• 드라이브 ㆍ 컨트롤
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• 제11권3호
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• pp.47-54
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• 2014

Clutches are an integral part of the automatic transmission for changing gears. Modern automatic transmissions make extensive use of wet multiple-disc clutches employing hydraulic actuation mechanism with electronic control. Although nowadays, highly advanced shifting algorithm implements the superior shift quality and transmission efficiency, its performance should be based on smooth, reliable engagement with a reasonably durable friction material as well as stable clutch piston dynamics. Particularly, clutch filling control is the crucial part of shifting process because only the open-loop control is available due to the lack of measurement. In this paper, the effect of clutch-fill control parameters on clutch piston dynamics is experimentally investigated by using clutch piston test equipment which enables the clutch piston to actuate similar to real shifting conditions. The experimental analysis results can be expected to be utilized for the calibration of proportional solenoid valve as reference current profile data in vehicle test.

• 드라이브 ㆍ 컨트롤
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• 제17권4호
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• pp.46-53
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• 2020

In this paper, the development of a manually and continuously variable impact force control mechanism for hydraulic breakers was studied. Generally, a hydraulic breaker has one or two piston strokes. Hydraulic breakers, which have two strokes, have two valve-switching ports and make short and long piston strokes. The piston stroke valve controls the piston stroke by opening and closing a short stroke-switching port. The short piston stroke mode is used to break soft rock, concrete, or asphalt. This stroke control valve system is not popular for small hydraulic breakers mounted on 1 to 14-ton excavators. To preserve the carrier-like excavator, proper breaking force is needed, and it can be easily controlled by multiple piston stroke control valves. The easiest way to control these breakers is to use several switching ports and valves but they are not easy to install in small hydraulic breakers and are expensive. To use only one switching port and valve, a method can be used to change the open area of the switching port to delay valve switching. This method provides multiple piston strokes.

• 드라이브 ㆍ 컨트롤
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• 제18권4호
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• 드라이브 ㆍ 컨트롤
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• 제19권3호
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• pp.9-15
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• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

• 산업경영시스템학회지
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• 제45권3호
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• 대한임베디드공학회논문지
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• 제17권5호
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• pp.273-280
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• 2022

Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

• 드라이브 ㆍ 컨트롤
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• 제19권2호
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• pp.17-26
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• 2022

Recently, automatic transmissions caused a good improvement in the shift quality of a forklift. An advanced shift control algorithm, which was based on TCU firmware, was applied with embedded control technology and microcontrollers. In the clutch-to-clutch shifting, one friction element is released and the other friction element is activated. During this process, if the release and application timings are not synchronized, an overrun or tie-up occurs and ultimately leads to a shift shock. The TCU, which measures only the speed of the forklift, inevitably applies the open-loop shift control. In this situation, the speed ratio does not change during the clutch fill. The torque phase occurs until the clutch is disengaged. In this study, an offline shift logic of the learning control was proposed. It induced a synchronous shift when the learning control progressed. During this process, the reference current trajectory of the release clutch was corrected and applied to the next upshift. We considered the results of the overrun/tie-up characteristics of the upshift performed immediately before. The vehicle test proved that the deviation in shift quality, which was caused by the difference in the mechanical characteristics of the clutch, could be improved by the learning control.

• Journal of Advanced Marine Engineering and Technology
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• 제40권7호
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• pp.635-641
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• 2016

