Winding Deformation Research Articles

Adsorption and gas sensing properties of Cun, Agn and Rhn (n=1–3) clusters doped with WTe2 for transformer winding deformation fault gases

In order to solve the problem that the initial WTe2 has poor adsorption effect on transformer winding deformation fault gas, this paper uses density functional theory (DFT) to study the adsorption behavior of three target gases (CO, C2H2 and CO2) on the surface of WTe2 substrate doped with three metal clusters: Cun, Agn, and Rhn (n=1–3). By analyzing the adsorption distance, adsorption energy, DCD and DOS of the three systems, the effect of metal cluster doping on the adsorption of fault gas by WTe2 was revealed. The results show that metal cluster doping can effectively improve the conductivity of WTe2 substrate and make its band structure more compact. CO and C2H2 have good adsorption characteristics in the three doping systems, while CO2 can be effectively adsorbed by Rh cluster-doped WTe2. In addition, this article also uses work function and band gap to analyze the effect of gas adsorption on substrate conductivity, and discusses the practical application prospects of the three metal cluster doping systems from the perspectives of recovery time and sensitivity, and achieved good results. This paper provides theoretical guidance for exploring the application prospects of WTe2 substrate in transformer winding deformation fault diagnosis and gas detection.

Research on the calibration method of winding deformation tester

Abstract The focus of this paper is the calibration method and process for winding deformation tester, encompassing its working principle, metrological characteristics, calibration conditions and measurement methods. The calibration conditions are divided into environmental conditions and measurement standards and other equipments. The measurement methods are divided into indication error of scanning frequency and indication error of amplitude ratio. The key steps in the calibration process are elaborated, including the selection of standard equipments, error analysis, data processing. The method’s feasibility is verified through experiments.

Online detection of transformer winding deformation based on ΔP⁃U2 improved lissajous plot

Online detection of transformer winding deformation based on ΔP⁃U2 improved lissajous plot

Research on Transformer Multiple Fault Detection Based on Pulse Coupled Injection

Abstract The fault diagnosis method of winding deformation based on pulse coupling injection is becoming more and more popular due to its advantages of online detection. In order to further improve the method, a pulse generator with adjustable parameters is developed in this paper to provide stable excitation. Its amplitude is adjustable from 600v to 5000v, pulse width is adjustable from 100 to 1000ns, and frequency is adjustable from 1 to 20kHz. In the diagnosis of winding deformation, the current research mainly focuses on the single deformation fault, and rarely involves the mixed deformation fault. Therefore, based on the pulse coupling injection method, field experiments are carried out to verify the feasibility of the method and find out the important reasons affecting the curve. At the same time, the detection experiment of multi-winding deformation fault superposition of a transformer is carried out, and the RVM frequency divider is used to accurately diagnose the mixed fault types of transformer windings.

Distributed Vibration Monitoring System for 10 kV-400 kVA 3D Wound Core Transformer under Progressive Short-Circuit Impulses.

As large-scale, high-proportion, and efficient distribution transformers surge into the grids, anti-short circuit capability testing of transformer windings in efficient distribution seems necessary and prominent. To deeply explore the influence of progressively short-circuit shock impulses on the core winding deformation of efficient power transformers, a finite element theoretical model was built by referring to a three-phase three-winding 3D wound core transformer with a model of S20-MRL-400/10-NX2. The distributions of internal equivalent force and total deformation of the 3D wound core transformer along different paths under progressively short-circuit shock impulses varying from 60% to 120% were investigated. Results show that the equivalent stress and total deformation change rate reach their maximum as the short-circuit current increases from 60% to 80%, and the maximum and average variation rate for the equivalent stress reach 177.75% and 177.43%, while the maximum and average variation rate for the total deformation corresponds to 178.30% and 177.45%, respectively. Meanwhile, the maximum equivalent stress and maximum total deformation reach 29.81 MPa and 38.70 μm, respectively, as the applied short-circuit current increased to 120%. In light of the above observations, the optimization and deployment of wireless sensor nodes was suggested. Therefore, a distributed monitoring system was developed for acquiring the vibration status of the windings in a 3D wound core transformer, which is a beneficial supplement to the traditional short-circuit reactance detection methods for an efficient grid access spot-check of distribution transformers.

