Fault Defects Research Articles

Research on Bearing Fault Diagnosis Based on Optimized CNN and Information Fusion

Aiming at the problem of the low recognition rate of a bearing fault under a single sensor condition, an intelligent detection method of a bearing fault based on an optimized convolutional neural network (CNN) and information fusion is proposed. Firstly, a NU216 bearing is selected as the research object to prefabricate fault defects. Then, the orthogonal test method is used to design the test scheme, and the vibration signal and acoustic emission signal of the NU216 bearing are collected; Secondly, the mutual feature fusion method of convolutional neural network is used to fuse the vibration signal and the acoustic emission signal. Then, the fused one-dimensional data is converted into a two-dimensional image dataset by continuous wavelet transform. Finally, the three datasets are divided into training sets and test sets, and input into the optimized convolution neural network model for training and testing. The test results show that the accuracy of fault diagnosis based on vibration signal is 95.76%, the accuracy of fault diagnosis based on acoustic emission signal is 92.33%, and the accuracy of fault diagnosis based on fusion signal is 98.59%.

Study on the damage characteristics of high-temperature superconducting cable insulation under air gap discharge

This study explores the impact of small air gaps in high-temperature superconducting cables on the insulating material polypropylene-laminated paper (PPLP), and the aging rules and mechanisms of the insulating material during practical uses. An air gap discharge test platform was built to simulate air gap fault defects of superconducting cables in the real operating environment. Hierarchical clustering method was used to divide the gap discharge process of defect model into four stages. Insulation damage assessment was conducted on the intermediate layer PP of the superconducting insulation material PPLP at different discharge stages, revealing surface changes and periodic alterations in dielectric properties. The morphological features, roughness, infrared spectra, dielectric loss, surface resistivity, and other phase characteristics of the superconducting insulation layer material were analyzed at different stages of air gap defects. Molecular group cracking in PP was attributed to the bond breakage on the main chain. These findings provide insights into high-temperature superconducting cable insulation under air gap discharge and provide a guideline for practical applications in semi-conductive industries.

Uniqueness of suspiciousness scores: towards boosting evolutionary fault localization

Context. Software is subject to the presence of faults, which impacts its quality as well as production and maintenance costs. Evolutionary fault localization uses data from the test activity (test spectra) as a source of information about defects, and its automation aims to obtain better accuracy and lower software repair cost. Motivation. Our analysis identified that the test spectra commonly used in research exhibit a high ratio of sample repetition, which impairs the training and evolution of Genetic Programming (GP) evolved heuristics. Problem. We investigate whether evolutionary training based on the uniqueness of suspiciousness scores can increase the ability to find software faults (defects), even in repeat-sample scenarios. Specifically, we examine whether the GP-evolved heuristic, which is based on the distinguishability of program elements in terms of faults, is really competitive. Methodology. The investigation formalized hypotheses, introduced three training strategies to guide the research and carried out an experimental evaluation, aiming to reach conclusions regarding the assessment of research questions and hypotheses. Analysis. The results have shown the competitiveness of all the proposed training strategies through evaluation metrics commonly used in the research field. Conclusion. Statistical analyses confirmed that the uniqueness of suspiciousness scores guides the generation of superior heuristics for fault localization.

Interface-rich porous Fe-doped hcp-PtBi/fcc-Pt heterostructured nanoplates enhanced the C[sbnd]C bond cleavage of C3 alcohols electrooxidation

