In order to achieve accurate diagnosis for rotating machinery automatically and considering that test data under actual fault conditions are rather difficult to obtain, a novel fault diagnosis strategy based on rotor dynamics and computational intelligence was proposed in this paper. Considering the nonlinear restoring force of ball bearing, the dynamic equation of a rotor–bearing system contai...

Bearing failures are the most frequent causes of breakdowns in rotating machinery. Different levels severity these exhibit distinct fault characteristics vibration signal. This paper presents a bearing diagnosis method that considers different levels, involving selection statistics detection index symptom parameter and application canonical discriminant analysis (CDA). Initially, kurtosis is em...

seismic base isolation are devices that used to limit the human and material damage caused by an earthquake. this devices diffuse the energy induced at the time of the earthquake before being transferred to the structure.the base isolated structures when subjected to the near-fault eathquakes which contain long-period velocity pulses that may coincide with the period of base isolated structures...

Earthquakes are the result of slip along faults and are due to the decrease of rock frictional strength (dynamic weakening) with increasing slip and slip rate. Friction experiments simulating the abrupt accelerations (>>10 m/s2), slip rates (~1 m/s), and normal stresses (>>10 MPa) expected at the passage of the earthquake rupture along the front of fault patches, measured large fault dynamic we...

Bearing is a component that affects the performance of a rotating machine in order to be used properly. The purpose of using ball bearing is to reduce rotational friction and support radial and axial loads. Diagnosis of bearing vibration data is an important process to identify either the bearing is normal or defect. In this paper, we consider a single bearing system that consists of one normal...

There has been immense success on the application of Convolutional Neural Nets (CNN) to image and acoustic data analysis. In this paper, rather than preprocessing vibration signals to denoise or extract features, we investigate the usage of CNNs on raw signals; in particular, we test the accuracy of CNNs as classifiers on bearing fault data, by varying the configurations of the CNN from one-lay...