Search Results (56)

This research proposes a wire-breakage detection method based on a Time-Domain Feature Weighted Network (TDFWNet) to address the challenging issue of wire-breakage detection in the feed source cabin drive cables of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The study begins with a temporal domain morphology analysis, revealing significant differences between wire-breakage signals and interference signals in key characteristic parameters such as waveform factor, pulse factor, and kurtosis. These parameters are thus employed as the basis for feature input, and their corresponding feature probabilities are calculated to provide prior feature weights for the model. The TDFWNet model integrates the feature learning capability of a Convolutional Neural Network (CNN) with temporal domain feature analysis using the feature probabilities derived from key temporal domain characteristic parameters as weight inputs to enhance the sensitivity and recognition accuracy of wire-breakage signals. Furthermore, the research team has developed a data augmentation method based on Feature-Constrained Dynamic Time Warping (FCDTW). This method processes the original wire-breakage signals to generate high-quality augmented data, thereby improving the model’s ability to recognize wire-breakage signals. Ultimately, the TDFWNet outperforms traditional CNN models by 1.5%, 2.0%, 1.8%, and 16.6% in precision, recall, F1 score, and accuracy, respectively. In practical engineering applications, this method demonstrated excellent stability and practicality in three domestic FAST drive cable-bending fatigue tests. The detected suspected wire-breakage signals were highly consistent with the results of post-fatigue test disassembly inspections, effectively supporting the wire-breakage detection requirements in actual engineering scenarios. Full article

This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a dispersive optical link up to 120 km. DFE is essential for improving signal quality in several communication systems, including WiFi networks, cable modems, and long-term evolution (LTE) systems. Its capacity to mitigate inter-symbol interference (ISI) and rapidly adjust to channel variations renders it a flexible option for high-speed data transfer and wireless communications. Conversely, MLD is utilized in applications that require great precision and dependability, including multi-input–multi-output (MIMO) systems, satellite communications, and radar technology. The ability of MLD to optimize the probability of accurate symbol detection in complex, high-dimensional environments renders it crucial for systems where signal integrity and precision are critical. Lastly, RDE is implemented as an alternative algorithm to the CMA-based equalizer, utilizing the idea of adjusting the amplitude of the received distorted symbol so that its modulus is closer to the ideal value for that symbol. The algorithms are tested using a converged 5G mm-wave analog radio-over-fiber (A-RoF) system at 60 GHz. Their performance is measured regarding error vector magnitude (EVM) values before and after equalization for different optical fiber lengths and modulation formats (QPSK, 16-QAM, 64-QAM, and 128-QAM) and shows a clear performance improvement of the output signal. Moreover, the performance of the proposed algorithms is compared to three commonly used algorithms: the simple least mean square (LMS) algorithm, the constant modulus algorithm (CMA), and the adaptive median filtering (AMF), demonstrating superior results in both QPSK and 16-QAM and extending the transmission distance up to 120 km. DFE has a significant advantage over LMS and AMF in reducing the inter-symbol interference (ISI) in a dispersive channel by using previous decision feedback, resulting in quicker convergence and more precise equalization. MLD, on the other hand, is highly effective in improving detection accuracy by taking into account the probability of various symbol sequences achieving lower error rates and enhancing performance in advanced modulation schemes. RDE performs best for QPSK and 16-QAM constellations among all the other algorithms. Furthermore, DFE and MLD are particularly suitable for higher-order modulation formats like 64-QAM and 128-QAM, where accurate equalization and error detection are of utmost importance. The enhanced functionalities of DFE, RDE, and MLD in managing greater modulation orders and expanding transmission range highlight their efficacy in improving the performance and dependability of our system. Full article

Medium-voltage cables in hydropower plants are typically arranged in multi-circuit configurations to ensure reliability, yet their exposure to harsh operational conditions accelerates insulation degradation and increases partial discharge risks. Traditional fault localization methods, such as the traveling wave method using wavelet transform to process fault signals, suffer from wavefront distortion due to inter-line reflections and noise interference in multi-circuit systems, because wavelet-based techniques are limited by preset basis functions and environmental noise. To address these challenges, a fault localization method for multi-circuit parallel cables based on the Teager–Kaiser Energy Operator (TKEO) is proposed in this paper. First, the fault signal is decoupled using Clarke transformation to suppress common-mode interference, obtaining the α component. Subsequently, the α component is subjected to wavelet transform to obtain the high-frequency components, which are then optimized using the TKEO. The TKEO is applied to optimize the wavelet-transformed signal, enhancing transient energy variations to precisely identify the arrival time of the fault wavefront at measurement points, thereby enabling accurate fault localization. The results of the four types of fault experiments indicate that the use of the TKEO to optimize the wavelet transform of the traveling wave method improved the accuracy of fault localization. Full article

