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fault localization using sliding adaptive data segmentation and improved k-nearest neighbour with application to railway track circuits

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 122卷

作者： Zhao, Shilin Chen, Guangwu Li, Peng Shi, Jianqiang Potekhin, Vyacheslav Lanzhou Jiaotong Univ Sch Automat & Elect Engn 88 Anning West Rd Lanzhou 730070 Gansu Peoples R China Lanzhou Univ Arts & Sci Sch Digital Media Lanzhou 730010 Peoples R China Lanzhou Jiaotong Univ Key Lab Plateau Traff Informat Engn & Control Gan Lanzhou 730070 Gansu Peoples R China Peter Great St Petersburg Polytech Univ Sch Cyber Phys & Control Syst St Petersburg 195251 Russia

This paper addresses the challenges of disorganized sampling data, high misjudgement rates in manual fault localization, lengthy analysis periods, and inefficiencies in jointless track circuits (JTCs), it introduces a novel fault localization method for JTC compensated capacitors, which is based on sliding adaptive data segmentation (SADS) and fast dynamic time warping (FDTW), to enhance the K-nearest neighbour (KNN) algorithm. The approach models the track circuit to understand voltage signal changes and establishes a universal fault discrimination model, this is followed by applying the SADS approach, which breaks down the measured induced voltage signal into distinct segments reflecting the characteristics of compensation capacitor faults. The method then employs FDTW to refine the traditional K-nearest neighbour algorithm for effective fault localization. Experimental results show that the segmented dataset achieves accuracy rates of 97.8% on simulated datasets and 97.1% on measurement datasets, offering a powerful tool for locating compensation capacitor faults in rail circuits.

关键词： Railway circuit Compensation capacitor fault diagnosis fault localization Dynamic time warping K-nearest neighbour

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fault localization Method Based on Surge Diagram

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ELECTRICAL ENGINEERING IN JAPAN 2025年第1期218卷

作者： Inuzuka, Tatsuki Maesaka, Tatsuya Iida, Yoshikazu Ono, Tetsushi Hitachi Ltd Res & Dev Grp Hitachi Japan Kansai Elect Power Co Inc Transmiss & Distribut Co Osaka Japan

The paper presents a new fault location method with traveling waves (surge) on distribution line to restore power supply as soon as possible. The proposed method builds a diagram that describes transmission and reflection of traveling waves over the lines and generates pseudo waves based on the diagram. The least error condition including fault point is estimated by numerical analysis comparing measured waves and pseudo waves. The method is robust and accurate without line parameters such as the speed of traveling waves. The method can be applicable for multiple faults and branch line faults without any additional modification.

关键词： distribution line fault localization ground fault surge (traveling wave)

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Incipient fault localization Using Sheath and Impedance-Based Method for Single-Bonded Underground Cables

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IEEE ACCESS 2025年 13卷 32529-32539页

作者： Carmo, Elaine C. Silva, Leonardo A. R. Maia, Thales A. C. Fed Univ Minas Gerais UFMG Grad Program Elect Engn BR-31270901 Belo Horizonte Brazil Fed Univ Sao Joao del Rei UFSJ Dept Telecommun & Mechatron Engn BR-36307352 Sao Joao Del Rei Brazil Fed Univ Minas Gerais UFMG Elect Engn Dept BR-31270901 Belo Horizonte Brazil

Electric energy plays a fundamental role in driving global productivity and is essential for industrial, commercial, and residential activities. As energy demand continues to rise, insulated power cables have become increasingly critical in modern power grids, ensuring reliable transmission and distribution. However, insulation aging can progressively lead to faults and result in system outages. Given that over 70% of these interruptions in isolated cables are caused by phase-to-ground faults, this presents a significant challenge to the stability and reliability of power systems. Current fault detection strategies aim to identify incipient faults-small, transient electrical discharges within the insulation-before they escalate into permanent faults. Despite this, traditional methods face limitations in terms of precision and applications, especially for single-bonded cables with short lengths and low impedance values. To overcome these limitations, this paper proposes an enhanced impedance-based method for locating incipient faults using the metallic sheath of single-bonded cables. This method integrates metallic sheath parameters to improve the accuracy of incipient fault localization while avoiding the uncertainty associated with estimating unknown parameters. Unlike previous approaches that rely on voltage and current measurements at both ends of the cable, the proposed method simplifies data collection by reducing the number of monitored parameters. Simulations validate the proposed approach, demonstrating its ability to reduce errors in locating fault points in underground cables. The primary contribution of this study is improving the accuracy of incipient fault localization, offering a more efficient and effective solution for identifying and locating faults in insulated cables at their earliest stages.

