• Journal of Digital Convergence
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• v.17 no.12
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• pp.203-210
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• 2019

Most cars today use electronic control to control the state of the engine to achieve optimum performance. This study developed a device for maintaining fault diagnosis and optimal vehicle status by displaying the engine information of a car on the screen in real time using can communication. This system displays information generated from the engine to the driver in real time such as engine intake and exhaust temperature, current battery voltage, tire pressure, RPM, DPF collection amount, torque, and horsepower through the OBD2 socket. You can check immediately. It can help you to drive safely by measuring tire pressure and displaying it on the screen, and it provides a mode to set the shift timing to suit your taste. In particular, in the case of diesel engine cars, the problems caused by smoke can adversely affect the performance and environmental pollution. Therefore, the system was developed to display the DPF collection amount on the system screen to prevent environmental pollution and to manage the vehicle efficiently.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.142-152
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• 2011

In general, existing emergency evacuation guiding systems depend on visual techniques like emergency lights or LEDs. Actually people in the case of fire emergency condition may not obtain a range of view because of smoke from the fire. This paper introduces a technique to design an emergency guiding system using directivity sound to cope with this problem. In this case all speakers are serially connected for audio signal transmission in a serial fashion to achieve convenient speaker installation. Floyd algorithm is used to find shortest evacuation paths. Because serially connected multi-channel speakers are weak in case of disconnection, this paper uses a technique to solve the diagnostic problem. In the proposed system, a PC based on the USB protocol is used for control and observation. The system has achievements, such as increasing evacuation rate under emergency conditions, and serial transmission of audio signal for easy maintenance and low installation cost.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.23-35
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• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.