Novel gear diagnosis technique based on spectral kurtosis

In this paper, a new thresholding technique used for diagnosis of gearbox pitting tooth faults is introduced. The diagnosis procedure involves in estimation of the Time Synchronous Average (TSA) signal and the gear residual signal, and then the Spectral Kurtosis optimal filter is estimated using the proposed thresholding procedure. By considering overlapping among the TSA segments, several realizations of the TSA signal are estimated. It is important that the SK estimated over the realizations should be consistent. The statistical SK thresholding procedure presented in literature is used for comparing the performance of the proposed approach. A three stage diagnosis decision making technique based on weighted majority rule is used for final diagnosis

Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor

Diagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides an overview of selected methods of diagnosis of induction motor bearings, based on measurement of the supply current. The problem here is the high disturbance components level of the motor current in relation to diagnostic components. The paper presents the new approach to signal analysis solutions, based on statistical methods, which have been adapted to be used by this diagnostic system. First experimental results with use of this method are also presented, they confirm the advantages of this method

Novel spectral kurtosis technology for adaptive vibration condition monitoring of multi-stage gearboxes

In this paper, the novel wavelet spectral kurtosis (WSK) technique is applied for the early diagnosis of gear tooth faults. Two variants of the wavelet spectral kurtosis technique, called variable resolution WSK and constant resolution WSK, are considered for the diagnosis of pitting gear faults. The gear residual signal, obtained by filtering the gear mesh frequencies, is used as the input to the SK algorithm. The advantages of using the wavelet-based SK techniques when compared to classical Fourier transform (FT)-based SK is confirmed by estimating the toothwise Fisher's criterion of diagnostic features. The final diagnosis decision is made by a three-stage decision-making technique based on the weighted majority rule. The probability of the correct diagnosis is estimated for each SK technique for comparison. An experimental study is presented in detail to test the performance of the wavelet spectral kurtosis techniques and the decision-making technique

Triple correlation for detection of damage-related nonlinearities in composite structures

Nonlinear effects in vibration responses are investigated for the undamaged composite plate and the composite plate with a delamination. The analysis is focused on higher harmonic generation in vibration responses for various excitation amplitude levels. This effect is investigated using the triple correlation technique. The dynamics of composite plate was modelled using two-dimensional finite elements and the classical lamination theory. The doubled-node approach was used to model delamination area. Mode shapes and natural frequencies were estimated based on numerical models. Next, the delamination divergence analysis was used to obtain relative displacements for delaminated plies. Experimental modal analysis test was carried out to verify the numerical models. The two strongest vibration modes as well as two vibration modes with the smallest and largest motion level of delaminated plies were selected for nonlinear vibration test. The Fisher criterion was employed to verify the effectiveness and confidence level of the proposed technique. The results show that the method can be used not only to reveal nonlinearities, but also to reliably detect impact damage in composites. These results are confirmed using the statistical analysis

Novel adaptation of the demodulation technology for gear damage detection to variable amplitudes of mesh harmonics

In this paper, a novel adaptive demodulation technique including a new diagnostic feature is proposed for gear diagnosis in conditions of variable amplitudes of the mesh harmonics. This vibration technique employs the time synchronous average (TSA) of vibration signals. The new adaptive diagnostic feature is defined as the ratio of the sum of the sideband components of the envelope spectrum of a mesh harmonic to the measured power of the mesh harmonic. The proposed adaptation of the technique is justified theoretically and experimentally by the high level of the positive covariance between amplitudes of the mesh harmonics and the sidebands in conditions of variable amplitudes of the mesh harmonics. It is shown that the adaptive demodulation technique preserves effectiveness of local fault detection of gears operating in conditions of variable mesh amplitudes

An automated methodology for performing time synchronous averaging of a gearbox signal without speed sensor.

In this paper we extend a sensorless algorithm proposed by Bonnardot et al. for angular resampling of the acceleration signal of a gearbox submitted to limited speed fluctuation. The previous algorithm estimates the shaft angular position by narrow-band demodulation of one harmonic of the mesh frequency. The harmonic was chosen by trial and error. This paper proposes a solution to select automatically the mesh harmonic used for the shaft angular position estimation. To do so it evaluates the local signal-to-noise ratio associated to the mesh harmonic and deduces the associated low-pass filtering effect on the time synchronous average (TSA) of the signal. Results are compared with the TSA obtained when using a tachometer on an industrial gearbox used for wastewater treatment. The proposed methodology requires only the knowledge of an approximate value of the running speed and the number of teeth of the gears. It forms an automated scheme which can prove useful for real-time diagnostic applications based on TSA where speed measurement is not possible or not advisable due to difficult environmental conditions

Adaptive diagnosis of the bilinear mechanical systems.

A generic adaptive approach is proposed for diagnosis of the bilinear mechanical systems. The approach adapts the free oscillation method for bilinearity diagnosis of mechanical systems. The expediency of the adaptation is proved for a recognition feature, the decrement of the free oscillations. The developed adaptation consists of variation of the adaptive likelihood ratio of the decrement with variation of the resonance frequency of the bilinear system. It is shown that in the cases of the frequency-independent and the frequency- dependent internal damping, the adaptation is expedient. To investigate effectiveness of the adaptation in these cases, a numerical simulation was carried out. The simulation results show that use of the adaptation increases the total probability of the correct diagnosis of system bilinearity

Vibration diagnosis of a gearbox by wavelet bicoherence technology

Gearboxes are critical elements of mechanical systems that are widely used in aerospace, energy generation, land and naval applications. The early detection of changes in the technical condition of this equipment is of great importance for the optimisation of maintenance costs. Vibration signal components resulting from the presence of the developing faults of meshing gears contain the information that, once extracted from the signal, may allow for a reliable estimation of the technical condition of the meshing gears. Wavelet bicoherence (WB)-based technology has been used to obtain the signal feature characterising the phase relationship between the signal components generated by gear faults in the selected frequency bandwidths. In previous research, WB has been successfully applied to the detection of artificially-created gearbox faults. This paper will present the application of WB in the detection of naturally-developing gear faults