关键词： Cables Circuit faults Mathematical models Insulation Conductors fault location Current measurement Accuracy Location awareness Integrated circuit modeling fault localization impedance-based method incipient faults metallic sheath single-bonded underground cables

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A novel approach for sun gear fault localization using on-rotor sensing and tidal periods effect

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MEASUREMENT 2025年 253卷

作者： Du, Xinda Feng, Guojin Shi, Dawei Zhen, Dong Cheng, Zhe Hu, Niaoqing Gu, Fengshou Hebei Univ Technol Sch Mech Engn Tianjin 300131 Peoples R China Natl Univ Def Technol Natl Key Lab Equipment State Sensing&Smart Support Changsha 410073 Peoples R China Adv Equipment Res Inst Co Ltd HEBUT Tianjin 300401 Peoples R China Univ Huddersfield Ctr Efficiency & Performance Engn Huddersfield HD1 3D England

Due to the complex structure of planetary gearboxes, fault localization through vibration analysis presents certain challenges. Existing methods rely on absolute phase references provided by external laser tachometers, which are challenging to implement in complex industrial settings. To overcome these limitations, this study introduces a novel method for fault localization in planetary gearboxes utilizing a single On-Rotor Sensing (ORS) sensor. This method utilizes ORS technology to capture high signal-to-noise ratio vibration signals and employs position information derived from changes in gravitational acceleration sensed by the sensor as the absolute phase reference for locating faulty sun gear teeth. Subsequently, the phase relationships between the extracted and enhanced fault impulse signals from the vibration signals and the absolute phase reference were analyzed. By integrating the effects of tidal periods effect, encodings for the number of single-tooth meshings lagging behind the absolute phase reference at different positions of the faulty sun gear tooth are derived. Finally, two indicators, mean Spearman coefficient (MSC) and mean encoding value (MEV), are employed to locate the faulty sun gear tooth. The proposed method is validated on a planetary gearbox test rig with the sun gear fault exhibiting in different gear tooth, showing the proposed method can effectively identify the potential faulty sun gear tooth.

关键词： Tidal periods effect On-rotor sensing (ORS) Phase difference fault localization Planetary gearbox

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Survey on incipient fault localization methods in underground cables

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 123卷

作者： Carmo, Elaine C. da Silva, Leonardo A. R. Maia, Thales A. C. Fed Univ Minas Gerais UFMG Grad Program Elect Engn Belo Horizonte MG Brazil Fed Univ Sao Joao Del Rey UFSJ Dept Telecommun & Mechatron Engn Sao Joao Del Rei MG Brazil Fed Univ Minas Gerais UFMG Elect Engn Dept Belo Horizonte MG Brazil

The increasing demand for high-quality electric power requires a reliable and secure supply. While underground installations meet these requirements, aging cable insulation can lead to failures and disruptions that negatively affect consumers. An effective strategy to mitigate these issues is the early detection and localization of incipient faults before they cause major disruptions in the electrical system. However, a significant gap exists in the literature, particularly in the field of incipient fault localization in underground cables, which lacks a comprehensive systematic review. This paper addresses existing gaps in the literature by reviewing and consolidating the main methodologies, tools, and applications for incipient fault localization. This review aims to establish a solid foundation for developing new solutions and methodologies, encouraging future advancements in underground network reliability. This can be achieved through the detection and localization of incipient faults, which are lowintensity, short-duration electrical discharges that precede a total failure. However, despite growing interest in this topic, there are still discrepancies in methodologies and approaches. Moreover, there is a lack of studies that provide a solid foundation for advancing research in this area. This paper aims to address this gap by reviewing existing literature and consolidating the key techniques, methods, tools, and applications discussed in the studies thus far. The systematic review is structured to provide an overview of the methodologies used, assessing their results, effectiveness, and limitations. Additionally, it identifies emerging trends and highlights promising opportunities for future research, encouraging the development of new studies and solutions. The information compiled here aims to facilitate the integration and advancement of knowledge in this field, contributing to the development of more effective solutions for the localization of incipient fa

关键词： Incipient faults Insulated cables fault localization Underground circuits

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Boosting mutation-based fault localization by effectively generating Higher-Order Mutants

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INFORMATION AND SOFTWARE TECHNOLOGY 2025年 180卷

