The sound signals of power transformer operation contain extensive information regarding the transformer's operational state. Detecting internal mechanical failures and abnormal states holds significant importance. However, fan noise and other low-frequency noises can interfere with the received acoustic signals, resulting in collected signals that do not accurately represent the transformer's vibration acoustic signals. Current Active Noise Control (ANC) techniques perform better in the low-frequency range. This paper proposes using the FxLMS algorithm to remove low-frequency noise from the acoustic pattern, thereby improving the signal-to-noise ratio. The comparison between the soundprint signals acquired with the turbine off and the noise-reduced soundprint signals verifies the method's feasibility.

The imaging processes of optoelectronic devices are affected by vibration in the transportation platform, which can cause image shaking and blurring. Nowadays, devices often solve problems of image shaking and blurring using motion rotors. However, there is relatively little research on the influence of optical fixtures themselves under vibration conditions. This article analyzes the influence of sinusoidal vibrations on the MTF of an imaging process, pointing out the randomness of imaging effects under conditions of low-frequency vibration. To address the issue of low-frequency vibration effects, an analysis of the designs, and experimental verification, of a specific optical system mount were conducted to verify the influence of the mount’s own properties on imaging under random vibration conditions, providing a basis for the design of future optical mechanical systems.

Transformer vibration analysis yields critical information with practical implications. Examining vibration variations throughout the aging process of transformers contributes significantly to understanding the rules governing these changes and assessing internal structural aging. The interplay between mechanical vibration, thermal aging, and the resistance of transformer cores and windings fosters a progressive degradation of the internal structure. However, the relationship between this internal deterioration and changes in the external casing’s wall vibrations remains elucidated. In order to study the synergistic effect of mechanical-thermal aging on the deterioration of the internal structure performance of the transformer, this paper designed an experimental platform for the aging of the internal structure of the transformer and collected the full-cycle vibration data of the internal pressure data and the vibration of the outer case wall of the transformer through continuous overloading operation for 60 days, and carried out vibration entropy, specific gravity of the fundamental frequency, and comprehensive correlation analyses on the data. The study shows that the internal structure pressure fluctuates and decreases during thermal aging, and the two indicators, vibration entropy, and fundamental frequency specific gravity, have opposite trends. This study can provide a reference role for analyzing the deteriorated vibration characteristics under the combined effect of machine-heat aging and diagnosing the location of the deployment points.

This study investigates vibration changes due to transformer core deterioration by monitoring core vibration, compression force and shell wall vibrations simultaneously. The transformer core operates in a compound environment of mechanical vibration and thermal ageing for extended periods, and the correlation mechanism between core structural deterioration and shell vibration changes remains unclear. This study first derives and analyses the propagation mechanism of core vibration in oil. The experiments simulate the internal deterioration of a 10 kV transformer using pressure sensors to monitor the compression force on the core and windings and vibration sensors on the internal upper yoke and the enclosure to capture full vibration measurements. Analysis of the vibration data during the experiment, using two quantitative indicators—vibrational entropy and fundamental frequency weight—reveals that measurement point #2 (on the outer case wall corresponding to the internal upper yoke) shows a value approximately 1.2 times that of the internal upper yoke. However, measurement point #5 (located away from the upper yoke near the windings) demonstrates a value about 2.3 times that of the internal upper yoke. The results indicate that measurement point #2 has high vibration consistency with the internal upper yoke, whereas it exhibits significant variability compared to measurement point #5. To validate these findings, researchers collected 24‐h vibration data from 105 in‐service 220 kV transformers and the results aligned with those from the experimental platform. This study quantitatively addresses the changes in case vibration characteristics caused by core degradation and proposes a novel method for detecting the mechanical state of transformer cores through vibration analysis.

