In this paper, we propose an off-the-grid compressive sensing based method to detect brokenbar fault in squirrel-cage induction motors. To validate our method, we first build a dynamic model of squirrel-cage induction motor using multi-loop equivalent circuit to simulate motor current under fault conditions. We then develop an off-the-grid compressive sensing algorithm to extract the fault char...

In this paper, we propose a new gear fault recognition method by using morphological undecimated wavelet decomposition (MUWD), sample entropy and grey incidence. MUWD possesses both the characteristic of morphological filter in morphology and multi-resolution in wavelet transform. Then we develop multi-scale MUWD based on the characteristic of impulse feature extraction in difference morphologi...

[1] We investigate seismicity near faults in the Southern California Earthquake Center Community Fault Model. We search for anomalously large events that might be signs of a characteristic earthquake distribution. We find that seismicity near major fault zones in Southern California is well modeled by a Gutenberg-Richter distribution, with no evidence of characteristic earthquakes within the re...

this paper illustrates the application of s-transform and continuous wavelet transform (cwt) for fault location in combined overhead line and cable distribution networks. the high frequency transient signals originated by faults are analyzed using s-transform and cwt. the s-transform is found to be applicable in transient based fault location in distribution networks. this technique is an expan...

the running status of it can be more comprehensive judged through acquisition and analysis of vibration signal for water pump rotary machinery. Therefore, the collection of vibration signal is the key to monitor equipment running status and diagnose faults. This paper introduces water pump fault diagnosis system based on DSP and wavelet transform, and the system can realize water pump vibration...

This paper proposed an approach of mechanical failure information extraction and recognition in the early fault state variables, combined with the principal component analysis algorithm with FCM algorithm. Principal component analysis algorithm to get the characteristic value of data sets carries enough about fault in the time domain. Then FCM algorithm is used to analysis model is established ...

Fault diagnosis method based on the moment characteristic of system pressure data is presented in this paper. Using AMESim simulation technology, three typical faults of the brake system are studied. After the moment and the percentile characteristics of the pressure curve of the hydraulic system are extracted and used as characteristic parameter, fault information is diagnosed effectively usin...

As the fault information of power transformers has characteristics such as complementarities, redundancy and uncertainty, the diagnosis task can’t be finished by the simple fault characteristic vector and the diagnosis method. The basic ideas of information fusion are introduced, and DGA (the Dissolved Gas Analysis) is combined tightly with other information such as the results of conventional ...

Probabilistic seismic hazard analysis (PSHA) is classically performed through the Cornell approach by using a uniform earthquake distribution over the source area and a given magnitude range. This study aims at extending the PSHA approach to the case of a characteristic earthquake scenario associated with an active fault. The approach integrates PSHA with a high-frequency deterministic techniqu...