The existing linear frequency increment cable defect detection method using frequency domain reflectometry suffers from severe pseudo-peak phenomena due to non-targeted frequency domain sampling, which interferes with diagnosis. To address this issue, this paper proposes an optimized frequency domain sampling method based on the exponential frequency increment reflection coefficient spectrum. This method optimizes the distribution of frequency domain sampling points, reducing the sampling of high-frequency noise signals, thereby effectively suppressing pseudo-peaks. Research indicates that the low-frequency band of the cable reflection coefficient spectrum contains richer information about the cable’s condition and has less noise compared to the high-frequency band. Therefore, an exponential frequency increment is used instead of the current linear frequency increment, resulting in a denser sampling in the low-frequency band and sparser sampling in the high-frequency band, better matching the information distribution characteristics of the cable reflection coefficient spectrum. To avoid spectral leakage caused by non-uniform sampling under exponential frequency increments, this method locally linearizes exponential sampling and uses interpolation to complete the overall frequency sampling rate, ensuring it meets the basic assumption of Fourier transform—uniform and equally spaced sampling signals. Finally, this method was validated on a 500 m laboratory test cable and a 2000 m operational cable. Experimental results show that this method can make the amplitude of regions other than impedance mismatch points in the positioning curve flatter and effectively suppress abnormal peak interference, significantly improving the accuracy of defect diagnosis. Full article

This study presents a system for precisely measuring pulsed magnetic fields with high amplitude and microsecond duration with minimal interference. The system comprises a probe with an advanced magnetic field sensor and a measurement unit for signal conversion, analysis, and digitization. The sensor uses a thin nanostructured manganite La-Sr-Mn-O film exhibiting colossal magnetoresistance, which enables precise magnetic field measurement independent of its orientation. Films with different compositions were optimized and tested in pulsed magnetic fields. The measurement unit includes a pulsed voltage generator, an ADC, a microcontroller, and an amplifier unit. Two versions of the measurement unit were developed: one with a separate amplifier unit configured for the sensor positioned more than 1 m away from the measurement unit, and the other with an integrated amplifier for the sensor positioned at a distance of less than 0.5 m. A bipolar pulsed voltage supplying the sensor minimized the parasitic effects of the electromotive force induced in the probe circuit. The data were transmitted via a fiber optic cable to a PC equipped with a special software for processing and recording. Tests with 20–30 μs pulses up to 15 T confirmed the effectiveness of the system for measuring high pulsed magnetic fields. Full article

Due to the challenges in antenna installation and detection performance caused by metal obstruction along the propagation path at a Gas-Insulated Switchgear (GIS) cable terminal, as well as the adverse effects of environmental interference on the detection of partial discharge (PD) by existing flexible antennas, this paper proposes a directional flexible antenna design to mitigate these issues and improve detection performance. The proposed design employs a coplanar waveguide (CPW)-fed monopole antenna structure, where the grounding plane is extended to the back of the antenna to enhance directional reception. The designed flexible antenna measures 88.5 × 70 × 20 mm, and its low-profile design allows it to be easily mounted on the outer wall of the epoxy sleeve at the GIS cable terminal. The measurement results show that the flexible antenna has a Voltage Standing Wave Ratio (VSWR) of less than 2 in the 0.541–3 GHz frequency range. It also maintains stable impedance characteristics across various bending radii, with an average effective height of 10.79 mm in the 0.3–1.5 GHz frequency range. A GIS cable terminal PD experimental platform was established, and the experimental results demonstrate that the bending has minimal impact on the detection performance of the flexible antenna, which can cover the detection range of the GIS cable terminal; metal obstruction significantly impacts the PD signal amplitude, and the designed flexible antenna is suitable for detecting PDs in confined spaces with metal obstruction. Full article

Online partial discharge (PD) detection for power cables is one reliable means of monitoring their health. However, strong interference by white noise poses a major challenge in the process of collecting information on partial discharge signals. To solve the problem whereby the wavelet threshold estimation based on sample entropy falls into the local optimal and the wavelet noise reduction makes it difficult to process detailed information, we propose a partial discharge signal noise reduction method based on a combination of improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and discrete wavelet transform (DWT) with multiscale sample entropy (MSE). Firstly, the ICEEMDAN method was used to decompose the original sequence into multiple intrinsic mode components. The intrinsic mode function (IMF) components were grouped using the mutual information method, and high-frequency noise was eliminated using the kurtosis criterion. Next, an MSE model was established to optimize the wavelet threshold, and wavelet noise reduction was applied to the effective component. The ICEEMDAN-MSE-DWT method can retain effective information while achieving complete denoising, which alleviates the problem of information loss that occurs after denoising using the wavelet method. Lastly, as shown by our simulation and experimental results, the proposed method can effectively realize noise reduction for power cable partial discharge signals, thus providing an effective method. Full article

