scholarly journals On the Origin of Low-Angle Detachment Faults

Eos ◽  
2017 ◽  
Author(s):  
Terri Cook
Keyword(s):  
Normal Faults ◽  
Detachment Faults ◽  
Different Types ◽  
Types Of Faults ◽  
Whipple Mountains

Data from California's Whipple Mountains suggest this complex was formed by a succession of steep normal faults, challenging the paradigm that detachments are different types of faults.

A New Approach To Evaluate Fault-Sliding Potential With Reservoir Depletion

SPE Journal ◽  
2019 ◽  
Vol 24 (05) ◽  
pp. 2320-2334
Author(s):  
Kai Zhao ◽  
Xiaorong Li ◽  
Chuanliang Yan ◽  
Yongcun Feng ◽  
Liangbin Dou ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Fault Reactivation ◽  
Normal Faults ◽  
Gas Industry ◽  
Fault Stability ◽  
Different Types ◽  
Fault Properties ◽  
Derivatives Of ◽  
Types Of Faults

Summary Fault reactivation caused by reservoir depletion has been an important issue faced by the oil and gas industry. Traditional views suggest that with reservoir depletion, only normal faults can be activated and fault stability either monotonically decreases or increases, which are not consistent with field observations. In this paper, a fault–sliding–potential (FSP) model was developed to analyze fault stability during reservoir depletion for different types of faults. The evolution trend of fault stability with reservoir depletion and the corresponding judging criteria were obtained by calculating the derivatives of FSP. The influences of reservoir depletion on nonsealing and sealing faults were investigated. Case studies were performed to analyze FSP for different types of nonsealing and sealing faults with different fault properties and attitudes. The results show that reverse and strike faults might also be reactivated with reservoir depletion. The fault stability might not monotonically decrease or increase; instead, four evolution patterns of fault stability might occur, with reservoir depletion dependent on the parameters of the faults. Reservoir depletion usually leads to a higher sliding risk for sealing faults than for nonsealing faults. The results also indicate that fault stability is a strong function of fault attitudes, including the dip and strike of the fault.

scholarly journals An Efficient Neural Network-Based Method for Diagnosing Faults of PV Array

2021 ◽  
Vol 13 (11) ◽  
pp. 6194
Author(s):  
Selma Tchoketch_Kebir ◽  
Nawal Cheggaga ◽  
Adrian Ilinca ◽  
Sabri Boulouma
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Modeling Process ◽  
Photovoltaic Arrays ◽  
Mode Of Operation ◽  
Different Types ◽  
The Neural Networks ◽  
Operational Modes ◽  
Types Of Faults ◽  
Electrical Data

This paper presents an efficient neural network-based method for fault diagnosis in photovoltaic arrays. The proposed method was elaborated on three main steps: the data-feeding step, the fault-modeling step, and the decision step. The first step consists of feeding the real meteorological and electrical data to the neural networks, namely solar irradiance, panel temperature, photovoltaic-current, and photovoltaic-voltage. The second step consists of modeling a healthy mode of operation and five additional faulty operational modes; the modeling process is carried out using two networks of artificial neural networks. From this step, six classes are obtained, where each class corresponds to a predefined model, namely, the faultless scenario and five faulty scenarios. The third step involves the diagnosis decision about the system’s state. Based on the results from the above step, two probabilistic neural networks will classify each generated data according to the six classes. The obtained results show that the developed method can effectively detect different types of faults and classify them. Besides, this method still achieves high performances even in the presence of noises. It provides a diagnosis even in the presence of data injected at reduced real-time, which proves its robustness.

scholarly journals On the Use of LoRa Technology for Logic Selectivity in MV Distribution Networks

