• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1731-1739
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• 2000

The Vibration signals of a gear driving system is often associated with gear tooth faults. Many studies have been done on the detection of impulsive vibration signals, which characterize the breaka ge of a gear tooth. Also, most of the studies on gear fault diagnosis are only about the fault existence at one gear-pair. This study concerns on the several possible faults of a geared motor that has three gear pairs. The measurement and analysis on the vibration signals of a running geared motor shows the relationship between the gear faults and the vibration signals. This study also shows that adaptive interference canceling technique can be appropriately applicable to detect which gear-pair has the fault, and that wavelet is better than spectrogram to figure out the gear fault.

• Advances in Computational Design
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• v.8 no.3
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• pp.255-271
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• 2023

The gear drive of a combat aircraft engine is responsible for power transmission to the different accessories necessary for the engine's operation. Incorrect power transmission can occur due to the presence of failure modes in the gears like bending fatigue, pitting, adhesive wear, scuffing, abrasive wear and polished wear etc. Fault diagnosis of the gear drive is necessary to get an early indication of failure of the gears. The present research is to develop an algorithm using different vibration signal processing techniques on industrial vibration acquisition systems to establish gear fault diagnosis architecture. The signal processing techniques have been used to extract various feature vectors in the development of the fault diagnosis architecture. An open-source dataset of other gear fault conditions is used to validate the developed architecture. The results is a basis for development of artificial intelligence based expert systems for gear fault diagnosis of a combat aircraft engine.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1759-1766
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• 2001

Vibration transient generated by developing localized fault in gear can be used as indicators in gear fault detection. In this paper, we propose the zoomed phase map for a fault signal using continuous wavelet transfers to detect this vibration transient. Local fault induces the abrupt fluctuation of load exciting tooth and phase lag in the vibration signal measured on the gearbox. The relatively large fault like "tip breakage" easily can be detected by the clear fluctuation of exciting load. However, minor fault like "initial pitting"cannot be detected using the load fluctuation. To defect this kind of minor fault, the phase map for a fault signal is taken into account. The phase lag by minor fault is observed well in the zoomed phase map.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1114-1118
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• 2000

Impulsive sound and vibration signals in gear are often associated with their faults. Thus these impulsive sound and vibration signals can be used as indicators in the diagnosis of gear fault. The early detection of impulsive signal due to gear fault prevents from complete failure in gear. However it is often difficult to make objective measurement of impulsive signals because of background noise signals. In order to ease the detection of impulsive signals embedded in background noise, we enhance the impulsive signals using adaptive signal processing.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.268-277
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• 1999

Impulsive acoustic and vibration signals within gear are often induced by impacting of fault tooths in gear. Thus the detection of these impulses can be useful for fault diagnosis. Recently there is an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals then to increase the kurtosis values. We show that the fourth order Wigner Moment Spectrum, called the Wigner Trispectrum, has found superior detection performance to second order Wigner distribution for typical impulsive signals in a condition monitoring application. These methods are also applied to data sets measured within an industrial gear box.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.590-595
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• 2001

Vibration transient generated by developing localized fault in gear can be used as indicators of condition monitoring in a gear. In this paper, we propose the phase map for a fault signal using continuous wavelet transform to detect this vibration transient. Local fault induces the abrupt fluctuation of load exciting tooth and phase lag in the vibration signal measured on the gearbox. The relatively large fault like "tip breakage" easily can be detected by the clear fluctuation of exciting load. However, minor fault like "initial pitting" cannot be detected using the load fluctuation. To detect this kind of minor fault, the phase map for a fault signal is taken into account. The phase lag by minor fault is observed well in the phase map.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.505-508
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• 2014

Transmission error (TE) is defined as "the angular difference between the ideal output shaft position and actual position". As TE is one of the major source of the noise and vibration of gears, it is originally studied with relation of the noise and vibration of the gears. However, recently, with the relation of mesh stiffness, TE has been studied for fault detection of spur gear sets. This paper presents a physics-based theory on fault diagnostics of a planetary gear using transmission error. After constructing the lumped parameter model using DAFUL, multi-body dynamics software, we developed a methodology to diagnose the faults of the planetary gear including phase calculation, signal processing. Using developed methodology, we could conclude that TE could be a good signal for fault diagnostics of a planetary gear.

• Journal of Power System Engineering
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• v.11 no.4
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• pp.65-71
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• 2007

According to the survey, abnormal condition of the system is the main source for interrupting an elevator service, especially faults in worm gears used for the traction machine. Worm gear is popularly used in traction machine for middle and low speed elevators. Elevators need high reliability and stability, because they are closely related to human life. Usually, traction machine is applied to drive the elevators that have height about 35 m and it is an important mechanical unit for riding quality in elevators. There are some research results about types of vibration fault for worm gear in International Association Elevator Engineers (IAEE). But this study concerns with diagnosis of various faults in elevator worm gear using vibration signal. The analysis of fault characteristics is compared with previous researches in traction machine.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2069-2070
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• 2011

In this paper, the fault diagnosis for a gearbox of BLDC motor. The stator of BLDC motor consists of coil winding so it is easy to cool down and it also has a high reliability. In addition, it doesn't have a brush so it is less trouble and good in maintenance. Coupling with the motor which is the power sources, the gear has a high power transfer efficiency and various rotation speed. The gear gets a high driving force through deceleration. Thus it has been widely used. The gearbox fault detection area has not attracted much attention from electrical engineering community. A few papers describe gearbox fault based on vibration. Gearbox fault is diagnosed through FFT analysis of current and voltage. Fault characteristic frequency side band detected by calculating fault frequency. A threshold value is suggested by comparing normal peak value with fault peak value using detected fault characteristic frequency side band. Experimental results demonstrate that motor current and voltage signal analysis are viable tools in detecting these gear faults. Lower side band(LSB) is bigger than upper side band(USB) in current FFT. LSB and USB are similar in voltage FFT. Finally, fault diagnosis system that can easily detect flaws is developted for gearbox of BLDC motor.