This paper proposes a novel optimization method for fault current limiter (FCL) reactance configuration based on joint simulation and penalty function constraint optimization. By integrating MATLAB and ATP for joint simulation, the method accurately derives the constraint conditions of the objective optimization function, providing critical data support for the optimization process. To address the challenges of high computational complexity and solution difficulties in constrained optimization, the Penalty Function Method (PFM) is employed to transform the original constrained optimization problem into a standard unconstrained optimization problem, significantly reducing computational complexity and ensuring the feasibility of the solution. On this basis, the Gravitational Search Algorithm (GSA) is applied to compute the optimal reactance value. Through comparative analysis of engineering case studies, the superiority of the GSA over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in optimization performance is validated, further confirming the accuracy and efficiency of the proposed method. The results indicate that this method not only achieves precise calculation results but also significantly improves computational efficiency. Moreover, the integration of PFM and GSA demonstrates excellent robustness, providing reliable technical support for the optimized deployment of fast-switching fault current limiters in large-scale power grids.

Power transformer is one of the key equipment in the power grid. Due to its complex structure and frequent on-site malfunctions, it is necessary to study targeted detection methods. The acoustic-vibration joint detection method has become the current research hotspot because of its advantages such as no direct electrical connection with electrical equipment, safety and reliability, high sensitivity and strong anti-interference ability. In this paper, a transformer with abnormal vibration and operation noise in a power plant becomes the key analysis object. In order to explore the source of abnormal signal and accurately distinguish the operation condition of transformer, acoustic-vibration joint detection method is adopted. It is found that the vibration spectrum of the abnormal transformer has abnormal vibration peak at A-phase 600 Hz and abnormal vibration peak at C-phase 300 Hz. In the noise 1/3 octave band sound pressure level diagram, the amplitude of the abnormal transformer is larger at 100 Hz, 200 Hz and 300 Hz, followed by at 400 Hz and 600 Hz. Based on comprehensive judgment, the abnormal transformer may have faults such as loose A-phase core or windings, and deteriorated C-phase core quality, with underlying causes possibly attributed to environmental factors such as ground micro-subsidence. The research process can provide reference for on-site fault maintenance personnel of transformers.

Detecting the magnetic field of the electrical equipment is crucial. To achieve high-sensitivity detection of magnetic fields, this paper presents an innovative high-sensitivity magnetic field sensor that utilizes an all-fiber Mach-Zehnder (MZ) interferometer constructed from standard single-mode fibers (SMFs). The core of the interferometer comprises two concatenated tapered optical fibers immersed in magnetic fluid (MF). The sensor operates on the principle that the refractive index (RI) of the MF varies with changes in magnetic flux density. This variation in the RI causes a shift in the attenuation peak wavelength of the interference observed in the transmission spectrum. To analyze light propagation within this dual-tapered fiber MZ interferometer, numerical simulations were conducted using the beam propagation method (BPM). These simulations were critical in predicting the sensor's performance and optimizing its design. Following the simulations, a series of experiments were performed to evaluate the sensor's response to different magnetic flux densities. The experimental results demonstrated a high sensitivity of 0.095 nm/mT within a magnetic flux density range of 0-20 mT. This level of sensitivity, coupled with the low cost and simplicity of the all-fiber construction, makes the proposed sensor highly suitable for practical applications, particularly in the monitoring of electric equipment. Its ability to provide precise and real-time measurements of magnetic fields can significantly enhance the reliability and safety of electrical systems. The research findings suggest that this sensor could be a valuable tool in various industrial and technological fields, where accurate magnetic field detection is crucial.

