Observation of Fatigue Damage to Gear Tooth Using Image Processing

2007 ◽  
Author(s):  
Tomoya Masuyama ◽  
Takuya Ikeda ◽  
Satoshi Yoshiizumi ◽  
Katsumi Inoue
Keyword(s):  
Image Processing ◽  
Acoustic Emission ◽  
Strain Distribution ◽  
Cyclic Load ◽  
Early Stage ◽  
Gear Tooth ◽  
Digital Camera ◽  
Correlation Method ◽  
Point Of View ◽  
Strain Diagram

The detection of damage in early stage of fatigue is important for a reliable evaluation of gear life and strength. From this point of view, the variation of strain distribution in a tooth due to cyclic load contains useful information because the fatigue crack will initiate as a result of the accumulation of plastic strain. Meanwhile, digital image equipments are widely used in our life and the performance is in progress. We took digital pictures of cyclic loaded tooth by the digital camera and compared with the picture of no load to find displacement. The strain distribution of tooth is calculated by the correlation method using those pictures. The initiation of a micro crack is observed by the method. It is also confirmed by the detection of acoustic emission wave with higher energy. The variation of stress-strain diagram in fatigue process is presented, and this illustrates the increase of strain in the final stage of fatigue.

APPLICATION OF THE EARLY DAMAGE DIAGNOSTICS TECHNIQUE TO EXAMINATION OF THE AVIATION PANEL

2019 ◽  
Vol 85 (6) ◽  
pp. 53-63 ◽  
Author(s):  
I. E. Vasil’ev ◽  
Yu. G. Matvienko ◽  
A. V. Pankov ◽  
A. G. Kalinin
Keyword(s):  
Acoustic Emission ◽  
Damage Detection ◽  
High Speed ◽  
Early Stage ◽  
Video Data ◽  
High Speed Video ◽  
Damage Diagnostics ◽  
Subsurface Defect ◽  
Sensitive Coating ◽  
Early Damage

The results of using early damage diagnostics technique (developed in the Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN) for detecting the latent damage of an aviation panel made of composite material upon bench tensile tests are presented. We have assessed the capabilities of the developed technique and software regarding damage detection at the early stage of panel loading in conditions of elastic strain of the material using brittle strain-sensitive coating and simultaneous crack detection in the coating with a high-speed video camera “Video-print” and acoustic emission system “A-Line 32D.” When revealing a subsurface defect (a notch of the middle stringer) of the aviation panel, the general concept of damage detection at the early stage of loading in conditions of elastic behavior of the material was also tested in the course of the experiment, as well as the software specially developed for cluster analysis and classification of detected location pulses along with the equipment and software for simultaneous recording of video data flows and arrays of acoustic emission (AE) data. Synchronous recording of video images and AE pulses ensured precise control of the cracking process in the brittle strain-sensitive coating (tensocoating)at all stages of the experiment, whereas the use of structural-phenomenological approach kept track of the main trends in damage accumulation at different structural levels and identify the sources of their origin when classifying recorded AE data arrays. The combined use of oxide tensocoatings and high-speed video recording synchronized with the AE control system, provide the possibility of definite determination of the subsurface defect, reveal the maximum principal strains in the area of crack formation, quantify them and identify the main sources of AE signals upon monitoring the state of the aviation panel under loading P = 90 kN, which is about 12% of the critical load.

Accurate Detection and Quantization of Leaf- Diseases through Soft Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 236-247
Author(s):  
Divya Srivastava ◽  
Rajitha B. ◽  
Suneeta Agarwal
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Agricultural Production ◽  
Bacterial Blight ◽  
Early Stage ◽  
Second Phase ◽  
Computationally Efficient ◽  
Stage Of Disease ◽  
Accurate Detection ◽  
Two Phases