Efficient CC bond cleavage and the complete oxidation of alcohols are key to improving the efficiency of renewable energy utilization. Herein, we successfully prepare porous Fe-doped hexagonal close-packed (hcp)-PtBi/face-centered cubic (fcc)-Pt heterostructured nanoplates with abundant grain/phase interfaces (h-PtBi/f-Pt@Fe1.7 PNPs) via a simple solvothermal method. The open porous structure, abundant grain/phase interface and stacking fault defects, and the synergistic effect between intermetallic hcp-PtBi and fcc-Pt make h-PtBi/f-Pt@Fe1.7 PNPs an effective electrocatalyst for the glycerol oxidation reaction (GOR) in direct glycerol fuel cells (DGFCs). Notably, the h-PtBi/f-Pt@Fe1.7 PNPs exhibit an excellent mass activity of 7.6 A mgPt−1 for GOR, 4.75-fold higher than that of commercial Pt black in an alkaline medium. Moreover, the h-PtBi/f-Pt@Fe1.7 PNPs achieve higher power density (125.8 mW cm−2) than commercial Pt/C (81.8 mW cm−2) in a single DGFC. The h-PtBi/f-Pt@Fe1.7 PNPs can also effectively catalyze the electrochemical oxidation of 1-propanol (17.1 A mgPt−1), 1,2-propanediol (7.2 A mgPt−1), and 1,3-propanediol (5.2 A mgPt−1). The in-situ Fourier-transform infrared spectra further reveal that the CC bond of glycerol, 1-propanol, 1,2-propanediol, and 1,3-propanediol was dissociated for the complete oxidation by the h-PtBi/f-Pt@Fe1.7 PNPs. This study provides a new class of porous Pt-based heterostructure nanoplates and insight into the intrinsic activity of different C3 alcohols.

Defect-Rich CuZn Nanoparticles for Model Catalysis Produced by Femtosecond Laser Ablation.

Femtosecond laser ablation of Cu0.70Zn0.30 targets in ethanol led to the formation of periodic surface nanostructures and crystalline CuZn alloy nanoparticles with defects, low-coordinated surface sites, and, controlled by the applied laser fluence, different sizes and elemental composition. The Cu/Zn ratio of the nanoparticles was determined by energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and selected area electron diffraction. The CuZn nanoparticles were about 2-3 nm in size, and Cu-rich, varying between 70 and 95%. Increasing the laser fluence from 1.6 to 3.2 J cm-2 yielded larger particles, more stacking fault defects, and repeated nanotwinning, as evident from high-resolution transmission electron microscopy, aided by (inverse) fast Fourier transform analysis. This is due to the higher plasma temperature, leading to increased random collisions/diffusion of primary nanoparticles and their incomplete ordering due to immediate solidification typical of ultrashort pulses. The femtosecond laser-synthesized often nanotwinned CuZn nanoparticles were supported on highly oriented pyrolytic graphite and applied for ethylene hydrogenation, demonstrating their promising potential as model catalysts. Nanoparticles produced at 3.2 J cm-2 exhibited lower catalytic activity than those made at 2.7 J cm-2. Presumably, agglomeration/aggregation of especially 2-3 nm sized nanoparticles, as observed by postreaction analysis, resulted in a decrease in the surface area to volume ratio and thus in the number of low-coordinated active sites.

Stacking Fault-Enriched MoNi4/MoO2 Enables High-Performance Hydrogen Evolution.

Producing green hydrogen in a cost-competitive manner via water electrolysis will make the long-held dream of hydrogen economy a reality. Although platinum (Pt)-based catalysts show good performance toward hydrogen evolution reaction (HER), the high cost and scarce abundance challenge their economic viability and sustainability. Here, a non-Pt, high-performance electrocatalyst for HER achieved by engineering high fractions of stacking fault (SF) defects for MoNi4/MoO2 nanosheets (d-MoNi) through a combined chemical and thermal reduction strategy is shown. The d-MoNi catalyst offers ultralow overpotentials of 78 and 121mV for HER at current densities of 500 and 1000mA cm-2 in 1M KOH, respectively. The defect-rich d-MoNi exhibits four times higher turnover frequency than the benchmark 20% Pt/C, together with its excellent durability (> 100 h), making it one of the best-performing non-Pt catalysts for HER. The experimental and theoretical results reveal that the abundant SFs in d-MoNi induce a compressive strain, decreasing the proton adsorption energy and promoting the associated combination of *H into hydrogen and molecular hydrogen desorption, enhancing the HER performance. This work provides a new synthetic route to engineer defective metal and metal alloy electrocatalysts for emerging electrochemical energy conversion and storage applications.

