The multi-scale Hermitian wavelet order envelope spectrum based bearing fault detection and diagnosis method under run-up condition is presented in this paper. This new approach based on the fusion of the computed order tracking, Hermitian wavelet transform and envelope spectrum is used for detection defects in roller element bearings. Firstly, Non-stationary vibration signal under run-up condi...

in this study, detection and identification of common faults in industrial gas turbines is investigated. we propose a model-based robust fault detection(fd) method based on multiple models. for residual generation a bank of local linear neuro-fuzzy (llnf) models is used. moreover, in fault detection step, a passive approach based on adaptive threshold is employed. to achieve this purpose, the a...

in this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. in one case, parameters of membership functions are selected in a conventional manner. in another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genet...

we present an approach to design of fault tolerant computing systems. in this paper, a technique is employed that enable the combination of several codes, in order to obtain flexibility in the design of error correcting codes. code combining techniques are very effective, which one of these codes are turbo codes. the algorithm-based fault tolerance techniques that to detect errors rely on the c...

Artificial Neural Networks (ANN) is succesfully used in many areas such as fault detection, control and signal processing in our daily technology. Artificial Neural Networks have nonlineer structure and this is an effective feature that it approaches to the results of learning phase. Then, it gives results in test phase in short time (the degree about 10 second). It is a very preferable accordi...

Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed c...

Envelope analysis is a widely used method for bearing fault detection. To obtain high detection accuracy, it is critical to select an optimal narrowband for envelope demodulation. Fast Kurtogram is an effective method for optimal narrowband selection. However, fast Kurtogram is not sufficiently robust because it is very sensitive to random noise and large aperiodic impulses which normally exist...

A tractor gearbox test rig has been used to collect signals from different types of bearing faults. For vibration monitoring accelerometers have been used to obtain vibration data. For fuel-injectors a bearing checker has been used in order to collect acoustic data. One class Self Organizing Maps (OCSOM) are used for detecting faults when exposed to actual data from the system representing a ye...

When operating under harsh condition (e.g., time-varying speed and load, large shocks), the vibration signals of rolling element bearings are always manifested as low signal noise ratio, non-stationary statistical parameters, which cause difficulties for current diagnostic methods. As such, an IMF-based adaptive envelope order analysis (IMF-AEOA) is proposed for bearing fault detection under su...

Roller bearing is one of the most widely used and critical elements in rotating machinery. In consequence, bearing fault diagnosis in machines, as well as to discriminate the different fault conditions have been a great interest. In this study, firstly, analytical model of a shaft-ball bearing system is developed. The shaft is assumed to be perfectly rigid and uniform, and supported by two radi...