Wire Breakage Research Articles

A neural network-based classifier for identifying and locating neutral wire breaks in low voltage distribution networks

The breakage of the neutral conductor in low voltage distribution networks is a major concern for distribution companies. This breakage causes significant voltage deviations that can damage the connected equipment as well as jeopardizing people. The detection and localization of the breakage is a major challenge as it does not always manifest in the same way. This work presents a methodology based on artificial intelligence for the detection and localization of neutral conductor breaks in distribution networks. Two neural networks are trained in attempt to solve each of the challenges. For this purpose, measurements commonly taken by smartmeters such as power and nodal voltages are used. The methodology is evaluated in simulation exhibiting a good performance.

Fatigue life prediction of corroded hangers with parallel steel wire in a network arch bridge under vehicle-bridge interaction based on a novel noniterative simplified method

Fatigue damage is a main concern during the life-cycle maintenance of bridges with corroded hangers under vehicle-bridge interaction (VBI). In this study, a novel noniterative simplified method for VBI is proposed to analyze the responses of hangers in a network arch bridge, considering the effects of vehicle types, driving lanes, and road surface roughness. Furthermore, the fatigue life of corroded hangers is investigated, considering the actual traffic flow and uneven distribution of stress in the hanger’s cross-section. The results show that longitudinal and transverse bending moments of the hanger significantly affect the stress of steel wires in one hanger but have limited influence on stress amplitudes. The fatigue lives of steel wires are considerably reduced when subjected to both uniform and pitting corrosion. The fatigue life of steel wires is reduced under deteriorating road surface conditions. Moreover, as the fatigue life of steel wires in the hangers declines, the variations in fatigue life among individual steel wires within a single hanger gradually decrease. Consequently, this trend leads to a heightened likelihood of continuous wire breakage.

Microscopic mechanism of ultrasonically welded joints: The role of terminal roughness and wire diameter

The ultrasonic welding technology is widely promoted as a new connection approach in the field of current energy vehicle wiring harness connection. In this paper, three kinds of 25mm2 copper wire harnesses with different wire diameters and T2 copper terminals with different surface roughness were welded by ultrasonic welding. The mechanical properties of the joints were investigated by tensile experiments and the microstructure of joints was characterised using SEM and EBSD techniques. Excessive roughness increases plastic deformation at the weld interface during ultrasonic welding. This increases the dislocation density at the weld interface and refines the grain size. However, at the same time it inhibits recrystallisation to a certain extent. The lower roughness facilitates recrystallisation, but the low density of HAGBs makes the interface susceptible to slip in extended crystallographic plane and direction. Appropriate roughness allows the weld interface to generate fine equiaxed grains and a high density of HAGBs. This facilitates the obstruction of dislocation movement and improves the strength of joint. In addition, the high porosity of a longitudinal cross-section of the conductor with its small diameter was investigated. This results in a large number of wires remaining on the terminals when force is applied. It was determined that the larger a diameter of wire, the higher a cross-sectional porosity. The copper wire breaks at a weak point in cross-section when the force is applied, resulting in the entire wire being left on terminal. At a wire diameter of 0.2 mm, the porosity of a cross-section reaches an equilibrium and the strength of joint is even higher than the strength of material itself, resulting in the joint pulling off. The maximum strength reaches 4703.77 N.

IoT based Smart Fault Identification and Monitoring System for Electric Poles

Electricity is essential in modern life, but damaged power lines cause thousands of electrocutions in India every year. To fix a damaged power line, the power supply is turned off, and a fuse controller is placed on the electric feeder. If the fuse controller trips on a broken wire, the electricity is cut off until the damage is located. This process can be time-consuming and requires resources. This research aims to design a IoT based control system to reduce the time for repairing broken electrical lines and prevent accidents by adopting measures to expedite the repair process, enhance safety, and optimize maintenance efficiency. LoRa devices are installed every 1 km along the cable for a total range of 10 km. A central tower marks the halfway point. A single LoRa device at the tower may be more cost-effective than multiple devices at each pole. A control circuit embedded by transistor and diode safeguard the circuit's integrity and ensure current flows in a single direction, protecting it if a wire between two poles is damaged. After locating damage to a pole, an email is sent to the relevant authority, including location, pole number, and incident time. An automatic alarm will sound when electricity is turned off, warning the public of the danger. Additionally, this system saves time and resources, and is cost-effective.

