Iet Science Measurement & Technology最新文献

Yellowing phenomena have been frequently observed at the interface between the cross-linked polyethylene (XLPE) insulation and the semiconducting rubber in the joint when a failure occurs at the end bushing in gas (EBG) of the XLPE transmission cable joint. It is known that lubricants deteriorate thermally and electrically, which is related to connection material failure. In this study, in order to analyse the cause of the yellowing phenomenon in the XLPE cable termination, modelled experiments including liquid silicone rubber (LSR) semiconducting rubber and ethylene propylene diene monomer (EPDM) semiconducting rubber were carried out with the long-term electrical and thermal deterioration, and the degree of deterioration was investigated through chemical analysis and visual inspection. As a result, it was found out that the yellowing phenomenon of the lubricant at the joint interface was caused by partial discharges deterioration and was accelerated by thermal deterioration. Also, it is shown that LSR absorbs lubricant, whereas EPDM does not absorb lubricant but extracts surfer compound, which directly affects yellowing and solidification of lubricant. In addition, it is revealed that the micro-bubbles produced in the lubricant may provide a fundamental cause of partial discharges, which results in the yellowing phenomena.

The insulation pull rod is the main transmission mechanism of the circuit breaker. In addition to strong electrical performance, it should also have strong mechanical properties. Studying the dynamic characteristics and response insulation pull rods during opening and closing operation and exploring the changes in mechanical characteristics of insulation pull rods during multiple openings and closings are of great significance. In this paper, a 252kV GIS circuit breaker simulator is used to carry out an opening and closing impact fatigue test on an insulation pull rod. The strain signals of the insulation pull rod during the opening and closing stages are obtained. The strain distribution of insulation pulls rod and the influence of operation times on strain are analyzed. The results show that the force on the pull rod is uneven during operation. The force on the mechanism side and contact side is small, and the force on the rod body is large. Also, the pull rod is unstable and bent under pressure force. The impact response frequency is mainly distributed between 0∼1500Hz. With the increase in operation times, the low-frequency component of frequency response basically remains unchanged, while the high-frequency component decreases. After 10000 times opening and closing operations, there was no obvious mechanical loss on the pull rod, but the mechanical properties decreased. The research results can provide reference and basis for the formulation of the performance test method, and specifications of insulating rod materials.

Here, the transient surface charge distribution of a basin-type insulator is investigated under thermal–electric coupled fields. Horizontally installed ±200 kV direct current gas-insulated transmission lines (DC-GIL) are employed, and a 3D geometric model is applied. An improved method is introduced in the transient simulation under coupled fields, which involves simplifying geometric model, decoupling calculation, applying weak form partial differential equation, and simplifying ion transport equation. The influence of volume and surface electric conductivity on the transient surface charge and electric field distribution is discussed. With increasing volume conductivity, the transient charge accumulation is accelerated due to the promotion of conduction through the insulator. With increasing volume conductivity, the polarity of the charge on convex surface changes from negative to positive, while it changes from positive to negative with increasing surface conductivity. This is the consequence of the transition in dominant conduction mechanism. Non-monotonic variation of charge density is observed attributing to the variation transient field distribution. It can be concluded that the influence of volume and surface conductivity should be focused on when evaluating the insulation characteristics of DC-GIL insulators, and the thermal gradient should be considered in dealing with the long-term operating insulators.

Due to the strong coupling among the conductors of 10 kV three-core armored cables and the difficulty in identifying its defects and fault types, a method is proposed based on the input impedance spectrum. Firstly, the phase mode transformation matrix of a three-core cable is obtained by combining the multi-conductor transmission line theory with the loop analysis method to realize decoupling between conductors. Secondly, the input impedance matrices of a cable under different situations are derived. Based on this, a method is proposed to identify the local defects and fault types. The capacitive defects and inductive defects are identified according to the left or right offset of the amplitude spectrum; the short circuit and break faults of the cable can be identified according to the number of resonant points in the amplitude spectrum and the initial phase angle of the phase spectrum. Finally, to verify the correctness of the proposed method, a 10 kV three-core cable is taken as an example to carry out PSCAD circuit simulation and practical test. The results show that the proposed method can effectively identify the local defects and fault types of the three-core cable.

Saturable reactor is the key equipment in converter valves; it is important to evaluate the core condition. In this paper, a recognition model of saturable reactor core loosening based on variational mode decomposition (VMD)-symmetrized dot pattern (SDP) feature fusion images and scale-invariant feature transform (SIFT) was proposed. Firstly, the saturable reactor vibration test under high frequency pulse excitation was carried out, and the vibration signals in different core loosening degrees were collected. Secondly, the VMD algorithm was used to decompose the broadband vibration signal into multiple narrowband functions, which were used to reflect the characteristics of each frequency band. Thirdly, each function and the original signal were transformed by SDP, the generated spiral arms were fused into a new image, and the typical templates in different loosening degrees were selected. Finally, the improved SIFT algorithm was used to obtain the matching results between test sets and templates. The results show that the recognition accuracy of the proposed model for core loosening is 97.5%, which is better than traditional algorithms. It can find the core loosening defect early and avoid further failures such as water pipe break and discharge, which can provide an important basis for saturable reactor monitoring.

