Fault Location Research Articles

Teager–Kaiser Energy Operator-Based Short-Circuit Fault Localization Method for Multi-Circuit Parallel Cables

Medium-voltage cables in hydropower plants are typically arranged in multi-circuit configurations to ensure reliability, yet their exposure to harsh operational conditions accelerates insulation degradation and increases partial discharge risks. Traditional fault localization methods, such as the traveling wave method using wavelet transform to process fault signals, suffer from wavefront distortion due to inter-line reflections and noise interference in multi-circuit systems, because wavelet-based techniques are limited by preset basis functions and environmental noise. To address these challenges, a fault localization method for multi-circuit parallel cables based on the Teager–Kaiser Energy Operator (TKEO) is proposed in this paper. First, the fault signal is decoupled using Clarke transformation to suppress common-mode interference, obtaining the α component. Subsequently, the α component is subjected to wavelet transform to obtain the high-frequency components, which are then optimized using the TKEO. The TKEO is applied to optimize the wavelet-transformed signal, enhancing transient energy variations to precisely identify the arrival time of the fault wavefront at measurement points, thereby enabling accurate fault localization. The results of the four types of fault experiments indicate that the use of the TKEO to optimize the wavelet transform of the traveling wave method improved the accuracy of fault localization.

Centralized Monitoring System for Street Light Fault Detection and Location Tracking Hardware Smart Automation.

Abstract - This paper presents the design and implementation of a centralized monitoring system for street light fault detection and location tracking using smart hardware automation. The objective is to enhance the operational efficiency of urban street lighting by enabling real-time monitoring, automated fault identification, and accurate location tracking. The proposed system integrates a microcontroller-based unit equipped with current sensors, light sensors, and a GPS module, allowing it to detect faulty street lights and transmit their status and location to a centralized control unit via wireless communication. A custom dashboard provides visualization and management capabilities for maintenance teams. The methodology significantly reduces the need for manual inspection, optimizes maintenance schedules, and ensures better energy utilization. Field testing demonstrated high accuracy in fault detection and prompt reporting, contributing to improved public safety and reduced operational costs. This system is scalable and can be integrated with broader smart city infrastructure for enhanced urban management. Key Words: Smart street lighting, fault detection, location tracking, centralized monitoring, IoT automation, GPS-based system.

A novel strategy for fault location, isolation, and service restoration in active distribution networks

Abstract When a fault arises in an active distribution network, both the grid upstream of the fault point and the distributed generation (DG) downstream of the fault point contribute short-circuit currents, posing challenges for existing centralized feeder automation (FA) technologies in accurately locating and isolating the fault. Moreover, the radial network structure of the distribution network can lead to power outages for downstream loads when the DG downstream of the fault point ceases operation due to islanding effects. To tackle this issue, this paper introduces a communication-based distributed FA strategy that employs interlocking signals between adjacent switches to pinpoint and isolate faults in active distribution networks, effectively minimizing the scope of fault-induced power outages. Furthermore, an inverter control strategy integrating voltage negative feedback control, reactive power negative feedback control, and quasi-synchronization grid-connection control is proposed. This strategy allows for seamless switching between grid-following and grid-forming inverter control modes, enabling adaptive grid-connection/islanding control of DGs. Consequently, non-fault areas downstream of the fault point maintain uninterrupted power supply, significantly enhancing the reliability of power supply in distribution networks. Simulation models have been constructed using MATLAB/Simulink to validate the efficacy of the proposed approach.