48‐2: Research on Mechanical Simulation of Flexible AMOLED Module Bottom Frame

With the development of science and technology and consumers' pursuit of high screen ratio, the frame of terminal flagship products has become an important research direction. However, the thinner the bottom frame is, the higher probability of metal wire breakage in bending area. In this paper, we use finite element analysis to simulate the whole bending process of bottom frame, study the influence of bending path, indenter displacement, bending radius and buffer zone on metal wire, summarize the failure mechanism, which provides theoretical basis for fault analysis, stacking structure design and smaller radius design.

Research on Intelligent Identification Algorithm for Steel Wire Rope Damage Based on Residual Network

As a load-bearing tool, steel wire rope plays an important role in industrial production. Therefore, diagnosing the fracture and damage of steel wire ropes is of great significance for ensuring their safe operation. However, the detection and identification of wire rope breakage damage mainly focus on identifying external damage characteristics, while research on inspecting internal breakage damage is still relatively limited. To address the challenge, an intelligent detecting method is proposed in this paper for diagnosing internal wire breakage damage, and it introduces residual modules to enhance the network’s feature extraction ability. Firstly, time–frequency analysis techniques are used to convert the extracted one-dimensional magnetic flux leakage (MFL) signal into a two-dimensional time–frequency map. Secondly, the focus of this article is on constructing a residual network to identify the internal damage accurately with the features of the time–frequency map of the MFL signal being automatically extracted. Finally, the effectiveness of the proposed method in identifying broken wires is verified through comparative experiments on detecting broken wires in steel wire ropes. Three common recognition methods, the backpropagation (BP) neural network, the support vector machine (SVM), and the convolutional neural network (CNN), are used as comparisons. The experimental results show that the residual network recognition method can effectively identify internal and external wire breakage faults in steel wire ropes, which is of great significance for achieving quantitative detection of steel wire ropes.

Artificial intelligence-based distributed acoustic sensing enables automated identification of wire breaks in prestressed concrete cylinder pipe

The inspection of broken wires in prestressed concrete cylinder pipes is crucial for ensuring the safety and reliability of the pipeline. Traditional point detection techniques always require labor-intensive periodic inspections and cannot deployed along the entire pipeline, significantly limiting the development of the industry. Hence, there is an urgent need for more advanced and intelligent sensors that can achieve 100% coverage and provide sufficient accuracy assurance. In this work, we develop a distributed acoustic sensing -based automated monitoring system to accurately classify the rupture of prestressed wires. First, a computer vision approach is employed to primarily screen out potential vibrational signals from DAS array images. Then, a pre-trained support vector machine model is used to classify the vibrations as either wire breakages or non-wire breakages. This model's performance surpassed other classification strategies, achieving 99.62% accuracy, 99.41% precision, 98.82% recall, and 99.12% F1-score in a side-to-side comparison. Our innovative workflow provides a comprehensive solution for detecting broken wires and offers guidance for the application of artificial intelligence-based DAS to complex vibration systems with limited training data.