Enhancement of thermoelectric performance by stacking fault control in (GeTe)1-x(Bi2Te3)x compounds, synthesized by hot press sintering method

We investigated the thermoelectric (TE) properties of GeTe by incorporating Bi2Te3 in the GeTe system. The addition of Bi2Te3 into the GeTe matrix leads to phonon scattering caused by stacking fault or structural defect, resulting in a substantial reduction in lattice thermal conductivity κlat. We observed a significant decrease in total thermal conductivities in the vertical and horizontal pressing directions, respectively. The optimized carrier properties and low thermal conductivity in the composites have led to a remarkable improvement in the dimensionless figure of merit (zT) 1.26 at 650 K. This study highlights the potential for creating high-performance thermoelectric materials through GeTe-Bi2Te3 compounds, emphasizing the importance of defect engineering and stacking faults in reducing thermal conductivity and improving thermoelectric efficiency.

Advancing Catalysts by Stacking Fault Defects for Enhanced Hydrogen Production: A Review (Adv. Mater. 21/2024)

Advancing Catalysts by Stacking Fault Defects for Enhanced Hydrogen Production: A Review (Adv. Mater. 21/2024)

Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for Smart Machine

In smart meter technology, the reliability of Backplane to Bezel (BTB) Liquid Crystal Displays (LCDs) is crucial for efficient functioning within intelligent grid systems. Defects in these LCD screens can significantly impact overall smart meter performance, necessitating effective detection methods for proper management and utilization. Current detection approaches, which combine manual and automatic methods based on machine vision, have shown unsatisfactory performance. This research addresses this challenge by proposing a novel method for advanced fault detection in BTB LCDs of smart meters, Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for smart machine (BTB-LCD-FD- MCDSGAN) is proposed. The study begins by collecting datasets specifically tailored for LCD screen localization and defect detection. To enhance data quality, a Window Adaptive Extended Kalman Filter (WAEKF) is applied during preprocessing for noise removal. Feature extraction follows, utilizing Parameterized Multi Synchrosqueezing Transforms (PMST) with a primary focus on Gray Level Co-occurrence Matrix features. These extracted features serve as input for classification by a Multimodal Contrastive Domain Sharing Generative Adversarial Network (MCDSGAN), categorizing defects into five types likes normal display, no display, abnormal display, liquid crystal rupture, and incomplete display. Furthermore, the proposed method optimizes the MCDSGAN weight parameter using the Red Fox Optimization Algorithm (RFOA) to achieve accurate LCD fault defect prediction. The entire approach is implemented in Python, performance metrics likes accuracy, precision, recall, F-score, computational time are thoroughly analyzed. Performance of proposed BTB-LCD-FD-MCDSGAN approach attains 20.89%, 33.67% and 25.98% high accuracy, and 17.98%, 23.78% and 33.45% higher recall compared with existing methods such as automatic detection of display defects for smart meters depend on deep learning (AD-AM-DL), deep learning-enabled image content-adaptive field sequential color LCDs by mini-LED backlight (DL-AFSC-LCD) and new multi category defect detection method depend on convolutional neural network technique for TFT-LCD panels (MDF-CNN-LCD), methods respectively.

Advancing Catalysts by Stacking Fault Defects for Enhanced Hydrogen Production: A Review.

