Feature Extraction Using Discrete Wavelet Transform for Gear Fault Diagnosis of Wind Turbine Gearbox

Vibration diagnosis is one of the most common techniques in condition evaluation of wind turbine equipped with gearbox. On the other side, gearbox is one of the key components of wind turbine drivetrain. Due to the stochastic operation of wind turbines, the gearbox shaft rotating speed changes with high percentage, which limits the application of traditional vibration signal processing techniques, such as fast Fourier transform. This paper investigates a new approach for wind turbine high speed shaft gear fault diagnosis using discrete wavelet transform and time synchronous averaging. First, the vibration signals are decomposed into a series of subbands signals with the use of a multiresolution analytical property of the discrete wavelet transform. Then, 22 condition indicators are extracted from the TSA signal, residual signal, and difference signal. Through the case study analysis, a new approach reveals the most relevant condition indicators based on vibrations that can be used for high speed shaft gear spalling fault diagnosis and their tracking abilities for fault degradation progression. It is also shown that the proposed approach enhances the gearbox fault diagnosis ability in wind turbines. The approach presented in this paper was programmed in Matlab environment using data acquired on a 2 MW wind turbine

VIBRATION FEATURE EXTRACTION METHODS FOR GEAR FAULTS DIAGNOSIS -A REVIEW

The key point of condition monitoring and fault diagnosis of gearboxes is a fault feature extraction. The study of fault feature detection in rotating machinery from vibration analysis and diagnosis has attracted sustained attention during past decades. In most cases determination of the condition of a gearbox requires study of more than one feature or a combination of several techniques. This paper attempts to survey and summarize the recent research and development of feature extraction methods for gear fault diagnosis, providing references for researchers concerning with this topic and helping them identify further research topics. First, the feature extraction methods for gear faults diagnosis are briefly introduced, the usefulness of the method is illustrated and the problems and the corresponding solutions are listed. Then, recent applications of feature extraction methods for gear faults diagnosis are summarized, in terms of industrial gearboxes. Finally, the open problems of feature extraction methods for gear fault diagnosis are discussed and potential future research directions are identified. It is expected that this review will serve as an introduction summary of vibration feature extraction methods for gear faults diagnosis for those new to the concepts of its applications to gear fault diagnosis based on vibratio

Gearbox faults feature selection and severity classification using machine learning

The most widely used technique for gearbox fault diagnosis is still vibration analysis. The need for gearbox condition monitoring in an automated process is essential and there is still a problem with the selection of features that best describe a fault or its severity level. For this purpose, multiple-domain vibration signals statistic features are extracted through time and frequency domain by postprocessing of raw time signal, time-synchronous average signal, frequency spectra and cepstrum. Five different datasets are considered with different levels of fault analyzing gear chipped and a missing tooth, gear root crack, and gear tooth wear under stable running speed and load. A preliminary experimental study of a single stage test bench gearbox was performed in order to test feature sensitivity to type and level of fault in the process of clustering and classification. Selected features were finally processed using an artificial neural network classifier

The analysis of influential parameters on calibration and feeding accuracy of belt feeders

Continual material feeding represents a process of great importance for process industries. Feeding with belt feeders represents one of the most common methods. Belt feeders are devices that require little space, they are not expensive and, most importantly, they do not interrupt material flow while feeding. Calibration of belt feeders, as well as other measuring devices, is a prerequisite for measuring and achieving a defined level of measurement accuracy. On the other hand, the defined level of measurement accuracy is often difficult to achieve in practice due to the multitude of factors that affect the operation of belt feeders. Existing mathematical models indicate a number of influential factors on measurement accuracy. The paper presents the measurement procedure performed on a belt feeder in laboratory conditions, with variable speeds and belt tensions and the known raised position of the measuring idler. Based on the obtained results, appropriate conclusions were made about the influences on calibration and measurement accuracy

Analysis of the influence of hydraulic fluid quality on external gear pump performance

The basis of every hydraulic system is based on energy transformations, which are realized through hydraulic working fluid. Hydraulic oils are certainly subject to changes within their structure, meaning the basic characteristics and parameters of hydraulic oil, such as density, viscosity, humidity. The oils that are exploited are exposed to the process of degradation, which largely leads to significantly poorer quality of hydraulic fluid. The paper deals with the influence of changes in the characteristics of the hydraulic fluid on the hydraulic operating parameters of the gear pump installed on the hydraulic press. The parameters refer to pressure, flow, and temperature, as well as the quality of hydraulic oil, which affects the volumetric efficiency of the pump, and the results presented in the conclusion are based on the measured values of parameters before and after corrective measures. The control of parameters aims to increase the efficiency and reliability of the hydraulic system, a way of modern detection of deviations of parameters from standard, required values