엔진과 전기추진장치를 혼합한 하이브리드 추진 장치를 구동하기 위해서는 셀 단위로 이루어진 수십 개의 리튬계열의 배터리가 들어 있는 팩들로 접속이 된 전원을 사용한다. 따라서 많은 량의 배터리 셀의 상태를 언제든지, 엄격하게 관리할 필요가 있다. 일반적으로 배터리 관리(Battery management system, BMS)는 셀 전압, 전류 및 온도 등의 데이터를 운전 중에 받아서 상태를 컴퓨터로 모니터링 한다. 배터리의 상태를 확인하기 위한 또 다른 중요한 데이터는 배터리의 잔존수명(State of charge, SOH)을 알 수 있는 내부저항과 충전상태(State of charge, SOC)를 알 수 있는 무 부하 단자전압(Open circuit voltage, OCV)이 있다. 그러나 연속운전 중에는 내부 손실저항과 캐패시턴스의 병렬 등가회로로 인하여 내부저항의 측정이 어렵다. 또한 대부분의 에너지저장시스템에는 전압, 전류, 온도 등의 데이터를 이용하여 BMS가 수행되고 있지만, 운전 중에 예기치 않게 배터리 셀의 고장이 발생하는 경우에는 구동 전원장치의 출력전압이 변동하고, 하이브리드 자동차 또는 선박의 추진이 어려울 수가 있다. 본 논문에서는 리튬인산철 배터리 팩을 이용한 하이브리드 선박용 직류전원장치를 대상으로 배터리 셀의 돌발고장 순간에도 직류전원장치의 일정전압을 유지하면서 내부저항의 추정이 가능하고, 정상운전 중에는 OCV의 추정이 가능한 고 안전 BMS를 구현하고자 한다.

• 우울조울병
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• 제16권3호
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• pp.140-151
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• 2018

Objectives : The purpose of this study was to examine effects of adjunctive aripiprazole versus bupropion, on depressive symptoms of female depression. Methods : Sixty six female patients with major depressive disorders were enrolled from a six-week, randomized prospective open-label multi-center study. Participants were randomized to receive aripiprazole (2.5-10 mg/day) or bupropion (150-300 mg/day). Montgomery Asberg Depression Rating Scale, 17-item Hamilton Depression Rating scale (HAM-D17), Iowa Fatigue Scale, Drug-Induced Extrapyramidal Symptoms Scale, Psychotropic-Related Sexual Dysfunction Questionnaire scores, and Clinical Global Impression-Severity (CGI-S) were obtained at baseline and after one, two, four, and six weeks. Changes on individual items of HAM-D17 were assessed as well as on composite scales (anxiety, insomnia and drive), and on four core subscales that capture core depression symptoms. Results : Overall, both treatments improved depressive symptoms, without causing serious adverse events. There were significant differences in the HAM-D17 total score (p=0.046) and CGI-S (p=0.004), between aripiprazole and bupropion augmentation, favoring aripiprazole over bupropion. Aripiprazole revealed significantly greater effect size in depressed mood (p=0.006), retardation (p=0.005), anxiety psychic (p=0.032), and general somatic symptom (p=0.01). Conclusion : While both treatments were effective, results of this study suggested that aripiprazole may be preferable, in treating general and core symptoms of female depression.

• 대한지구과학교육학회지
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• 제13권3호
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• pp.284-296
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• 2020

본 연구는 지역사회 환경문제에 관한 토론 수업이 고등학생들의 환경 인식, 환경 문제에 대한 의견과 그 판단근거, 환경 문제 해결방안에 미치는 영향을 알아보는 연구이다. 본 연구에서 개발된 토론 수업은 도심 내의 백로 서식지 문제를 주제로 3차시에 걸쳐 지역사회 환경문제에 대해 알아보고, 토론하는 수업이다. 연구의 주요 데이터로 수업 전후 환경 인식 검사지, 환경 인식 설문지, 학습지가 수집되었다. 환경인식 검사지는 Likert 척도로 기술적 통계로 분석되었으며, 환경 인식 설문지의 응답은 귀납적 질적연구 방법을 통해 분석되었다. 본 연구의 결과는 먼저 환경 인식 검사지의 환경 인식에서 사전-사후 유의미한 통계적 효과가 있었다. 다음으로 SSI 토론 주제인 "백로의 서식지를 이동해야 하는가?"에 대하여 과반수의 학생들이 찬성하였으며, 토론 수업이후에도 의견에 변화가 없었다. 하지만 토론 수업 이후 학생들의 해경방안은 단기적이고 실현 가능하며, 구체적이고 비용이 적게 드는 해결방안으로 바뀌었다. 본 연구 결과를 바탕으로 학생들의 지역환경문제에 대한 관심을 높이고 문제해결력 증가를 위해 학교 과학 수업에서 지역 환경 문제와 관련된 SSI 토론 수업의 필요성을 제언한다.