Powerful UAV manipulation via bioinspired self-adaptive soft self-contained gripper.

Existing grippers for unmanned aerial vehicle (UAV) manipulation have persistent challenges, highlighting a need for grippers that are soft, self-adaptive, self-contained, easy to control, and lightweight. Inspired by tendril plants, we propose a class of soft grippers that are voltage driven and based on winding deformation for self-adaptive grasping. We design two types of U-shaped soft eccentric circular tube actuators (UCTAs) and propose using the liquid-gas phase-transition mechanism to actuate UCTAs. Two types of UCTAs are separately cross-arranged to construct two types of soft grippers, forming self-contained systems that can be directly driven by voltage. One gripper inspired by tendril climbers can be used for delicate grasping, and the other gripper inspired by hook climbers can be used for strong grasping. These grippers are ideal for deployment in UAVs because of their self-adaptability, ease of control, and light weight, paving the way for UAVs to achieve powerful manipulation with low positioning accuracy, no complex grasping planning, self-adaptability, and multiple environments.

Patterned, flexible, self-supporting humidity sensor with core-sheath structure for real-time sensing of human-related humidity

Self-supported nanofiber membranes were fabricated by the rhombus-patterned collector in the electrospinning process in this work. The rhombus nanofiber networks were used to retain the mechanical flexibility of the device and stable responses such as bending and winding deformation. A resistive humidity sensor was developed by applying hydrophilic PANI with varying contents onto nanofiber surfaces through in situ polymerization, serving as electrodes. In this context, the self-supported membranes serve dual roles as both the sensing material and the substrate for the sensor. A comprehensive assessment was conducted to analyze how variations in relative humidity affect the sensing characteristics of the acquired sensors. By facilely regulating the ratio of dopant and oxidant concentration to monomer concentration in the polymerization process, the response of the sensors was increased from 49% to 83% with increasing relative humidity from 13% to 93%, good linearity (R2 = 0.97) and a short response/recovery times (33/88 s). The prepared sensors exhibited appreciable mechanical properties and showed outstanding stability after 1000 cycles of bending and the resistances only slightly increased by 2.5%. Moreover, the sensor can monitor both human respiration and non-contact skin humidity. Its exceptional performance makes it easily integrable into textiles for the creation of wearable electronics.

Fault diagnosis and analysis of a 110 kV transformer

This paper aims to provide valuable insights and assistance for ensuring the safe operation of a 110 kV main transformer by conducting an in-depth analysis of tap changer breather oil leakage defects. By employing transformer testing, disassembly analysis, and other methods, this study successfully identifies and prevents the possibility of transformer failure. The analysis reveals that the deformation of the transformer winding is caused by insufficient short-circuit resistance, which leads to the deformation of the medium-voltage windings under the continuous action of electrodynamic forces during near-area short-circuit currents. Near-area short-circuits are a significant contributing factor to transformer failures. Therefore, it is recommended to enhance operation and maintenance management for older main transformers and optimize protection settings to reduce the risk of near-area short-circuit failures, thus ensuring the safe and stable operation of the main transformer.

Application of generative AI-based data augmentation technique in transformer winding deformation fault diagnosis