Green hydrogen, derived from water splitting powered by renewable energy such as solar and wind energy, provides a zero-emission solution crucial for revolutionizing hydrogen production and decarbonizing industries. Catalysts, particularly those utilizing defect engineering involving the strategical introduction of atomic-level imperfections, play a vital role in reducing energy requirements and enabling a more sustainable transition toward a hydrogen-based economy. Stacking fault (SF) defects play an important role in enhancing the electrocatalytic processes by reshaping surface reactivity, increasing active sites, improving reactants/product diffusion, and regulating electronic structure due to their dense generation ability and profound impact on catalyst properties. This review explores SF in metal-based materials, covering synthetic methods for the intentional introduction of SF and their applications in hydrogen production, including oxygen evolution reaction, photo- and electrocatalytic hydrogen evolution reaction, overall water splitting, and various other electrocatalytic processes such as oxygen reduction reaction, nitrate reduction reaction, and carbon dioxide reduction reaction. Finally, this review addresses the challenges associated with SF-based catalysts, emphasizing the importance of a detailed understanding of the properties of SF-based catalysts to optimize their electrocatalytic performance. It provides a comprehensive overview of their various applications in electrocatalytic processes, providing valuable insights for advancing sustainable energy technologies.

Assessment of the Performance and Defect Investigation of PV Modules after Accelerated Ageing Tests

Photovoltaic (PV) modules' degradation behaviour, together with outdoor field condition and fault diagnostics, consist valuable data in evaluating efficiency and establishing long-term reliability of a PV system. However, since PV modules commonly come with 25 (even over) years of warranty, testing modules in field for that long period is not feasible. Thus, due to time constraints, many accelerated aging tests have been recently introduced for testing reliability and durability of PV modules. Scope of the presented study is the assessment of the performance degradation and fault (defect) propagation mechanisms with regard to three monocrystalline silicon (mc-Si) PV modules, through a specific thermal cycle accelerated ageing test. The parameters that were experimentally evaluated towards the accelerated ageing process of this study, were: i) the thermal signature evolution and/or propagation of any diagnosed defects, especially in two modules, by means of infrared (IR) thermographic measurements, ii) the overall performance degradation of each module, by means of electrical I-V measurements, together with iii) specific morphological characteristics, by means microscopy imaging. The intended study gave useful and promising results in assessing the effect of the applied thermal cycles upon the modules’ thermal behaviour, electrical efficiency and morphology.

Research on the source of internal fault defects in 40Mn2 oil drill pipe

As an essential material in various industries, steel’s internal defects can seriously affect its performance and cause huge economic losses. To investigate the source of internal fault defects in oil drill pipes, this study used ultrasonic testing equipment to accurately locate internal fault defects in steel, and obtained the spatial coordinates of the defects as (2.15, 2.29, 0.77). Then, by dissecting layer by layer, the target defect was determined to be a large Al2O3 inclusion with a length of 1.609 mm and a width of 0.2 mm. Afterwards, based on the results of automatic scanning of inclusions, this study used extreme value statistical method to estimate the maximum size inclusions that may exist in steel, and found that the target defect size was much larger than the estimated value. Finally, to further determine the source of large inclusions, this study conducted sampling and analysis on immersion nozzles, refining slag, tundish slag, and mold flux. The study found that the matching degree between the composition of large inclusions and the composition of submerged nozzle nodules was the highest, indicating that the fault defect was caused by the peeling of nozzle nodules. This indicates the direction for process optimization.

Tailoring van der Waals interactions in ultra-thin two dimensional metal-organic frameworks (MOFs) for photoconductive applications.

The diverse structural tunability of 2-dimensional π-stacked layered metal-organic frameworks (2D MOFs) enables the control of charge carrier mobility to achieve specific photoconductive characteristics. This study demonstrates the potential of various theoretical methodologies and frameworks in establishing a correlation between structure and functionality for such purposes. Through a focus on the archetypal Ni3(HITP)2 2D MOF, we examine the impact of quantum confinement and stacking fault defects on the absorption spectra using our recently-developed Frenkel-Holstein Hamiltonian. Specifically, the relationship between optical properties and number of layer units along the π-stacking direction is discussed. We employ Marcus rate theory to evaluate vertical carrier mobility subject to inter-layer proximity and different crystal packing which affect van der Waals interactions between layers. The insights presented in this research can inform the development of guidelines for enhancing photoconductive properties in 2D MOF nanosheets.

