• Journal of the Korea institute for structural maintenance and inspection
• /
• v.4 no.2
• /
• pp.175-184
• /
• 2000

The maintenance of tunnels is often neglected since tunnels has tendency to become stable with time. The determination of safety of tunnels is a complicated problem. So the role of experienced engineer in the maintenance is very important and development of an expert system which can perform as these engineers has been needed. In this study, an expert system which can determine the safety of tunnels is developed. The developed knowledge base contains the maintenance procedure which is used in KlSTEC(Korea Infrastructure Safety & Technology Corporation). Field test, laboratory test and nondestructive test methods are considered in this knowledge base. Criteria for each item and integrated diagnosis criteria are implemented in the expert system based on literatures and reports. The expert system includes basic inspection. detail inspection and precision inspection. For precision inspection. it has the capacity to exchange the result from numerical analysis by a commercial program FLAC. To verify the expert system. the proposed procedure was compared with an existing tunnel diagnosis report.

• Safety and Health at Work
• /
• v.14 no.1
• /
• pp.124-130
• /
• 2023

The increase in the number of fatal electric accidents over the years has escalated the demand for specialized forensic engineers to determine their relevant technical causes. Likewise, the complexities associated with identifying the causes of electrocution accidents have prompted the General Department of Forensic Science and Criminology at Dubai Police to adopt a new methodology to diagnose electrocution accidents, consisting of an approach that involves medico-legal examination, electrical diagnosis of the evidence, and trace evidence analysis. This paper will discuss the application of the adopted method in further detail by unfolding two case reports. The first report outlines a case in which a worker got electrocuted at a construction site while attempting to turn on a lamp. The second case report involves the death of a technician in a workshop after trying to disconnect a washing machine from its plug. The methodology was utilized during the investigation of both cases, which were attended by the appointed forensic engineers and showed promising results.

• Bulletin of the Korean Chemical Society
• /
• v.25 no.5
• /
• pp.757-760
• /
• 2004

• Magazine of the Korea Institute for Structural Maintenance and Inspection
• /
• v.16 no.3
• /
• pp.23-32
• /
• 2012

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.10
• /
• pp.931-940
• /
• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.4123-4141
• /
• 2019

Autonomous driving technology is divided into 0~5 levels. Of these, Level 5 is a fully autonomous vehicle that does not require a person to drive at all. The automobile industry has been trying to develop Level 5 to satisfy safety, but commercialization has not yet been achieved. In order to commercialize autonomous unmanned vehicles, there are several problems to be solved for driving safety. To solve one of these, this paper proposes 'A Deep Learning Part-diagnosis Platform(DLPP) based on an In-vehicle On-board gateway for an Autonomous Vehicle' that diagnoses not only the parts of a vehicle and the sensors belonging to the parts, but also the influence upon other parts when a certain fault happens. The DLPP consists of an In-vehicle On-board gateway(IOG) and a Part Self-diagnosis Module(PSM). Though an existing vehicle gateway was used for the translation of messages happening in a vehicle, the IOG not only has the translation function of an existing gateway but also judges whether a fault happened in a sensor or parts by using a Loopback. The payloads which are used to judge a sensor as normal in the IOG is transferred to the PSM for self-diagnosis. The Part Self-diagnosis Module(PSM) diagnoses parts itself by using the payloads transferred from the IOG. Because the PSM is designed based on an LSTM algorithm, it diagnoses a vehicle's fault by considering the correlation between previous diagnosis result and current measured parts data.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.18 no.36
• /
• pp.175-182
• /
• 1995

Industrial safety management program can be divided three part that is education, technology, and management. The effectiveness of a industrial safety management program depends on the ability to manage hardware which is technology and software, education and management, In this research, it will be described that how to design and develop Computer Integrated Safety System and Computer Based Training System for Press operations which is how to integrated industrial safety program wi th production planning and control in order to control efficiently using personnel computer system.

• Proceedings of the KIEE Conference
• /
• 2005.05b
• /
• pp.10-12
• /
• 2005

This paper describes MV switchgear technology trends and diagnosis technology. MV switchgear has been rapidly changed into compact, reliability and safety situation. And suggested road-map to implement condition assessment or condition based maintenance. On-line diagnosis technology, life evaluation technology and system technology are suggested.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1536-1540
• /
• 1997

Recently, many advanced technologies in electronics, mechanics, material and computer science have been applied to medictine and they have changed the method of diagnosis and treatment to more quantitative way than before. Now day, with the aid of this technology, the device for the minimal invasive diagnosis and treatment is being developed for the convenience and safety of patients. this paper introduces application of senso and MEMS(Micro Electro Mechnical System) in medicine and biotechnology, which are essential factor for the realization of minimal invasive diagnosis and treatment.

• Journal of Advanced Marine Engineering and Technology
• /
• v.20 no.1
• /
• pp.13-23
• /
• 1996

Weld defects degrade the strength and safety of astructure and are resulted from the various cases. The complexity of causal relation of weld defects requires an expert for the analysis of weld defects and the measures counter to them. An expert system has the intelligent functions such as the representation of knowledge and the inference. On this research, weld defect are systematically analysed and their causal model is developed. This information is saved to the knowledge base. The suitable inference algorithm for the diagnosis of weld defects is developed and realized with C++ programming.