Accurately diagnosing various winding deformation faults is significant in power transformer maintenance. Among the different fault diagnosis methods, frequency response analysis (FRA) is widely used but still poses challenges. Artificial intelligence (AI)-based methods have recently been proposed to interpret FRA data. Nevertheless, these approaches are either complicated or exhibit limited generalization performance due to real-world FRA fault data scarcity. Inspired by AI-generated content (AIGC), this study proposes a data augmentation technique named conditional Wasserstein generative adversarial network with gradient penalty (Conditional-WGAN-GP) combined with fault diagnosis model. Numerous FRA-based data are automatically generated using the proposed data augmentation technique based on real FRA data obtained from a specially designed 10 kV transformer. The augmented dataset is then used to train fault diagnosis models to detect winding deformation faults. The trained fault diagnosis model is subsequently applied to assess two actual transformers. Experimental results demonstrate that when combined with the proposed method, even simpler fault diagnosis models can achieve high accuracy, exhibiting an improvement of approximately 5 % compared to the previous baseline model. The fault diagnosis models combined with the proposed data augmentation technique demonstrate improved generalization and robustness. (GitHub code: https://github.com/cy1034429432/Diagnosing-Transformer-Winding-Deformation-Fault-Types-from-FRA-Based-on-Conditional-WGAN-GP-/tree/main).

Comparative analysis of the characteristics of outlet short circuit and winding insulation fault of distribution transformer and its preventive measures

AbstractOutlet short circuit on the low‐voltage (LV) side and winding inter‐turn short circuit faults are hazardous to transformer operation. To investigate the formation mechanism of winding insulation faults of distribution transformer, ANSYS Maxwell was used to build a coupled magnetic field‐circuit model with the same structural dimension as the actual distribution transformer. An outlet short circuit and winding inter‐turn insulation faults were set by using the voltage‐controlled switch in the external circuit of the model. Subsequently, the differences in the electromagnetic characteristics and the electrodynamic force distributions of the windings under three operating conditions, namely, nominal load, three‐phase outlet short circuit on the LV side and inter‐turn insulation failure were studied, respectively. The results show that compared with the rated load, in the cases of outlet short circuit and inter‐turn insulation faults, the amplitude of winding current increases by 20 and 50 times, the magnetic field strength grows by 20 and 17 times, and the electrodynamic force rises by 400 and 230 times, respectively. Outlet short circuit fault is more likely to cause the winding instability and deformation, and inter‐turn short circuit fault can easily burn out winding insulation. Therefore, corresponding preventive measures were proposed.

Progressive failure of asphalt shingles under high winds: Assessment via full-field deformation measurements on full-scale roof panels

Failures of roof asphalt shingles under high winds have been reported to occur at wind speeds lower than the shingle performance classification. The understanding of the progressive failure mechanisms of shingles subjected to high-wind pressures has been hindered by difficulty in accurately quantifying uplifts and wind-induced pressures with high spatial resolution, especially for large-scale wind test setups that simulate realistic scenarios. This paper reports on an experimental study to assess the use of three-dimensional digital image correlation (‘StereoDIC’) to accurately measure full-field surface deformations of shingles installed on full-scale roof structures and subjected to realistic high winds. Deformation measurements were acquired on shingles installed on typical wood-frame roof panels and subjected to winds with speed up to 257 km/h (160 mph) using an outdoor wind tunnel. The specimens were designed to study the proposed test setup and StereoDIC measurement method for two different combinations of shingle surface coloration (and thus speckle pattern) and field of view. The experiments produced accurate local and full-field shingle deformation measurements. Different datasets were used to gain new insight into the influence of salient aspects of the wind test setup and deformation measurement method on the understanding of the temporal evolution of shingle uplift and failure mechanisms.

Deformation Characteristics of Three-Dimensional Spiral Soft Actuator Driven by Water Hydraulics for Underwater Manipulator.

The emergence of bionic soft robots has led to an increased demand for bionic soft actuating ends. In this study, a three-dimensional spiral water hydraulic soft actuator (3D-SWHSA), inspired by the winding action of an elephant's trunk, is proposed to provide a more targeted soft actuator catching method. The 3D-SWHSA is composed of multiple bending and twisting units (BATUs), which can produce winding deformation after being pressed. By using the principles of virtual work and integrating the Yeoh 3rd order model, a predictive model for winding was established to investigate the bending and twisting characteristics of BATUs with varying structural parameters through finite element simulation. Following the selection of an optimal set of structural parameters for the 3D-SWHSA, its bending and deformation capabilities were simulated using finite element analysis and subsequently validated experimentally. To validate its flexibility, adaptability, and biocompatibility, successful catching experiments were conducted in both air and underwater environments. Underwater organisms, including organisms with soft appearance such as starfish and sea cucumbers, and organisms with hard shell, such as sea snails and crabs, can also be caught harmlessly. In cases where a single 3D-SWHSA is insufficient for capturing objects with unstable centers of gravity or when the capture range is exceeded, the double 3D-SWHSAs can be utilized for cooperative winding. This study affirms the great potential of 3D-SWHSA in diverse marine applications, including but not limited to marine exploration, fishing, and operations.