Event identification in acoustic emission from wire breaks in pre-stressing/post-tensioning cables

Steel tendons commonly used in pre-stressed/post-tensioned concrete structural systems can lose cross-section due to corrosion, eventually leading to acoustic emission (AE) events when the stress exceeds the breaking strength of the wires that make up the tendons. Reliable differentiation of wire break AE events from traffic or grout crack events is critical for monitoring large structures, even where the distance between sensors may produce highly attenuated signals. In this paper, the Fuzzy c-means clustering algorithm was employed to differentiate AEs released from breaking wires of steel tendons from a database of 13464 AEs, including wire breaks, environmental and grout crack AEs. Wire breaks and grout crack AEs were collected from axial loading tests of grouted tendons in which the load increased until a wire broke. Environmental acoustic signals were collected from a bridge. Then all the collected AEs were gathered in a database and post-processed to simulate attenuation of up to 20 m from source to sensor. To optimize the speed and reliability of the Fuzzy c-means clustering algorithm, a non-dominated sorting genetic algorithm-II (NSGA-II) was used to find the minimum number of acoustic features needed. The NSGA-II algorithm started with 201 possible acoustic features and found 12 combinations of features that resulted in more than 80% wire break detection accuracy. In contrast, less than 3% of grout cracks and 0% of environmental signals were detected as wire breaks. The proposed method is suitable for deployment in a large sensor network and has sufficiently low-computational requirements for at-the-sensor processing, eliminating the need to send high-frequency sampled data outside the sensor node.

Acoustic Emission Monitoring in Prestressed Concrete: A Comparative Study of Signal Attenuation from Wire Breaks and Rebound Hammer Impulses

Acoustic emission monitoring (AEM) has emerged as an effective technique for detecting wire breaks resulting from, e.g., stress corrosion cracking, and its application on prestressed concrete bridges is increasing. The success of this monitoring measure depends crucially on a carefully designed sensor layout. For this, the attenuation of elastic waves within the structure’s material is ideally determined in situ through object-related measurements (ORMs) with a reproducible signal source, typically a rebound hammer. This assumes that the attenuation coefficients derived from rebound hammer tests are comparable to those from wire breaks, thus allowing their results to be directly applied to wire break detection without further adjustments. This study challenges this assumption by analysing attenuation behaviour through an extensive dataset. Employing time-domain and frequency analysis, the research generates attenuation profiles from laboratory experiments and in situ measurements across various girders and bridge structures, extracting the slope and residual standard deviation (RSD). While generally validating this approach, the findings highlight differences in attenuation behaviour from among wire break signals and rebound hammer impulses, whereby the latter potentially underestimates the relevant attenuation of wire breaks by approximately 20%. Consequently, a transfer factor is proposed to adjust ORM results obtained with the rebound hammer for wire break scenarios. It consists of a scaling factor of 1.2 to modify the average attenuation coefficient and a constant term of ±1.0 dB/m to cover a 95% confidence interval, and thus, account for sample scattering. Moreover, the anisotropic attenuation behaviour across different structures was studied, showing that transverse attenuation consistently exceeds the longitudinal, significantly influenced by structural features such as voids. In prefabricated concrete bridges with in situ-cast concrete slabs, transverse signal transmission remains unhindered across multiple elements. Finally, the results provide a valuable reference for the design of sensor layouts in bridge monitoring, particularly benefiting scenarios where direct in situ experiences are lacking.

Migration of patella tension band metal wires to popliteal fossa: Retrieval by posterior knee arthroscopy – A case report and literature review

Breakage of metal wires after fixation of patella fractures are common. However, migration of the broken wires to intraarticular location, popliteal fossa and distant sites can be least expected and a difficult scenario for retrieval. We describe in a 58-year male who presented with recurrent locking and migration of broken wires in popliteal fossa. he had fixation of patella fracture nine years ago. The metal wire was retrieved safely from the posterior lateral aspect of knee popliteal fossa by posterior knee arthroscopy using two posterior lateral portals. Through this case, we review the presentation of migrated wires, methods of retrieval and role of arthroscopy. Retrieval of migrated wires by knee arthroscopy can be successful in intraarticular location and in select cases at popliteal fossa, however with significant challenges. To avoid concerns with migration of wires, patients treated with wires for patella fractures should be adequately followed with radiography and sensitized for removal before breakage or at the time of breakage.

