• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.25 no.9
• /
• pp.637-643
• /
• 2015

In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.21 no.5
• /
• pp.700-712
• /
• 1997

The flowfield generated by a 2-D rotating cylinder on a plane moving at freestream velocity was experimentally investigated in a wind tunnel to simulate aerodynamic characteristics of rotating wheels of an automobile. In the flowfield around a rotating cylinder at 3*10$^{3}$ < Re$_{d}$<8*10$^{3}$, unique mean flow and turbulence characteristics were confirmed by hot-wire measurements as well as frequency analysis, which was supported by flow visualization. In the vicinity of a rotating cylinder, a unique turbulence structure on .root.over bar u'$^{2}$ profiles was formed in hump-like shape at 1 < y/d < 3. A peak frequency which characterized the effect of a rotating cylinder had the same value of the rotation rate of a cylinder. In case of cylinder rotation, the depths of mean velocity -defect and turbulent-shear regions were thickened by 20-40% at 0 < x/d < 10 compared with the case of cylinder stationary. Far downstream beyond x/d > 10, the flowfield generated by a rotating cylinder showed self-similarity in the profiles of mean velocity and turbulence quantities. The effect of a rotating cylinder was independent of its rotation rate and Reynolds number in the measurement range.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.11
• /
• pp.218-226
• /
• 1998

In this study a neural network based expert system designed to diagnose operating status of a rotating spindle system supported by ball bearings was introduced. In order to facilitate practical failure situations, five exemplary abnormal status was fabricated. Out of several possible data source locations, seven most effective spots were chosen and proven to be the most successful in predicting single and multiple abnormalities. Increased signal strength was measured around where abnormality was embedded. Signal mea-surement locations producing high prediction rate were also classified. Even though multiple abnormalities were hard to be decoupled into their individual causes, proposed diagnostic system was somewhat effective in predicting such cases under certain combination of sensor locations. Among several abnormal operating conditions, highest prediction rate can be expected when signal is spoiled by the failure or damage in outer race. Proposed diagnostic system was again proven to be the most effective system in analyzing and ranking the importance of data sources.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.20 no.1
• /
• pp.104-112
• /
• 2014

The counter-rotating approach on wind turbine has been recently put in interest for its certain advantages in both design and performance. This paper introduces a study on a counter-rotating wind turbine designed and modeled using NREL airfoils S822 and S823. The aims of the study is to evaluate and discover the performance of the counter-rotating system, and compares to that of single rotor turbine of same design using numerical simulation. The results show higher performance of the counter-rotating system compared with single rotor case at TSR 3 to 5 but lower performance at higher TSR. This is due to the interaction between upstream and downstream rotors. Thus, the counter-rotating turbine is more efficient at low rotor rotational speed.

• Tribology and Lubricants
• /
• v.16 no.6
• /
• pp.461-468
• /
• 2000

In this study, a neural network based diagnostic system of a rotating spindle system supported by ball bearings was introduced. In order to create actual failure situations, two exemplary abnormal status were made. Out of several possible data source locations, ten measurement spots were chosen. In order to discriminate multiple abnormal status, a neural network system was introduced using back propagation algorithm updating connecting weight between each nodes. In order to find the optimal structure of the neural network system reducing the information sources, magnitude of the weight of the network was referred. Hinton diagram was used to visually inspect the least sensitive weight connecting between input and hidden layers. Number of input node was reduced from 10 to 7 and prediction rate was increased to 100%.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.12
• /
• pp.75-83
• /
• 2004

With the rotating machinery getting more accurate and diversified, the necessity fur an appropriate diagnosis technique and maintenance system has been greatly recognized. However, until now, the operator has executed a monitoring of the machine by the senses or simple the change of RMS (root mean Square) value. So, the diagnostic expert system using the fuzzy inference which the operator can judge easily and expertly a condition of the machine is developed through this study. In this paper, the hardware and software of the diagnostic expert system was composed and the identification of the diagnostic performance of the developed system for 5 fault phenomena was carried out.

• Progress in Superconductivity and Cryogenics
• /
• v.2 no.1
• /
• pp.7-13
• /
• 2000

A rotating cryogenic system was designed similar to the cooling system for the rotor of a superconducting generator. The experimental rotor has an inner vessel which simulates the winding space of an actual superconducting rotor, and a torque tube of comparable design. This paper describes the evaluation of the total heat leak into the inner vessel that leads to the study of the heat transfer characteristic of the rotating cryogenic system. To examine the insulation performance of the experimental rotor. temperature was measured at each part of the system at various rotaing speeds from 0 rpm to 600 rpm. Total heat leak into the inner vessel was calculated by measuring the boil-off rate of liquid helium. Conduction heat leak to the inner vessel was obtained by the vent tube, and radiation heat leak was calculated by subtracting the conduction heat lent from the total heat leak. There seemed to be no rotaional dependency of total heat leak at least up 600 rpm.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.7
• /
• pp.98-105
• /
• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• International Journal of Precision Engineering and Manufacturing
• /
• v.8 no.3
• /
• pp.54-59
• /
• 2007

It is widely recognized that increasing the accuracy and diversity of rotating machinery necessitates an appropriate diagnostic technique and maintenance system. Until now, operators have monitored machinery using their senses or by analyzing simple changes to root mean square output values. We developed an expert diagnostic system that uses fuzzy inference to expertly assess the condition of a machine and allow operators to make accurate judgments. This paper describes the hardware and software of the expert diagnostic system. An assessment of the diagnostic performance for five fault phenomena typically found in pumps is also described.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.4
• /
• pp.301-308
• /
• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.