Research on Accurate Fault Location of Multi-Terminal DC Distribution Network

The rise of direct current (DC) distribution networks, driven by distributed energy storage and large-scale photovoltaic integration, has significantly altered distribution network configurations. In DC networks, short-circuit faults cause a sharp drop in voltage and a rapid increase in current, negatively impacting system stability. To solve this problem, we used an improved red fox optimization (IRFO) algorithm to calculate the distance to failure of the protection device. The algorithm shows higher convergence and accuracy compared to conventional methods. The isolated forest algorithm rejects anomalous data, while an adjustable feedback factor and genetic crossover operator further improve performance. Adaptive interpolation is employed to address low sampling frequency issues, enhancing fault localization precision. Simulations performed in Simulink show that the method is highly resistant to interference with minimal localization error. It is also resistant to changes in system parameters, highlighting its robustness and usefulness in fault localization.

Real-Time Underground Cable Fault Monitoring with Iot

The objective of this project is to determine the distance of underground cable fault from thebase station in kilometers and displayed over the internet. Underground cable system is acommon practice followed in major urban areas. While a fault occurs for some reason, at thattime the repairing process related to that particular cable is difficult due to exact unknownlocation of the fault in the cable. Proposed system is used to find out the exact location of thefault and to send data in graphical format to a dedicated website together with on board LCDdisplay using a Wi-Fi module.The project uses the standard theory of Ohms law, i.e., when a low DC voltage is applied atthe feeder end through a series resistor (Cable lines), then the current would vary dependingupon the location of the fault in the cable as the resistance is proportional to the distance. Incase there is a short circuit (Line to Ground), the voltage across series resistors changesaccording to the resistance that changes with distance.This is then fed to an ADC to developprecise digital data which the programmed microcontroller of the Atmega328 displays inkilometers.The project is assembled with a set of resistors representing the cable length in km and thefault creation is made by a set of switches at every known km to cross check the accuracy ofthe same. The fault occurring at a particular distance, the respective phase along with thedistance is displayed on the LCD. The same information is also sent to a dedicated websiteover internet activated Wi-Fi module, interfaced to the microcontroller.Keywords: Underground Cable Fault Detection, Fault Location System, Ohm's LawApplication, Distance Measurement, DC Voltage Method, Resistance Proportional toDistance, ADC (Analog-to-Digital Converter), Microcontroller (ATmega328), Wi-Fi Module(Internet Connectivity), Remote Monitoring.Introduction:

Rolling bearings fault diagnosis using a one-dimensional vision transformer with multi-scale residual convolution

Abstract Traditional transformer-based fault diagnosis methods exhibit inherent limitations in extracting local features, making it challenging to effectively identify critical fault characteristics when processing rolling bearing vibration signals, especially in high-noise environments. Therefore, this paper proposes an intelligent diagnosis method based on noise learning, called the multi-scale residual convolution one-dimensional vision transformer (MRC-1DViT). Firstly, the MRC module is constructed using an adaptive noise learning approach to extract local fault features across multiple scales, capturing fault information of varying dimensions, and reduce noise interference. Subsequently, the extracted features are fed into a 1DViT based fault diagnosis model to identify the long-distance dependencies between features. Additionally, contra norm is introduced to mitigate the issue of dimensional collapse in the model. Finally, the effectiveness of MRC-1DViT is validated using the Case Western Reserve University (CWRU) rolling bearing dataset and the Southeast University (SEU) gearbox dataset. Experimental results demonstrate that MRC-1DViT exhibits superior noise robustness and higher stability compared to existing methods. Notably, under a high-noise environment of −6 dB signal-to-noise ratio, the proposed method achieves fault diagnosis accuracies of 91.38% and 89.38%, respectively.

No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone

It has been previously proposed that a megasplay fault within the Cascadia accretionary wedge, spanning from offshore Vancouver Island to Oregon, has the potential to slip during a future Cascadia subduction zone earthquake. This hypothetical fault has major implications for tsunami size and arrival times and is included in disaster-planning scenarios currently in use in the region. This hypothesis is evaluated in this study using CASIE21 deep-penetrating and U.S. Geological Survey high-resolution seismic reflection profiles. We map changes in wedge structural style and seismic character to identify the inner-outer wedge transition zone where a megasplay fault has been previously hypothesized to exist and evaluate evidence for active faulting within this zone. Our results indicate that there is not an active, through-going megasplay fault in Cascadia, but instead, the structure and activity of faulting at the inner-outer wedge transition zone is highly variable and segmented along strike, consistent with the segmentation of other physical and mechanical properties in Cascadia. Wedge sedimentation, plate dip, and subducting topography are proposed to play a major role in controlling megasplay fault development and evolution. Incorporating updated megasplay fault location, geometry, and activity into modeling of Cascadia earthquakes and tsunamis could help better constrain associated hazards.

