• 한국정밀공학회지
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• 제22권3호
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• pp.123-129
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• 2005

The unbalance of the power output, noise, and vibration is happened by the disproportionate pressure variation in the cylinder. For this reason, decrease of the pressure in the cylinder and increase of the residual gas effect on the engine performance. If the abnormal combustion is continued, the crack would be occurred in the engine block. And it could be broken down. For the normal combustion of the SI engine, it is important to supply the balanced mixture by each operating condition. In this study, it was tested the combustion characteristics in the cylinder according to the abnormal adjusting of intake & exhaust valve. This test is willing to set a basic data's analysis fur developing an automotive diagnosis system by analyzing the pressure in the cylinder, the output signal of MAP sensor, the exhaust gas, etc.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.259-262
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• 2002

This paper provides the experimental verification of a non-destructive time domain approach to examine structural damage. Time histories of the vibration response of structure were used to identify the presence of damage. Damage in a structure cause changes in the physical coefficients of mass density, elastic modulus and damping coefficient. This paper examines the use of beam like structures with PVDF sensor and PZT actuator to perform identification of those physical parameters, and hence to detect the damage. Experimental results are presented from tests on cantilevered composite beams damaged at different location and with damage of different dimensions. It is demonstrated that the method can sense the presence of damage, and characterize the damage to a satisfactory precision.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.1116-1121
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• 2013

Mechanical imbalances are common mechanical faults in induction motors. Vibration monitoring techniques have been widely used for the diagnosis of mechanical faults in induction motors, but electrical detection methods have been preferred in recent years. For many years, researchers have concentrated on the Motor Current Signature Analysis (MCSA). This paper examines the effect of mechanical imbalances to induction machine electrical parameters. Instantaneous Power Signature Analysis (IPSA) technique used to detect these faults. In the paper, a full analysis of the proposed technique is presented, and experimental results for healthy and faulty motors have been shown and discussed.

• 대한기계학회논문집
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• 제18권5호
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• pp.1347-1354
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• 1994

This paper deals with the experimental research, including measurement and analysis and field survey, on the causes of occurring noise defective gear boxes in hoist production plant in order to reduce the fraction of their occurrence. In this reserch following investigations are performed : measurement and gear-boxes, examination of each machining process of production, measurement and analysis of dimensional accuracy of each part, comparative vibration test with exchanging inaccurate parts. From these investigations, it is found that the machining accuracy of pinion gear tooth thickness is the most sensitive factor of noise problem. By maintaining the tooth thickness error within 0.05 mm tolerance in the gear cutting process, the fraction of noise defective gear-boxes are greatly reduced to less than 2%, where the usual rate of it has been 20-50%.

• 한국생산제조학회지
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• 제9권4호
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• pp.108-116
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• 2000

Undesired trouble such as chatter vibration and burning on the ground surface appears frequently in the cylindrical plunge grinding process. Establishment of a credible fault diagnostic system for the grinding process is the major purpose of this study. Power signals generated during the grinding operation were sampled and analyzed to determine the relationship between grinding troubles and behavior of signal changes. In addition, a neural network was optimized with a momentum coefficient a learning rate, and a structure of the hidden layer through the iterative learning process. Based on the established system, success rates of the trouble recognition were verified.

• Smart Structures and Systems
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• 제11권3호
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• pp.299-314
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• 2013

This paper presents a nonlinear time series analysis technique for evaluating machine defect severity, based on the Recurrence Plot (RP) entropy. The RP entropy is calculated from the probability distribution of the diagonal line length in the recurrence plot, which graphically depicts a system's dynamics and provides a global picture of the autocorrelation in a time series over all available time-scales. Results of experimental studies conducted on a spindle-bearing test bed have demonstrated that, as the working condition of the bearing deteriorates due to the initiation and/or progression of structural damages, the frequency information contained in the vibration signal becomes increasingly complex, leading to the increase of the RP entropy. As a result, RP entropy can serve as an effective indicator for defect severity assessment of rolling bearings.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.1257-1259
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• 2001

In this paper, the diagnosis method for AC traction motor is to reduce their maintenance loads. We tried to apply this method to maintenance of traction motor in railway vehicle. Sample coils for stator of traction motor were tested by accelerative thermal degradation which composed of heat, vibration, moisture, and overvoltage applying. Reliability and expected life were evaluated on the insulation system for 200 class traction motor.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.522-526
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• 1994

There are great needs for checking machine operation status precisely in the iron and steel plants. Rotating machines such as pumps, compressors, and motors are the most important objects in the plant maintenance. In this paper back-propagation neural network is utilized in diagnosing rotating machines. Like the finger print or the voice print of human, the abnormal vibrations due to axis misalignment, shaft bending, rotor unbalance, bolt loosening, and faults in gear and bearing have their own spectra. Like the pattern recognition technique, characteristic. feature vectors are obtained from the power spectra of vibration signals. Then we apply the characteristic feature vectors to a back propagation neural net for the weight training and pattern recognition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 C
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• pp.1742-1744
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• 2002

This paper described the outputs of acoustic sensors due to the vibration of particles in the mock up GIS. We used the two type of acoustic sensors which had 150kHz resonant frequency and 60kHz resonant frequency respectively. In the experiment of the mock up GIS, we paid attention to the relationship between outputs of sensors and particles and we found that the ratios of outputs related with the lengths of particles. We developed the apparatus including the above diagnosis algorithm for GIS.

• Tribology and Lubricants
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• 제17권2호
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• pp.153-161
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• 2001

The development of techniques in diagnosing the state of the system is one of the essential tools in establishing the automation and unmanned manufacturing system for the realization of CIM/FMS in the fields. In this paper, we developed various diagnostic schemes for the journal bearing supported rotor system. Up to now, vibration of the shaft, measurement of the displacement and the temperature have been used for diagnostic tools, however, the statistical features only could not differentiate the state from states. Thus, we identified the sensor data f3r the steady state in the signal processing and then applied the fuzzy c-mean technology to cope with the nonlinear characteristics of the system. This will, in return, establish a possible diagnostic system for the rotor system in the fields.