作者： Wu, Shumei Yang, Binbin Chang, Zexing Li, Zheng Chen, Xiang Liu, Yong Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Nantong Univ Sch Artificial Intelligence & Comp Sci Nantong Peoples R China

Context: fault localization (FL) is an important and tedious phase of software debugging. Among various FL techniques, Mutation-Based fault localization (MBFL) demonstrates promising FL accuracy utilizing impact information of statements provided by First-Order-Mutants (FOMs). Despite its success in Single-fault Scenarios (SFSs), it fails to achieve satisfactory performance in Multiple-fault Scenarios (MFSs). Higher-Order-Mutants (HOMs) provide a solution for MFSs. However, existing work on HOM generation is inadequate and ignores the correlation among faults in MFSs. Objective: In this article, we systematically analyze three relationships among single-faults in MFSs, and further propose three HOM generation methods (i.e., SFClu, SFDis, and SFDen) to simulate different multiple-faults and improve the effectiveness of MBFL in MFSs. Method: We investigate the multiple-fault composition on real-world 393 faulty programs from Defects4J, and then apply our methods to generate HOMs for FL. Specifically, SFClu focuses on generating appropriate HOMs for Multi-Single-Source fault (MSSF) scenarios, where each single-fault is responsible for different observed failures. SFDis is well-suited for Multi-Coupled-Source fault (MCSF) scenarios where at least two single-faults can interact with each other, leading to certain failures either being observable or masked. SFDen aims to generate suitable HOMs for Single-Coupled-Source fault (SCSF) scenarios with multiple single-faults that occur within a statement. Results: (1) The proportion of MFSs is as high as 63.10% in real-world programs, with MSSF, MCSF , and SCSF scenarios accounting for 35.08%, 53.23%, and 11.69%, respectively. (2) Compared to the best-performing mutant generation method Neural-MBFL, SFClu, SFDis, and SFDen can improve the FL performance for MBFL by 36.78%, 49.80%, and 16.36% in Top-1, respectively, outperforming eight established SBFL and MBFL techniques. (3) SFClu, SFDis, and SFDen are more suitable for MSSF,

关键词： fault localization Multiple-fault scenarios Mutation-based fault localization High-order mutant generation

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Efficient fault localization in Smart Grid Through Analysis of the Wave Matrix Image Using Convolutional Neural Networks

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IEEE ACCESS 2025年 13卷 53407-53419页

作者： Carlos Filho, Jose Abreu, Francisco C. M. Silva, Mauricio Borges, Fabbio Rabelo, Ricardo A. L. Fed Inst Educ Sci & Technol Piaui Dept Ind Secur & Cultural Prod BR-64000040 Teresina Brazil Fed Univ Piaui UFPI Dept Comp Sci BR-64049550 Teresina Brazil Sch Mkt Recife SORECH BR-51030065 Recife Brazil State Univ Piaui UESPI Dept Comp Sci BR-64001030 Teresina Brazil

This article presents a methodology for fault localization in electric power distribution systems through the analysis of wave matrix image using Convolutional Neural Networks (CNN). Ensuring a continuous and high-quality supply of electric power is crucial for the efficient operation of a Power System. However, the extensive coverage of the Electric System makes it susceptible to various disturbances caused by factors such as adverse weather conditions, equipment failures, presence of animals in the networks, and human errors. These disturbances can result in faults, characterized as short-circuits or abnormal currents between conductors or to the ground. With approximately 80% of power supply interruptions attributed to Distribution System faults, the need for effective fault localization methods is evident. By extracting voltage signal characteristics at measurement points during disturbances and transforming them into a panoramic representation of the system in the form of an image, the panoramic image generation, derived from simulated short-circuit values at each system bus, provides a comprehensive visualization of the network, enabling precise fault localization. The results demonstrate the accuracy of the CNN method in fault localization. This approach offers scalability, efficient transformation into images, and precise fault localization in electric power distribution systems.

