Sentence examples for detection of gears from inspiring English sources

The aim of this paper is to develop a methodology which is robust for fault detection of gears under fluctuating load and speed conditions.

Finally the effectiveness of the proposed method in fault detection of gears is validated using experimental signals from a planetary gearbox test rig.

Compared with the conventional synchronous averaging scheme or the envelope analysis approach, the proposed method is robust for the incipient local fault detection of gears.

Results show that utilizing this approach may improve the ability for fault detection of a gear transmission system, especially when the faulty gear rotates in an angular speed close to those of other gears.

An improved understanding of vibration signal is required for the early detection of incipient gear failure to achieve high reliability.

So far, a vast number of vibration signal processing methods have been used in fault detection of the gear box and bearing for wind turbines, such as spectrum analysis [8], wavelet transform [9], Wigner-Vile distribution [10] and empirical mode decomposition (EMD) [11].

Detection of faults in gears under variable rotational speed by vibration analysis becomes in a difficult task because events characterizing faults are not periodic.

The proposed method is applied on the signals, extracted from simulated gearbox for detection of the simulated gear faults.

This paper presents a robust model-based technique for the detection and diagnosis of gear faults under varying load conditions using the gear motion residual signal.

Then more specific applications namely crack detection of a beam and mechanical gear and roller damage are presented.

For the gear fault feature detection of vehicle transmission gearbox, the proposed technique is applied in the extraction of the signal transients that shows the gear fault, which proves the effectiveness of the proposed technique in extracting the signal transients in the practical application.