Strain analysis of the superconductor REBCO tape of CORC cables under winding, bending and twist deformations

Strain analysis of the superconductor REBCO tape of CORC cables under winding, bending and twist deformations

Power Transformer Winding Deformation Diagnosis Based on the Sum of Two‐Way Shortest Distance

Frequency response analysis (FRA) method has been widely used in the world, but the interpretation of its signatures is still a hard problem to solve. This paper introduces a method of the sum of two‐way shortest distance for transformer winding deformation fault diagnosis, which is based on trajectory similarity between FRA signatures. Compared with most existing methods, it does not need order preservation; however, it focuses more on the trajectory itself. The geometric principle of the sum of two‐way shortest distance is introduced and analyzed in detail. By using the circuit analysis software, the equivalent circuit model of the transformer is established, a group of the FRA signatures of three types of transformer winding fault, including axial displacement, radial deformation, and disk space variation fault, are obtained. The distribution of different type of faults is studied by using the sum of two‐way shortest distance to process the FRA signatures in three different frequency bands. Using the sum of two‐way shortest distance as input, the support vector machine (SVM) is employed to train a predictive engine for transformer winding deformation fault diagnosis. Result shows that the proposed method can well classify and diagnose transformer winding deformation fault. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A new method for analyzing the impact of winding mechanical defects on the equivalent circuit parameters of power transformers

AbstractCondition monitoring of the power transformer winding and diagnose of the fault in its incipient stages can prevent the spread of defect, and as a result, the unexpected exit of the transformer. Correct and accurate perception of the effects of each defect or winding deformation on the detailed or any other model parameters is essential. In this article, a software based on finite element method is used, in order to increase accuracy of the study to model the transformer in healthy and defected cases. Three types of winding mechanical deformation, that is, axial displacement, radial deformation, and disc space variation , have been simulated for different locations and extents. From the simulation of the finite element model in the healthy and other defected cases, R, L, and C matrices are obtained for each case. Each of the above matrices in defected cases has been compared with the corresponding matrix of the healthy case. The amount and manner of the above matrices’ element variations have been investigated in detail, might help the fault classification in terms of the type, extent and location, and risk assessment of using the transformer in the current defective situation.

Novel power distribution short‐circuit testing technique based on supercapacitor and modular multi‐ports AC/DC conversion

AbstractWith the growing capacity of the distribution network, the probability of short circuit accidents gradually increases. Accidents such as deformation of distribution transformer windings, shift of laminations, fracture and even explosion of mechanical and insulation components caused by insufficient short‐circuit withstand ability seriously affect the safe and stable operation of the distribution network. The short‐circuit test proved to be an effective way to detect the performance of equipment under fault impact. A power source with supercapacitor is proposed here for short‐circuit test of 10 kV distribution transformers, which can realize the short‐circuit test application economically and flexibly with expandable capacity. First, the advantages and disadvantages of test power source by short‐circuit test generators, special power line, and the proposed method are compared. Second, the structure, working principle, design scheme, and control strategy of the novel short‐circuit testing device are introduced. Furthermore, a 14 MVA/5 MJ energy storage short‐circuit test power source is designed for the testing requirements of 10 kV/630 kVA distribution transformers. Finally, the simulations and experiments are used to verify its feasibility.

