Fault indicator

About: Fault indicator is a research topic. Over the lifetime, 10057 publications have been published within this topic receiving 143482 citations. The topic is also known as: FCI & power line fault indicator.

High Impedance Fault Identification on Distribution Networks

Abstract: This paper presents a transient-based algorithm for high-impedance fault identification on distribution networks. It uses the discrete wavelet transform to monitor high- and low-frequency voltage components at several points of the power system, being able to indicate the most likely area within which the disturbance has occurred, without requiring data synchronization nor the knowledge of feeder or load parameters. The proposed algorithm is evaluated through electromagnetic transients program simulations of high-impedance faults in a 13.8 kV system modeled from actual Brazilian distribution grid data. Solid faults, capacitor bank switching, and feeder energization are also simulated, considering the system with and without distributed generation. Obtained results show that the algorithm significantly reduces the search field of the high-impedance fault, reliably distinguishing it from other disturbances.

A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis

Abstract: A DSP-based measurement system dedicated to the vibration analysis on rotating machines was designed and realized. Vibration signals are on-line acquired and processed to obtain a continuous monitoring of the machine status. In case of a fault, the system is capable of isolating the fault with a high reliability. The paper describes in detail the approach followed to built up fault and non-fault models together with the chosen hardware and software solutions. A number of tests carried out on small-size three-phase asynchronous motors highlight the excellent promptness in detecting faults, low false alarm rate, and very good diagnostic performance.

Flattening without picking

Abstract: We present an efficient full-volume automatic dense-picking method for flattening seismic data. First local dips (stepouts) are calculated over the entire seismic volume. The dips are then resolved into time shifts (or depth shifts) using a nonlinear Gauss-Newton iterative approach that exploits fast Fourier transforms to minimize computation time. To handle faults (discontinuous reflections), we apply a weighted inversion scheme. The weight identifies locations of faults, allowing dips to be summed around the faults to reduce the influence of erroneous dip estimates near the fault. If a fault model is not provided, we can estimate a suitable weight (essentially a fault indicator) within our inversion using an iteratively reweighted least squares (IRLS) method. The method is tested successfully on both synthetic and field data sets of varying degrees of complexity, including salt piercements, angular unconformities, and laterally limited faults.

Incipient Bearing Fault Detection via Motor Stator Current Noise Cancellation Using Wiener Filter

Abstract: Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. The key issue in current-based bearing fault detection is to extract bearing fault signatures from the motor stator current. Since the bearing fault signature in the stator current is typically very subtle, particularly when the fault is at an incipient stage, it is difficult to detect the fault signature directly. Therefore, in this paper, the bearing fault signature is detected alternatively by estimating and removing nonbearing fault components via a noise cancellation method. In this method, all the components of the stator current that are not related to bearing faults are regarded as noise and are estimated by a Wiener filter. Then, all these noise components are cancelled out by their estimates in a real-time fashion, and a fault indicator is established based on the remaining components which are mainly caused by bearing faults. Machine parameters, bearing dimensions, nameplate values, and the stator current spectrum distribution are not required in the method. The results of online experiments with a 20-hp induction motor under multiple load levels have confirmed the effectiveness of this method.

Automatic fault diagnostic apparatus for a heat pump air conditioning system

Abstract: Microprocessor controlled apparatus is provided for automatically diagnosing faults in a heat pump system. Temperature sensors located at strategic points in the system are read periodically in accordance with a preprogrammed diagnostic routine. Temperature measurements preferably representing comparison of two temperature readings that produce temperature differentials outside pre-established tolerance limits are stored with a fault identification representative of the corresponding fault measurement. A service technician can read the fault data from storage by activation of control means for that purpose whereby the nature of the causative fault or faults can readily be determined.