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3079 ◽  
Author(s):  
Leopoldo Angrisani ◽  
Francesco Bonavolontà ◽  
Annalisa Liccardo ◽  
Rosario Schiano Lo Moriello
Keyword(s):  
Cost Effectiveness ◽  
Long Range ◽  
Distribution Networks ◽  
Fault Isolation ◽  
Optimized Design ◽  
Medium Voltage ◽  
Different Types ◽  
The Times ◽  
The Cost ◽  
Types Of Faults

In this paper, a logic selectivity system based on Long Range (LoRa) technology for the protection of medium-voltage (MV) networks is proposed. The development of relays that communicate with each other using LoRa allows for the combination of the cost-effectiveness and ease of installation of wireless networks with long-range coverage and reliability. The realized demonstrator to assess the proposed system is also presented in the paper; based on different types of faults and different locations, the times needed for clearing a fault and restoring the network were estimated from repeated experiments. The obtained results confirm that, with an optimized design of transmitted packets and of protocol characteristics, LoRa communication grants fault management that meets the criteria of logic selectivity, with fault isolation occurring within the maximum allowed time.

scholarly journals Design and construction of a prototype for the analysis of vibrations in an induction motor for the detection of faults

2020 ◽  
pp. 27-33
Author(s):  
Javier Garrido ◽  
Beatris Escobedo-Trujillo ◽  
Guillermo Miguel Martínez-Rodríguez ◽  
Oscar Fernando Silva-Aguilar
Keyword(s):  
Fourier Transform ◽  
Induction Motor ◽  
Wavelet Transforms ◽  
Data Acquisition System ◽  
Time Frequency ◽  
Different Types ◽  
Control Devices ◽  
The Fourier Transform ◽  
And Control ◽  
Types Of Faults

The contribution of this work is to present the design of a prototype integrated by an induction motor, a data acquisition system, accelerometers and control devices for stop and start, to generate and identify different types of faults by means of vibration analysis. in the domain: time, frequency or frequency-time, through the use of the Fourier Transform, Fast Fourier Transform or Wavelet Transforms (wavelet transform). In this prototype, failures can be generated in the induction motor such as: unbalance, different types of misalignment, mechanical looseness, and electrical failures such as broken bars or short-circuited rings, an example of a misalignment failure is presented to show the process of analysis and detection.

scholarly journals Application of Model-Based Deep Learning Algorithm in Fault Diagnosis of Coal Mills

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yifan Jian ◽  
Xianguo Qing ◽  
Yang Zhao ◽  
Liang He ◽  
Xiao Qi
Keyword(s):  
Deep Learning ◽  
Fault Diagnosis ◽  
Learning Algorithm ◽  
Mechanism Model ◽  
Model Based ◽  
Deep Learning Algorithm ◽  
Stacked Autoencoders ◽  
Different Types ◽  
Operation Status ◽  
Types Of Faults

The coal mill is one of the important auxiliary engines in the coal-fired power station. Its operation status is directly related to the safe and steady operation of the units. In this paper, a model-based deep learning algorithm for fault diagnosis is proposed to effectively detect the operation state of coal mills. Based on the system mechanism model of coal mills, massive fault data are obtained by analyzing and simulating the different types of faults. Then, stacked autoencoders (SAEs) are established by combining the said data with the deep learning algorithm. The SAE model is trained by the fault data, which provide it with the learning and identification capability of the characteristics of faults. According to the simulation results, the accuracy of fault diagnosis of coal mills based on SAE is high at 98.97%. Finally, the proposed SAEs can well detect the fault in coal mills and generate the warnings in advance.