Diseases in leaves can cause the significant reduction in both quality and quantity of agricultural production. If early and accurate detection of disease/diseases in leaves can be automated, then the proper remedy can be taken timely. A simple and computationally efficient approach is presented in this paper for disease/diseases detection on leaves. Only detecting the disease is not beneficial without knowing the stage of disease thus the paper also determine the stage of disease/diseases by quantizing the affected of the leaves by using digital image processing and machine learning. Though there exists a variety of diseases on leaves, but the bacterial and fungal spots (Early Scorch, Late Scorch, and Leaf Spot) are the most prominent diseases found on leaves. Keeping this in mind the paper deals with the detection of Bacterial Blight and Fungal Spot both at an early stage (Early Scorch) and late stage (Late Scorch) on the variety of leaves. The proposed approach is divided into two phases, in the first phase, it identifies one or more disease/diseases existing on leaves. In the second phase, amount of area affected by the disease/diseases is calculated. The experimental results obtained showed 97% accuracy using the proposed approach.

Electrical Resistance and Acoustic Emission During Fatigue Testing of Pristine and High Velocity Impact SiC/SiC Composites at Room and Elevated Temperature

2016 ◽  
Author(s):  
Zipeng Han ◽  
Gregory N. Morscher ◽  
Emmanuel Maillet ◽  
Manigandan Kannan ◽  
Sung R. Choi ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Acoustic Emission ◽  
Cyclic Loading ◽  
Electrical Resistance ◽  
Fatigue Testing ◽  
Early Stage ◽  
Loading Conditions ◽  
Initial Attempt ◽  
Matrix Cracks ◽  
Sic Composites

Electrical resistance (ER) is a relatively new approach for real-time monitoring and evaluating damage in SiC/SiC composites for a variety of loading conditions. In this study, ER of woven silicon carbide fiber-reinforced silicon carbide composite systems in their pristine and impacted state were measured under cyclic loading conditions at room and high temperature (1200C). In addition, modal acoustic emission (AE) was also monitored, which can reveal the occasion of matrix cracks and fiber. ER measurement and AE technique are shown in this study to be useful methods to monitor damage and indicate the failure under cyclic loading. Based on the slope of the ER evolution, an initial attempt has been made to develop a method allowing a critical damage phase to be identified. While the physical meaning of the critical point is not yet clear, it has the potential to allow the failure to be indicated at its early stage.

scholarly journals RECOGNIZING DIFFERENT TYPES OF STOCHASTIC PROCESSES

2006 ◽  
Vol 06 (01) ◽  
pp. L1-L6
Author(s):  
JONG U. KIM ◽  
LASZLO B. KISH
Keyword(s):  
Image Processing ◽  
Stochastic Processes ◽  
Cross Correlation ◽  
Correlation Method ◽  
Correlation Coefficients ◽  
Power Density Spectrum ◽  
Density Spectrum ◽  
Random Telegraph Signals ◽  
Different Types ◽  
Coefficient Method

We propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image processing applications. The method, which we call bispectrum correlation coefficient method, makes use of the cross-correlation of the bispectra. Three kinds of cross-correlation coefficients are introduced. To demonstrate the new method, six different random telegraph signals are tested, where four of them have the same power density spectrum. It is shown that the three coefficients can map the different stochastic processes to specific sub-volumes in a cube.

Integrating Image Computation in Undergraduate Level Data-Structure Education

1998 ◽  
Vol 12 (08) ◽  
pp. 1071-1080 ◽  
Author(s):  
Sudeep Sarkar ◽  
Dmitry Goldgof
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Data Structure ◽  
Data Structures ◽  
Science Curriculum ◽  
Early Stage ◽  
Real Life ◽  
South Florida ◽  
The University ◽  
Structure Education

There is a growing need for expertise both in image analysis and in software engineering. To date, these two areas have been taught separately in an undergraduate computer and information science curriculum. However, we have found that introduction to image analysis can be easily integrated in data-structure courses without detracting from the original goal of teaching data structures. Some of the image processing tasks offer a natural way to introduce basic data structures such as arrays, queues, stacks, trees and hash tables. Not only does this integrated strategy expose the students to image related manipulations at an early stage of the curriculum but it also imparts cohesiveness to the data-structure assignments and brings them closer to real life. In this paper we present a set of programming assignments that integrates undergraduate data-structure education with image processing tasks. These assignments can be incorporated in existing data-structure courses with low time and software overheads. We have used these assignment sets thrice: once in a 10-week duration data-structure course at the University of California, Santa Barbara and the other two times in 15-week duration courses at the University of South Florida, Tampa.