The jitter frequency domain of long-span railway cable-stayed bridges considering the influence of pneumatic admittance

The long-span bridge is highly sensitive to wind loads, and their random vibration response under static wind deformation and fluctuating wind load are relatively complex. The analysis of jitter response has become a key issue in the design. Taking the Hanjiatuo Yangtze River Bridge in the chongqing-lichuan railway as the engineering background, the influence of different aerodynamic admittance functions on the main girder jitter response is studied through frequency domain analysis. The results show that aerodynamic admittance has a great influence on the jitter response. Considering that the jitter displacement response of the aerodynamic admittance function is obviously smaller than the calculated results, the influence of aerodynamic admittance should be considered in the calculation and analysis.

Numerical Investigations for Vibration and Deformation of Power Transformer Windings under Short-Circuit Condition

The analysis of the dynamic process of winding destabilization under sudden short-circuit conditions is of great importance to accurately assess the short-circuit resistance of power transformers. Based on magneto-solid coupling, an axisymmetric model of the transformer and a 3D multilayer model of the transformer considering the support components are established, respectively, and the short-circuit electromagnetic force (EF) is simulated by using the finite element method. It is concluded that the middle layer of the winding is subjected to the larger radial EF, while the axial EF has a greater effect on the layers at both ends. Moreover, the impression of the preload force, aging temperatures, and the area share of spacers on the vibration and deformation of windings are studied under short-circuit conditions. The overall distribution of plastic strain and residual stress in the winding is symmetrical, and the maximum values occur in the lower region of the middle of the winding. Finally, considering the material properties of disks and insulating components, the cumulative effect of plastic deformation under multiple successive short-circuit shocks is calculated. Compared with the traditional axisymmetric model of transformer, the three-dimensional multilayer model of the transformer established in this paper is more suitable for the actual winding structure and the obtained results are more accurate.

An Insulation Monitoring Method for Transformer Windings Based on Electroluminescence Effect

Currently, the insulation monitoring method for transformer windings mainly monitors voltage, current, leakage inductance, leakage magnetic field, temperature, and dissolved gas in oil. However, these methods often have the disadvantages of low sensitivity, inability to locate, and slow response time. This paper presents a novel insulation monitoring method for transformer windings based on electroluminescence. In this method, electroluminescent coatings are sprayed on the sides of the blocks between pancake windings. The electric field intensity between the windings is measured according to the coating’ luminance, then the winding insulation state is monitored, and faults can be located. To verify this method, we make a transformer winding model based on the principle of capacitive voltage division. Interturn and interlayer insulation faults are simulated by changing capacitors. The results show that the method has an error of less than 3% in measuring the electric field between transformer pancake windings and is feasible for transformer winding insulation monitoring. In addition, this method also can be used for the detection of transformer winding deformation.

Transformer winding deformation accompanied by magnetic flux leakage field distribution variation and its diagnostic analysis of deformation degree

During the transformer winding deformation process, the leakage magnetic field around the winding will change accordingly. Therefore, it is an effective method to monitor and track the change of the leakage magnetic field and then analyze and judge the state of the transformer. This paper firstly uses Comsol Multiphysics software to establish a 110 kV transformer electromagnetic simulation calculation model. Based on the simulation results of magnetic leakage distribution, an installation plan for the internal magnetic leakage sensor of a 110 kV true transformer is determined. The measurement results of the true single short-circuit test under different working conditions verify the accuracy of the simulation model. Subsequently, a number of B-phase high-centered three-phase short circuit (H-M B) true type tests were carried out, and the relationship between the magnetic leakage distribution characteristics and the impedance change rate after each impact was analyzed. The results show that before the transformer is seriously deformed due to multiple short circuit shocks, the sensitivity of the impedance change rate to the winding deformation is low, and the first five shocks only increase from 0.11% to 0.39%. However, the difference ratio between the simulation value and the test value of magnetic flux leakage (MFL) has obvious changes in each small deformation. BX3 increases from 1.77% to 5.62%, and BX4 increases from 2.08% to 6.55%. The difference ratio of four shocks before winding deformation is more than 6%. Therefore, by monitoring the flux leakage magnetic induction intensity, when the difference ratio is greater than 6%, strengthen the vigilance, which can provide a certain basis for winding monitoring before serious deformation.