Noise Effects on Detection and Localization of Faults for Unified Power Flow Controller-Compensated Transmission Lines Using Traveling Waves

This paper presents a comprehensive analysis of the effects of noise on the detection and localization of faults in transmission lines compensated with a unified power flow controller using traveling wave-based methods. This study focuses on the impact of harmonic and transient noises, which are inherent to power generation, transmission, and UPFC operation. A novel algorithm is proposed combining the Discrete Wavelet Transform and Clarke Transform to detect and localize faults under various noise conditions. The algorithm is tested on a simulated transmission line model in MATLAB/Simulink (Version R2022b) with noise levels of 20 dB, 30 dB, and 40 dB and transient frequencies of 1 kHz, 5 kHz, and 10 kHz. The results demonstrate that the algorithm achieves an average fault localization error of 0.523% under harmonic noise and 0.777% under transient noise, with fault detection rates of 96.3% and 90.75%, respectively. This study highlights the robustness of the traveling wave method in noisy environments and provides insights into the challenges posed by UPFC-compensated lines.

Test suite prioritization and hybrid deep model for software fault detection and localization

Test suite prioritization and hybrid deep model for software fault detection and localization

Characterization of a geothermal system in the shallow structure of Seulawah volcano, Indonesia, using transient electromagnetic methods

Seulawah volcano, located in Sumatra, Indonesia, is renowned for its geothermal potential, a crucial source of cleaner energy for Indonesia’s future growth and security. Available studies of Seulawah volcano primarily focus on its general geological, geochemical, and regional characteristics, with limited research on its shallow subsurface conditions. This study aimed to fill this research gap and enhance our understanding of the geothermal system of Seulawah volcano. There are two objectives of this study: (1) to conduct a transient electromagnetic (TEM) survey across the study area and (2) to better visualize and characterize the shallow subsurface conditions of the geothermal system of Seulawah volcano. The TEM method, which employed 60 stations (with distances between stations ranging from 0.5 to 1 km) and intersected several geothermal manifestations as well as local and regional faults, was used to achieve the objectives of this study. The Occam algorithm was applied for 1D inversion of TEM data, which was then validated using magnetotelluric data. The results of this study indicate that the geothermal system of Seulawah volcano has the potential to generate up to 230 Mwe of electrical energy. Moreover, the shallow depth (<200m) of Seulawah volcano is dominated by a resistive zone, which is interpreted to be related to the basaltic rocks of the Lamteuba Formation. The reservoir layer is located at depths of 200–500 m, exhibiting moderate resistivity values of >10 Ωm. At a depth of 500 m, a conductive layer with resistivity values <10 Ωm was observed, interpreted as a clay cap where fluids from the reservoir layer accumulate. Validation with magnetotelluric data shows results consistent with the TEM data, confirming that the findings of this study are reliable. These findings contribute to a deeper understanding of the geothermal system of Seulawah volcano and are expected to support the development of greener, renewable energy sources for Indonesia.