Social Intelligence and its Relation to School Adaptation among Female Students with Learning Difficulties from Perspective of Instructors and Teachers in Elementary School in Jeddah: الذكاء الاجتماعي وعلاقته بالتكيف المدرسي لدى طالبات صعوبات التعلم من وجهة نظر مرشدات ومعلمات المرحلة الابتدائية بجدة

2020 ◽  
Vol 4 (47) ◽  
Author(s):  
Omniah Dhaif Allah Al-otaibi, Hadeel Abdullah Akram
Keyword(s):  
General Education ◽  
Social Intelligence ◽  
School Adjustment ◽  
Learning Difficulties ◽  
Correlation Method ◽  
Female Students ◽  
Point Of View ◽  
Years Of Experience ◽  
School Adaptation ◽  
Study Results

This study aimed to reveal the correlation between social intelligence and school adjustment concerning female students with learning difficulties from the perspective of female guides and teachers at the primary level in Jeddah, as well as knowing the level of social intelligence and school adjustment in addition to checking for differences between averages of the degrees of social intelligence and school adjustment among female students from the perspective of female guides and teachers due to the variable type of profession, scientific specialization and years of experience. The sample of the study consisted of (152) guides and teachers where the researcher followed the descriptive correlation method, and the scale of social intelligence and school adaptation (2020) was used by the researcher. The findings indicated a positive relationship between social intelligence and school adaptation among female students learning difficulties and they have an average level in both social intelligence and school adaptation. In addition, there are no differences between the average scoring of social intelligence and school adaptation among female students of learning difficulties from the point of view of female counselors and teachers due to the variable of profession, scientific specialization and number of years of experience. As a result of the study results, the researcher reached a number of recommendations addressed to educational institutions and female teachers and guides of general education schools applied to learning disabilities programs, which contributes to the development of social intelligence and school adaptation for female students with learning difficulties.

scholarly journals Enhanced Clean-In-Place Monitoring Using Ultraviolet Induced Fluorescence and Neural Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3742 ◽  
Author(s):  
Alessandro Simeone ◽  
Bin Deng ◽  
Nicholas Watson ◽  
Elliot Woolley
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Computation Time ◽  
Cleaning Process ◽  
Food Manufacturing ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Potential Benefits ◽  
Image Acquisition System ◽  
Nonlinear Autoregressive

Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.

AUTOMATIC SEGMENTATION OF BREAST TISSUE THERMAL IMAGES

2018 ◽  
Vol 30 (03) ◽  
pp. 1850024 ◽  
Author(s):  
Zeinab Heidari ◽  
Mehrdad Dadgostar ◽  
Zahra Einalou
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Breast Imaging ◽  
Breast Tissue ◽  
Early Stage ◽  
Automatic Segmentation ◽  
Image Data ◽  
Thermal Images ◽  
Early Stages ◽  
Invasive Method

Breast cancer is one of the main causes of women’s death. Thermal breast imaging is one the non-invasive method for cancer at early stage diagnosis. In contrast to mammography this method is cheap and painless and it can be used during pregnancy while ionized beams are not used. Specialists are seeking new ways to diagnose the cancer in early stages. Segmentation of the breast tissue is one of the most indispensable stages in most of the cancer diagnosis methods. By the advancement of infrared precise cameras, new and fast computers and nouvelle image processing approaches, it is feasible to use thermal imaging for diagnosis of breast cancer at early stages. Since the breast form is different in individuals, image segmentation is a hard task and semi-automatic or manual methods are usual in investigations. In this research the image data base of DMR-IR has been utilized and a now automatic approach has been proposed which does not need learning. Data were included 159 gray images used by dynamic protocol (132 healthy and 27 patients). In this study, by combination of different image processing methods, the segmentation of thermal images of the breast tissues have been completed automatically and results show the proper performance of recommended method.