Acid selenites as new selenium precursor for CdSe quantum dot synthesis

Chemical precursors for nanomaterials synthesis have become essential to tune particle size, composition, morphology, and unique properties. New inexpensive precursors investigation that precisely controls these characteristics is highly relevant. We studied new Se precursors, the acid selenites (R–O–SeOOH), to synthesize CdSe quantum dots (QDs). They were produced at room temperature by the ▪ reaction with alcohols having different alkyl chains and were characterized by 1H NMR confirming their structures. This unprecedented precursor generates high-quality CdSe nanocrystals with narrow size distribution in the zinc-blend structure showing controlled optical properties. Advanced characterization detailed the CdSe structure showing stacking fault defects and its dependence on the used R–O–SeOOH. The QDs formation was examined using a time-dependent growth kinetics model. Differences in the nanoparticle surface structure influenced the optical properties, and they were correlated to the Se-precursor nature. Small alkyl chain acid selenites generally lead to more controlled QDs morphology, while the bigger alkyl chain leads to slightly upper quantum yields. Acid selenites can potentially replace Se-precursors at competitive costs in the metallic chalcogenide nanoparticles. ▪ is chemically stable, and alcohols are cheap and less toxic than the reactants used today, making acid selenites a more sustainable Se precursor.

Automatic Relay Protection Calibration Device and System Design for New Intelligent Power Grid

Maintaining the protection device and eliminating the abnormal and fault defects of the device are important tasks for the maintenance of the power system. In general, relay protection equipment managers need to regularly check the relay protection device. According to the usual practice, relay protection professionals use the relay protection tester to manually connect. The traditional relay protection verification method has complicated operation, high professional requirements for testers. In this paper, a set of intelligent relay protection verification device with high degree of automation and harmonious human-computer interaction is developed to realize the communication between the host computer and the protection device and the tester. The host computer software and database were developed. The thermal overload protection in the SPAM150C motor protection device of ABB company is verified, and the reliability of the device is verified. The device can improve the efficiency of relay protection equipment inspection, reduce the technical threshold of operators, and reduce the probability of human error. It realizes the process and standardized control of the operation process of relay protection verification which has strong practical application value.

Defect Engineering of a High-Entropy Metallic Glass Surface for High-Performance Overall Water Splitting at Ampere-Level Current Densities.

Platinum-based electrocatalysts possess high water electrolysis activity and are essential components for hydrogen evolution reaction (HER). A major challenge, however, is how to break the cost-efficiency trade-off. Here, a novel defect engineering strategy is presented to construct a nanoporous (FeCoNiB0.75 )97 Pt3 (atomic %) high-entropy metallic glass (HEMG) with a nanocrystalline surface structure that contains large amounts of lattice distortion and stacking faults to achieve excellent electrocatalytic performance using only 3at% of Pt. The defect-rich HEMG achieves ultralow overpotentials at ampere-level current density of 1000mAcm-2 for HER (104mV) and oxygen evolution reaction (301mV) under alkaline conditions, while retains a long-term durability exceeding 200h at 100mAcm-2 . Moreover, it only requires 81 and 122mV to drive the current densities of 1000 and 100mAcm-2 for HER under acidic and neutral conditions, respectively. Modelling results reveal that lattice distortion and stacking fault defects help to optimize atomic configuration and modulate electronic interaction, while the surface nanoporous architecture provides abundant active sites, thus synergistically contributing to the reduced energy barrier for water electrolysis. This defect engineering approach combined with a HEMG design strategy is expected to be widely applicable for development of high-performance alloy catalysts.

