• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.146-154
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• 2023

In nuclear power plants, ultrasonic test for pipe wall thickness measurement is used during periodic inspections to prevent pipe rupture due to pipe wall thinning. However, when measuring pipe wall thickness using ultrasonic test, a significant amount of measurement error occurs due to the on-site conditions of the nuclear power plant. If the maximum pipe wall thinning rate is decided by the measured pipe wall thickness containing a significant error, the pipe wall thinning rate data have significant uncertainty and systematic overestimation. This study proposes preprocessing of pipe wall thinning measurement data using support vector machine regression algorithm. By using support vector machine, pipe wall thinning measurement data can be smoothened and accordingly uncertainty and systematic overestimation of the estimated pipe wall thinning rate data can be reduced.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.2
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• pp.47-57
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• 1989

This paper aims at describing a series development of the electrical machine, by using the Similarity Theory. The character of the electrical machine defined as the Four Terminal Network of the electrical and mechanical energy transmission system, and the analogy theory of the modelmachine can be developed by the Four Termianl System. Also the Restriction Parameter and Disturbance Parameter can be founded by the comparative data of the developed machine that is the character of the theory and measurement.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.158-163
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• 2002

This paper presents a multiple sensor system for rapid and high-precision coordinate data acquisition in the OMM (On-machine measurement) process. In this research, three sensors (touch probe, laser, and vision sensor) are integrated to obtain more accurate measuring results. The touch-type probe has high accuracy, but is time-consuming. Vision sensor can acquire many point data rapidly over a spatial range but its accuracy is less than other sensors. Also, it is not possible to acquire data for invisible areas. Laser sensor has medium accuracy and measuring speed among the sensors, and can acquire data for sharp or rounded edge and the features with very small holes and/or grooves. However, it has range- constraints to use because of its system structure. In this research, a new optimum sensor integration method for OMM is proposed by integrating the multiple-sensor to accomplish mote effective inspection planning. To verify the effectiveness of the proposed method, simulation and experimental works are performed, and the results are analyzed.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.180-188
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• 1994

Error assessment and evaluation for machine for machine tool slides have been considered as essential tools for improving accuracy. In this paper, a computer aided measurement technique is proposed using photo pin diodes of quadrant type and laser source. In thedeveloped system, three photo diodes are mounted on a sensor mounting table, and the sensored signal is processed by specially designed signal conditioner to give fine resolution with minimum noise. A micro computer inputs the processed signal, and the geometric errors of five degree of freedoms are successfully evaluated. Pitch, roll, yaw, vertical and horizontal straightness errors are thus assessed simultaneously for a machine tool slide. Calibration techniques such as optics calibration, photo diode calibration are proposed and implemented, giving precise calibration for the measurement system. The developed system has been applied to a practical machine tool slide, and has been found as one of efficient and precise technique for machine tool slide.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.413-418
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• 2005

This paper proposes a measurement method for the surface of micro-parts by using AFM(Atomic Force Microscope). To this end, two techniques are presented to extend the capacity of AFM. First, the measurement range is extended by using an image matching method based on correlation coefficients. To account for the inaccuracy of the coarse stage implemented in AFM's, the image matching technique is applied to two neighboring images intentionally overlapped with each other. Second, a method to measure the shape of relatively large specimen is presented by using the inherent trigger mechanism due to the atomic force. The proposed method is proved effective through a series of experiments.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.22-30
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• 2005

This paper proposes a measurement method for the surface shape of micro-parts by using an atomic force microscope(AFM). To this end, two techniques are presented: First, the measurement range is expanded by using an image matching method based on correlation coefficients. To account for the inaccuracy of the coarse stage implemented in AFM, the image matching technique is applied to two neighboring images intentionally overlapped with each other. Second, a method to measure the shape of relatively large specimen is proposed that utilizes the inherent trigger mechanism due to the atomic force. The proposed methods are proved effective through a series of experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.366-370
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• 2002

A kinematic ball bar measurement system can analyze the various errors of a machine tool easily and rapidly in a procedure and can measure many types of equipment such as chip mounter, PCB router, precision stage, etc. In this paper, the thermally induced errors are loused among various errors of a chip mounter because it affects the accuracy of the machine very much. Linear regression technique is adapted for the thermal error modeling. While the measurement and calibration of a chip mounter is difficult in general, this developed system is not only easy to apply for it but also improves the accuracy by 4 times or more.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.3
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• pp.37-43
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• 2007

Recent technological developments in machine tools have been focused on high speed, low vibration machining and high precision machining. And the concern with multi-functional machining has been increased for the last several years. Multi-tasking machines are widely used in machine tool industries. Laser multi-tasking machine has been developed for high precision and fewer vibration machining. The purpose of this study is to evaluate the effects of structural reinforcement on Laser multi-tasking machine which is comprehensively combined turning center and laser machine. Up to date, for the structural stability evaluation of a multi-tasking machine, the analysis model has been considered only the weight of the upper parts. The positions of upper parts on multi-tasking machine have not been considered in the model. So, the results of the present FE model have revealed some difference with measurement data in case of multi-tasking machine. Design of the machine and structural analysis is carried out by FEM simulation using the commercial software CATIA V5. In the result of the structural analysis, effectiveness of reinforcement of the bed was confirmed.