Surface burn prevention based on the probability control of pulses with ignition delay in WEDM

This study aims to address surface burn and increased probability of wire breakage under high-energy cutting conditions in wire electrical discharge machining (WEDM). Firstly, the causes of surface burns are investigated, revealing that the deterioration of cooling, debris removal, and deionization status in the machining gap are the dominating factors. Maintaining a certain ratio of pulse to ignition delay is essential for proper discharge machining. Secondly, a servo control strategy based on the pulse probability of ignition delay is proposed. When the target probability is preset to 25%, the machining stability is significantly improved, preventing surface burns and decreasing the probability of wire breakage. With this servo control, the maximum average machining current free of surface burn is raised from 6 to 8 A. As a result, the max cutting speed is improved by 24%, and the tensile strength of the wire electrode is enhanced by 23.5%. In addition, the machined surface area increases by 22% when the diameter wear of the wire electrode reaches 0.01 mm. The new servo control has been demonstrated to be effective in facilitating machining efficiency and extending wire electrode durability in WEDM.

Detecting wire breaks in prestressed concrete pipes: an easy-to-install distributed fibre acoustic sensing approach

The escalating water stress resulting from drought conditions in certain global regions underscores the imperative to minimize water losses, particularly within drinking water supply networks. One way to achieve this is by improving pipe monitoring systems to allow the early detection of possible structural collapse of the pipes. One type of pipe widely used in water mains is the prestressed concrete pipe, whose main cause of structural failure is the breakage of prestressing wires. This research paper analyses the ability of an easy-to-install distributed acoustic sensing (DAS) monitoring system using fibre optics to identify and locate the acoustic signal produced by the wire breaks in prestressed concrete pipes to make early detection of possible structural failures. For this purpose, a large experimental pipeline stretch was built (approximately 1 m in diameter and 40 m long) where wire breaks were simulated. Several variables were studied: the origin of the signal (to distinguish wire breaks from events of a similar nature), the location of the event in the pipe, the presence of background noise, the internal water pressure, the length of the prestressed wire not subject to bonding with the concrete and the presence of water in the pipe. The results showed that the DAS system could detect almost all events. In addition, two of the multiple parameters measured in the signals, the zero-crossing rate and the short-time energy, made it possible to precisely determine the signal’s origin and the event’s location. Another parameter measured, the duration of the signal in this case, made it possible to differentiate whether the events had occurred when the pipe was empty or full of water. These and other results in this paper present a highly promising perspective on using this DAS system in water main monitoring.

Experimental study on identifying the number of wire breaks in prestressed concrete cylinder pipe based on piezoelectric sensing technology

Identifying wire breaks in prestressed concrete cylinder pipes (PCCP) has become an important research topic in recent years. Based on previous numerical studies, this paper presents the first experimental study to identify the number of wire breaks in a PCCP using piezoelectric sensing technology. During the experiment, wire breaks were simulated on a large-diameter embedded DN4000 PCCP and small-diameter lined DN700 PCCP, with a testing device designed to realise the identification method using body stress waves as a medium. Based on the analysis of the output voltage, two types of damage indices were adopted to evaluate the wire break damage. The optimal identification frequencies and corresponding damage indices were determined for different engineering application scenarios. The experimental results are consistent with those of previous numerical simulation studies, further confirming the validity of this technique.

Investigation of experimental and numerical analysis of thermal load of WEDM on all metals through process parameters on wire electrode temperature

The thermal load on wire electrode in a wire electrical discharge machining (WEDM) is the most important factor in predicting wire electrode breakage. Thermal failure of wire electrode may be expected when the maximum temperature of the wire crosses a critical value. The maximum temperature of wire electrode is a function of process parameters of the machine and hence the failure depends upon what settings we choose to run WEDM process. In this investigation, simulation is done using finite-difference thermal model for continuous pulse without clustering of the spark. The model is used for determining distribution of the temperature throughout the length of wire electrode and analyzed the significance of various factors on wire breakage. The outcome of the present simulation model is validated by comparing it with the works of other researchers followed by its validation through experiments. A parametric study is also done to determine the effect of input process parameters and their interaction on the temperature of the wire. For finding the interaction effect, analysis of variance analysis is carried out followed by developing an empirical model. The predictive performance of our simulation model and developed regression models is assessed by comparing them with experimental value. The regression model is found to be closer, with an average percentage deviation of −2.55% on the experimental dataset, compared to 2.64% for the simulation model. During the validation test, the minimum and maximum deviations are 0.08% and 0.20% for simulation versus regression model predictions, −3.31% and −1.65% for experimental versus predicted results, and 1.82% and 3.40% for simulation versus experimental results, respectively. It is observed through this study that temperature of wire electrode mainly depends on the intensity of sparks per unit area which is a function of the input parameters of the WEDM.

