• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.132-137
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• 2004

On-Board Diagnostic(OBD) systems are in most cars and light trucks on the load today. During the 1970's and early 1980's manufacturers started using electronic means to control engine functions and diagnose engine problems. The CARB's diagnostic requirements to meet EPA emission standards have been designated as OBD with a goal of monitoring all of the emissions-related components, as well as the chassis, body, accessory devices and the diagnostic control network of the vehicle for proper operation. In this paper, we present a remote measurement system for the wireless monitoring of diagnosis signal and sensors output signals of ECU adopted KWP2000, united the OBD communication protocol, on OBD-compliant vehicle using the wirless communication technique of Bluetooth. In order to measure the ECU signals, the interface circuit is designed to communicate ECU and designed terminal wirelessly according to the ISO, SAE regulation of communication protocol standard. A microprocessor S3C3410X is used for communicating ECU signals. The embedded system's software is programmed to measure the ECU signals using the ARM compiler and ANCI C based on MicroC/OS kernel to communicate between bluetooth modules using bluetooth stack. The diagnostic system is developed using Visual C++ MFC and protocol stack of bluetooth for Windows environment. The self-diagnosis and sensor output signals of ECU is able to monitor using PC with bluetooth board connected in serial port of PC. The algorithms for measuring the ECU sensor output and self-diagnostic signals are verified to monitor ECU state. At the same time, the information to fix the vehicle's problem can be shown on the developed monitoring software. The possibility for remote measurement of self-diagnosis and sensor signals of ECU adopted KWP2000 in embedded system verified through the developed systems and algorithms.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2026-2036
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• 1991

An expert system is developed which can diagnose the causes and remedies of the failures of power transmission gears. The basic components of the expert system are knowledge base, inference engine, and working memory. The knowledges in knowledge base are classified into the knowledges for determining the failure types and for diagnosis of causes and remedies of the failures. The former is represented hierarchically into the main category of eleven groups by rules and the sub category of twenty four groups by facts, while the later is represented by facts according to the each group of knowledges. In the inference engine some considerations are implemented, i.e., the backward chaining method and depth first search to determine the category of the failures, the meta-knowledges to shorten the search space, the certainty factor to evaluate the reliability of result, and the unification strategy to diagnose the causes and remedies of the failures. The working memory is established to hold the results during inference temporarily. In addition, knowledge acquisition facility, explanation facility, and user interface are included for the usefulness of user. This expert system is written with the PROLOG programming language on IBM-PC compatible computer operated by MS-DOS and be executed alone.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.5
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• pp.205-211
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• 2005

Recently, power system is getting larger and more complex. When the complex power system has a problem, it is very difficult even for the experts to find out where the problem is and to make a timely decision by operators. There have been many studies on these problems but the results are not good enough for applying to real power system. Therefore, power system operators always had to judge the exact state of power system and be preparative for the problems that can occur later. We developed new methods that can be applied to complex power system by dividing the system into small modules. By using 'module', we can combine small modules together to make complex power systems and the knowledge base that is applied to fault diagnosis system. As a result, compared to previously developed diagnosis products, operation time is shortened and the knowledge base is become simpler and clearer, which made online usage capable. This system can be used as a complementary measurement that helps the operator from making any mistakes.

• Journal of Navigation and Port Research
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• v.33 no.10
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• pp.671-678
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• 2009

Recently, there have been some researches in the equipment fault detection based on shock and vibration information. Most research of them is based on shock and vibration monitoring to determine the equipment fault or not. Different with engine fault detection based on shock and vibration information we focus on detection of engine for boat and system control. First, it use the duplicated-checking method for shock and vibration information to determine the engine fault or not. If there is a fault happened, we use the integral to determine the error engine shock wave width and detect the fault area. On the other hand, we use the engine trend analysis and standard of safety engine to implement the shock and vibration information database. Our simulation results show that the probability of engine fault determination is 98% and the probability of engine fault detection is 72%

• Journal of Society of Preventive Korean Medicine
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• v.20 no.1
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• pp.75-87
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• 2016

Objectives : This study aims to classify and analyze literature related to moire topography, as a diagnostic device of Korean medicine, discuss research trends and major results, and demonstrate the value of moire topography. Methods : To investigate moire topography research trends, Korean keywords that signify 'moire' were searched in a Korean journal search engine. Initially, 2,988 papers were found in the research, and, after classifying them and removing those that are duplicate in other databases, only 37 papers were applicable for the literature review in this study. To analyze research trends, the 37 papers were analyzed based on the publication year, research field, journal, and research type, and, clinical articles were classified based on the diagnosis purpose, subject characteristics, diagnosis method, test method, and test result, for analysis. Results : Moire topography research in South Korea was first conducted in 1995 and most active in 2003, mostly in the field of Korean medicine. In the journal analysis, The Journal of Korea CHUNA Manual Medicine for Spine & Nerves published the highest number of papers, most of which were clinical articles and the rest were literature review. And, in the analysis of clinical papers, based on the diagnosis purpose, muscle somatotype measurement was most common, followed by diagnosis of scoliosis. In terms of subjects, most studies focused on elementary, middle, and high school students, and, in terms of the diagnosis method, other tests were used in most studies. The analysis of moire topography methods showed that most studies measured the shoulder, back, and hip, and the most common measurement method in the studies measured the difference in contour lines on the left and right by designating a central line of the body. In terms of the result, most moire topography brought about significant diagnosis results, and many studies demonstrated its use for musculoskeletal diseases in particular. Conclusions : Moire topography is believed to be highly significant for diagnosis and treatment of musculoskeletal diseases and further research will be needed to support it.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.51-57
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• 2004

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.95-109
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• 2023

In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.

• Tribology and Lubricants
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• v.30 no.1
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• pp.21-28
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• 2014

Damage to the cylinder liner of large ship engines, such as scuffing on the surface, can occur very easily because it is operated in a corrosive environment. This scuffing may be due to oil film destruction and corrosive wear caused by water and sulfur included in the fuel, abrasive impurities, and poor lubricants. Thus, a method for monitoring the condition and diagnosing the failure of the cylinder liner and piston ring is needed. In this study, a reciprocating friction and wear test was carried out with a cast iron specimen, which simulated an engine cylinder in a corrosive atmosphere. The lubricants used were base oil, stirred oil with distilled water, a NaCl solution, and dilute sulfuric acid. The friction coefficient and frequency spectrum were measured using a load cell and acceleration sense in each experimental condition. We then used these results to diagnose the failure of the cylinder liner.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.203-210
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• 2015

This paper investigates the failure of a car with a 2.5-liter CRDi engine of the Hyundai Company. The failure is caused by intermittent poor acceleration while driving. To analyze the cause, we investigated the air intake volume, the fuel injection, and the air-fuel ratio, which were determined to be normal. The brake switch signal error was discovered while analyzing the function that limits the output of the engine. While investigating the cause, we discovered the corrosion of the pins on the connector of the brake switch. We determined that it was generated by soapy water flowing in the solar film. Therefore, the cause of the failure was the brake switch signal errors. Additionally, we determined that ECM was the normal fail-safe mode that implemented the override device for safety during normal acceleration. Based on these results, further solar film experiments must be conducted to fully elucidate the causes.