The Development of the Advanced Inspection System to Screen out the BPDs that Extend to Bar Shaped SSFs under Forward Biasing

We are currently developing an inspection system that will provide a low-cost means of screening prior to shipment by fully visualizing latent 1SSF (single Shockley stacking fault) defects originating from basal plane dislocations (BPDs) that cannot be detected by current defect inspection systems. The system will capture not only the defects that expand into right triangles under relatively low-level forward bias, but also the defects that expand into more serious bar-shaped 1SSFs under relatively high-level forward bias, with a particular focus on capturing TED (threading edge dislocation)-converted BPD at or below the buffer layer/substrate interface. Since these defects are known to cause forward voltage degradation during device operation, so-called "burn-in" (accelerated current stress) screening operation is currently utilized in some device manufacturers to avoid the shipping of the defective devices, but it is very time-consuming process which raises a total cost of production. The system we are developing, which can significantly reduce the screening time, has the potential to replace the "burn-in" operation.

Analysis of Typical Faults and Defects and Testing Methods of Complete Set of Turns-Regulating Arc Suppression Coil

In recent years, many automatic tracking compensation turns-regulating arc suppression coils have been installed in substations to compensate for the increasing capacitive current. However, the frequent occurrence of the fault defects of the arc suppression coil itself has caused a series of new problems, such as causing abnormal bus voltage at the low-voltage side of the substation. Through the analysis and classification of typical faults and defect cases of the complete set of turns-regulating arc suppression coil, it is found that the most vulnerable parts of the device are the on-load tap changer, damping resistance cabinet and control unit. Aiming at the problem that the detection means of the complete arc suppression coil device are insufficient, this paper proposes a new test method, including a compensation characteristic test and relevant accessories test. Based on the new test method, a simulation test platform was built to test 2 sets of turns-regulating arc suppression coil devices. The results show that the new test method has great application value.

Dynamic response and contact characteristics of shaft-bearing-pedestal system with localized defect using 2-D explicit dynamics finite element model

As the core and precision component of a mechanical system, rolling element bearings would cause irreparable results once it breaks down. In order to study the dynamic response of bearing system caused by different localized defect sizes on outer raceway, a two-dimensional (2-D) explicit dynamics Finite Element Method (FEM) model of shaft-bearing-pedestal system with a localized defect is proposed. The model is verified by the experimental results. A new numerical method is used to investigate the influence of different defect sizes on the contact characteristics in this model. The indicator scfdefect-health is introduced to study the contact force with different defect sizes. The results show that the scfdefect-health increases with the increasing of defect depth and width, and the mathematic relationships are given for scfdefect-health. Therefore, the dynamic FEM model can be used to bearing fault diagnosis and defect prediction.

Onset temperature of intrinsic pinning in a REBCO coated conductor from critical current anisotropy

• A detailed analysis is given of the evolution with temperature of the angle dependence of critical current in a REBCO coated conductor. • Particular attention is given to the development of the ubiquitous ab -plane peak for field parallel to the plane of the tape. We highlight that this peak appears as the result of two distinct mechanisms, stacking faults at higher temperatures and intrinsic pinning at lower temperatures. • This peak is unusually weak at 77K, due to process conditions favouring a low density of stacking fault defects. • The peak grows rapidly with decreasing temperature relative to the c-axis critical current starting from 60K, signalling the onset of intrinsic pinning by the layered structure of REBCO. • This growth is quantified through fitting with maximum entropy functions. • The angle dependence of n -values is also shown. With decreasing temperature, the ab -plane feature appears first as a dip at 65K, then a sharper peak starting from 45K. Both of these features broaden with decreasing temperature. The field-angle dependence of the critical current in a REBa 2 Cu 3 O 7 coated conductor has been measured over a fine range of temperatures from 15 K to 80 K. The particular sample is demonstrated to have a very low fraction of extrinsic planar defects by its near-isotropic critical current at 77 K. At a representative magnetic field of 3 T we are able to track the emergence of the ab-plane peak usually associated with intrinsic pinning and quantify its evolution with temperature by fitting to a maximum-entropy function. We are also able to observe the evolution of dip and peak features in the angle dependence of the power-law index n with decreasing temperature and show that a dip appearing at 65 K is supplanted by a sharper positive peak from 50 K. The combination of critical current and power-law index temperature dependences shows the onset of intrinsic pinning at 50 K.