 649-654
Author(s):  
S. Navaneethan ◽  
N. Nandhagopal ◽  
V. Nivedita
Keyword(s):  
Real Time ◽  
Detection System ◽  
Detection Algorithm ◽  
Video Frame ◽  
Smart Camera ◽  
Verilog Hdl ◽  
Real Time System ◽  
Human Eye ◽  
Pupil Detection ◽  
Main Motive

Threshold based pupil detection algorithm was found tobe most efficient method to detect human eye. An implementation of a real-time system on an FPGA board to detect and track a human's eye is the main motive to obtain from proposed work. The Pupil detection algorithm involved thresholding and image filtering. The Pupil location was identified by computing the center value of the detected region. The proposed hardware architecture is designed using Verilog HDL and implemented on aAltera DE2 cyclone II FPGA for prototyping and logic utilizations are compared with Existing work. The overall setup included Cyclone II FPGA, a E2V camera, SDRAM and a VGA monitor. Experimental results proved the accuracy and effectiveness of the hardware realtime implementation as the algorithm was able to manage various types of input video frame. All calculation was performed in real time. Although the system can be furthered improved to obtain better results, overall the project was a success as it enabled any inputted eye to be accurately detected and tracked.

The Real Time System of Hair Detection in Mushroom Based on Computer Vision

2012 ◽  
Vol 588-589 ◽  
pp. 1199-1203
Author(s):  
Tong Qiang Li ◽  
Cai Feng Zheng ◽  
Jian Peng Gan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Real Time ◽  
Detection System ◽  
Contour Detection ◽  
Time System ◽  
Real Time System ◽  
Extraction Algorithm ◽  
Structure Extraction ◽  
Line Direction

By analysing the Mushroom image, the paper puts forward a kind of line-structure extraction algorithm combination of local gray value and continuity of line direction .After the operations in many aspects of basis image processing, such as gray-scale, denoising , segmentation, contour detection and morphological, this article has developed a set of hair detection system based on computer vision for the Mushroom. The experimental results show this system could well meet the actual needs, and has a broad market prospect.

scholarly journals Surface Defects Detection of Stamping and Grinding Flat Parts Based on Machine Vision

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4531 ◽  
Author(s):  
Hongzhi Tian ◽  
Dongxing Wang ◽  
Jiangang Lin ◽  
Qilin Chen ◽  
Zhaocai Liu
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Light Source ◽  
Surface Defects ◽  
Detection System ◽  
Detection Methods ◽  
Source Image ◽  
Real Time Detection ◽  
Anomaly Region ◽  
Illumination Mode

Currently, surface defect detection of stamping grinding flat parts is mainly undertaken through observation by the naked eye. In order to improve the automatic degree of surface defects detection in stamping grinding flat parts, a real-time detection system based on machine vision is designed. Under plane illumination mode, the whole region of the parts is clear and the outline is obvious, but the tiny defects are difficult to find; Under multi-angle illumination mode, the tiny defects of the parts can be highlighted. In view of the above situation, a lighting method combining plane illumination mode with multi-angle illumination mode is designed, and five kinds of defects are automatically detected by different detection methods. Firstly, the parts are located and segmented according to the plane light source image, and the defects are detected according to the gray anomaly. Secondly, according to the surface of the parts reflective characteristics, the influence of the reflection on the image is minimized by adjusting the exposure time of the camera, and the position and direction of the edge line of the gray anomaly region of the multi-angle light source image are used to determine whether the anomaly region is a defect. The experimental results demonstrate that the system has a high detection success rate, which can meet the real-time detection rEquation uirements of a factory.

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