• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.437-440
• /
• 1989

In the paper a failure detection and diagnosis method of a stochastic system is proposed. It is based on the comparison of the moving averages generated from outputs of the real plant and a modeled normal plant. The proposed method allows us to locate the failed sensor and can be efficiently used for the failure detection and diagnosis of a plant with many sensors.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.3
• /
• pp.255-263
• /
• 2014

Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.

• Journal of IKEEE
• /
• v.8 no.1 s.14
• /
• pp.12-21
• /
• 2004

Error control is one of major concerns in many electronic systems. Experience shows that most malfunctions during system operation are caused by transient faults, which often mean abnormal signal delays that may result in violations of circuit element timing constraints. This paper presents a novel CMOS-based concurrent timing error detector that makes a flip-flop to sense and then signal whether its data has been potentially corrupted or not by a setup or hold timing violation. Designed circuit performs a quiescent supply current evaluation to determine timing violation from the input changes in relation to a clock edge. If the input is too close to the clock time, the resulting switching transient current in the detection circuit exceeds a reference threshold at the instant of the clock transition and an error is flagged. The circuit is designed with a $0.25{\mu}m$ standard CMOS technology at a 2.5 V supply voltage. The validity and effectiveness are verified through the HSPICE simulation. The simulation results in this paper shows that designed circuit can be used to detect setup and hold time violations effectively in clocked circuit element.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.6
• /
• pp.1403-1412
• /
• 2019

Effect of damage and loss cost for downtime is huge, if physical devices such as turbines, pipe, and storage tanks are in the abnormal state originated from not only aging, but also cyber attacks on the control and monitoring system like PLC (Programmable Logic Controller). To improve availability and dependability of the physical devices, we design and implement an indirect health monitoring system which sense temperature, acceleration, current, etc. indirectly, and put sensor data into Influx DB in real-time. Then, the actual performance of detecting abnormal state is shown using the indirect health monitoring system. Analyzing data are acquired using the real-time indirect health monitoring system, abnormal state and security threats can be double-monitored and lower maintenance cost utilizing prognostics and health management.

• The Journal of the Korea Contents Association
• /
• v.6 no.6
• /
• pp.16-25
• /
• 2006

Most water tanks operating have been managed by people's five senses. A human material resource have been wasted awfully at this. In the present study, we suggest the wireless integrated system for managing water tank of reducing the wastage human resources and on-line real time managing efforts of water tanks. Water level sensor works the pump sending the data from water tank control to the wireless control on sensing water level. At this time, every kind data which happens in the water tank transmits the line transmission modem. Data to be received from the line transmission modem is stored at the database after we record the logs by each hour. We display the result to the web pages, after checking the pump motion, the pump error, the water level, the solar battery error, the chemicals, and the telephone line to the foundation data to be saved. Furthermore, this paper suggests empirical applications of the proposed wireless integrated system for managing water tank in order to verify its feasibility.

• Journal of KSNVE
• /
• v.8 no.6
• /
• pp.1181-1192
• /
• 1998

This paper describes the performance of a full-authority neural network-based fault tolerant system within a flight control system. This fault tolerant flight control system integrates sensor and actuator failure detection, identification, and accommodation (SFDIA and AFDIA), The first task is achieved by incorporating a main neural network (MNN) and a set of n decentralized neural networks (DNNs) to create a system for achieving fault tolerant capabilities for a system with n sensors assumed to be without physical redundancy The second scheme implements the same main neural network integrated with three neural network controllers (NNCs). The function of NNCs is to regain equilibrium and to compensate for the pitching, rolling. and yawing moments induced by the failure. Particular emphasis is placed in this study toward achieving an efficient integration between SFDIA and AFDIA without degradation of performance in terms of false alarm rates and incorrect failure identification. The results of the simulation with different actuator and sensor failures are presented and discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.6
• /
• pp.483-490
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of IKEEE
• /
• v.26 no.2
• /
• pp.265-270
• /
• 2022

This paper proposes the detection algorithm for switch open fault of asymmetric 6-phase PMSM based on stationary reference frame dq-axis currents. In this paper, target motor has an asymmetric structure in which two upper three windings have an electrical phase difference of 30° and a neutral point is separated. As a result, dual 3-phase PWM inverters and the detection techniques due to open failures of switch are definitely required. In this paper, the dual dq-axis current control method is used for driving the asymmetric 6-phase PMSM and the open fault switch should be detected by using variable all pass filter and low pass filter in order to detect the current amplitude. The effectiveness and usefulness of the proposed method is verified by several experiments.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.689-696
• /
• 2021

In this paper, in order to apply Prognostics and Health Management(PHM) to an electronic system or circuit, a circuit capable of detecting and predicting defect characteristics inside the system or circuit is implemented, and the results are described. In the previous study, we demonstrated that the frequency of the amplitude of S-parameter changed as the circuit defect progressed. These characteristics were measured by network analyser. but in this study, even if the same defect detection method is used, a circuit is proposed to check the progress of the defect, the remaining time, and the occurrence of the defect without large measurement devices. The circuit is designed to detect the change in impedance that generates changes of S-parameter, and it is verified through simulation using the measurement results of Bond-wires.

• Korean Journal of Construction Engineering and Management
• /
• v.25 no.2
• /
• pp.36-44
• /
• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.