Distributed Acoustic Sensing (DAS) offers numerous advantages, including resistance to electromagnetic interference, long-range dynamic monitoring, dense spatial sensing, and low deployment costs. We initially deployed a water–land DAS system at the Xinfengjiang (XFJ) Reservoir in Guangdong Province, China, to monitor earthquake events. Environmental noise analysis identified three distinct noise zones based on deployment conditions: periodic 18 Hz signals near surface-laid segments, attenuated low-frequency signals (<10 Hz) in the buried terrestrial sections, and elevated noise at transition zones due to water–cable interactions. The system successfully detected hundreds of teleseismic and regional earthquakes, including a Mw7.3 earthquake in Hualien and a local ML0.5 microseismic event. One year later, the DAS system was upgraded with two types of spiral sensor cables at the end of the submarine cable, extending the total length to 5.51 km. The results of detecting both active (transducer) and passive sources (cooperative vessels) highlight the potential of integrating DAS interrogators with spiral sensor cables for the accurate tracking of underwater moving targets. This field trial demonstrates that DAS technology holds promise for the integrated joint monitoring of underwater acoustics and seismic signals beneath lake or ocean bottoms. Full article

Partial discharge (PD) detection plays an important role in online condition monitoring of electrical equipment and power cables. However, the noise of PD measurement will significantly reduce the performance of the detection algorithm. In this paper, we focus on the study of a PD noise reduction algorithm based on improved singular value decomposition (SVD) and multivariate variational mode decomposition (MVMD) for white Gaussian noise (WGN) and periodic narrowband interference signal noise. The specific noise reduction algorithm is divided into three noise reduction processes: The first noise reduction completes the suppression of narrowband interference in the noisy PD signal by the SVD algorithm with the guidance signal. The guidance signal is composed of a sinusoidal signal of the accurately estimated narrowband interference frequency component, and the amplitude is twice the maximum amplitude of the noisy PD signal. The second noise reduction decomposes the noisy PD signal after filtering the narrowband interference signal into k optimal intrinsic mode function by the MVMD after parameter optimization. By calculating the kurtosis value of each intrinsic mode function, it is determined whether it is the PD dominant component or the noise dominant component, and the noise dominant component is subjected to 3σ filtering to obtain the reconstructed PD signal. The third noise reduction uses a new wavelet threshold algorithm to denoise the reconstructed PD signal to obtain the denoised PD signal. The overall noise reduction algorithm proposed in this paper is compared with some existing methods. The results show that this method has a good effect on reducing the noise of PD signals measured in simulation and field. Full article

This study introduces a multi-point optical flow cable force measurement method based on Euler motion amplification to address challenges in accurately measuring cable displacement under small displacement conditions and mitigating background interference in complex environments. The proposed method combines phase-based magnification with an optical flow method to enhance small displacement features and improve SNR (signal-to-noise ratio) in cable displacement tracking. By leveraging magnified motion data and integrating auxiliary feature points, the approach compensates for equipment-induced vibrations and background noise, allowing for precise cable displacement measurement and the identification of vibration modes. The methodology was validated using a scaled model of a cable net structure. The results demonstrate the method’s effectiveness, achieving a significantly higher SNR (e.g., from 7.5 dB to 22.24 dB) compared to traditional optical flow techniques. Vibration frequency errors were reduced from 6.2% to 1.5%, and cable force errors decreased from 11.38% to 3.13%. The multi-point optical flow cable force measurement method based on Euler motion magnification provides a practical and reliable solution for non-contact cable force measurement, offering potential applications in structural health monitoring and the maintenance of bridges and high-altitude structures. Full article

Accurately measuring the thickness of the oxide film that accumulates on nuclear fuel assemblies is critical for maintaining nuclear power plant safety. Oxide film thickness typically ranges from a few micrometers to several tens of micrometers, necessitating a high-precision measurement system. Eddy current testing (ECT) is commonly employed during poolside inspections due to its simplicity and ease of on-site implementation. The use of swept frequency technology can mitigate the impact of interference parameters and improve the measurement accuracy of ECT. However, as the nuclear assembly is placed in a pool for inspection, a cable several dozen meters in length is used to connect the ECT probe to the instrument. The measurement is affected by the transmission line and its effect is a function of the operating frequencies, resulting in errors for swept frequency measurements. This paper proposes a method for precisely measuring oxide film thickness based on the swept frequency technique and long transmission line impedance correction. The signals are calibrated based on a transmission line model of the cable, effectively eliminating the influence of the transmission cable. A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. To verify the feasibility of the method, measurements are conducted on fuel cladding samples with varying conductivities. It is found that the method can accurately assess oxide film thickness with varying conductivity. The maximum error is 3.42 μm, while the average error is 1.82 μm. The impedance correction reduces the error by 66%. The experimental results indicate that this method can eliminate the impact of long transmission cables, and the algorithm can mitigate the influence of material conductivity. This method can be utilized to measure oxide film thickness in nuclear power maintenance inspections following extensive testing and engineering optimization. Full article