AbstractThis research introduces an equivalent circuit model and a computational method to address complex mechanical motion issues through electromechanical analogies. The study initially refines core vibration characteristics using single‐ and multi‐degree‐of‐freedom models, subsequently establishing equivalent circuit models for these various degrees of freedom. However, employing high degree‐of‐freedom models for detailed modelling of the core proves overly cumbersome. The research advocates for a distributed equivalent circuit model to more accurately represent the core's layered structure, thus facilitating enhanced core modelling. Moreover, the study formulates a mechanical wave transmission equation pertinent to the vibration of the iron core, which constitutes the foundation of the distributed mechanical vibration model. This model comprehensively assesses the impact of three critical factors on core vibration: the non‐linearity of winding resistance, the electromechanical coupling coefficient, and the dynamic stiffness of the core. A case study elucidates the distinct influences of each factor on vibration characteristics. Furthermore, this study derives vibration calculations from a 60‐day overload ageing test conducted on a 10 kV transformer under 135°C overload conditions. The methodology involves integrating measured compression force values and the calculated dynamic stiffness of the core into an equivalent circuit model. Subsequent analysis compares the results from the equivalent circuit model with experimental measurements. These comparisons indicate an agreement between the calculated and measured values in the time–frequency domain, thereby confirming the accuracy of the equivalent circuit model calculations.

The integrated energy system industrial park can comprehensively use different energy sources such as grid power, distributed power generation, and natural gas to meet the cooling, heating, and power demands of the industrial park. For integrated energy systems connected to external power grids through substations, the power grid needs the assistance of the integrated energy system load to cut peak and fill the valley. When it is difficult to expand the capacity of the substation, the power demand of the load on the power grid can also be reduced through the automatic adjustment capability of the park. In order to evaluate the demand regulation capability of integrated energy system parks, this paper studies the production simulation methods of integrated energy systems. By setting different research objectives, it provides an evaluation method for the load regulation capability of integrated energy system parks. Finally, a numerical example is provided to verify the method.

The safety and reliability of optical fiber structure are the key factors to ensure the normal operation of the whole system, and slight damage can potentially cause catastrophic accidents. In order to avoid this situation, structural damage must be identified. At present, academic circles are actively developing new methods for structural health monitoring and damage analysis. In recent years, the intelligent method represented by RBFNN (RBF neural network) has been applied to structural damage diagnosis. In this paper, the damage assessment of optical fiber intelligent structure based on RBFNN is studied. Experiments show that the average time of the system in this paper is the shortest, with an average time of 24.09min, followed by the system in literature [5] with an average time of 71.03min, and finally the system in literature [8] with an average time of 75.90min. Therefore, the system established in this paper is more suitable for damage assessment of optical fiber intelligent structures. Therefore, it is an ideal method to apply RBFNN to signal processing in optical fiber intelligent structure.

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.

When a transformer suffers a permanent fault, it will suffer a short-circuit impulse again after reclosing. If the previous vibration of the winding is not attenuated completely and the winding is subjected to a secondary impulse within a short time, the secondary vibration response will have a superposition. The aim of this study was to analyze the effect of the anti-short-circuit ability of operational transformers subjected to a secondary short-circuit current impulse. In this paper, a model is established for calculating axial vibration in transformer windings and effects on the vibration response of windings under different closing phase angles and short-circuit intervals are analyzed. The results show that the vibration acceleration of windings is a V-shaped variation at phase angles from 0° to 180°, reaching the maximum values at 0° and 180° and reaching the minimum value at 90°. When the transformer recloses on a permanent short circuit, due to the superposition effect, the vibration acceleration amplitude of the secondary impulse will be greater than that of the primary impulse, but as the reclosing interval increases, the superposition effect decreases continuously. When the interval is 600 ms, the superposition effect for the vibration acceleration of the secondary impulse attenuates to 83.3%. The superposition effect is not significant after 600 ms. The research provides a theoretical reference for transformer closing-control strategies.