Research on quantitative identification method for wire rope wire breakage damage signals based on multi-decomposition information fusion

Steel wire ropes are widely used in various fields, such as mining, elevators, and cable cars. However, their long-term use can lead to wire breakage, posing safety risks. The detection of wire breakages in steel wire ropes is crucial. This study addresses the shortcomings of existing quantitative identification methods for steel wire rope damage detection and proposes a novel model for fusion-based classification and recognition of wire rope damage. This model first combines the continuous wavelet transform and variational mode decomposition for feature extraction. Subsequently, it utilized convolutional neural networks to learn data features and introduced an attention mechanism to weigh and select the fused data. The final output provides the classification results, aiming to enhance the classification accuracy. Comparative experiments and ablation studies were conducted using the memory networks, autoencoder, and support vector machine models. The experimental results demonstrate the superiority of the proposed model regarding feature extraction, classification accuracy, and automation. The model achieved an accuracy rate of 94.44 % when classifying the nine types of wire breakages. This study presents an effective approach for signal processing and damage classification in steel wire rope damage detection, which is crucial for improving the reliability of wire breakage detection in steel wire ropes.

Analysis of Wire Breakage Fault Caused by Galloping on 66kV Debao A and B Line in November 2023

In early November 2023, affected by extreme weather conditions such as rain, snow, and freezing, some transmission lines in northeast region experienced icing and galloping, which brought lots of tripping and disconnection faults. Taking the wire breakage faults of the 66kV Debao A and B line as examples, the causes, processes, and characteristics were all detailed analysed. It can be basically identified that after the first-order galloping of icing the wire, due to the lack of or limited effectiveness of anti-galloping measures, interphase flashover occurred. The flashover melted some of the stranded of galloping wire, resulting in dynamic tension caused by galloping concentrated towards the broken position, the remaining cross-section of the stranded. Due to repeated bending and stretching, the remaining stranded wires exceeded the limit of fracture stress, leading to fracture and overall wire breakage and landing. So the wire breakage fault in this case is strongly related to the interphase flashover caused by galloping. This article conducted fault analysis work by collecting line design, on-site meteorological conditions, and fault characteristics, providing technical support for subsequent prevention and control work.

Application of magnetic flux leakage method in the crimping inspection of carbon fiber conductor

Compared with steel core aluminum strand wire, carbon fiber composite core wire has many excellent characteristics such as large flow capacity, good heat resistance, light weight, but its mechanical properties are poor, and the unqualified crimping quality is easy to lead to wire breakage accidents, which greatly affects its popularization. For this reason, a scheme for the detection of crimping defects of carbon fiber composite mandrel based on magnetic leakage method is proposed. Firstly, the finite element analysis model of the clamping fixture was established, and then the magnetic pole distance k and radial air gap n of the magnetic leakage testing device were explored. Based on the signal-to-noise ratio under the two typical defect conditions of fracture and low pressure, the most suitable excitation structure parameters of the magnetic leakage device were obtained. The results show that when k=55mm and n=3.5mm, the signal-to-noise ratio of MFL detection device reaches the best effect. The research results are of great significance to the quality inspection of compacts of carbon fiber composite mandrel.

