• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3863-3869
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• 2009

In recent years, globalization of markets and increased consumer sophistication in automotive industry have led to an increase in the variety of products and a consequent increase in the number of variants of any given product line that a manufacturer must supply. Also, the modularity trend of automotive production systems greatly affects on the production systems of automotive parts suppliers. These typically requires the implementation of cost efficient, flexible production systems, so called mixed-model assembly lines. We studied the problems of mixed-model assembly and assembly error-preventing techniques, and developed the error-preventing monitoring system using RFID in the mixed-model automotive parts assembly line. Especially, this study aimed to solve the problems and supplement the existing systems for preventing assembly errors, by developing a monitoring system using RFID to minimize the issues currently occurring in the field of automotive parts assembly, such as losses from incorrect installation and omission.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1196-1200
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• 2003

The degree of supersaturation is an important measure for the operation of crystallization processes, because it is directly related to the control of crystal size distribution and shape. A conventional technique utilizing solution composition and temperature has a variety of problems caused from the measurement error and the handling of analyzing samples. A monitoring system of the supersaturation using a quartz crystal sensor is proposed here, and its performance is examined applying different manipulations of coolant temperature. The experimental outcome and photographic examination indicate that the measurements of resonant frequency and resistance of the sensor can be used for the prediction of the formation and growth of solid crystal from the crystallization process. The monitoring system eliminates the intrinsic error source of the conventional system to give the improved measurement and on-line application availability.

• Journal of Biosystems Engineering
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• v.25 no.3
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• pp.233-240
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• 2000

A commercially available Doppler radar was modified and evaluated for on-board monitoring of ground speed. The radar output was corrected for pitch angle of aircraft based on the output of an electrolytic tilt sensor. The effects of aircraft speed, height and mounting angle on error in the ground speed were evaluated. The speed error decreased with an increase of the mounting angle since the radar contact angle with respect to the ground approached to the mounting angle. The error increased with an increase of the nominal aircraft speed. The altitude insignificantly affected the speed error. The Doppler radar provided acceptable percent errors within 5% in most measurements. The error can be reduced within ${\pm}$1.5% by increasing the mounting angle ($43^{\circ}$). The error of -3.8% at the mounting angle of $29^{\circ}$could be reduced by adjusting the mounting angle with respect to the radar contact angle.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.41-49
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• 2010

Digital broadcasting system has various affecting factors unlike analog broadcasting system, and has possibility of no signal reception in case of errors due to characteristics of digital system. And, digital broadcasting system has monitoring system for error occurrences handling various factors. ATSC mobile DTV system uses legacy frequency and provides mobile broadcasting services, and also requires monitoring systems for monitoring online broadcasting services and reporting to administrator about interference or influence with legacy systems, and error situations. In this paper, we propose efficient monitoring system which monitors online broadcasting status of ATSC mobile DTV, reports on poor signal reception, video streaming failures to administrator, and maintains reliable digital broad ca sting system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.2
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• pp.99-104
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• 2011

In this paper, the intelligent landscape lighting power control and monitoring system with solar sell generator equipment is proposed. The first, the intelligent landscape lighting power controller is designed using the fuzzy logic control method. And the fuzzy logic controller is used to save power consumption for various reference intensity of the illumination. The second, the GUI monitoring system is presented. It has control and display faculty. And the practical experiment device is used to evaluate the performance criteria of the proposed intelligent landscape lighting power control system with the solar cell power generation equipment. From the experiment results, we present the property of proposed fuzzy controller such as steady state error, the tracking and power consumption characteristic for the reference intensity of illumination. And also we show the superiority of power control as well as the characteristic of GUI monitoring system in the proposed system.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.2
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• pp.159-165
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• 2011

Purpose: In this paper, the reliability and reproductivity of anti-reflection (AR) coating on ophthalmic lens using optical monitoring system (OMS) were investigated. Methods: The random error simulation and RunSheet performance in Essential Macleod software to confirm possibility of AR coating using OMS were performed. The coating process of 19 batches was carried out in order to perform reproductivity test of AR coating after simulation process. Results: As a result, the coating results of 19 batches had shown the excellent reproductivity of about 0.5% error. Conclusions: We confirmed the excellent reproductivity and reliability of AR coating on ophthalmic lens using optical monitoring system from our results.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.230-242
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• 2010

In this paper, an environmental monitoring and diagnosis system based on ubiquitous computing technology, shortly u-Eco Monitoring System, is proposed. u-Eco Monitoring System is designed to: 1) Collect information from the manufacturing processes via ubiquitous computing technology, 2) Analyze the current status, 3) Identify the cause of problem if detected by rule-based and case-based reasoning, and 4) Provide the results to the operator for proper decision making. Based on functional modeling, a generic architecture is derived, followed by application to a manufacturing system in iron and steel making industry. Finally, to show the validity of the proposed method, a prototype is developed and tested. The developed methods can be used as a conceptual framework for designing environmental monitoring and diagnosis system for industrial practices by which monitoring accuracy and response time for abnormal status can be significantly enhanced, and relieving operator pressure from manual monitoring and error-prone decision making.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.95-102
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• 1994

This paper presents a Cable Stayed Bridge Construction Management System, which consists of Structural System Identification Method (SSIM), Error Sensitivity Analysis and Optimum Error Adjustment & Prediction System. The 1st System Identification Method builds an error influence matrix using the linear superposition of each error modes. The 2nd SSIM also considers the second error mode term, which shows good error factor estimation. The optimal cable adjustment can be accomplished within the allowable range of both cable tension and camber. The Post processor, constituted with Motif and GL library on SGI platform, is useful for monitoring construction stage management by displaying construction data, adjustment and prediction results at each construction step.