The instability of the winding-cushion structure is one of the primary causes of transformer failures. Insulation cushion compression and offset are the predominant forms leading to structural instability. Therefore, this paper, using the SFSZ7-31500/110 transformer as an example, first derives the theoretical formula for mechanical stress calculation. It clarifies the key influencing parameters of the winding-cushion block structure on the axial bending stress of the winding. Subsequently, an electromagnetic force finite element calculation model is established to obtain the axial force distribution in the winding and the distribution of unbalanced displacement during short-circuit processes. Based on the force and offset distribution, a specific cushion block compression and offset test platform is constructed. By setting different cushion block variables, the effects of cushion block unbalanced height and cushion block offset on the winding’s bending elastic modulus are determined. Finally, a simulation model for stress calculation of the winding-cushion block structure is established, revealing the influence pattern of cushion block compression and offset instability on the axial strength of the winding. The results of this study indicate that the greater the uneven cushion block height, the lower the axial strength of the winding. Under the same cushion block offset angle, winding structures with non-uniform cushion block offsets exhibit the worst axial stability. When the offset angles are 30°, 45°, and 60°, the maximum axial bending stress of the winding increases by 1.73%, 3.46%, and 7.82%, respectively. Increasing the offset angle exacerbates the decrease in the axial strength of the winding up to a certain extent. The findings in this study have significant implications for enhancing a transformer’s short-circuit resistance.

Winding deformation caused by short-circuit is one of the main causes of transformer damage. Even if the transformer successfully withstands one short-circuit impact, accumulative effect of multiple short-circuit impacts will cause sudden permanent deformation of the winding. Internal winding deformation is a hidden fault due to the visual blocking of the shell of transformer, so it is extremely important to measure the accumulative effect and analyze its influence. In this paper, a SFSZ7-31500/110 transformer was used for short-time multiple short-circuit impact tests. The measurability of accumulative effect was determined by calculating the difference between measured value and reference value of the acceleration of the time-domain vibration acceleration signal, and then a time-frequency matrix was constructed based on Wigner-Ville Distribution (WVD) time-frequency analysis. Based on Fuzzy C-Means (FCM) clustering and the singular values of the matrix, the membership degree of winding mechanical state was calculated, and the influence degree of the accumulative effect was quantitatively analyzed. Results show the method can reflect the deformation trend and degree of winding before the impedance change rate. Research provides some reference for the mechanical state evaluation and fault early warning of windings, and also has a guiding significance for the safe and stable operation of transformers.

Aiming at the problem of abnormal data generated by a power transformer on-line monitoring system due to the influences of transformer operation state change, external environmental interference, communication interruption, and other factors, a method of anomaly recognition and differentiation for monitoring data was proposed. Firstly, the empirical wavelet transform (EWT) and the autoregressive integrated moving average (ARIMA) model were used for time series modelling of monitoring data to obtain the residual sequence reflecting the anomaly monitoring data value, and then the isolation forest algorithm was used to identify the abnormal information, and the monitoring sequence was segmented according to the recognition results. Secondly, the segmented sequence was symbolised by the improved multi-dimensional SAX vector representation method, and the assessment of the anomaly pattern was made by calculating the similarity score of the adjacent symbol vectors, and the monitoring sequence correlation was further used to verify the assessment. Finally, the case study result shows that the proposed method can reliably recognise abnormal data and accurately distinguish between invalid and valid anomaly patterns.

Power simulation analysis has become an important work content of enterprises grid in China. However, other domestic large-scale production enterprises have less conventional quantitative calculations in the operation of power systems, and there is still a lack of a calculation and analysis platform for security analysis of enterprise grid. This paper develops a power analysis platform for enterprise grid, which implements quantitative analysis and calculation for enterprise grid operations.

The existing research on the distribution characteristics of displacement and acceleration of the transformer axial vibration under short-circuit conditions is based on ignoring the damping parameters. An accurate description of the axial distribution characteristics of the windings, especially for the axial vibration of the winding under short-circuit conditions, has a poor effect. In this paper, the damping, stiffness, and mass parameters between windings are comprehensively considered, and the classical “mass-spring-damping” axial vibration mathematical model of transformer windings is established. After solving, the natural frequency, main mode shape, displacement, and acceleration of each wire cake of the multi-degree-of-freedom (multi-DOF) vibration system were quickly obtained. The relationship between the axial displacement and acceleration of the wire cake and the axial deformation of the transformer winding was discussed, and the transformer winding axis was summarized as well as characteristics of the vibration distribution.