Chemical asphyxiation at petrochemical factories can provoke the unconsciousness or death of factory workers through suffocation. Some chemicals vaporize and mix with air without showing any warning properties that raise the risk of oxygen deficiency. In light of this, Industry 5.0 focuses more on human-centricity than technology-driven implementations to ensure secured and work-friendly environments in industries. Recently, research on factory safety management dependent on the Internet of things (IoT) sensors have been executed unwaveringly. In this work, the ultra-wideband (UWB) sensor is adopted to recognize the motion and breathing pattern of workers in smart factory scenarios. After capturing the data from the UWB sensor in real-time, the proposed dataset is further inspected by the deep learning (DL) and traditional machine learning (ML) approaches. Twofold detection schemes are considered where the movement and vital patterns are distinguished first by the stacked ensemble (SE) and the long short-term memory (LSTM) frameworks. The Bayesian optimized ensemble learning (EL) and bidirectional (Bi-LSTM) models are further occupied to analyze abnormalities in the breathing rate of a worker in the smart shop floors. The investigated outcome shows that the DL frameworks (LSTM and Bi-LSTM) outperformed the others by acquiring 99.90% and 99.94% accuracy in 147 s and 293 s, respectively. The devised perception indicates prominent attainment to the smart factory shop floor, Internet of medical things (IoMT), the smart city paradigm, and e-health appliances.

This study is for the case where the available data of power transformer oil–paper insulation is limited to a small amount furfural data, to solve the problems in oil–paper insulation degradation modelling, such as few samples available, unknown function form of the degradation process, differences of individual transformers among degradation processes, and commonality of degradation trends. A power transformer oil–paper insulation degradation modelling and prediction method based on functional principal component analysis (FPCA) is proposed. First, discrete furfural data of oil–paper insulation degradation are converted into continuous functional data, and the common degradation information of transformers is extracted based on functional time warping technology. Second, the principal components of insulation degradation are extracted based on FPCA method, and the difference of degradation information of individual transformers is obtained by analysing the differential of principal component scores. Subsequently, power transformer oil–paper insulation degradation model is constructed, and finally, the degradation model is updated based on Bayesian theory and the oil–paper insulation degradation is predicted. The example results show that compared with traditional transformer oil–paper insulation degradation modelling method, the proposed method has obvious superiority in model accuracy.

Service unavailability of transmission lines, due to the direct and indirect lightning strikes, is evaluated as a challenging issue within electric companies. The lightning event can produce dangerous overvoltage, equipment failures, and power supply interruptions. Here, externally gapped line arresters (EGLAs) performances installed on a 63 kV transmission line are modelled using EMTP-ATP to investigate their capability to withstand current and energy discharged by lightning strokes during back flashover phenomena. Frequency behaviour of the grounding system impedance, first and subsequent lightning current parameters effects on insulators back flashover and lightning flashover failure rate have been considered by Monte-Carlo method. Then, extensive analysis has been carried out to study the absorbed energy of the EGLA and its expected life. The results show the dependency of failure rate and the EGLA expected life on the soil resistivity and lightning strike parameters. The selected EGLA must be provided sufficient lightning protection to the transmission line based on its absorbed energy capability, the soil and lightning parameters and be complied with the discharge energy capability requirement specified by the utility company.

Surface charge accumulation is an important issue when dealing with the insulation property of direct-current gas-insulated transmission lines with insulators. An improved method is introduced to calculate the surface charge distribution of insulators based on three-dimensional (3D) geometry models with high solution accuracy and computing efficiency. More than 90% of the computing memory and time are reduced by applying weak form partial differential equation (PDE) to the ion transport equation compared to adding artificial diffusion term. The computing memory and time are further reduced by 70% when removing the diffusion term from the ion transport equation, whereas the accuracy remains unchanged. Thus, the method of combining the modification of ion transport equation and the application of weak form PDE is suggested in calculating the surface charge of 3D geometry models. Finally, this method is applied in calculating the surface charge distribution of a ±200-kV basin-type insulator under thermal-electric coupled fields and a ±500-kV tri-post insulator. Results show satisfying accuracy and efficiency. It is concluded that the proposed method can be applied in analysing the charge accumulation and ion transport behaviour based on 3D models under various operating conditions.

Wavelet theory has disentangled numerous complexities, including those pertinent to transient and steady-state responses of systems, when Laplace and Fourier transforms face insoluble obstacles. Reactive linear components (e.g. inductors and capacitors) are typically handled in the frequency plane. Non-linear (e.g. diodes) or time-variant components (e.g. switches) are conventionally simulated in the time plane (e.g. a diode via its I–V characteristic) and are considered open or short circuits in AC analyses (e.g. in circuit simulation software). Although translating circuits in an alternative plane, such as the Haar wavelet plane, significantly simplifies the process, a wide integration of wavelets into instruments and education is not yet realised; an underlying reason is the considerate complexity of applying wavelet theory to circuits and signals. The aim of this paper is to bridge this gap, providing a new user-friendly, Laplace-alike approach, utilising measurement-based models and the Haar wavelet. The Haar wavelet transform and a numerical method for the inverse Laplace transform which uses the Haar operational matrix are applied, to calculate the total current of a non-linear, time-variant system, that is the total current of a voltage source which powers a non-linear, time-variant load.