Fault location technique for multi-terminal DC-microgrid based Gaussian process regression

Fault location technique for multi-terminal DC-microgrid based Gaussian process regression

Fault localization of AI-enabled cyber-physical systems by exploiting temporal neuron activation

Fault localization of AI-enabled cyber-physical systems by exploiting temporal neuron activation

SBFL fault localization considering fault-proneness

SBFL fault localization considering fault-proneness

Reweighted periodic overlapping group lasso for impulsive feature extraction and its application to spiral bevel gear local fault diagnosis

Reweighted periodic overlapping group lasso for impulsive feature extraction and its application to spiral bevel gear local fault diagnosis

Can Earthquake Locations Be Improved for Real-time Monitoring? Revisiting the 1995 seismicity at Soufri`ere Hills Volcano, Montserrat

Volcanic earthquakes provide a wealth of information about the magmatic system. Monitoring volcanic seismicity is one of the primary methods used by volcano observatories globally, including at Soufri`ere Hills Volcano, Montserrat. Computed earthquake locations represent the optimal solution given the information available, and vary depending on the chosen location method and seismic velocity model, but rarely are these parameters tested for suitability in each region. We propose a new method that utilises synthetic earthquakes to evaluate whether the calculated hypocenters and their associated errors accurately represent the true source locations. We define this evaluation as a confidence parameter that highlights events we can 'trust'. By comparing several location methods and seismic velocity models for Montserrat we show the current setup is not optimal, and suggest an alternative location method. Analysis using new 'trusted' relocations focuses on four seismic clusters distal from Soufriere Hills in 1995. Our results highlight differences in hypocenters during this period, suggesting alternative interpretations of the distal seismicity. We propose a WNW dyke orientation supporting previous studies, and local fault complexes in the region. Overall, this paper highlights the importance of using a robust location method suitable for the region to ensure that calculated hypocenters are trustworthy and accurate. Use of sub-optimal methods can influence apparent spatial earthquake trends, impacting interpretations and our understanding of volcanic systems.

IDENTIFICATION OF LINE-TO-LINE-TO-GROUND FAULT LOCATION IN ELECTRICAL POWER NETWORK USING ARTIFICIAL NEURAL NETWORK

The identifying of fault location line-to-line-to-ground (LLG) fault in electrical power network is critical for ensuring the system reliability, safety, and reducing the downtime, and minimizing outage times, and optimizing maintenance to efforts. Various faults that can occur, with line-to-line-to-ground (LLG) faults are complex and less frequent but can cause significant damage if not detected and resolved promptly. The study focuses on identifying the fault location of LLG fault in electrical power network. The ANN model uses voltage and current readings from both ends of the line to predicting the under LLG of fault location. The ANN model it was trained and tested using simulated fault data generated by a power system under various fault location. The result demonstrated the effectiveness of artificial neural Network in accurately identifying of the fault location with line-to-line-to-ground (LLG) faults in electrical power network.

Design of multi-antenna RFID passive bolt loosening fault location system based on the Internet of Things

Abstract Bolt connections are the most common form of connection in hydroelectric generator units. The manhole of spiral case in hydroelectric generator unit is highly susceptible to loosening and fatigue of the bolts due to long-term exposure to hydraulic vibrations, which can lead to bolt breakage and pose significant safety risks. To address the issue of bolt loosening fault localization in the manhole of spiral case in hydroelectric generator unit, a passive bolt loosening fault localization system based on the Internet of Things (IoT) and multi-antenna radio frequency identification (RFID) is designed. First, a tag identification model for multi-antenna RFID is developed, and an optimization control scheme for the multi-antenna system is proposed. Second, an improved virtual reference elimination (VIRE) algorithm for bolt loosening fault localization is proposed, integrating cubic spline interpolation and dynamic threshold (Th). The positioning accuracy of the algorithm is verified by modifying simulation parameters. Finally, a passive bolt loosening fault localization hardware system using multi-antenna RFID is constructed, and upper and lower machine testing programs are developed to achieve precise fault localization of the bolt loosening using the multi-antenna system. Experimental results demonstrate that the IoT-based multi-antenna RFID passive bolt loosening fault localization system can achieve rapid and stable detection of bolt loosening faults. The positioning accuracy of the proposed improved VIRE algorithm is enhanced by 99.15% and 30.95% compared to the LANDMARC and VIRE algorithms, respectively. This system offers a novel approach for the localization of bolt loosening faults in the manhole of spiral case of hydroelectric generator unit under complex operating conditions.