Post-rift magmatism on the northern South China Sea margin

2020 ◽  
Vol 132 (11-12) ◽  
pp. 2382-2396 ◽  
Author(s):  
Qiliang Sun ◽  
Tiago M. Alves ◽  
Minghui Zhao ◽  
Jean-Claude Sibuet ◽  
Gérôme Calvès ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Northern South China Sea ◽  
Lava Flows ◽  
Normal Faults ◽  
Boundary Fault ◽  
China Sea ◽  
Detachment Faults ◽  
Plumbing Systems ◽  
Magma Migration

Abstract Intense magmatism in the form of widespread volcanoes and lava flows is identified in high-resolution 3-D seismic data over a post-rift sequence of the northern South China Sea (SCS). Such a magmatism post-dates the end of seafloor spreading in the SCS by at least 6.8 m.y. A detachment (boundary) fault propagating into a deep-seated magma chamber provided the main vertical pathway for magma migration. In turn, normal faults and dykes constituted a shallow plumbing system through which the magma migrated from the boundary fault and was extruded onto the paleo-seafloor. Volcanism occurred in the study area from ca. 8.2 Ma to ca. 1.1 Ma in the form of two distinct events, dated ca. 5.2 Ma and ca. 2.8 Ma, which are correlated with the Dongsha Event. Extrusive magma formed volcano edifices and extensive lava flows; the latter of which were confined to the troughs of sediment waves or, instead, flowed along submarine canyons. As a corollary, this study shows that in the SCS: (1) young magmatism is widespread on the northern continental margin, (2) seafloor morphology greatly influences the architecture of deep-water volcanoes, and (3) syn-rift faults (especially detachment faults) reactivated by regional tectonics closely control the magma plumbing systems.

scholarly journals Estimation of Phase Angle Jump (PAJ) for Different Types of Faults and Unbalancing in Distribution System

2018 ◽  
Vol 7 (4.38) ◽  
pp. 23 ◽  
Author(s):  
Muhammad Fawad Shaikh ◽  
Madad Ali Shah ◽  
Sunny Katyara ◽  
Bhawani Shankar Chowdhry
Keyword(s):  
Phase Angle ◽  
Power Supply ◽  
Distribution System ◽  
Research Work ◽  
Voltage Sag ◽  
Voltage Unbalance ◽  
Voltage Drops ◽  
Different Types ◽  
Zero Sequence ◽  
Types Of Faults

Voltage sag caused by the faults in the power system has serious power quality issues and sometimes leads to interruption of power supply. The characteristics of voltage sag are its magnitude, time and phase angle jump (PAJ). This paper represents the estimation of phase angle jump (PAJ) when different types of faults are occurred in distribution system. Since the unbalancing is one of the major issues in distribution system that increases the zero sequence currents, over heats the distribution transformer, causes huge voltage drops in distributor etc. Therefore, the method used in this paper shows the PAJ when distributor is unbalance due to uneven loading or the line parameters of the distributor are unsymmetrical. Simple radial system is used to analyze the PAJ caused by the different types of faults and unbalancing. Different comparisons are made that are associated with PAJ such as PAJ vs fault impedance, zero sequence current and percentage of voltage unbalance. The research work is performed on MATLAB/SIMULINK to analyze the real time results.  

scholarly journals Combined Diagnosis of PD Based on the Multidimensional Parameters

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Heidari
Keyword(s):  
Final Diagnosis ◽  
Semisupervised Learning ◽  
Adaptive Mutation ◽  
Characteristic Parameters ◽  
Ultrasonic Signals ◽  
Different Types ◽  
Diagnosis Method ◽  
Characteristic Values ◽  
Types Of Faults ◽  
Frequency Current

This paper presents a comprehensive multiparameter diagnosis method based on multiple partial discharge (PD) signals which include high-frequency current (HFC), ultrasound, and ultrahigh frequency (UHF). The HFC, ultrasound, and UHF PD are calculated under different types of faults. Therefor the characteristic values, as nine basic characteristic parameters, eight phase characteristic parameters, and the like are calculated. Diagnose signals are found with the method based on information fusion and semisupervised learning for HFC PD, adaptive mutation parameters of particle entropy for ultrasonic signals, and IIA-ART2A neural network for UHF signals. In addition, integrate the diagnostic results, which are the probability of fault of various defects and matrix, of different PD diagnosis signals, and analysis with Sugeno fuzzy integral to get the final diagnosis.

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