关键词： Location awareness Convolutional neural networks fault location Feature extraction Voltage measurement Power systems Smart grids Deep learning Accuracy Signal processing algorithms fault localization power systems convolutional neural networks panoramic image data analysis

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Enhanced fault localization in Energy Systems Using an Improved MVO Algorithm and Multistrategy Optimization

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IEEE ACCESS 2025年 13卷 50367-50378页

作者： Li, Ze Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur 50603 Malaysia

With the advancement of energy systems toward intelligence and renewability, fault localization in active distribution networks (ADNs) has become a critical issue due to its direct impact on power supply reliability and system stability. Existing fault localization methods often suffer from low accuracy and slow convergence, particularly in complex network structures and under variable fault scenarios. This paper proposes an Improved Multiverse Optimization (IMVO) algorithm to address these challenges. The IMVO algorithm enhances the standard Multiverse Optimization (MVO) by introducing a three-phase search strategy-exploration, development, and hybrid-and dynamically adjusting key parameters such as the Travel Distance Ratio (TDR) and Wormhole Existence Probability (WEP) to balance global and local search capabilities. Additionally, elite retention and differential evolution strategies are integrated to improve population diversity and prevent premature convergence. Validation on the IEEE 33-node ADN model with distributed energy sources demonstrates that the IMVO algorithm achieves fault localization accuracies of 97.2% for single-point faults and 97.6% for multipoint faults, with average convergence within 6 and 8 generations, respectively. Further experiments on the IEEE 69-node network validate the algorithm's scalability, achieving 96.8% and 97.0% accuracy for single-point and multipoint faults, respectively, with only a moderate increase in computational time. The results indicate that the IMVO algorithm maintains near-linear computational complexity as network size grows, making it a viable solution for real-time fault diagnosis in large-scale ADNs. These findings highlight the superior accuracy, convergence speed, and robustness of the proposed IMVO algorithm, demonstrating its potential as an efficient and reliable fault localization method for complex ADN environments and future smart grid applications.

关键词： fault localization MVO algorithm multistrategy optimization distribution networks fault localization MVO algorithm multistrategy optimization distribution networks

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Improving fault localization with External Oracle by Using Counterfactual Execution

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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2025年第2期34卷 1-22页

作者： Park, Jongchan Park, Tae eun Kim, Dongsun Heo, Kihong FuriosaAI Seoul South Korea Korea Adv Inst Sci & Technol Daejeon South Korea Kyungpook Natl Univ Daegu South Korea

We present FLEX, a new approach to improve fault localization with external oracles. Spectrum-based fault localization techniques estimate suspicious statements based on the execution trace of the test suite. Stateof-the-art techniques rely on test oracles that internally exist in the program. However, programs often have external oracles that observe their behavior from outside. This in turn hinders fine-grained and accurate estimation of suspicious statements in practice because the correctness of each execution can only be observed at termination. In this article, we aim to address this problem by observing counterfactual execution traces, which enable fine-grained estimation even without precise internal oracles. We observe two types of counterfactual scenarios related to different types of test cases: When the branch condition is set to a Boolean constant, (1) if most of the passing test cases still pass, we consider the newly executed statements in the branch statement as unrelated to the failure;(2) if failing test case still fails, we also consider the originally executed statements as unrelated to the failure. We evaluated the performance on widely used C and Java programs. FLEX improves the accuracy of state-of-the-art SBFL techniques on C and Java programs by 24% and 22% on average, respectively.

关键词： fault localization SBFL Counterfactual Execution

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Software fault localization Based on SALSA Algorithm

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APPLIED SCIENCES-BASEL 2025年第4期15卷

作者： Fan, Xin Shen, Zuxiong Fu, Zhenlei Ge, Yun Nanchang Hangkong Univ Sch Software Nanchang 330063 Peoples R China

In software development, debugging is the most tedious and time-consuming phase. Therefore, various automated fault localization techniques have been proposed to assist debugging. Among existing fault localization techniques, Spectrum-Based fault localization (SBFL) is one of the most extensively researched methods. Traditional SBFL techniques rely solely on the coverage of program execution for fault localization, which means they neglect the interactions between program entities and fault propagation paths during the execution of the program, resulting in a tie problem that reduces the accuracy of fault localization. To solve the above problem, this paper proposes SA-SBFL, a fault localization method based on the SALSA (Random Method for Link Structure Analysis) algorithm. First, a link graph of program entities is constructed, which includes interactions between program entities and fault propagation paths. Then, the suspicion values obtained from traditional SBFL methods are used as the initial weights of the link graph. Finally, the random walk model is employed to simulate the propagation of faults among program entities, analyze the importance of program entities in the fault propagation process, and obtain a ranking list of suspicious program entities. The experiments in this paper demonstrate that the SA-SBFL method significantly outperforms general SBFL methods. For instance, in the Defects4J dataset, the SA-SBFL technique outperforms traditional SBFL in terms of fault localization accuracy, with a 47% improvement in the Top-1 metric and a 10% increase in the Top-5 metric, and it also showed an average improvement of 19% in the EXAM metric.

关键词： fault localization program spectrum link propagation SALSA algorithm

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