Имитационная модель для исследования третьей гармоники в ЭДС синхронного генератора

The principle of operation of the known versions of ground fault protection systems in stator windings, based on the use of third harmonic in EMF (electromotive force) of generators, is usually based on a simplified idea of uniform and linear distribution of EMF and, consequently, the voltage of this harmonic along the stator winding. However, as experimental data presented in several scientific papers show, such simplified assumptions do not always reflect the actual distribution of third harmonic voltage in stator windings. This can lead to false operation of these protection systems during non-ground fault conditions. Due to the difficulties to conduct experimental measurements on an operating generator, it is essential to develop a simulation model that accurately represents the actual behavior of the third harmonic voltage. This model should take into account the operational mode and design characteristics of the synchronous machine. Such a model is necessary to both develop efficient protection against ground faults in the stator windings and assess the technical effectiveness of existing generator protection against this type of failure. To develop a simulation model of a synchronous generator, the authors have used the SIMULINK environment in the MATLAB software package. The model has been developed based on the theory of electrical machines. To validate the model, the authors have used typical characteristics and experimental data from scientific publications and educational and reference books. A simulation model of a synchronous generator has been designed, which takes int account complex and non-linear nature of the third harmonic voltage distribution along the stator winding. The model considers the design and operation mode of the machine as well as the location of any ground faults. The developed model can be used to both develop protection against ground faults in the stator winding of generators based on the third harmonic, which has higher technical perfection compared to existing designs, and evaluate the effectiveness of current protections against this type of damage.

Fault Detection in Transmission Line

Abstract: This project focuses on the design and implementation of an advanced fault detection system for overhead transmission lines, utilizing key components such as the ESP 8266 microcontroller, current sensors, a GPS module, and IoT integration. The system is capable of detecting and classifying four major fault types: single line to ground (L-G), line to line (LL), double line to ground (L-L-G), and three-phase faults (L-L-LG). By placing current sensors at the transmission line's sending end, the system identifies faults and accurately determines their location through GPS coordinates. Simulations using protect us software were conducted to verify the system’s performance prior to building a hardware prototype. Upon fault detection, the system provides alerts via an LCD display and a buzzer, while real-time fault data is transmitted to an Android app and web server through the arduino IoT cloud. Testing confirmed the system’s precision in fault identification and location tracking, ensuring timely notifications for control room and remote device operators. This successful implementation highlights the system's potential for improving safety and efficiency in power transmission networks. the project lays the groundwork for further exploration into advanced fault detection and real-time monitoring solutions in electrical engineering.

Nonunit protection based on the ratio of IVRW tangent envelope area for modular multilevel converter based HVDC grid

In modular multilevel converters-based DC power grid, short faults develop rapidly and have complex characteristics. The power electronic converter has a limited ability to withstand overcurrent. So, protection needs to quickly identify the fault area in an extremely short time. Non-unit protection based on traveling waves has the advantage of rapid action, but its ability to resist fault resistance needs to be improved. To improve protection performance, a non-unit protection based on the ratio of initial fault voltage reversal wave (IVRW) tangent envelope area is proposed. First, the waveform distortion characteristics and the waveform characteristics of the IVRW at different fault locations are analyzed. Second, the tangent envelope area ratio is used to characterize the waveform distortion characteristics, which gets rid of the influence of fault resistance. Then, a fault identification criterion is constructed. And a protection scheme based on the tangent envelope area ratio is proposed by combining the start criterion and the fault pole criterion. Simulation results show that the proposed scheme has strong resistance to fault resistance and the setting value does not depend on simulation. In addition, the scheme can still effectively identify the protection area under weak boundaries and strong noise interference.