Early Warning Mechanism for the Surge of Passengers in Metro Systems Based on Automated Fare Collection Data: Case Study of Guangzhou, China

2019 ◽  
Vol 2673 (4) ◽  
pp. 917-929 ◽  
Author(s):  
Ning Huan ◽  
Enjian Yao ◽  
Binbin Li
Keyword(s):  
Early Warning ◽  
Traffic Control ◽  
Safety Management ◽  
Early Stage ◽  
Point Of View ◽  
Control Measures ◽  
Passenger Flow ◽  
Early Warning Mechanism ◽  
Metro Systems

Recently, surges of passengers caused by large gatherings, temporary traffic control measures, or other abnormal events have frequently occurred in metro systems. From the standpoint of the operation managers, the available information about these outside events is incomplete or delayed. Unlike regular peaks of commuting, those unforeseen surges pose great challenges to emergency organization and safety management. This study aims to assist managers in monitoring passenger flow in an intelligent manner so as to react promptly. Compared with the high cost of deploying multisensors, the widely adopted automated fare collection (AFC) system provides an economical solution for inflow monitoring from the application point of view. In this paper, a comprehensive framework for the early warning mechanism is established, including four major phases: data acquisition, preprocessing, off-line modeling, and on-line detection. For each station, passengers’ tapping-on records are gathered in real time, to be further transformed into a dynamic time series of inflow volumes. Then, a sequence decomposition model is formulated to highlight the anomaly by removing its inherent disturbances. Furthermore, a novel hybrid anomaly detection method is developed to monitor the variation of passenger flow, in which the features of inflow patterns are fully considered. The proposed method is tested by a numerical experiment, along with a real-world case study of Guangzhou metro. The results show that, for most cases, the response time for detection is within 5 min, which makes the surge phenomenon observable at an early stage and reminds managers to make interventions appropriately.

scholarly journals Entre La Creación Y La Crí­tica Literaria. Letras De Alfonso Reyes Y Martí­n Luis Guzmán

Xihmai ◽  
2014 ◽  
Vol 9 (17) ◽  
Author(s):  
Isabel Lincoln Strange Reséndiz
Keyword(s):  
Literary Criticism ◽  
Mexican Revolution ◽  
Early Stage ◽  
Intimate Relationship ◽  
Point Of View ◽  
Palabras Clave ◽  
Alfonso Reyes ◽  
Personal Interests

  ¡Pobre hombre de Dios! El mundo está necesitado de realidades externas, objetivas, vulgares, y Usted a través del zodiaco de sus cartas actuales se me esfuma en radiosas visiones de poetas o se me rompe en un fracaso de cristales… CARTA DE REYES A GUZMÁN, 1914. Resumen El presente artí­culo analiza la crí­tica literaria contenida en la correspondencia que mantuvieron los Ateneí­stas Alfonso Reyes y Martí­n Luis Guzmán, a partir de 1913 y hasta 1959. Dichas cartas exponen el punto de vista de ambos autores sobre la configuración de la obra propia y la ajena. La correspondencia dibuja un panorama de la relación í­ntima entre Reyes y Guzmán, que se vio afectada desde un momento temprano en la vida de ambos, debido al estallido de la Revolución Mexicana y a partir de la Decena trágica, en la que fallece Bernardo Reyes. El resultado de sus intereses personales se manifiesta en estas cartas; Reyes se muestra como autor cosmopolita y Guzmán como un narrador con profundas preocupaciones polí­ticas. Palabras clave: Literatura, crí­tica, correspondencia, Reyes, Guzmán. Abstract   This article analyzes the literary criticism that exists in the letters written by Alfonso Reyes and Martin Luis Guzman, from 1913 and until 1959. These letters outlined the point of view of both authors on setting their own work and that of others. The correspondence paints a picture of the intimate relationship between Reyes and Guzman, who were affected from an early stage in the life of both, due to the outbreak of the Mexican Revolution and from La Decena trágica, in which Bernardo Reyes dies. The results of their personal interests are manifested in those letters; Reyes is seen as a cosmopolitan author and Guzman as a writer with deep political concerns.   Keywords: Literature, criticism, correspondence, Reyes, Guzmán.

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