Traditional surveying methods have various drawbacks in monitoring cable-stayed bridge deformations. Global Navigation Satellite System (GNSS) technology is increasingly recognized for its critical role in structural deformation monitoring, providing precise measurements for various structural applications. Accurate signal extraction is essential for reliable deformation monitoring, as it directly influences the quality of the detected structural changes. However, effective signal extraction from GNSS data remains a challenging task due to the presence of noise and complex signal components. This study integrates Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and wavelet packet decomposition (WPD) to extract GNSS deformation monitoring signals for the ropeway pillar. The proposed approach effectively mitigates high-frequency noise interference and modal mixing in GNSS signals, thereby enhancing the accuracy and reliability of deformation measurements. Simulation experiments and real-world scenario applications with operational field data processing demonstrate the effectiveness of the proposed method. This research contributes to advancing GNSS-based deformation monitoring techniques, offering a robust solution for detecting and analyzing subtle structural changes in various engineering contexts. Full article

Cable termination is an important part of energy transmission in high-speed trains, and it is also a weak link in the insulation. It is important to determine the insulation status of cable terminals by the detection results of partial discharge signals, but the partial discharge signals in the field test circuit are mixed with a large amount of external corona interference, which affects the detection accuracy. This paper proposes a signal recognition model that incorporates Stockwell transform (ST) and 2DCNN, which in combination with wavelet noise reduction can achieve a high-precision classification effect for partial discharge and corona interference with an accuracy rate of up to 98.75%. By selecting the maximum energy moment in the ST matrix to correct the position of the time window during the recognition of long time series signals, the problem of corona interference being truncated by the time window and being misidentified as partial discharge is overcome, and the generalization ability of the model is enhanced. Experimental results show that the method has an excellent performance in separating partial discharge and corona interference in long time series signals. Full article

Electromagnetic waves (EMWs) have become an integral part of our daily lives, but they are causing a new form of environmental pollution, manifesting as electromagnetic interference (EMI) and radio frequency signal leakage. As a result, the demand for innovative, eco-friendly materials capable of blocking EMWs has escalated in the past decade, underscoring the significance of our research. In the realm of modern science, the creation of new materials must consider the starting materials, production costs, energy usage, and the potential for air, water, and soil pollution. Herein, we utilized biowaste materials generated during the distillation of fruit schnapps. The biowaste from apple and quince schnapps distillation was used as starting material, mixed with KOH, and carbonized at 850 °C, in a nitrogen atmosphere. The structure of samples was investigated using various techniques (infrared, Raman, energy-dispersive X-ray, X-ray photoelectron spectroscopies, thermogravimetric analysis, BET surface area analyzer). Encouragingly, these materials demonstrated the ability to block EMWs within a frequency range of 8 to 12 GHz. Shielding efficiency was measured using waveguide adapters connected to ports (1 and 2) of the vector network analyzer using radio-frequency coaxial cables. At a frequency of 10 GHz, carbonized biowaste blocks 78.5% of the incident electromagnetic wave. Full article

In order to reduce the influence of coupling capacitance variations on cable voltage measurement, this paper proposes a self-compensating non-intrusive ring-type AC voltage sensor based on capacitive coupling. A theoretical model of the sensor was established, and the influence of parasitic capacitance changes on sensor output was analyzed. Furthermore, a theoretical analysis shows that the parasitic capacitance between the external cable and the sensing probe, as well as between the ground and the sensing probe, will significantly affect the sensitivity of the sensor and increases the measurement error. A ring-type inductive probe and a signal processing circuit were designed, incorporating a reference signal to compensate for the influence of coupling capacitance variations. Additionally, to minimize the impact of parasitic capacitance on sensor output, the length of the outer ring electrode was extended, and a PTFE housing was designed for protection. A prototype of the sensor was developed and tested. This prototype has a good linear response to AC voltage in the measurement range of 0–1000 V with a linearity of 0.86%. The effects of changes in cable diameter and cable position on the measurement were tested separately. The worst-case error of the sensor output is less than 6.44%, representing a reduction of 21.4% compared to the uncompensated case. Under external cable interference, the sensor exhibited an output error of less than 1.85%. The results show that the designed sensor can accurately measure cable voltage despite changes in cable diameter or installation position, and also demonstrates effective shielding against external interference. Full article