Matched Filter for Acoustic Emission Monitoring in Noisy Environments: Application to Wire Break Detection

Regular inspections of important civil infrastructures are mandatory to ensure structural safety and reliability. Until today, these inspections are primarily conducted manually, which has several deficiencies. In context of prestressed concrete structures, steel tendons can be susceptible to stress corrosion cracking, which may result in breakage of individual wires that is visually not observable. Recent research therefore suggests Acoustic Emission Monitoring for wire break detection in prestressed concrete structures. However, in noisy environments, such as wind turbines, conventional acoustic emission detection based on user-defined amplitude thresholds may not be suitable. Thus, we propose the use of matched filters for acoustic emission detection in noisy environments and apply the proposed method to the task of wire break detection in post-tensioned wind turbine towers. Based on manually conducted wire breaks and rebound hammer tests on a large-scale test frame, we employ a brute-force search for the most suitable query signal of a wire break event and a rebound hammer impact, respectively. Then, we evaluate the signal detection performance on more than 500 other wire break signals and approximately one week of continuous acoustic emission recordings in an operating wind turbine. For a signal-to-noise ratio of 0 dB, the matched filter approach shows an improvement in AUC by up to 0.78 for both, the wire break and the rebound hammer query signal, compared to state-of-the-art amplitude-based detection. Even for the unscaled wire break measurements originally recorded at the 12 m large laboratory test frame, the improvement in AUC still lies between 0.01 and 0.25 depending on the wind turbine noise recordings considered for evaluation. Matched filters may therefore be a promising alternative to amplitude-based detection algorithms and deserve particular consideration with regard to Acoustic Emission Monitoring, especially in noisy environments or when sparse senor networks are required.

Sheath-outside AE monitoring method for multiple sources of damage to cables considering the effect of an HDPE sheath on AE propagation

Cable is one of the important components of cable-stayed bridges, there are three common damages: broken wire, corrosion and fatigue. High-density polyethylene (HDPE) sheaths will induce the attenuation of acoustic emission (AE) signals of damage to cables. Therefore, three cables with different wire counts are used for AE monitoring. The relationship between the thickness and the AE transmittance coefficient of HDPE sheaths, and a circumferential AE attenuation model are established for each cable. According to the transmittance coefficient and circumferential attenuation model, a sensor arrangement method for monitoring the wire breakage, corrosion, and fatigue of cables is quantitatively given. The results show that the transmission coefficient linearly decreases with an increase in HDPE sheath thickness with a slope of approximately 0.012. The circumferential AE amplitude attenuation rates for the three types of cables are 9.9%, 18.74%, and 21.13%, respectively. Monitoring the wire breakage requires only one sensor; monitoring corrosion and fatigue damage only requires one sensor for the 61-strand cable, symmetrical-arrangement two sensors for cables with 349 and 547 strands.

Design of an efficient neural network model for detection and classification of phase loss faults for three-phase induction motor

AbstractIn industrial applications, three-phase induction motors (IMs) are widely used, and they are subjected to many types of faults. One such fault is the loss of a motor phase caused by a blown fuse, a broken wire, mechanical damage, etc. When this fault occurs during motor operation, it continues to rotate but experiences rapid heating, which can ultimately lead to motor failure. Therefore, various protection devices are available to protect the motor against this fault, but most traditional protection devices do not offer a comprehensive classification of such a fault. So, in this paper, an efficient neural network model is presented for detecting and classifying 12 types of phase loss faults for a three-phase induction motor (IM) based on factors such as the unhealthy phase, fault location, and motor action modes (standstill, transient, and steady-state modes). Thus, the main goal of this work is to determine the motor mode during the fault, the defective phase, and its location to help the maintenance team repair the fault quickly. The system is simulated and tested using the “MATLAB/Simulink” software, employing a feed-forward neural network. The simulation results demonstrate that the proposed network achieves correct detection and classification of phase loss faults within a short time frame from the occurrence of the fault. Therefore, the proposed network model proves to be a simple and reliable solution for integration into the protection system of a three-phase IM, enabling the detection and classification of various phase loss faults.